abstract treatments in pistachio
TRANSCRIPT
ABSTRACT
EFFICACY TRIALS OF NEW DORMANCY-BREAKING TREATMENTS IN PISTACHIO
This thesis focused on the problem of adapting pistachio cultivation to warm
winters such as the Central Valley of California is likely to face in the future. Warm
winters negatively affect pistachio yields through two known mechanisms: bloom
asynchrony and the accelerated depletion of energy reserves in winter. The California
pistachio industry currently has no dormancy-breaking agents (DBAs) purposefully
developed to counter the physiological effects of low chill. This thesis work concerns
efficacy trials of new candidate DBAs (GA3, ethephon) in pistachio, a comparison of the
new DBAs with oil sprays, an investigation of DBAs’ effects on the mobilization and
utilization of non-structural carbohydrates by pistachio trees, and the prototyping of new
plant tissue analysis methods to predict effective DBA application times.
A suite of carbohydrate movements that signify growth initiation in spring has
been identified. A new diagnostic procedure has been prototyped to assess the
physiological transition from endodormancy to ecodormancy in pistachio shoots. Single
large doses of GA3 can break endodormancy in pistachio shoots, and the minimum
effective dose of GA3 that breaks endodormancy is a proxy of endodormancy depth.
Even though no tested treatment protected yield against the threat of low chill,
more is now known about proper concentrations and application times for the new DBAs
to avoid adverse side effects. The monitoring techniques developed in this thesis
contribute to filling in the 5-month tissue-testing gap between leaf fall and bloom with
direct indicators of a tree's endodormant, ecodormant, or active status.
Daniel Yuenheen Poon Syverson December 2019
EFFICACY TRIALS OF NEW DORMANCY-BREAKING
TREATMENTS IN PISTACHIO
by
Daniel Yuenheen Poon Syverson
A thesis
submitted in partial
fulfillment of the requirements for the degree of
Master of Science in Plant Science
in the Jordan College of Agricultural Sciences and Technology
California State University, Fresno
December 2019
APPROVED
For the Department of Plant Science:
We, the undersigned, certify that the thesis of the following student meets the required standards of scholarship, format, and style of the university and the student's graduate degree program for the awarding of the master's degree. Daniel Yuenheen Poon Syverson
Thesis Author
Gurreet pal Singh Brar (Chair) Plant Science
Louise Ferguson Plant Science
University of California, Davis
Masood Khezri Plant Science
John Bushoven Plant Science
For the University Graduate Committee:
Dean, Division of Graduate Studies
AUTHORIZATION FOR REPRODUCTION
OF MASTER’S THESIS
DYPS I grant permission for the reproduction of this thesis in part or in its
entirety without further authorization from me, on the condition that
the person or agency requesting reproduction absorbs the cost and
provides proper acknowledgment of authorship.
Signature of thesis author:
ACKNOWLEDGMENTS
To those who care for us, for they make us great.
To those who inspire us, for they bring out our best.
To those who share our journeys, for they give us measure of our true selves.
To those who believe in us, for they are all we have when we are alone.
I especially wish to thank my advisor Gurreet Brar for having accepted
professional risk above and beyond a teacher’s norm to open opportunity for me to
develop as a scientist.
To Masood and Phoebe, for unexpected friendship.
To Louise, for constant support.
To John, for helping me grapple with my past self.
The California Pistachio Research Board funded this project. Rob Willmott
manages the test orchard and provided necessary technical and logistical support.
Madison Hedge and Georgina Reyes Solorio assisted with field and laboratory work.
Florence Cassel-Sharma provided valuable early criticism of the carbohydrate analysis
methodology.
My academic studies were supported for two years by the Harvey Graduate
Scholarship and I thank the family of John & Cora Harvey for their kind sponsorship.
TABLE OF CONTENTS
Page
LIST OF TABLES ............................................................................................................. ix
LIST OF FIGURES ............................................................................................................ x
I. PROJECT EXECUTIVE SUMMARY................................................................... 1
II. LITERATURE REVIEW: FLORAL BUD DORMANCY AND DORMANCY-BREAKING AGENTS IN PISTACHIO ....................................... 4
Executive Summary ............................................................................................................ 4
Dormancy in Seeds and Buds ............................................................................................. 5
Older Perspectives on Bud Dormancy ................................................................................ 7
Physiological Markers of Bud Dormancy........................................................................... 9
Modeling Bud Dormancy Release .................................................................................... 10
Dehydrins and Free Water Status ..................................................................................... 12
Genetic Mechanisms of Dormancy & Dormancy-Breaking ............................................. 14
Chemical Factors Influencing Bud Dormancy Status ....................................................... 15
ABA/GA Antagonism and the Carbon Starvation Response ................................... 15
Sugars and their Interaction with the ABA/GA Antagonism ................................... 18
Reactive Oxygen Species (ROS) .............................................................................. 21
Reactive Nitrogen (Nr), Nitric Oxide and Cyanide .................................................. 22
Jasmonic Acid ........................................................................................................... 23
Brassinolides ............................................................................................................. 24
Dormancy-Breaking Agents (DBAs) and Their Modes of Action ................................... 25
Horticultural Oil ........................................................................................................ 25
DNOC and the Dinitrophenol Derivatives ................................................................ 27
Exogenous Gibberellic Acids ................................................................................... 28
Reactive Nitrogen and Cyanide ................................................................................ 29
Page
vi vi
Hydrogen Cyanamide ............................................................................................... 30
Garlic Extract and Diallyl Disulfide ......................................................................... 32
Exogenous Ethylene and Ethylene-Related Compounds .......................................... 33
Aminoethoxyvinylglycine (AVG) ............................................................................ 34
Exogenous Jasmonic Acid/Jasmonate ...................................................................... 34
Future Directions .............................................................................................................. 35
Elucidating the Role of Carbohydrates and Respiration In DBA Action ................. 35
Improving Bud Diagnostics ...................................................................................... 35
Investigating Alternatives to H2NCN ....................................................................... 37
Designing an Efficacy Trial Pipeline for DBAs ....................................................... 37
Elucidating the Relationship Between Phenology and Yield ................................... 40
References ......................................................................................................................... 41
III. EFFICACY OF DORMANCY BREAKING AGENTS FOR IMPROVED BLOOM SYNCHRONY AND YIELD IN CALIFORNIA PISTACHIOS ......... 52
Abstract ............................................................................................................................. 52
Introduction ....................................................................................................................... 53
Methods............................................................................................................................. 57
Study Site and Treatments ........................................................................................ 57
Bud Respiration Measurements ................................................................................ 58
Overview of Carbohydrate Analysis ......................................................................... 59
Bloom Rating ............................................................................................................ 60
Yield and Quality Components ................................................................................. 61
Results ............................................................................................................................... 62
Bud Respiration Increases and Peaks Before Bloom ................................................ 62
Carbohydrate Levels in Twigs Respond to Bud Activity ......................................... 65
GA and Oil Can Induce Premature Carbohydrate Mobilization to Buds ................. 69
Page
vii vii
Bloom Advancement and Compaction ..................................................................... 71
Yield and Quality Components ................................................................................. 74
Discussion ......................................................................................................................... 76
Study Limitations ...................................................................................................... 76
Endogenous Carbohydrate Mobilization Patterns During Ecodormancy ................. 77
Predictions of the C-T Model ................................................................................... 78
DBA Effects on Respiration ..................................................................................... 80
DBA Effects on Carbohydrate Mobilization and Bloom Synchrony ....................... 81
Possible DBA Modes of Action ................................................................................ 82
DBAs, Synchrony, and Yield .................................................................................... 86
Conclusions ....................................................................................................................... 88
References ......................................................................................................................... 90
Appendix: Methodology of NSC measurements .............................................................. 94
Operating Principles of the Acid Methods ................................................................ 94
The Order of Addition .............................................................................................. 96
Towards Automation ................................................................................................ 98
Tissue Sampling, Extraction, and Digestion for Carbohydrate Analysis ................. 99
Tandem H2SO4-UV/Anthrone Method ................................................................... 100
References ............................................................................................................... 102
IV. VALIDATING A BIOASSAY OF ENDODORMANCY DEPTH FOR CALIFORNIA PISTACHIO (PISTACIA VERA CV. 'KERMAN') .................... 103
Abstract ........................................................................................................................... 103
Introduction ..................................................................................................................... 103
Methods........................................................................................................................... 105
Results ............................................................................................................................. 107
Discussion ....................................................................................................................... 110
Page
viii viii
Conclusion ...................................................................................................................... 112
References ....................................................................................................................... 114
LIST OF TABLES
Page
Table 1: Homologous stages of bud and seed dormancy ................................................... 7
Table 2: Yield and quality summary* for the field trial, crop year 2018. ....................... 74
Table 3: 1st-shake fresh weights from 2018 and 2019, block established 2018. ............. 75
Table 4: Average 1st-shake fresh weights (lbs.) from 3-tree plots, block established 2019. .................................................................................................................. 76
Table 5: Concentrations and dates of GA3 applications in the bioassay experiment. .... 106
Table 6: Contingency table of advancement ratings in the bioassay experiment. ......... 109
LIST OF FIGURES
Page
Figure 1. Chronology of bud respiration increase before bloom, 2018. ........................... 63
Figure 2. (upper) Chronology of bud respiration increase before bloom, 2019.(lower) Daily temperature highs and lows, same period. ............................................. 64
Figure 3. Absolute TSS, hexose, starch, and computed non-hexose sugar (NHS) content in twigs during the month of March, 2019. ......................................... 65
Figure 4. Relative TSS, hexose, and starch content in twigs during the month of March, 2019. .................................................................................................... 66
Figure 5. Boxplot of differences in twig starch accumulation (day 77) between ON and OFF shoots shortly after growth initiation. .............................................. 67
Figure 6. Absolute TSS, hexose, starch, and computed non-hexose sugar (NHS) content in floral buds during the month of March, 2019. ................................ 68
Figure 7. Relative hexose (a), non-hexose sugar (b), and starch (c) contents in female pistachio floral buds throughout the month of March, 2019. ........................... 70
Figure 8. Bloom window hindcasts for crop year 2018. .................................................. 72
Figure 9. Bloom window hindcasts for crop year 2019. .................................................. 73
Figure 10. The budbreak response to applied GA3 concentrations shows a decreasing minimum effective dose with time. ................................................................ 108
I. PROJECT EXECUTIVE SUMMARY
Pistachio cultivation in the Central Valley of California contributes an estimated
$3.6 billion annually and rising to the region's economic vitality. Pistachio acreage in the
region continues to increase, justifying renewed attention to long-term physiological
problems of pistachio production.
In the 20th century, the physiological problem in pistachio production that
received the most scientific attention was alternate bearing, the strong year-to-year
fluctuation in yields. But because bearing pistachio acreage has increased to the point
where the industry now has substantial carryover crop from year to year, alternate bearing
has ceased being such a pressing concern for the industry as a whole. Emerging
horticultural research priorities have to do with adapting pistachio cultivation to saline
soils and warm winters. This thesis focused on the latter problem.
Warm winters are a problem for pistachio due to climatic mismatch between its
native and cultivated ranges. Pistachios are native to the high mountains of Iran and
Afghanistan, where the last frost can be well into the month of May. Pistachios were only
introduced to California in the 20th century, and have not had time to adapt to the Central
Valley's climate in which the last frost seldom extends past March. Pistachios have thus
retained a relatively high chilling requirement that is not always fulfilled by the weather
here in California.
Warm winters negatively affect pistachio yields through two known mechanisms.
First, low winter chill can cause uneven or delayed bloom in spring. Asynchrony in
bloom time between male and female pistachio plants impedes effective pollination.
Second, warmth during winter causes trees to use up more of their energy reserves,
reducing what remains available for growth and crop development in the spring.
Statistical relationships between yield and chill suggest that in marginal years, a single
2 2
day's worth of favorable chill may be worth $50-100 million to California's pistachio
growers in a heavy-crop year, not including additional value from processing also at risk.
Yet to this day, the California pistachio industry still has no treatments
purposefully developed to counter the physiological effects of low chill. This thesis work
concerns efficacy trials of new dormancy-breaking agents (DBAs) in pistachio and the
prototyping of new plant tissue analysis methods to monitor DBAs' physiological effects.
Chapter II presents a literature review of the physiology of floral bud dormancy,
with a focus on applications to pistachio cultivation. This chapter justifies the research
objectives that were pursued using the experiments described in the other chapters of this
thesis. Definitions of dormancy and its stages (i.e., paradormancy, endodormancy,
ecodormancy, and growth initiation) are reviewed. Some endogenous mechanisms of
dormancy maintenance and release are discussed and related to potential modes of action
of DBAs. In view of the industry's interest in new DBAs that substitute for chill, as well
as new decision support for the use of horticultural oil, pertinent and unanswered
physiological questions are posed, chief of which is: how is the efficacy of DBAs
modulated by endogenous and induced carbohydrate mobilization?
Chapter III presents the investigation of how several candidate DBAs (GA3,
ethephon, and horticultural oil) affect the mobilization of carbohydrates to floral buds in
late winter. The investigation sought to relate the movements of stored energy to bloom
synchrony and to the same year's yield. In both years of the project, trees were
sufficiently chilled, so there were no adverse yield effects from low chill to mitigate.
Nevertheless, a previously unreported suite of carbohydrate movements was successfully
associated with growth initiation in spring. DBAs can desynchronize some of the
responses in this suite, depending on when they are applied. Desynchronizing treatments
were associated with more uneven bloom. These results cast doubt on the wisdom of
selecting putative DBAs based on their effects on carbohydrate transport.
3 3
Chapter IV presents the development of a diagnostic procedure to assess the
physiological transition from endodormancy to ecodormancy in pistachio shoots. The
endo-to-eco transition (for short) seems to be an important application time benchmark
for DBAs. To predict its timing, a bioassay of budbreak response to GA3 reported in the
mid-20th-century peach literature was adapted for use in pistachio. Single large doses of
GA3 can break endodormancy in pistachio shoots, and the minimum effective dose of
GA3 that breaks endodormancy is a proxy of endodormancy depth.
Taken as a whole, this thesis work was successful from both basic and applied
standpoints. The applied contribution lies in the experience gained with the new
candidate dormancy breaking agents. Even though no tested treatment protected yield
against the threat of low chill, more is now known about proper concentrations and
application times to avoid adverse side effects. This thesis work has also exposed
potential pitfalls in study design to be avoided in future experimental trials as the industry
continues its search for effective countermeasures against low-chill winters.
This thesis's contribution to basic science has been in observing, by direct analysis
of plant samples, the cryptic transitions between endodormancy, ecodormancy, and
growth initiation that are typically only modeled mathematically. No genetic techniques
are used, and the procedures either currently use or can be modified to use only
minimally sophisticated lab equipment. The techniques developed in this thesis
contribute to filling in the 5-month tissue-testing gap between leaf fall and bloom with
indicators of a plant's progress towards dormancy release.
II. LITERATURE REVIEW: FLORAL BUD DORMANCY AND DORMANCY-BREAKING AGENTS IN PISTACHIO
Executive Summary
The overarching goal of this research program has been to put control of
dormancy induction and dormancy release within a growers' control to maximize crop
performance during warm winters. A combination of new dormancy-breaking agents
(DBAs) and new decision support for both new and existing DBAs will likely be
necessary to achieve this goal.
On one hand, our review of literature and past experience suggests a wide variety
of possible DBA candidates that could be tried. Consequently, we are highly uncertain
about which candidates or formulations will eventually prove simplest and best to use. To
promptly and quickly test the efficacy and efficiency of such a wide variety of possible
formulations and chemical strategies, a systematic and efficient research pipeline needs to
be designed. Because many DBA candidates are quite costly, efficacy trials should
include dose-response trials across multiple orders of magnitude, application timing
trials, and mode-of-action studies to identify the mixtures and application strategies most
likely to be synergistic. To support registration for DBA use, efficacy trials will
eventually need to cover a range of soil types and chill accumulation regimes
representative of California's pistachio acreage.
On the other hand, we are much more certain that the industry would benefit from
transitioning from solely calendar-based dormancy management towards a framework
based additionally on chilling accumulation and/or tissue analysis. In buds, a chilling
requirement during the rest stage of dormancy is followed by a requirement for heat and
light during the quiescent stage of dormancy. We strongly suspect that some DBAs will
only work during rest and others will only work during quiescence. It is unknown if or
how the transition between rest and quiescence may be indicated by available chemical
5 5
measures. Industry researchers should prioritize developing a "chemical atlas" of the
typical course of bud development from dormancy induction through dormancy release.
In constructing a "chemical atlas" of bud development during dormancy,
researchers should take advantage of the physiological parallels between seed and bud
dormancy. In various plant tissues, dormancy maintenance and release are analogous
processes sharing regulatory pathways at the cellular level. Progress through
afterripening in seeds and endodormancy in buds seems to be indicated by antagonism
between the plant hormones ABA and GA. Scavengers of reactive oxygen species (ROS)
may be the best indicators of accumulated temperature history. Transport of sugar into
floral buds has unknown effects on the activities of many plant hormones and also affects
the performance of the inflorescences after dormancy is broken. Lastly, bud free water
status affects the activities of every other intracellular component. We therefore propose
that the "chemical atlas" survey of dormancy begin by monitoring ABA/GA levels, ROS-
scavenging activities, carbohydrates, and dehydrin abundance in buds and supporting
cambium.
Dormancy in Seeds and Buds
Dormancy can be defined as the inability to initiate meristematic growth under
favorable conditions (Rohde and Bhalerao, 2007). This surprisingly recent definition
unifies earlier notions of dormancy and dormancy release in different tissues and at
different times.
Dormancy in plants is a response to long-term conditions unfavorable for growth
and metabolism. Whole plants will go dormant in response to seasonal changes, and
individual meristems within plants may be held dormant when a plant is otherwise active.
Dormancy regulation is thus an important component of plants' allocation of resources in
space and time. Although the basic mechanisms of dormancy induction and dormancy-
6 6
breaking seem to be ancestral to flowering plants and conserved across many plant
families, generalizations from one species to another, or from one tissue type to another,
have to be made with care.
Seeds and buds are two common dormant structures in plants. While seeds are
reproductive propagules most typically associated with sexual reproduction, buds contain
miniature pre-formed structures and are more associated with the growth and persistence
of a single organism through seasons. Nevertheless, some plants also use buds as
reproductive structures, such as those that propagate vegetatively by fragmentation. Many
commercially important plants are artificially propagated via bud transfer, such as by
budding or grafting.
In most temperate plants, both seeds and buds tend to require a period of chilling
before they will resume their activity. In buds, this length of time is known as their
chilling requirement. In seeds, the undergoing of chilling treatment before germination is
known as stratification. Cambium is also a meristematic tissue and can also go dormant.
Dormancy in the cambium was first demonstrated through grafting experiments in which
cuttings grafted onto chilled wood outperformed cuttings grafted onto unchilled wood.
This observation suggests that the release of floral buds from dormancy without also
releasing the cambium that would support those buds' growth could lead to the resulting
inflorescences performing poorly.
Despite repeated recognition of similarities between seed and bud dormancy, as
well as between these processes and the vernalization of cuttings, scholars through the
20th century were quite careful to distinguish between them all, because it was unknown
whether their similarities were shared due to homology or due to functional convergence.
Yet it is now known that vernalization and the bud chilling requirement share genetic
regulatory networks (Brunner et al., 2014), as do the bud and seed chilling requirements
(Leida et al., 2012). The emerging consensus is that the dormancies of various tissues are
7 7
homologous responses, with stages that share identifiable similarities and regulatory
mechanisms. Table 1 summarizes some similarities between the physiologies of seed and
bud dormancy.
Table 1: Homologous stages of bud and seed dormancy
Bud dormancy
stage
Bud processes Corresponding
seed dormancy
stage
Advancing
forces/events
References
Paradormancy
(correlative
inhibition)
Floral induction Embryo
formation and
seed filling
Defoliation,
fruit ripening
(Lang et al.,
1987)
Endodormancy
induction
Bud scale
formation
Fruit ripening Shorter days,
decreasing
temperatures
(Tanino,
2004)
Endodormancy
(rest)
Arrested
gynoecium
differentiation
(floral buds)
Afterripening Moist chilling,
dryness
(Beauvieux
et al., 2018)
Ecodormancy
(quiescence)
Xylem
differentiation
Imbibition Light, heat,
hydration
(Beauvieux
et al., 2018)
Older Perspectives on Bud Dormancy
Lang et al. (1987) distinguished three types/stages of bud winter dormancy:
1. Paradormancy, or correlative inhibition, in which the bud is held dormant
by other plant parts, usually by high concentrations of the auxin IAA
(usually leaves). Removal of those other plant parts (e.g. by defoliation)
leads to bud burst unless a different type of dormancy is first induced.
2. Endodormancy, or rest, in which the bud is prevented from bursting by
forces internal to the bud. Chilling is thought to be the primary
environmental force that advances the bud out of this stage of dormancy,
8 8
but the biochemical mechanisms of chill forcing and chill accumulation
have remained unknown.
3. Ecodormancy, or quiescence, in which growth is repressed by
environmental factors. The accumulation of heat and light advances buds
out of quiescence and causes their meristems to resume division, resulting
in green tip. Quiescence contains what is called the "delayed-dormant"
period, between visible bud swell and green tip. Note that dormancy sensu
Rohde and Bhalerao (2007) explicitly excludes quiescence.
Ecologically, correlative inhibition is necessary for the maintenance of plant
growth form, especially in response to herbivory or pruning. In contrast, rest and
quiescence are seasonal responses to temperate winters. The transition between
correlative inhibition and rest is evinced by the shedding of the suppressing organs, and is
easier to understand than the transition between rest and quiescence.
In addition to winter dormancy, some plants exhibit summer dormancy, induced
by great heat. Summer dormancy is much more poorly studied than winter dormancy and
may provide a useful parallel for future study of dormancy induction, maintenance, and
release. Pistachio does not enter summer dormancy. For further discussion on this topic,
see the review of Gillespie and Voltaire (2017).
Historically, as noted by Nee (1986), there has been substantial confusion
between the study of breaking correlative inhibition, rest, or quiescence. Even though it is
thought that these three modes of dormancy can affect buds at the same time and use
shared chemical and genetic pathways, many studies have simply recorded the timing of
bud break after intervention and do not identify the suppressing forces in operation.
Owing to continued lack of unambiguous biochemical markers of each dormancy
stage/mechanism, this confusion persists. Indeed, the quest for such markers begs the
central question of characterizing dormancy itself.
9 9
To overcome these systematic issues, many researchers have chosen to use
repeated sampling at time points "known" to be at certain stages of dormancy to do
comparative studies between those stages. While this approach has been fruitful, such
choice of sampling times relies on the correctness of received wisdom, and is a risky
approach for our own investigations because we are working at a poorly explored
boundary between sufficient and insufficient chilling in pistachios under ongoing climate
change.
Experimentally, green tip is often used as an indicator of dormancy having ended,
but this practice is problematic. Although green tip requires dormancy release, green tip
never occurs immediately upon dormancy release, so there is always a lag. Furthermore,
green tip lies at the end of a long string of processes with an unclear beginning. Research
is ongoing to push the earliest known events in the sequence preceding green tip back
towards the onset of quiescence and the completion of rest.
Physiological Markers of Bud Dormancy
Dormant buds are identifiable by several physiological markers.
Symplastic isolation of bud cells. During dormancy, the plasmodesmata
are blocked by callose plugs that must be degraded for dormancy to be
broken. Membrane permeability is also low.
Low activity of free water. Water in dormant buds is bound by dehydrins.
Lipid storage. In Norway spruce, the first microscopic change associated
with bud burst is an increase in the size and number of lipid droplets
before the onset of heat accumulation. (Sutinen et al., 2012)
Sugars stored as starches in twigs. Levels of mono- and small saccharides
are low.
10 10
High ABA and low GA levels at the start of dormancy, this balance
reversing as dormancy progresses. These two hormones are antagonistic to
each other.
The causal relationships between these markers of bud dormancy are not well
elucidated.
Depending on the species, floral bud development may or may not be arrested
during the rest period. In Prunus avium, floral development is arrested at a stage in which
all floral whorls are present, the bud scales are brown, and the pistil shows incipient
ovary, style, and stigma (Fadón et al., 2018). In Prunus persica, there is continuous
anatomical development throughout the rest period (Reinoso et al., 2002). In Pistacia
vera, floral development is arrested in October and does not resume until March, after
rest is complete (Hormaza and Polito, 1996). Pistillate flowers of P. vera in their dormant
stage show clearly separated carpel, stamen, and sepal primordia, but no differentiated
structures are visible (ibid.). In March, the staminate primordia are absorbed into the
rapidly growing carpel primordium (ibid.).
Modeling Bud Dormancy Release
Most models of bud dormancy release take only the temperature history as the
input. To my knowledge, no models are in commercial use that explicitly incorporate
either light or moisture (fog or rain). However, the conditions that reliably induce
dormancy-breaking in seeds are dry storage or moist chilling, followed by light (Bentsink
& Koorneef, 2008). The effectiveness of moist chilling in seeds raises the interesting
possibility that chilling in the presence of free water may promote the breaking of bud
dormancy as well. Indeed, Rawls et al. (2019) showed that imposing water stress delays
bloom in almonds. Future dormancy release models ought to take water stress into
account.
11 11
Many early models of chill accumulation simply counted hours, or degree-hours,
and assumed that these units (however they were computed) were interchangeable
whenever they were accumulated during the season. The Dynamic Model was first to
challenge this assumption and was designed to reflect the observation that heat disrupts
the accumulation of small quantities of chilling (Fishman et al., 1987). Mechanistically,
the Dynamic Model posits the existence of a labile factor that can exist in two states, one
chilled and one unchilled. Chilling converts the factor to its chilled state, and heat
converts it back to unchilled. Sufficient accumulation of the labile factor in its chilled
state results in irreversible conversion into one quantum of a dormancy-breaking factor, a
Chill Portion (CP). The various rate constants for the interconversion and accumulation
steps are typically assumed to be unvarying across species. Variations in chilling
requirements between species or between cultivars can then be expressed in the number
of CP required for dormancy to be broken.
The success of modeling chill accumulation using quantized/stochastic dynamics
instead of continuous dynamics (e.g., by ordinary differential equations) itself suggests
that if a labile factor hypothesized by the Dynamic Model exists, then it is likely present
at very low effective concentration. This line of thought suggests taking a closer look at
reactive oxygen species (ROS) and brassinolides, the former because they are typically
present at low concentration and often sensed by their own chemical scavengers, and the
latter because their signaling is dependent upon aggregation and endocytosis steps
(Russinova et al., 2004) that can also create quantized responses.
A different line of thought has inquired whether the stages of rest and quiescence
(endodormancy and ecodormancy) are disjointed. The two most successful attempts to
resolve this issue have both started from the assumption that chilling accumulates during
rest and heat during quiescence. A statistical approach that assumed the existence of an
abrupt transition between rest and quiescence was successful at predicting the blooming
12 12
dates of 44 almond cultivars in Spain from temperature records alone (Alonso et al.,
2005). Later, Darbyshire et al. (2016) compared the assumptions of abrupt and gradual
transition between rest and quiescence. Their results favored gradual transition; support
was strongest for the models in which chill continued to accumulate until 75% of the heat
requirement was met. The assumption of gradual rest-to-quiescence transition underlies
the family of models now known as the Chill Overlap models (Pope and DeJong, 2017).
It remains unclear whether or when the Chill Overlap models outperform the Dynamic
model.
The newest model of dormancy completion is the T-C model (Sperling et al.
2019). This model posits that in plant tissue, temperature history is converted into a
biochemical signal through temperature effects on the interconversion between starch and
soluble sugars. Interestingly, the T-C model is capable of explaining the common
observation that chill during rest and heat during quiescence can substitute for each other.
(ibid.)
In the future, as more machine learning techniques are applied to the problem of
predicting dormancy release, approaches that integrate data across multiple species will
likely become more salient. Unfortunately, many challenges exist in the construction of
inter-species phenological models for agriculture, among which is that crops and other
plants in managed landscapes tend to be poorly included in larger ecological datasets
(e.g. the National Phenological Network.)
Dehydrins and Free Water Status
Around the turn of the millenium, the Golan-Goldhirsh lab in Israel chose
pistachio as a model system for the study of floral bud proteomes in deciduous trees
(Golan-Goldhirsh et al., 1998; Yakubov et al., 2005). They found and named two proteins
involved in dormancy, IBP32 and IBP27 (Inflorescence Bud Protein 32 kDa and 27 kDa,
13 13
respectively). IBP32 is found in male floral buds while both IBP32 and IBP27 are found
in female floral buds (Golan-Goldhirsh et al., 1998). Concentrations of these proteins are
extremely high relative to total cellular protein content during dormancy, and these
proteins are catabolized rapidly during early spring (ibid.) Sequence homology analysis
indicated that these proteins are Kn-type dehydrins (Yakubov et al., 2005). A full-length
cDNA clone of IBP32, coding for a polypeptide only 25.87 kDa large, was isolated from
male trees (ibid.) Based on the induction and localization patterns of IBP32, the Golan-
Goldhirsch lab proposed that these proteins function both as antifreeze proteins during
winter and as a store of nitrogen to be mobilized during bud break and bloom (ibid.) The
induction and localization patterns of IBP27 remain unknown, and no further studies
have been conducted on IBP27.
In fact, dehydrins have been studied in other plants, and they are known not only
to act as stores of nitrogen. Indeed, dehydrins are so named because of their ability to
bind water; they also bind ions and shield enzymes and mRNA from activity (Greather &
Boddington, 2014). In short, an abundance of dehydrins within a cell can put it into
stasis, not only sequestering the many cytosolic solutes, but also reducing the activity of
the cytosolic solvent, free water (ibid.).
Importantly, many dehydrins are natively unfolded proteins. This is the basis for
the only tenuous link that has yet been established from these dehydrins, known from
pistachio, to the genetic mechanisms known to be involved in bud break in other plants,
likely conserved in pistachio. Using qRT-PCR, the transcriptomic changes in Prunus
persica following both endodormancy completion in buds and stratification in seeds have
been linked to ER stress and the unfolded protein response (Fu et al., 2014). Those
authors did not draw a connection between the unfolded protein response and natively
unfolded dehydrins; however, I believe they provided renewed evidence that the activity
of dehydrins may be intimately related with dormancy status and the completion of rest,
14 14
contrary to a prominent earlier suggestion (Erez et al., 1998) that dehydrins and bud free
water status were more associated with cold tolerance than with dormancy status. This
conclusion would also agree with the observation that dehydrins are also expressed
during summer dormancy and in summer-dormant species are more associated with the
dormancy itself than with heat tolerance (Volaire et al., 2005).
Genetic Mechanisms of Dormancy & Dormancy-Breaking
Because our group is not using any genetic tools to monitor the physiological
effects of our applied DBAs, I shall limit the extent of discussion of the genetic
mechanisms involved in dormancy release, despite their known importance. The
understanding of plant genetic responses in bud break has developed much in recent
years, thanks both to purely genetic methods as well as to recent advances in sequencing
throughput and the design of microarrays for gene expression from whole genomes.
A relatively straightforward genetic approach to the study of chill requirements is
to cross parents with contrasting chill requirements and perform QTL mapping on the
resulting F2 generation. This approach, which effectively treats each locus as a functional
black box, was taken by Fan et al. (2010). They found that QTLs for chilling requirement
in Prunus persica were extensively colocalized, suggesting that there may be one unified
temperature sensing and action system regulating chilling requirement, heat requirement
and bloom date together (ibid.).
Whole-genome transcriptome studies have tended to link variations in dormancy
release with genes related to photosynthesis and auxin response, e.g., the work of Porto et
al. (2015). In apple, several important mRNA transcripts that are differentially expressed
in dormancy also have antisense transcripts that are differentially expressed (ibid.). These
patterns contrast with and supplement earlier findings from chemical approaches that
15 15
identified the ABA/GA antagonism as the most direct regulators of dormancy release.
Elucidating how these parts all fit together is an ongoing challenge in this field.
One important recent advance was the discovery of EBB1 (Early Bud Break 1).
EBB1 is an ethylene-responsive transcription factor. EBB1 was first isolated from
vegetative buds of Populus, in which its overexpression is sufficient to cause early bud
break, and its knockout causes delayed bud break (Yordanov et al., 2014). Since its first
report, an ortholog has since been found in both the vegetative and the floral buds of
Pyrus pyrifolia Nakai (Pham et al., 2016). Exactly how endogenous EBB1 responds to
ethylene, however, is unknown, because the ethylene-responsive transcription factors do
not directly bind to ethylene. Instead, a network of secondary sensors that integrates
crosstalk from other hormones enables the generic stress signal from ethylene to be
interpreted in the cell's instant context and situation-specific responses to be thereby
induced. It remains unknown how EBB expression is endogenously controlled.
Chemical Factors Influencing Bud Dormancy Status
ABA/GA Antagonism and the Carbon Starvation Response
It is useful to consider how the state of dormancy is induced and maintained when
evaluating potential mechanisms of dormancy release. Tarancón et al. (2017) reported a
comparative analysis of disparate plant genomes and concluded that the dormancy
induction is based upon a carbon starvation response ancestral to and conserved in woody
and herbaceous plants. Four gene regulatory networks involved in dormancy induction
were identified: 1) auxin-, gibberellin-, and ethylene-based signaling; 2) ABA-based
signaling and abiotic stress; 3) senescence and lipid/amino acid metabolism; and 4)
protein catabolism, especially ubiquitination. The former two networks are most
independent, although all the networks are connected through the latter two. The
16 16
independence of ABA-based signaling suggests that ABA is likely the single most
important hormone to monitor when studying bud dormancy.
In Betula pubescens, high ABA levels were linked to water stress and suppressed
bud break in summer dormancy (Rinne et al., 1994). In Picea abies, bud break from
winter dormancy was linked to a set of processes leading to the transport of water into the
bud, which included the development of protoxylem and the transport of water through
that newly developed protoxylem almost reaching the meristem (de Faÿ et al., 2000).
ABA suppression of dormancy release may also explain why imposing water stress on
almonds delays their bloom, as observed by Rawls et al. (2019).
ABA levels should not be considered alone. Antagonism between ABA and GA
activity is the more significant determinant of tissue-level responses, including dormancy.
Both ABA and GA are isoprenoid compounds, biosynthesized from multiple isoprenyl
building blocks (i.e., the isomers isopentenyl diphosphate and dimethylallyl diphosphate).
Isoprenyl building blocks are used in a great variety of relatively carbon-rich and
specialized cellular components, including nucleotides (as well as their biochemically
related hormones, the auxins and cytokinins), sterols, and lipidated proteins. It was
thought before that isoprenyl building blocks derive exclusively from the mevalonate
pathway, as in bacteria. In fact, it is now known that in plants, both ABA (Nambara and
Marion-Poll, 2005) and GA (Kasahara et al., 2002) are synthesized from isoprenyl
building blocks derived primarily from the methylerythritol pathway in plastids. Plastid
isoprenoid synthesis is tightly linked to photosynthetic carbon fixation (Schultze-Siebert
& Schultz, 1987), so the availability of isoprenoids is an indicator of plant photosynthetic
activity.
ABA/GA antagonism operates on at least two levels: reciprocal repression of
biosynthesis, and antagonistic regulation of downstream components (Liu and Hou,
2018). In Arabidopsis, when ABA alone is absent, GA biosynthesis is upregulated and
17 17
GA4 levels are higher. When ABA degradation is impaired, causing ABA
hyperaccumulation, the light-mediated upregulation of GA biosynthesis genes is
suppressed. These results show that GA biosynthesis is negatively regulated by ABA
(Seo et al., 2009). The negative regulation is reciprocal: GA3 also negatively regulates
ABA by inhibiting its biosynthesis. This mechanism is more clearly elucidated. GA3
degrades DELLA proteins, which induce the messenger XERICO and thereby promote
ABA biosynthesis (Ariizumi et al., 2013).
The ABA/GA antagonism is known to have a governing role in the maintenance
and breaking of seed dormancy, as covered in a recent review (Pham et al., 2018). The
ABA/GA ratio gradually decreases through dormancy (Duan et al., 2004). Different
genes likely become active at different ABA/GA ratios, so variation between genes in
their ABA/GA response threshold is likely related to the sequence of physiological
changes at dormancy release. Arabidopsis germination studies on a doubly deficient GA
and ABA mutant suggest that GA is not required to lift dormancy when ABA is absent
(Seo et al., 2009).
Instantaneous concentrations of both ABA and bioactive GA are maintained by
dynamic equilibrium of biosynthesis and degradation. This system allows resistance to
exogenous application of either chemical. While exogenous application of one chemical
may evade the inhibitory effects of the other on its own biosynthesis, large quantities of
ABA or GA will still be subject to rapid degradation, presumably with a constant half-
life.
Analysis of the dynamics of a simplified model of reciprocal antagonism
(Rabajante and Talaue, 2015) suggest that whenever there exists both an ABA-dominated
stable equilibrium and a GA-dominated stable equilibrium, there will usually also be an
unstable equilibrium that lies between the two extremes. The existence of the unstable
equilibrium in the phase space of ABA and GA concentrations, like a mountain between
18 18
two valleys, prevents direct transition between the dormant, ABA-dominated, and the
active, GA-dominated, states. Instead, a dormant tissue must make an excursion away
from the unstable equilibrium to execute the hormonal transition of dormancy release,
like a traveller walking around the mountain.
It follows that when intracellular concentrations of ABA and GA lie far from the
stable and non-stable equilibria, the dynamics of the ABA/GA system are likely very
sensitive to external forcings. This line of thought suggests that multiple DBAs may share
a common period of effectiveness. Endogenously, the diurnal cycle likely plays a very
important role during this period. Sample collection procedures and spray applications
should specify time of day.
Sugars and their Interaction with the ABA/GA Antagonism
Complicating the picture of simple progression from an ABA-dominated state to a
GA-dominated state is that GAs and ABA are both capable of conjugating with sugars.
GAs, being acids, can form glucosides. These glucosides may have a storage role,
enabling bioactive GAs to be quickly released. For example, GA20-glucoside can act as a
substrate of the enzymes GA3ox and GA2ox (Schneider et al., 2002), suggesting that GA
precursors can be synthesized, glucosylated, and transformed to glucosides of bioactive
GA, which would then directly release bioactive GA upon hydrolysis. ABA also forms an
inactive glucose ester (often abbreviated ABA-GE), so conversion of ABA to ABA-GE
could similarly sequester ABA.
The interplay between the hormones GA and ABA and tissue-level sugar
dynamics has not been given as much attention as it perhaps deserves, because during
most of the growth season a steady-state concept of tissue-level sugar budget is often
tacitly assumed. However, extensive sugar mobilization between tissues is involved in
the dormancy-breaking process. In pistachio, twig starch is mobilized into bud soluble
19 19
sugar beginning in early February and continuing throughout March (Zhang, 2018),
preceding bud break which typically occurs only in April.
The effect of changes in sugar levels on the bioactive GA-ABA balance would
likely depend on the relative kinetics of GA and ABA esterification to the chemically
sequestered forms GA-glucoside and ABA-GE, respectively. Further understanding and
modeling of exogenously forced ABA/GA/sugar dynamics, including those induced by
GA spray treatments, will likely remain elusive until the catalytic pathways that govern
ABA/ABA-GE and GA/GA-glucoside equilibria become well elucidated. Currently, the
enzymes governing ABA/ABA-GE equilibrium are better studied, e.g., by Schroeder and
Nambara (2006), while even the identity of the enzymes that catalyze the GA
glucosylation reactions remain unknown.
Some conceptual predictions are nevertheless possible. Before bud break, the
photosynthetic production of sugar is negligible, so the main source of sugar in buds is
mobilization from storage. The main sugar sinks opposing the accumulation are
respiration and sugar polymerization into starch, both of which have rates that are
dependent on temperature. Diurnal fluctuation in temperature causes similar fluctuations
in respiration, which means that during the day, the depletion of cytosolic sugar may thus
release impulses of both GA and ABA into the cytosol. As days get longer and warmer, a
progressively greater portion of a gradually increasing sugar pool is catabolized. If the
cellular response to the released GA is greater than the response to the released ABA,
then this impulse may function as a carbohydrate-dependent trigger linking ABA/GA
antagonism to the accumulation of carbohydrate reserves adequate to support subsequent
growth.
Strong support for this theory can be found in the barley germination research.
Treatment of the barley scutellum with sucrose, glucose, or maltose prevents GA
production/release, while sugar depletion promotes GA release (Radley, 1969). Briggs
20 20
(1992) first advanced the hypothesis that depletion of sugar in the barley scutellum
during germination leads to stimulation of GA synthesis or release. I have not been able
to uncover whether the formation of GA glucoside has ever been directly implicated as
the mechanism of sugar action.
As for perennial plants, bloom probabilities for almonds in the spring have been
linked to the previous season's carbohydrate status (Fernandez et al., 2018), and the T-C
model of bud break in almonds (Sperling et al. 2019) is based upon the mechanistics of
sugar-starch interconversion in the twig. Clearly, elucidating the interplay between
starch-sugar interconversion and ABA/GA antagonism now presents an important
frontier in understanding endodormancy release/the rest-to-quiescence transition.
In summary,
GA and ABA levels are both maintained by the balance between synthesis
and degradation.
GA and ABA reciprocally negatively regulate each other.
This system of reciprocal negative regulation has two stable states, an
ABA-dominated state and a GA-dominated state. These states are
separated by an unstable state that is necessarily circumvented during both
dormancy induction and dormancy release.
Cellular perception of ABA and GA is strongly affected by intracellular
sugar levels.
GA-glucosides and ABA-GE are both physiologically important reservoirs
of sugar-bound phytohormones. Each may serve as a hormone reserve that
is resilient to degradation by processes induced by the antagonistic
hormone.
The accumulation of cytosolic sugar preceding budbreak may enhance GA
sequestration as GA-glucoside as well as ABA sequestration as ABA-GE.
21 21
Following sugar consumption events, the release of bioactive GA from
accumulated GA-glucosides may trigger transition from a dormant ABA-
dominated state to an active GA-dominated state.
The regulation of catalytic mechanisms of GA glucosylation and
hydrolysis remain understudied.
Reactive Oxygen Species (ROS)
Reactive oxygen species, including ●O2- (superoxide) and H2O2 (hydrogen
peroxide), function as signaling molecules in plants. Because of the many deleterious
effects that ROS-induced oxidative stress has on animal cells, it was long thought that
cell death in plants caused by ROS was also due to toxicity. A newer view is that ROS-
induced plant cell death is programmed, and that healthy baseline levels of ROS are
needed for cellular proliferation and differentiation (Mittler, 2017).
Beauvieux et al. (2018) reviewed the known involvement of ROS in dormancy
release. The NADPH oxidase family of enzymes are important sources of ROS in plants.
NADPH oxidases can generate ●O2- or H2O2. ROS generated by NADPH oxidase act as
downstream effectors for brassinolide signaling (Xia et al., 2009). In Arabidopsis, ROS
signaling activates a MPK3/MPK6 signaling pathway in response to cadmium stress (Liu
et al., 2010). In Arabidopsis (Liu and Zhang, 2004; Li et al., 2012; Ye et al., 2015) and
rose (Meng et al., 2014), the MPK3/MPK6 signaling pathway upregulates ACC synthase,
the enzyme that catalyzes the rate-limiting step in ethylene biosynthesis.
ROS are typically not accumulated; instead, they are quickly scavenged by an
array of sensor chemicals. Consequently, while ROS generation by NADPH oxidase can
be measured directly (Cortés-Ríos et al., 2017), ROS-related activity is also commonly
measured by proxy, using the activities of the enzymes that catalyze specific ROS-
scavenging reactions. Commonly measured enzyme activities include those of catalase,
22 22
ascorbate peroxidase, and polyphenol oxidase. For example, a recent report from walnuts
implicated differences in these enzyme activities, and not carbohydrate status, as being
involved with differences in chilling requirements between cultivars (Gholizadeh et al.,
2017).
In seeds of Bunium persicum, cold stratification alters endogenous ROS content
and induces a dormancy release process involving interplay between the ABA/GA
antagonism and ROS (Amooaghaie and Ahmadi, 2017). With only 5 weeks' cold
stratification, GA failed to stimulate germination without aid from a secondary source of
ABA biosynthesis inhibition, either fluridone or an ROS donor (ibid.) Even with 15
weeks' stratification, ROS donors failed to stimulate germination in the presence of
paclobutrazol (ibid.) These results suggest that ROS may be needed to induce dormancy
release in seeds, and GA may be needed to finish it. The applicability of these results to
the context of bud dormancy is worth investigating.
Reactive Nitrogen (Nr), Nitric Oxide and Cyanide
Several forms of reactive nitrogen (Nr) are plant hormones, including nitrate,
nitrite, nitric oxide (NO), and cyanide. These four compounds all share a common
dormancy-alleviating pathway that involves NO (Bethke et al., 2006). The NO scavenger
cPTIO (carboxy-2-phenyl-4,4,5-tetramethylimidazole-1-oxyl-3-oxide) blocks the
dormancy-alleviating effect of all four compounds (ibid.) Exogenous NO increases
expression of CYP707A2, the enzyme that degrades ABA, and cPTIO suppresses the
same (Liu et al., 2009), indicating that NO modulates the ABA-GA antagonism by
promoting ABA degradation.
Recently there has been interest in nitroxyl anion (NO–), a diradical isoelectronic
to dioxygen, which is spontaneously formed from NO under reducing conditions at high
pH, such as present in the cytosol. It is thought that some of the activity that has
23 23
historically been attributed to NO may actually be due to NO–. Nitroxyl will bind to thiols
in proteins (cysteine residues), but this binding is very specific and the mechanisms of
specificity are not known. The binding process is thought to involve nucleophilic attack
of the nitroxyl N on the sulfur, so active-site thiol groups coordinated to metals may be
more vulnerable.
Jasmonic Acid
Jasmonate, also known by its protonated form jasmonic acid (JA), is a plant
hormone that has emerged as a key player in the decision between cell acclimation and
cell death in response to the ROS 1O2, singlet oxygen (Laloi and Havaux, 2015).
However, reports concerning the role of jasmonate in bud burst are sparse. Activation of
the endogenous JA signaling pathway has been demonstrated in H2NCN-assisted sweet
cherry budbreak (Ionescu et al., 2017).
Jasmonic acid itself is not bioactive (Staswick and Tiryaki, 2004). The JA
signaling pathway actually recognizes an amino-acid conjugated form, the most active of
which is JA-isoleucine (JA-Ile). JA tends to conjugate with α-amino acids that have short
aliphatic side chains, producing JA-Val, JA-Leu, JA-Phe, and importantly, JA-ACC.
(ibid.) (ACC is an α-amino acid too, just not one of the 20 amino acids used to build
proteins.) Concentrations of JA-ACC are physiologically significant, and are elevated
when JA-Ile formation is deficient. (ibid.)
Conjugation of JA to both Ile and ACC is achieved by the formation of an amide
bond between the carboxylic acid group of JA and the amine N of the amino acid. In
particular, because ACC is proposed to bind to ACC oxidase in bidentate fashion using
both its amino and its carboxylic acid group (Rocklin et al., 1999, 2004; Zhang et al.,
2004), conjugation of JA to ACC likely inactivates ACC and prevents it from binding to
ACC oxidase. Free JA therefore inhibits ethylene biosynthesis. Interestingly, JA-ACC is
24 24
not effective as a JA signal either (Staswick and Tiryaki, 2004). These observations
suggest that JA "crosstalk" regulation of ethylene biosynthesis may actually have been
JA's most ancestral function, and signaling machinery later evolved around JA-Ile to
sequester and sense JA not bound to ACC.
As reviewed by Hou et al. (2013), the interaction between the JAZ proteins and
DELLA proteins, which are targets of JA and GA signaling respectively, creates crosstalk
between these two pathways. Future work on JA’s role in dormancy release will likely
revolve around its interplay with GA, ethylene, and ROS.
Brassinolides
Reports of the use of brassinolide on perennials are rare; one study in Vitis
vinifera × V. labrusca (Kojima et al., 1996) suggested that brassinolide did not stimulate
budbreak alone, but enhanced the effect of applied CaNCN (calcium cyanamide). The
label of the commercial product Repar, whose sole active ingredient is 0.1%
homobrassinolide, contains directions for use in rhubarb to substitute for a lack of chill
accumulation.
Brassinolide signaling depends both on the aggregation of transmembrane
receptor kinases into 'islands' in the plasma membrane and on clathrin activity (Russinova
et al., 2004). This latter dependency indicates that brassinolide signaling involves at least
one endocytosis step, possibly of the receptor kinase islands themselves. Brassinolide
signaling induces ROS generation at the membrane by NADPH oxidase (Xia et al.,
2009). The inhibition of ROS generation by NADPH oxidase and the scavenging of H2O2
both interfere with BR induction of downstream genes (ibid.).
25 25
Dormancy-Breaking Agents (DBAs) and Their Modes of Action
Any physical or chemical stimulus applied to plants that facilitates their
emergence from dormancy can be used as a dormancy-breaking agent (DBA). Because I
have used the term "rest" as a synonym for endodormancy, in this section I avoid the
uncareful use of the colloquial term "rest-breaking agent" because not all the known
DBAs are known to affect the accumulation of chill, or otherwise hasten rest completion.
To my knowledge, only H2NCN, oxirane, thiocyanate, homobrassinolide, and GA3 have
been shown to substitute directly for chill’s contribution toward rest completion (the first
notably in contravention of its own label text); these chemicals may properly be called
rest-breaking agents (RBAs). Other chemicals historically used as DBAs, like oil and the
dinitro compounds, likely function as quiescence-breaking agents (QBAs) only. QBAs
may advance bloom and narrow the bloom window, but do not substitute for chilling.
Horticultural Oil
Horticultural oils are the most commonly used DBAs on pistachio in both
California and Iran. Together these two regions account for ~76% of the world's pistachio
production. Oil's dormancy-breaking activity has been known since 1950 at latest.
Weinberger (1950) noted the efficacy of the combination of oil and 2,4-dinitro-o-cresol
(DNOC) on peaches. Oil's dormancy-breaking activity on California pistachios was first
noticed by Bob Beede when it was used in combination with carbaryl during efficacy
trials for scale insect control (Beede et al., 1993). Despite this history, oil is only
currently registered in California for scale insect control. Even though using oil as a DBA
remains off label, government regulators have not objected because effective application
rates are not above maximum label rate for scale insect control. In Beede’s previous
dose-response trials (2007), an application rate of ~6% gave the best results; lower rates
seem ineffective, and should be avoided (ibid.).
26 26
In Iran, there are several commercially important pistachio cultivars with different
chilling requirements. In contrast, most California pistachio orchards are a single pair of
cultivars, 'Kerman' females and 'Peters' males. Yields in the 'Kerman'/'Peters' system have
been harmed when less than 65 CP are accumulated, and are below average when less
than 59 CP are accumulated (Pope et al., 2015). From 1993 to 2007, 59-65 CP had
typically accumulated by late January or early February, which is also when the
application of oil was determined to be most advantageous by Beede (2007). It therefore
seems plausible that oil is best used at the onset of quiescence, just after rest is
completed. Indeed, Beede (ibid.) notes that oil should be used on fully rested trees and
does not contribute chilling hours to the tree. Thus, with ongoing climate change bringing
warmer winters and less fog, it is uncertain whether the onset of quiescence might shift
earlier or later in the year. It may become important to update calendar-based oil use
recommendations, or develop new tissue-based diagnostics, to determine appropriate
application time.
Little is known about oil's mode of action as a dormancy-breaking agent. Various
suggestions exist: that oil coats the buds and causes anoxia; that oil chemically breaks the
bud scale coat and improves O2 diffusion into the bud interior; that it increases
respiration; that it decreases respiration; that it increases membrane permeability; that its
metabolites are weakly cytotoxic. Most of these suggestions are based on the admittedly
correct idea that budbreak can be promoted by nearly any source of sublethal stress (Nee,
1986), but this plethora of possibilities needs winnowing. More reports of tissue-level
responses following the application of currently commercially available oils are needed.
Interestingly, one of the first symptoms of incipient budburst is an increase in the
size and number of lipid droplets present in bud cells (Sutinen et al., 2012). Changes in
the size and composition of intracellular lipid droplets change the activity of lipid-droplet
associated proteins and can result in downstream cellular changes, as recently reviewed
27 27
(Huang, 2018). Our estimation of the amount of oil introduced by a 6% application rate at
~ 4 liters per tree shows that the total weight of oil applied to a tree is comparable to the
weight of the dormant buds themselves, suggesting that the potential role of oil as a lipid
and carbon source cannot be ignored. Thus, I add my own speculation to the existing pile
of suggestions and propose that added oil may diffuse into bud cells and increase the size
of intracellular lipid droplets upon incipient budbreak. This hypothesis could be tested
with microscopy.
DNOC and the Dinitrophenol Derivatives
In the past, 2,4-dinitro-o-cresol (DNOC) was used as a DBA, especially in
admixture with oil (Weinberger, 1950). But because the compound is cumulatively toxic
to a broad range of humans and animals, does not eliminate easily from the body, and
persists for a long time in the environment, its use is heavily disfavored. (In some
jurisdictions DNOC is also banned because it can be used to synthesize explosives.)
DNOC is a dinitrophenol derivative, and many dinitrophenol derivatives share a common
mode of action that is to dissipate the electromotive gradient across the mitochondrial
inner membrane and consequently uncouple respiration from ATP generation
(McLaughlin, 1972). The application of dinitrophenol to plant cells results in rapid CO2
evolution and elevated sugar consumption as the Krebs cycle continues to run while
producing minimal ATP (Sovonick et al., 1974). Thus, in addition to inducing sublethal
stress and producing heat, the dinitrophenol derivatives may also elicit a downstream GA
signal due to sugar consumption, as we discussed above. In apple, the dinitrophenol
derivatives seem to be effective only after the chilling requirement has been fulfilled
(Jackson, 2005). This experience suggests that DBAs whose sole mode of action is to
target respiration may only break quiescence and not rest.
28 28
Exogenous Gibberellic Acids
Both GA3 and GA4 have been used as rest-breaking agents before. Exogenous GA
is especially effective at breaking dormancy on those seeds that require light to
germinate, suggesting that light perception in seeds is GA-mediated (Derkx & Karssen,
1993). Also, by analogy with the role that GA plays in seed dormancy, GA may restore
symplastic communication between the bud and other tissues by inducing the production
of glucanases (Leubner-Metzger, 2003).
Some commercial GA formulations are currently registered to break dormancy in
rhubarb and seed potato, as well as to promote germination/emergence in rice (Fine
Americas, 2014). GA3 is also used as a breaker of floral bud dormancy in the ornamental
plants. For example, the label of the commercial formulation ProGibb (Valent
Biosciences, 2014) includes instructions for use in ornamentals; the product’s claimed
benefits include substituting for the chill requirement, accelerating bloom, and increasing
bloom size. GA3 also delays senescence in cut gerberas (Emongor, 2004). GA4 is thought
to have a more restricted set of activities than GA3, yet GA4 alone is sufficient to induce
dormancy-breaking in Prunus mume, Japanese apricot (Zhuang et al., 2015).
Notably, GA3 does not universally promote budbreak; a recent study in Vitis
vinifera identified a threshold date before which GA3 application retarded budbreak and
after which it advanced budbreak (Zheng et al., 2018). The mechanism behind this
behavior is unknown, nor is known the extent to which this behavior is general among
plants.
In pistachio, GA3 has budbreak-promoting effects when applied in early winter,
i.e., December or January (Tzoutzoukou et al., 1998). Paclobutrazol (PBZ), a GA
synthesis inhibitor, retards pistachio bloom (Porlingis and Voyiatzis, 1993), and those
authors proposed the use of PBZ on male trees to delay anthesis and thereby improve
bloom overlap. Unfortunately, the combination of cultivars 'Kerman' & 'Peters' used in
29 29
California typically suffers the opposite problem, with 'Peters' blooming later than
'Kerman' in low-chill years.
The dose range that has been tested on pistachio is from 2500 ppm to 40000 ppm.
This range is not economical. However, mathematical modeling of GA biosynthesis and
degradation dynamics predicts that the GA dose needed to saturate a plant cell's GA-
processing machinery is only on the order of 3-10 μM = 1-3 mg/l (Middleton et al.,
2012). Thus, repeated applications of lower GA doses might be just as effective and more
cost-effective as large single doses.
Reactive Nitrogen and Cyanide
A mixture of calcium nitrate, ammonium nitrate, and urea is used as a budbreak-
promoting agent under the trade name Erger. In sweet cherries, Erger has been found
effective when applied after H2NCN would be applied but before oil would be applied
(Glozer et al., 2005; Southwick et al., n.d.).
Cyanide donors, as a class, include thiocyanate (SCN-), nitroprusside
[Fe(NO)(CN)5]3-, and hydrogen cyanamide (H2NCN). Thiocyanate reduces the cold
storage requirement of potato tubers and has been known as a rest-breaking agent since
the 1920s. Nitroprusside as a soaking treatment can break seed dormancy (Hayat et al.,
2014), but nitroprusside cannot be used as a spray treatment because it acts as a strong
vasodilator in humans and poses a safety risk. I discuss cyanamide in its own section.
As in animals, cyanide inhibits plant mitochondrial cytochrome c. However, the
plant mitochondrial electron transport chain has a cyanide-insensitive alternative oxidase
(AOX) located downstream of the ubiquinone shuttle (Juszczuk and Rychter, 2003). The
presence of AOX enables plants to respire O2 in the presence of cyanide, but transporting
electrons through AOX is less energy-efficient than transporting them through Complex
III/IV and cytochrome c (ibid.). Thus, increased bud respiration may not indicate that bud
30 30
tissues are assimilating more energy. It may instead reflect increased consumption of
carbohydrates to satisfy constant energy demands. Moreover, the energy contained in the
extra consumed carbohydrates cannot go nowhere; if not captured in the form of ATP,
catabolism of carbohydrates by increased respiration will instead release heat, which may
also contribute to dormancy release.
Cyanide also inhibits catalase in the cytosol, resulting in accumulation of H2O2.
This could be the first step in a putative positive feedback loop, in which:
ROS signaling triggers a MAP-kinase cascade (Liu et al., 2010) that upregulates
ACC synthase (Li et al., 2012; Meng et al., 2014; Liu and Zhang, 2004);
up-regulated ACC synthase catalyzes the rate-limiting step in cyanide and
ethylene generation;
cyanide concentrations increase, which inhibits catalase and facilitates further
H2O2 accumulation.
Hydrogen Cyanamide
Cyanamide (H2NCN) is used on a wide variety of high-value, high-chill fruit
crops like apples (Jackson and Bepete, 1995), sweet cherries (Wang et al., 2016), and
grapes (Dokoozlian et al., 1995) to enable their cultivation in low-chill environments.
Like oil, H2NCN has a cryptic mode of action and is only effective in a narrow window
of time. Successfully predicting this window to provide decision support to users of
H2NCN is an active area of public- and private-sector horticultural research.
Consisting of an electrophile covalently bound to a nucleophile, H2NCN is a very
reactive molecule. Its dimer, which always coexists with the monomer wherever the
monomer is present, is even more reactive and will spontaneously polymerize peptides
(Danger et al., 2013) and phosphorylate sugars and nucleotides (Steinman et al., 1966).
31 31
Because of cyanamide’s extremely broad spectrum of potential reactivities, it has been
difficult to propose simple mechanisms of action.
While H2NCN in Prunus avium activates the cytokinin pathway, the jasmonate
pathway, and the cyanide pathway, it does not activate the EBB ortholog: this result
demonstrated that EBB is sufficient but unnecessary to induce early bud break (Ionescu
et al., 2017). Exactly how the H2NCN-induced activity in these pathways induces bud
break either independently or downstream of EBB is unknown.
The oxidation of H2NCN by catalase first creates N-hydroxy-cyanamide, which
then is sequentially oxidized to nitrosyl cyanide (Shirota et al., 1996). Dissociation of
nitrosyl cyanide can then produce hydrocyanic acid (HCN), azanone (HNO), nitrite and
CO2 (ibid.). Cyanamide thus may act as both a cyanide donor and as a nitroxyl donor.
Additionally, cyanamide may scavenge ethylene. Ethylene is the simplest olefin,
and synthetic chemists have used the attack of cyanamide on an olefin double bond in the
presence of a free-radical donor to produce vicinal diamines (Jung and Kohn, 1985). The
possible ethylene-scavenging activity of cyanamide has never been suggested before as
part of its mode of action. Oxidation of ACC in the cytosol stoichiometrically releases
cyanide and ethylene, and the regulation of toxic cyanide concentrations is actually
accomplished through the ethylene byproduct (Goudey et al., 1989). Specifically,
ethylene induces beta-cyanoalanine synthase activity, which is the primary way for plants
to detoxify free cyanide (ibid.). Consequently, any quenching of cytosolic ethylene by
H2NCN would further spur a cyanide-catalase-ROS-ACC synthase positive feedback
cycle and aid it to escape its endogenous control. In a manner consistent with this theory,
even though H2NCN itself is quickly hydrolyzed into urea after application to plants,
prolonged and high levels of ethylene release occur after H2NCN application (Nee, 1986;
Ionescu et al., 2017).
32 32
Trials of H2NCN on pistachio have been conducted in almost every major
producing region worldwide. In Greece, Pontikis (1989) achieved budbreak advancement
of 19 days by applying H2NCN. Iranian researchers applied H2NCN and oil, alone and in
combination, and found budbreak advancement of 15-20 days with the best combination
of treatments (Rahemi and Asghari, 2004). Muller (2008) described H2NCN applied to
pistachio trees but reported no phenology data. Interestingly, Muller noted that H2NCN
appears to break the apical dominance of pistachio (ibid.). Researchers in Tunisia
advanced bud break by 15 days and bloom by 11 days using 4% H2NCN sprayed 45 days
before budbreak (Ghrab and Mimoun, 2014).
Garlic Extract and Diallyl Disulfide
One potential alternative to H2NCN that has emerged is diallyl disulfide. Garlic
extract has been used with success for the accelerated breaking of buds in ‘Anna’ apple in
Egypt (Rady and Seif El-Yazal, 2014) and in ‘Kyoho’ grape in Japan, and diallyl
disulfide is the most consistently active ingredient in garlic extract (Kubota et al., 1999).
The diallyl tri- and tetra-sulfides also present in some commercial garlic oils may have
similar (even enhanced) activity compared to diallyl disulfide (ibid.). In human cells,
diallyl disulfide induces GSH production and increases intracellular concentrations of
ROS, inducing apoptosis (Wu et al., 2005). Its allyl groups have a similar-shaped HOMO
as that of cyanamide, again suggesting possible ethylene-scavenging activity. Diallyl
disulfide is also safer than cyanamide and would likely be compatible with USDA
organic production because of its derivation from garlic. Currently, the synthetic route to
diallyl disulfide is cheaper than its extraction from garlic oil. Its minimum effective dose
is unknown, and its use, both alone and as an adjuvant, should be tested.
33 33
Exogenous Ethylene and Ethylene-Related Compounds
2-chloroethanol was already known as a rest-breaking agent in the mid-20th
century. When single buds on twigs with multiple buds were exposed to the vapors of 2-
chloroethanol solution in water, using a flask to contain the vapors, only the treated buds
broke (Denny and Stanton, 1928). In fact, that experiment was the one that first justified
the notion of rest being maintained by factors internal to the bud, giving rise to the
modern notion of endodormancy.
The primary constituent of the vapors of 2-chloroethanol is ethylene oxide (EtO,
or oxirane). EtO is formed from 2-chloroethanol in basic aqueous conditions by
nucleophilic elimination of HCl. In plants, ethylene oxide is a product of ethylene
metabolism, and as a plant growth regulator it is not very well studied; its closest known
physiological link is to flooding resistance (Dodds et al., 1982). Because ethylene can
usually escape the cell by diffusion, the activation of a cellular mechanism that detoxifies
excess ethylene to ethylene oxide could be indicative of a need to escape from
anaerobiosis (Voesenek et al., 1992), such as caused by extremely enclosed conditions
like flooding, or possibly bud scale encapsulation.
The involvement of ethylene oxide in dormancy release suggests the possible use
of exogenous ethylene as a DBA. Indeed, ethylene signal transduction mutant studies
suggest that ethylene may suppress dormancy maintenance by inhibiting the action of
endogenous ABA (Beaudoin et al., 2000). Studies of the germination of dormant sweet
corn seeds linked a double soak treatment with ethylene and spermidine to reduced ABA
and increased ROS levels, promoting germination (Huang et al., 2017).
However, previous results from pistachio are that applied ethephon has a
complicated dose-response relationship with bud break date. Late-winter application of
ethephon to pistachios in Iran delayed bud break (Askari et al., 2011), and higher
concentrations of ethephon might delay it less. Ethylene dose-response bioassays suggest
34 34
that the active concentrations of gaseous ethylene capable of suppressing ABA are in the
range of 0.1-10 mg/L air (Zhang and Wen, 2010). Further trials are necessary to elucidate
the shape of the ethylene and ethephon dose-response curves in pistachios and identify
the effective dose range and effective application time or window.
Aminoethoxyvinylglycine (AVG)
As discussed previously, ROS signaling activates a MAPK signaling cascade (Liu
et al., 2012) that has many potential effects, including upregulation of ACC synthase (Li
et al., 2012; Meng et al., 2014; Liu and Zhang, 2004), the enzyme that catalyzes the
terminal step in cyanogenic ethylene biosynthesis. Thus, an ACC synthase inhibitor like
AVG (4-(2-aminoethoxy)-2S-amino-but-3-en-1-oic acid hydrochloride) would probably
break an important link between ROS signaling and downstream effects depending upon
either ethylene or cyanide. Activation of a cyanide signaling pathway is part of the mode
of action of H2NCN (Ionescu et al., 2017), so the cyanide signaling pathway is likely
budbreak-promoting; we thus speculate that AVG application would retard budbreak and
bloom.
Due to the interactions between their expected modes of action, a double
application of AVG and H2NCN could be enlightening, though likely ineffective. Such an
experiment could elucidate how H2NCN's effectiveness may depend upon ACC synthase
activity, especially the latter's role in the positive feedback loop proposed here.
Exogenous Jasmonic Acid/Jasmonate
JA is new as a potential dormancy-breaking agent, and is not likely to become
economical for use in the near future. As previously discussed, because free JA binds
ACC, JA fluctuations or JA signaling could have mixed effects upon ethylene and
cyanide biosynthesis and signaling (Van de Poel and Van der Straeten, 2014). In Pyrus
communis seeds, JA accelerates dormancy release when applied early in dormancy but
35 35
delays dormancy release when applied late (Yildiz et al., 2008). Elucidating the JA
application timing effects and dose response would provide useful applied data and help
narrow down its mechanisms of action.
Future Directions
Elucidating the Role of Carbohydrates and Respiration In DBA Action
Endogenously, resumption of growth in the spring is associated with increases in
carbohydrate movement (Tixier et al., 2019), increased respiration (Malyshev et al.,
2016), increased availability of free water (Faust et al., 1997), lipid biosynthesis (Sutinen
et al., 2012) and other undoings of the markers of dormancy. But we do not know which
of these signs are linked into the core causal chain of events that result in growth
resumption, and thus we do not know which of these signs could be used to assay DBA
effectiveness.
Additionally, despite there being many reports of how DBAs affect the timing of
growth resumption, there are fewer reports on how DBAs affect the quality of growth
thereafter, and even fewer still on how the DBAs affect the movement of energy before
growth resumption.
The literature has left unanswered a central question of how applied DBAs affect
the mobilization of carbohydrates into buds before bloom and leaf-out. In view of
potential crosstalk between starch-sugar interconversion and the ABA/GA antagonism,
identifying any tradeoffs that may exist between DBA use, carbohydrate status, and yield
is a key priority.
Improving Bud Diagnostics
Science-based DBA-timing decision support is highly sought. Given that a grower
has procured a DBA, the main uncertainty that they face is when to apply it; this
36 36
uncertainty is enough to deter some growers from using a DBA at all. Most existing
heuristics are based on either calendar date (e.g. "oil is best in mid-February or earlier")
or on the outputs of chilling accumulation models (e.g., "use the Dynamic Model; apply
Dormex at 42-50 CP or CAN at 42-53 CP"). In contrast, hardly any recommendations are
currently based upon direct measurement of the dormant buds themselves. Assays based
upon enzymatic activities, phytohormone levels, mRNA expression, miRNA expression,
and free water status may all have promise. Techniques would need to be first developed
and then refined to achieve the high throughput and low cost that would be needed to
support industry.
We strongly suspect that some DBAs will only work during rest and others will
only work during quiescence. It is unknown if or how the transition between rest and
quiescence may be indicated by available chemical measures. Industry researchers should
prioritize developing a "chemical atlas" of the typical course of bud chemical
development from dormancy induction through dormancy release.
Because many existing DBAs seem to perform best when applied close to rest
completion, methods of assessing whether buds have rested completely, or will likely
have rested adequately by the time of a scheduled spray, are highly desirable. Many
observable physiological changes occur near the end of rest and the onset of quiescence,
including changes in phenol content, redox potential, dehydrin abundance, and free water
content. In the past, 1H-NMR has successfully been used to assess the content of bound
and free water as a proxy for the dormancy state of buds in Malus (Faust et al., 1991),
Vitis (Gardea et al., 1994), Tulipa (Okubo et al., 1996), and Prunus (Erez et al., 1998). It
seems obvious that the same approach could work in Pistacia.
Improved bud-based methods of assessing whether or not a DBA substitutes for
the chilling requirement would be valuable. The first step would likely be to identify a
reliable indicator of chilling accumulation as experienced by the plant tissue. One starting
37 37
point would be to establish whether the ABA/GA ratio declines throughout
endodormancy in Pistacia, as it does in Prunus (Duan et al., 2004).
Lastly, reactive oxygen species (ROS) and their scavengers may be the best
indicators of accumulated temperature history (Beauvieux et al., 2018).
We therefore propose that the "chemical atlas" survey of dormancy begin by
monitoring ABA/GA levels, ROS-scavenging activities, carbohydrates, and dehydrin
abundance in buds and supporting cambium.
Investigating Alternatives to H2NCN
H2NCN's triple combination of donating both nitroxyl and cyanide and triggering
the prolonged evolution of ethylene is unique. It remains unclear which combination of
these functions, or H2NCN's indeterminate other functions, is instrumental in promoting
uniform bud break. If H2NCN is to be replaced with less noxious alternatives, chemicals
that mimic each of its activities should be tested alone and in combination. For example,
a combination of horticultural oil (mimicking the cytochrome c respiration inhibition),
ethephon (mimicking the prolonged ethylene release), and calcium ammonium nitrate
(equal to the added N) could be tested.
Designing an Efficacy Trial Pipeline for DBAs
Any efficacy trial pipeline has to systematically reduce the operational
uncertainties associated with applying the tested compound/mixture. Additionally, one of
the regulatory purposes of efficacy trials is to develop the label text, which contains
clearly defined statements of benefit along with exclusive directions for registered use on
crops. In the case of DBAs, the results of efficacy trials are also being used to develop
new hypotheses about physiological responses and modes of action, so enhanced
physiological monitoring is needed throughout the trials.
38 38
Both FAO and EPA have issued guidance documents that outline expectations for
efficacy trial documentation that would support registration. FAO's 2006 guidelines on
efficacy evaluation for the registration of plant protection products are more general than
EPA's guidelines for the efficacy testing of pesticides. On the other hand, EPA's
guidelines cover not only efficacy but also safety, with individual guidance documents
regarding product properties, fate/transport/transformation, spray drift, ecological effects,
residue chemistry, health effects, occupational/residential exposure, and endocrine
disruption screening. Some specific challenges relevant to efficacy trials for DBA
development are discussed below.
Dose-response trials of individual DBAs should be done to establish at least a
minimum effective dose (MED), and if possible, an effective dose range (EDR) for each
candidate. To my knowledge, it has not been well established whether the concentration
or the dose of applied PGRs is more important for the reproduction of dormancy-
breaking effects. Laboratory studies typically report applied concentration. In contrast,
growers typically operate in terms of per-acre doses delivered in fixed spray volumes.
Neither norm directly measures PGR uptake. Our approach is currently to spray known
concentrations to drip and report final volume used per tree, from which per-acre doses
can be calculated. Ideally, the MED and 75% or 50% the MED will be tested
concurrently as part of the final registration package (FAO, 2006), but to find the rate
eventually recommended, 3 or 4 orders of magnitude may need to be explored.
Application timing trials of individual DBAs are also necessary. In the
exploratory stage, these trials will be necessarily combined with dose-response trials,
because for many leading candidate DBAs (H2NCN and GA notably), the dose response
varies strongly with application time. Developing an effective rapid screening procedure
may be needed to cost-effectively winnow down the possibilities. The concept here
would be to cut shoots at regular intervals throughout winter, apply a range of DBA
39 39
concentrations to the shoots, force them in growth chambers, and observe how the
minimum effective dose varied with application time using the rapid screen. The rapid
screen is necessary to alleviate space constraints in the growth chambers and ensure that
carbohydrate limitation in the cuttings minimally skews the results.
Application mode trials of individual DBAs should be considered. Painting the
cut surface of a cutting and thereby introducing the compound to buds via the developing
xylem has different results from exposing a cutting via spray or painting the twig surface.
Some compounds give good responses one way, but not the other; for example, dimethyl
sulfide volatiles will promote bud break, but dimethyl sulfide does nothing when
introduced via the xylem. At low enough concentrations, introducing DBAs through the
irrigation during winter leaching or during aquifer recharge events could also be tried.
Trials across the entire range of likely geographic use are needed to give
confidence in the product's efficacy on the full range of production conditions to be
experienced. California’s diversity of chill accumulations and soil types, especially saline
and non-saline soils, makes this aspect of the efficacy trials difficult. The endogenous and
DBA-forced dormancy release responses are also likely to be entangled with water stress
as well as winter water management practices.
Adverse effects trials including trials for phytotoxicity, crop quality and yield
gain/loss are standard in pesticide testing. DBAs are relatively standard in this aspect.
Historically, there has been substantial interest in DBAs as potential growth accelerators
for pistachio. Growth acceleration may lead to improved nut weight and quality, or it may
lead to earlier harvest, which may give growers a way to dodge late-season navel
orangeworm damage. Beede (2002) used surveys of nut development at the onset of
kernel fill as a cost-effective method of evaluating horticultural oil for growth
acceleration.
40 40
As modes of action become elucidated through continued experiment, synergy
trials of mixtures of DBAs may become appropriate. Prolonged/repeated-application
trials may be necessary to evince orchard-scale or long-term effects. For example, a
decrease of the alternate bearing index was observed with the prolonged use of oil
(Beede, 2007).
Elucidating the Relationship Between Phenology and Yield
From a crop production perspective, DBA treatments must not only show efficacy
but also be cost-effective. Additionally, with view to allocating commodity-specific
research funding, there is substantial interest in decomposing actual or potential pistachio
yields into a set of components, e.g., the alternate bearing component, the chill
component, the nutrition component, the water component. This review raises the
question of whether phenology or phenological advancement should itself be considered
a component of yield in pistachio.
In this lens, phenological yield limitation in California pistachios is the result of a
physiological mismatch between pistachios’ adaptations to their native climate and
California’s actual growing conditions. Frosts are common into April, if not May, in the
Iranian mountains. In contrast, California seldom experiences frosts past March. The
difference between these climates presents a window of opportunity to be exploited by
advancing spring phenology, which could be especially important for pistachios because
it is thought that pistachios mobilize primarily the same season’s carbohydrates into the
developing nut tissues (Spann et al., 2008). It is tempting to presume that growers would
benefit from their trees being able to more fully utilize the milder California spring, but it
is unknown whether the use of DBAs can induce greater accumulation of photosynthate
in spring, how the trees might allocate such a surplus into vegetative and reproductive
41 41
growth, or whether any such differences could translate into greater yield or earlier
harvest.
References
Alonso, J.M., J.M. Ansón, M.T. Espiau, and R.S. i Company. 2005. Determination of
Endodormancy Break in Almond Flower Buds by a Correlation Model Using the
Average Temperature of Different Day Intervals and its Application to the
Estimation of Chill and Heat Requirements and Blooming Date. J. Am. Soc. Hortic.
Sci. 130(3): 308–318. doi: 10.21273/JASHS.130.3.308.
Amooaghaie, R., and F. Ahmadi. 2017. Triangular interplay between ROS, ABA and GA
in dormancy alleviation of Bunium persicum seeds by cold stratification. Russ. J.
Plant Physiol. 64(4): 588–599. doi: 10.1134/S1021443717040021.
Ariizumi, T., A.L. Hauvermale, S.K. Nelson, A. Hanada, S. Yamaguchi, et al. 2013.
Lifting della repression of Arabidopsis seed germination by nonproteolytic
gibberellin signaling. Plant Physiol. 162(4): 2125–2139. doi:
10.1104/pp.113.219451.
Askari, E., S. Irani, and K. Razmjoo. 2011. Bloom, maturity, and fruit set of pistachio in
response to early season application of ethephon. Hortic. Environ. Biotechnol.
52(1): 29–34. doi: 10.1007/s13580-011-0029-4.
Beaudoin, N., C. Serizet, F. Gosti, and J. Giraudat. 2000. Interactions between Abscisic
Acid and Ethylene Signaling Cascades. Plant Cell 12(7): 1103–1116.
Beauvieux, R., B. Wenden, and E. Dirlewanger. 2018. Bud Dormancy in Perennial Fruit
Tree Species: A Pivotal Role for Oxidative Cues. Front. Plant Sci. 9. doi:
10.3389/fpls.2018.00657.
Beede, R.H. 2007. Chilling, Cold Injury, and Dormant Oil Research in Pistachio (Kerman
and Peters cv.). http://cekings.ucanr.edu/files/19104.pdf.
Beede, R.H., C. Nichols, J. Starling, B. Lahorn, Z. Heath, et al. 2002. Growth, Yield, and
Nut Quality Responses in a Commercial Pistachio Orchard from Dormant Applied
Horticultural Mineral Oil. Calif. Pist. Comm. Res. Rep. 2002: 153–164.
Beede, R.H., D. Thomas, R. Rice, K. Daane, J. Padilla, et al. 1993. Relation of Phytocoris
Relativus to lecanium scale infestations on pistachio. Calif. Pist. Comm. Res. Rep.
1993: 100–111.
Bentsink, L., and M. Koornneef. 2008. Seed Dormancy and Germination. In: Arabidopsis
Book, Am. Soc. Plant Biol. 6. doi: 10.1199/tab.0119.
42 42
Bethke, P.C., I.G.L. Libourel, V. Reinöhl, and R.L. Jones. 2006. Sodium nitroprusside,
cyanide, nitrite, and nitrate break Arabidopsis seed dormancy in a nitric oxide-
dependent manner. Planta 223(4): 805–812. doi: 10.1007/s00425-005-0116-9.
Briggs, D.E. 1992. Barley germination: biochemical changes and hormonal control.
Biotechnol. Agric. http://agris.fao.org/agris-
search/search.do?recordID=US201301758887 (accessed 26 March 2019).
Brunner, A.M., L.M. Evans, C.-Y. Hsu, and X. Sheng. 2014. Vernalization and the
chilling requirement to exit bud dormancy: shared or separate regulation? Front.
Plant Sci. 5. doi: 10.3389/fpls.2014.00732.
Cortés-Ríos, J., M.J. Torres, M.P. Campos-Bustamante, J. Romero-Parra, M.E. Letelier,
et al. 2017. NADPH oxidase activity: Spectrophotometric determination of
superoxide using pyrogallol red. Anal. Biochem. 536: 96–100. doi:
10.1016/j.ab.2017.08.013.
Darbyshire, R., K. Pope, and I. Goodwin. 2016. An evaluation of the chill overlap model
to predict flowering time in apple tree. Sci. Hortic. C(198): 142–149. doi:
10.1016/j.scienta.2015.11.032.
Denny, F.E., and E.N. Stanton. 1928. Localization of response of woody tissues to
chemical treatments that break the rest period. Am. J. Bot. 15(5): 337–344.
Derkx, M.P.M., and C.M. Karssen. 1993. Effects of light and temperature on seed
dormancy and gibberellin-stimulated germination in Arabidopsis thaliana: studies
with gibberellin-deficient and -insensitive mutants. Physiol. Plant. 89(2): 360–368.
doi: 10.1111/j.1399-3054.1993.tb00167.x.
Dodds, J.H., A.R. Smith, and M.A. Hall. 1982. The metabolism of ethylene to ethylene
oxide in cultivars of Vicia faba: Relationship with waterlogging resistance. Plant
Growth Regul. 1(3): 203–207. doi: 10.1007/BF00036999.
Dokoozlian, N.K., L.E. Williams, and R.A. Neja. 1995. Chilling exposure and hydrogen
cyanamide interact in breaking dormancy of grape buds. HortScience 30(6): 1244–
1247.
Duan, C., X. Li, D. Gao, H. Liu, and M. Li. 2004. Studies on Regulations of Endogenous
ABA and GA3 in Sweet Cherry Flower Buds on Dormancy. Acta Hortic. Sin. 31:
149–154.
Emongor, V.E. 2004. Effects of Gibberellic Acid on Postharvest Quality and Vaselife
Life of Gerbera Cut Flowers (Gerbera jamesonii) - SciAlert Responsive Version. J.
Agron. 3: 191–195. doi: 10.3923/ja.2004.191.195.
43 43
Erez, A., M. Faust, and M.J. Line. 1998. Changes in water status in peach buds on
induction, development and release from dormancy. Sci. Hortic. 73(2): 111–123.
doi: 10.1016/S0304-4238(97)00155-6.
Fadón, E., M. Herrero, and J. Rodrigo. 2018. Dormant Flower Buds Actively Accumulate
Starch over Winter in Sweet Cherry. Front. Plant Sci. 9. doi:
10.3389/fpls.2018.00171.
Fan, S., D.G. Bielenberg, T.N. Zhebentyayeva, G.L. Reighard, W.R. Okie, et al. 2010.
Mapping quantitative trait loci associated with chilling requirement, heat
requirement and bloom date in peach (Prunus persica). New Phytol. 185(4): 917–
930. doi: 10.1111/j.1469-8137.2009.03119.x.
FAO. 2006. International Code of Conduct on the Distribution and Use of Pesticides:
Guidelines on Efficacy Evaluation for the Registration of Plant Protection Products.
Faust, M., D. Liu, M.M. Millard, and G.W. Stutte. 1991. Bound versus Free Water in
Dormant Apple Buds—A Theory for Endodormancy. HortScience 26(7): 887–890.
doi: 10.21273/HORTSCI.26.7.887.
Faust, M., A. Erez, L.J. Rowland, S.Y. Wang, and H.A. Norman. 1997. Bud dormancy in
perennial fruit trees: physiological basis for dormancy induction, maintenance, and
release. HortScience 32(4): 623–629.
de Faÿ, E., V. Vacher, and F. Humbert. 2000. Water-related phenomena in winter buds
and twigs of Picea abies L.(Karst.) until bud-burst: a biological, histological and
NMR study. Ann. Bot. 86(6): 1097–1107.
Fernandez, E., G. Baird, D. Farías, E. Oyanedel, J.A. Olaeta, et al. 2018. Fruit load in
almond spurs define starch and total soluble carbohydrate concentration and
therefore their survival and bloom probabilities in the next season. Sci. Hortic. 237:
269–276. doi: 10.1016/j.scienta.2018.04.030.
Fishman, S., A. Erez, and G.A. Couvillon. 1987. The temperature dependence of
dormancy breaking in plants: Computer simulation of processes studied under
controlled temperatures. J. Theor. Biol. 126(3): 309–321. doi: 10.1016/S0022-
5193(87)80237-0.
Fine Americas. 2014. Falgro 2X LV [product label]. EPA registration number 62097-32-
82917.
Fu, X.L., W. Xiao, D.L. Wang, M. Chen, Q.P. Tan, et al. 2014. Roles of Endoplasmic
Reticulum Stress and Unfolded Protein Response Associated Genes in Seed
Stratification and Bud Endodormancy during Chilling Accumulation in Prunus
persica (Z.-H. Chen, editor). PLoS ONE 9(7): e101808. doi:
10.1371/journal.pone.0101808.
44 44
Gardea, A.A., L.S. Daley, R.L. Kohnert, A.H. Soeldner, L. Ning, et al. 1994. Proton
NMR signals associated with eco-and endodormancy in winegrape buds. Sci.
Hortic. 56(4): 339–358.
Gholizadeh, J., H.R. Sadeghipour, A. Abdolzadeh, K. Hemmati, D. Hassani, et al. 2017.
Redox rather than carbohydrate metabolism differentiates endodormant lateral buds
in walnut cultivars with contrasting chilling requirements. Sci. Hortic. 225: 29–37.
doi: 10.1016/j.scienta.2017.06.058.
Ghrab, M., and M.B. Mimoun. 2014. Effective hydrogen cyanamide (Dormex®)
application for bud break, flowering and nut yield of pistachio trees cv. Mateur in
warm growing areas. Exp. Agric. 50(3): 398–406. doi:
10.1017/S0014479713000550.
Gillespie, L.M., and F.A. Volaire. 2017. Are winter and summer dormancy symmetrical
seasonal adaptive strategies? The case of temperate herbaceous perennials. Ann.
Bot. 119(3): 311–323. doi: 10.1093/aob/mcw264.
Glozer, K., J.A. Grant, and W.W. Coates. 2005. Evaluation of Chill Models in ‘Bing’
Sweet Cherry Rest-breaking Trials in California from 1994 to the Present:
Validation of the Dynamic Model. HortScience 40(4): 1141.
Golan-Goldhirsh, A., I. Peri, Y. Birk, and P. Smirnoff. 1998. Inflorescence bud proteins
of Pistacia vera. Trees 12(7): 415–419. doi: 10.1007/PL00009725.
Goudey, J.S., F.L. Tittle, and M.S. Spencer. 1989. A Role for Ethylene in the Metabolism
of Cyanide by Higher Plants. Plant Physiol. 89(4): 1306–1310. doi:
10.1104/pp.89.4.1306.
Graether, S.P., and K.F. Boddington. 2014. Disorder and function: a review of the
dehydrin protein family. Front. Plant Sci. 5: 576. doi: 10.3389/fpls.2014.00576.
Hayat, S., S. Yadav, M.N. Alyemeni, and A. Ahmad. 2014. Effect of sodium
nitroprusside on the germination and antioxidant activities of tomato (Lycopersicon
esculentum Mill.). Bulg. J. Agric. Sci. 20(1): 140–144.
Hormaza, J.I., and V.S. Polito. 1996. Pistillate and staminate flower development in
dioecious Pistacia vera (Anacardiaceae). Am. J. Bot. 83(6): 759–766. doi:
10.1002/j.1537-2197.1996.tb12765.x.
Hou, X., L. Ding, and H. Yu. 2013. Crosstalk between GA and JA signaling mediates
plant growth and defense. Plant Cell Rep. 32(7): 1067–1074. doi: 10.1007/s00299-
013-1423-4.
Huang, A.H.C. 2018. Plant Lipid Droplets and Their Associated Proteins: Potential for
Rapid Advances. Plant Physiol. 176(3): 1894–1918. doi: 10.1104/pp.17.01677.
45 45
Huang, Y., C. Lin, F. He, Z. Li, Y. Guan, et al. 2017. Exogenous spermidine improves
seed germination of sweet corn via involvement in phytohormone interactions,
H2O2 and relevant gene expression. BMC Plant Biol. 17. doi: 10.1186/s12870-016-
0951-9.
Ionescu, I.A., G. López-Ortega, M. Burow, A. Bayo-Canha, A. Junge, et al. 2017.
Transcriptome and Metabolite Changes during Hydrogen Cyanamide-Induced
Floral Bud Break in Sweet Cherry. Front. Plant Sci. 8. doi:
10.3389/fpls.2017.01233.
Jackson, J.E. 2003. The Biology of Apples and Pears by John E. Jackson. Camb. Core.
doi: 10.1017/CBO9780511542657.
Jackson, J.E., and M. Bepete. 1995. The effect of hydrogen cyanamide (Dormex) on
flowering and cropping of different apple cultivars under tropical conditions of sub-
optimal winter chilling. Sci. Hortic. 60(3–4): 293–304.
Jung, S.H., and H. Kohn. 1985. Stereoselective synthesis of vicinal diamines from
alkenes and cyanamide. J. Am. Chem. Soc. 107(10): 2931–2943.
Juszczuk, I.M., and A.M. Rychter. 2003. Alternative oxidase in higher plants. Acta
Biochim. Pol. 50(4): 1257–1271. doi: 0350041257.
Kasahara, H., A. Hanada, T. Kuzuyama, M. Takagi, Y. Kamiya, et al. 2002. Contribution
of the mevalonate and methylerythritol phosphate pathways to the biosynthesis of
gibberellins in Arabidopsis. J. Biol. Chem. 277(47): 45188–45194. doi:
10.1074/jbc.M208659200.
Kojima, K., T. Sumi, and S. Kuraishi. 1996. Effects of calcium cyanamide and
brassinolide on the budbreak, and ABA and IAA contents of grapevine [Vitis
vinifera x Vitis labrusca] buds. Bull. Exp. Farm Fac. Agric. - Kyoto Prefect. Univ.
Jpn. http://agris.fao.org/agris-search/search.do?recordID=JP2005001930 (accessed
30 March 2019).
Kubota, N., Y. Yamane, K. Toriu, K. Kawazu, T. Higuchi, et al. 1999. Identification of
active substances in garlic responsible for breaking bud dormancy in grapevines. J.
Jpn. Soc. Hortic. Sci. 68(6): 1111–1117.
Laloi, C., and M. Havaux. 2015. Key players of singlet oxygen-induced cell death in
plants. Front. Plant Sci. 6. doi: 10.3389/fpls.2015.00039.
Lang, G.A., J.D. Early, G.C. Martin, and R.L. Darnell. 1987. Endo-, para- and
ecodormancy: physiological terminology and classification for dormancy research.
HortScience 22: 371–77.
46 46
Leida, C., A. Conejero, V. Arbona, A. Gómez-Cadenas, G. Llácer, et al. 2012. Chilling-
Dependent Release of Seed and Bud Dormancy in Peach Associates to Common
Changes in Gene Expression (R.P. Niedz, editor). PLoS ONE 7(5): e35777. doi:
10.1371/journal.pone.0035777.
Leubner-Metzger, G. 2003. Functions and regulation of β-1, 3-glucanases during seed
germination, dormancy release and after-ripening. Seed Sci. Res. 13(1): 17–34.
Li, G., X. Meng, R. Wang, G. Mao, L. Han, et al. 2012. Dual-level regulation of ACC
synthase activity by MPK3/MPK6 cascade and its downstream WRKY
transcription factor during ethylene induction in Arabidopsis. PLoS Genet. 8(6):
e1002767.
Liu, X., and X. Hou. 2018. Antagonistic Regulation of ABA and GA in Metabolism and
Signaling Pathways. Front. Plant Sci. 9: 251. doi: 10.3389/fpls.2018.00251.
Liu, X.-M., K.E. Kim, K.-C. Kim, X.C. Nguyen, H.J. Han, et al. 2010. Cadmium
activates Arabidopsis MPK3 and MPK6 via accumulation of reactive oxygen
species. Phytochemistry 71(5–6): 614–618.
Liu, Y., L. Shi, N. Ye, R. Liu, W. Jia, et al. 2009. Nitric oxide-induced rapid decrease of
abscisic acid concentration is required in breaking seed dormancy in Arabidopsis.
New Phytol. 183(4): 1030–1042. doi: 10.1111/j.1469-8137.2009.02899.x.
Liu, Y., and S. Zhang. 2004. Phosphorylation of 1-aminocyclopropane-1-carboxylic acid
synthase by MPK6, a stress-responsive mitogen-activated protein kinase, induces
ethylene biosynthesis in Arabidopsis. Plant Cell 16(12): 3386–3399.
Malyshev, R.V., M.A. Shelyakin, and T.K. Golovko. 2016. Bud dormancy breaking
affects respiration and energy balance of bilberry shoots in the initial stage of
growth. Russ. J. Plant Physiol. 63(3): 409–416. doi: 10.1134/S1021443716030092.
McLaughlin, S. 1972. The mechanism of action of DNP on phospholipid bilayer
membranes. J. Membr. Biol. 9(1): 361–372. doi: 10.1007/BF01868062.
Meng, Y., N. Ma, Q. Zhang, Q. You, N. Li, et al. 2014. Precise spatio-temporal
modulation of ACC synthase by MPK 6 cascade mediates the response of rose
flowers to rehydration. Plant J. 79(6): 941–950.
Middleton, A.M., S. Úbeda-Tomás, J. Griffiths, T. Holman, P. Hedden, et al. 2012.
Mathematical modeling elucidates the role of transcriptional feedback in gibberellin
signaling. Proc. Natl. Acad. Sci. U. S. A. 109(19): 7571–7576. doi:
10.1073/pnas.1113666109.
Mittler, R. 2017. ROS Are Good. Trends Plant Sci. 22(1): 11–19. doi:
10.1016/j.tplants.2016.08.002.
47 47
Muller, A.M. 2008. The effects of rest breaking agents, pruning and evaporative cooling
on budbreak, flower bud formation and yield of three pistachio (Pistacia Vera L.)
cultivars in a climate with moderate winter chilling.
Nambara, E., and A. Marion-Poll. 2005. Abscisic acid biosynthesis and catabolism.
Annu. Rev. Plant Biol. 56: 165–185. doi:
10.1146/annurev.arplant.56.032604.144046.
Nee, C.-C. 1986. Overcoming bud dormancy with hydrogen cyanamide: timing and
mechanism. Ph.D. thesis, Oregon State University.
Okubo, H., M. Iwaya-Inoue, K. Motooka, N. Ishida, H. Kano, et al. 1996. Monitoring the
cold requirement in tulip bulbs by 1H-NMR imaging. VII International Symposium
on Flowerbulbs 430. p. 411–418
Pham, A.T., S. Bai, T. Saito, T. Imai, A. Ito, et al. 2016. Involvement of EARLY BUD-
BREAK, an AP2/ERF Transcription Factor Gene, in Bud Break in Japanese Pear
(Pyrus pyrifolia Nakai) Lateral Flower Buds: Expression, Histone Modifications
and Possible Target Genes. Plant Cell Physiol. 57(5): 1038–1047. doi:
10.1093/pcp/pcw041.
Pham, A.T., R. Kumar, P.K. Rehal, P.K. Toora, and B.T. Ayele. 2018. Molecular
Mechanisms Underlying Abscisic Acid/Gibberellin Balance in the Control of Seed
Dormancy and Germination in Cereals. Front. Plant Sci. 9: 668. doi:
10.3389/fpls.2018.00668.
Pontikis, C.A. (Agricultural U. of A. 1989. Effects of hydrogen cyanamide on bloom
advancement in female pistachio (Pistacia vera L.). Fruit Var. J. USA.
http://agris.fao.org/agris-search/search.do?recordID=US9322154 (accessed 6 April
2019).
Pope, K.S., and T.M. DeJong. 2017. Modeling spring phenology and chilling
requirements using the chill overlap framework. Acta Hortic. (1160): 179–184. doi:
10.17660/ActaHortic.2017.1160.26.
Pope, K.S., V. Dose, D. Da Silva, P.H. Brown, and T.M. DeJong. 2015. Nut crop yield
records show that budbreak-based chilling requirements may not reflect yield
decline chill thresholds. Int. J. Biometeorol. 59(6): 707–715. doi: 10.1007/s00484-
014-0881-x.
Porlingis, I.C., and D.G. Voyiatzis. 1993. Delaying anthesis of staminate pistachio with
paclobutrazol. HortScience 28(8): 814–816.
Porto, D.D., M. Bruneau, P. Perini, R. Anzanello, J.-P. Renou, et al. 2015. Transcription
profiling of the chilling requirement for bud break in apples: a putative role for
FLC-like genes. J. Exp. Bot. 66(9): 2659–2672. doi: 10.1093/jxb/erv061.
48 48
Rabajante, J.F., and C.O. Talaue. 2015. Equilibrium switching and mathematical
properties of nonlinear interaction networks with concurrent antagonism and self-
stimulation. Chaos Solitons Fractals 73: 166–182. doi:
10.1016/j.chaos.2015.01.018.
Radley, M. 1969. The Effect of the Endosperm on the Formation of Gibberellin by
Barley Embryos. Planta 86(3): 218–223.
Rady, M.M., and M.A. Seif El-Yazal. 2014. Garlic extract as a novel strategy to hasten
dormancy release in buds of ‘Anna’ apple trees. South Afr. J. Bot. 92: 105–111.
doi: 10.1016/j.sajb.2014.02.012.
Rahemi, M., and H. Asghari. 2004. Effect of hydrogen cyanamide (dormex), volk oil and
potassium nitrate on budbreak, yield and nut characteristics of pistachio (Pistacia
vera L.). J. Hortic. Sci. Biotechnol. 79(5): 823–827. doi:
10.1080/14620316.2004.11511849.
Rawls, M., K.A. Shackel, and J. Fei. 2019. Effects of dormant drought stress on almond
(Prunus dulcis) bloom; what if it doesn’t rain in the winter? Presented: 2019
California Plant and Soil Conference, February 7 2019, Fresno, CA. Proceedings: p.
145
Reinoso, H., V. Luna, R.P. Pharis, and R. Bottini. 2002. Dormancy in peach (Prunus
persica) flower buds. V. Anatomy of bud development in relation to phenological
stage. Can. J. Bot. 80(6): 656–663. doi: 10.1139/b02-052.
Rinne, P., H. Tuominen, and O. Junttila. 1994. Seasonal changes in bud dormancy in
relation to bud morphology, water and starch content, and abscisic acid
concentration in adult trees of Betula pubescens. Tree Physiol. 14(6): 549–561. doi:
10.1093/treephys/14.6.549.
Rocklin, A.M., K. Kato, H. Liu, L. Que, and J.D. Lipscomb. 2004. Mechanistic studies of
1-aminocyclopropane-1-carboxylic acid oxidase: single turnover reaction. JBIC J.
Biol. Inorg. Chem. 9(2): 171–182. doi: 10.1007/s00775-003-0510-3.
Rocklin, A.M., D.L. Tierney, V. Kofman, N.M.W. Brunhuber, B.M. Hoffman, et al.
1999. Role of the nonheme Fe(II) center in the biosynthesis of the plant hormone
ethylene. Proc. Natl. Acad. Sci. 96(14): 7905–7909. doi: 10.1073/pnas.96.14.7905.
Rohde, A., and R.P. Bhalerao. 2007. Plant dormancy in the perennial context. Trends
Plant Sci. 12(5): 217–223. doi: 10.1016/j.tplants.2007.03.012.
Russinova, E., J.-W. Borst, M. Kwaaitaal, A. Canno-Delgado, Y. Yin, et al. 2004.
Heterodimerization and Endocytosis of Arabidopsis Brassinosteroid Receptors
BRI1 and AtSERK3 (BAK1). Plant Cell Online 16(12): 3216–3229. doi:
10.1105/tpc.104.025387.
49 49
Schneider, G., P. Fuchs, and J. Schmidt. 2002. Evidence for the direct 2beta- and 3beta-
hydroxylation of [2H2]GA20-13-O-[6’-2H2]glucoside in seedlings of Phaseolus
coccineus. Physiol. Plant. 116(2): 144–147.
Schroeder, J.I., and E. Nambara. 2006. A Quick Release Mechanism for Abscisic Acid.
Cell 126(6): 1023–1025. doi: 10.1016/j.cell.2006.09.001.
Schulze-Siebert, D., and G. Schultz. 1987. β-Carotene synthesis in isolated spinach
chloroplasts: its tight linkage to photosynthetic carbon metabolism. Plant Physiol.
84(4): 1233–1237.
Seo, M., E. Nambara, G. Choi, and S. Yamaguchi. 2009. Interaction of light and hormone
signals in germinating seeds. Plant Mol. Biol. 69(4): 463–472. doi:
10.1007/s11103-008-9429-y.
Shirota, F.N., D.J. Goon, E.G. DeMaster, and H.T. Nagasawa. 1996. Nitrosyl cyanide, a
putative metabolic oxidation product of the alcohol-deterrent agent cyanamide.
Biochem. Pharmacol. 52(1): 141–147.
Southwick, S., Z. Khan, and K. Glozer. Undated. Evaluation of chill models from
historical rest-breaking spray experiments on 'Bing' sweet cherry. Accessed Nov 15
2019. Available: http://ucanr.edu/sites/fruitandnut/files/67017.pdf
Sovonick, S.A., D.R. Geiger, and R.J. Fellows. 1974. Evidence for active Phloem loading
in the minor veins of sugar beet. Plant Physiol. 54(6): 886–891. doi:
10.1104/pp.54.6.886.
Spann, T.M., R.H. Beede, and T.M. DeJong. 2008. Seasonal carbohydrate storage and
mobilization in bearing and non-bearing pistachio (Pistacia vera) trees. Tree
Physiol. 28(2): 207–213.
Staswick, P.E., and I. Tiryaki. 2004. The Oxylipin Signal Jasmonic Acid Is Activated by
an Enzyme That Conjugates It to Isoleucine in Arabidopsis. Plant Cell Online
16(8): 2117–2127. doi: 10.1105/tpc.104.023549.
Sutinen, S., J. Partanen, A. Viherä-Aarnio, and R. Häkkinen. 2012. Development and
growth of primordial shoots in Norway spruce buds before visible bud burst in
relation to time and temperature in the field. Tree Physiol. 32(8): 987–997. doi:
10.1093/treephys/tps063.
Tanino, K.K. 2004. Hormones and endodormancy induction in woody plants. J. Crop
Improv. 10(1–2): 157–199.
Tarancón, C., E. González-Grandío, J.C. Oliveros, M. Nicolas, and P. Cubas. 2017. A
Conserved Carbon Starvation Response Underlies Bud Dormancy in Woody and
Herbaceous Species. Front. Plant Sci. 8. doi: 10.3389/fpls.2017.00788.
50 50
Tixier, A., G.A. Gambetta, J. Godfrey, J. Orozco, and M.A. Zwieniecki. 2019. Non-
structural Carbohydrates in Dormant Woody Perennials; The Tale of Winter
Survival and Spring Arrival. Front. For. Glob. Change 2. doi:
10.3389/ffgc.2019.00018.
Tzoutzoukou, C.G., C.A. Pontikis, and A. Tolia-Marioli. 1998. Effects of gibberellic acid
on bloom advancement in female pistachio (Pistacia vera L.). J. Hortic. Sci.
Biotechnol. 73(4): 517–526. doi: 10.1080/14620316.1998.11511008.
Valent Biosciences. 2014. ProGibb 4% [product label]. EPA registration number 73049-
15.
Van de Poel, B., and D. Van Der Straeten. 2014. 1-aminocyclopropane-1-carboxylic acid
(ACC) in plants: more than just the precursor of ethylene! Front. Plant Sci. 5. doi:
10.3389/fpls.2014.00640.
Voesenek, L.A.C.J., A.J.M. van der Sman, F.J.M. Harren, and C.W.P.M. Blom. 1992. An
amalgamation between hormone physiology and plant ecology: A review on
flooding resistance and ethylene. J. Plant Growth Regul. 11(3): 171–188. doi:
10.1007/BF00194367.
Volaire, F., M.R. Norton, G.M. Norton, and F. Lelièvre. 2005. Seasonal patterns of
growth, dehydrins and water-soluble carbohydrates in genotypes of Dactylis
glomerata varying in summer dormancy. Ann. Bot. 95(6): 981–990. doi:
10.1093/aob/mci102.
Wang, L., L. Zhang, C. Ma, W. Xu, Z. Liu, et al. 2016. Impact of chilling accumulation
and hydrogen cyanamide on floral organ development of sweet cherry in a warm
region. J. Integr. Agric. 15(11): 2529–2538. doi: 10.1016/S2095-3119(16)61341-2.
Weinberger, J.H. 1950. Prolonged dormancy, a southern problem of peaches. Am. Fruit
Grow. 70(3): 17–1.
Wu, X.-J., F. Kassie, and V. Mersch-Sundermann. 2005. The role of reactive oxygen
species (ROS) production on diallyl disulfide (DADS) induced apoptosis and cell
cycle arrest in human A549 lung carcinoma cells. Mutat. Res. Mol. Mech. Mutagen.
579(1): 115–124. doi: 10.1016/j.mrfmmm.2005.02.026.
Xia, X.-J., Y.-J. Wang, Y.-H. Zhou, Y. Tao, W.-H. Mao, et al. 2009. Reactive oxygen
species are involved in brassinosteroid-induced stress tolerance in cucumber. Plant
Physiol. 150(2): 801–814.
Yakubov, B., O. Barazani, A. Shachack, L.J. Rowland, O. Shoseyov, et al. 2005. Cloning
and expression of a dehydrin-like protein from Pistacia vera L. Trees 19(2): 224–
230. doi: 10.1007/s00468-004-0385-0.
51 51
Ye, L., L. Li, L. Wang, S. Wang, S. Li, et al. 2015. MPK3/MPK6 are involved in iron
deficiency-induced ethylene production in Arabidopsis. Front. Plant Sci. 6: 953.
Yildiz, K., F. Muradoglu, and H. Yilmaz. 2008. The effect of jasmonic acid on
germination of dormant and nondormant pear (Pyrus communis L.) seeds. Seed Sci.
Technol. 36(3): 569–574.
Yordanov, Y.S., C. Ma, S.H. Strauss, and V.B. Busov. 2014. EARLY BUD-BREAK 1
(EBB1) is a regulator of release from seasonal dormancy in poplar trees. Proc. Natl.
Acad. Sci. 111(27): 10001–10006. doi: 10.1073/pnas.1405621111.
Zhang, L. 2018. Studies of Pistachio Flower Quality and Development as influenced by
Low Chill in California. Presented at CA Statewide Pistachio Day, January 19
2018, Visalia, CA.
http://lecture.ucanr.edu/Mediasite/Play/c8fa0c86a441459996ae1c07849ee1aa1d.
Zhang, Z., J.-S. Ren, I.J. Clifton, and C.J. Schofield. 2004. Crystal Structure and
Mechanistic Implications of 1-Aminocyclopropane-1-Carboxylic Acid Oxidase—
The Ethylene-Forming Enzyme. Chem. Biol. 11(10): 1383–1394. doi:
10.1016/j.chembiol.2004.08.012.
Zhang, W., and C.-K. Wen. 2010. Preparation of ethylene gas and comparison of
ethylene responses induced by ethylene, ACC, and ethephon. Plant Physiol.
Biochem. PPB 48(1): 45–53. doi: 10.1016/j.plaphy.2009.10.002.
Zheng, C., A. Kwame Acheampong, Z. Shi, T. Halaly, Y. Kamiya, et al. 2018. Distinct
gibberellin functions during and after grapevine bud dormancy release. J. Exp. Bot.
69(7): 1635–1648.
Zhuang, W., Z. Gao, L. Wen, X. Huo, B. Cai, et al. 2015. Metabolic changes upon flower
bud break in Japanese apricot are enhanced by exogenous GA4. Hortic. Res. 2(1).
doi: 10.1038/hortres.2015.46.
III. EFFICACY OF DORMANCY BREAKING AGENTS FOR IMPROVED BLOOM SYNCHRONY AND YIELD IN
CALIFORNIA PISTACHIOS
Abstract Low-chill winters can cause bloom asynchrony in California pistachio orchard
systems consisting of Pistacia vera L. cv. 'Kerman' and its pollinizer 'Peters'. Dormancy-
breaking agents (DBAs) can be used to extend the cultivation of tree crops with high
chilling requirements into warm regions. In this two-year exploratory efficacy trial of
DBAs on pistachio, we tested GA3, AVG, and ethephon against industry standard
treatments of dormant oil and unsprayed/water-sprayed control.
We evaluated whether each DBA advanced bloom or narrowed the bloom
window. AVG does not act as a DBA. GA3 can advance bloom and narrow the bloom
window, but has adverse effects on yield, so no effective GA3-based treatment was found.
Application of horticultural oil at a rate of 6% advanced average female bloom by 2-3
days, but widened the bloom window. 500 mg/l ethephon advanced female bloom by 2-3
days while maintaining natural bloom narrowness. In the second trial year, the trial was
expanded to include male trees and a second application time. In untreated blocks, male
trees bloomed before females. DBAs advanced female bloom by 1-4 days and delayed
male bloom by 1-2 days, causing male trees to bloom after females. Synchrony was lost
in all DBA-treated plots. The mid-February application time, nearest the transition from
endo- to ecodormancy, showed the strongest physiological effects and was better for
every tested DBA.
We monitored pre-bloom changes in bud respiration as well as changes in the
content of hexose, non-hexose soluble sugars (NHS), and starch in twigs and female
floral buds. Endogenous growth initiation is signified by a gradual increase in respiration
accompanied by NHS accumulation in floral buds and starch accumulation in twigs. GA3
53 53
and oil induced anomalous patterns of starch accumulation in buds before growth
initiation. Induced mobilization of carbohydrate reserves before growth initiation may be
deleterious and may lead to wider bloom windows. In contrast, ethephon has a mode of
action that does not involve modulating carbohydrate mobilization and maintains a
naturally narrow bloom window.
Further exploration of ethylene's dose-response curve may be necessary to
mitigate possible adverse yield effects. The use of GA3 should be restricted to small
quantities during endodormancy. Closer attention needs to be given to yield components
and processes affecting them.
Introduction
Pistachio (Pistacia vera L.) is an important nut crop in California, responsible for
$3.6 billion of annual economic activities in the state in 2018, according to the American
Pistachio Growers annual report from that year. Over 85% of California’s pistachio
acreage consists of 'Kerman' females and 'Peters' males. In the 20th century, 'Peters'
males were a good pollinizer for 'Kerman' females. However, both 'Kerman' and 'Peters'
have high chilling requirements, and their synchrony is dependent upon both cultivars
accumulating enough chill to complete winter rest. Recently, the Central Valley has seen
many low-chill years during which 'Kerman' flowered sooner than 'Peters', lowering
yields (Ferguson et al., 2005).
While the most powerful statistical predictor of pistachio yield in a given year is
the previous year’s yield, warm winter temperatures are the next factor (Kallsen, 2017).
The balance between postharvest carbon gain and overwintering respiration controls the
trees' carbohydrate status going into the new growing season. In the month before bud
break (late February and early March), twig starch is mobilized into bud sugar (Zhang,
2018). Bud carbohydrate status upon bloom is a major determinant of bloom quality
54 54
(ibid.). High winter temperatures (i.e. low chill) were associated with depletion of
carbohydrate reserves, and low-chill pistachio flower buds showed slower xylem
development, suggesting that flower primordia development might be adversely affected
by low chill (ibid.). Warm temperatures also affect bloom timing via trees' carbohydrate
status (Sperling et al., 2019).
Ongoing climatic change in California's Central Valley has been predicted to
result in earlier springs, erratic autumn temperatures, and warmer winters (Luedeling et
al., 2009) with less fog (Baldocchi and Waller, 2014). These predictions have matched
with recent weather patterns. The gradual loss of winter fog is especially important as fog
provides both shade and evaporative cooling. While the lifespan of pistachio orchards in
California is currently unknown, they are known to be long-lived species, and it is
conceivable that recently planted orchards have many productive decades ahead of them.
Eventually, the development of low-chill cultivars may provide a long-term solution, but
short-term solutions are necessary for orchards already planted.
Dormancy-breaking agents (DBAs) are widely used to extend the cultivation of
temperate tree species and cultivars with high chilling requirements into regions that
would otherwise be too warm. Any external physicochemical stimulus that promotes the
initiation of plant growth from a dormant state can be used as a DBA. Known DBAs
include hydrogen cyanamide (H2NCN), ethephon, GA3, GA4, GA7, nitrate, garlic extract,
and horticultural oils, as well as heat shock and light. Ongoing climatic change presents
California pistachio growers with an increasingly important risk management decision in
winter: should a DBA be used, and if so, which and when?
Historically, many dormancy-breaking chemicals were initially used for other
purposes and were later discovered to have dormancy management potential. Many
DBAs have modes of action that remain unelucidated. In practice, DBA effectiveness is a
function of tree physiological status, DBA dose, DBA application time, and the year's
55 55
weather. For example, H2NCN is a reliable and commonly used DBA in other tree crops
for which it is registered. Although H2NCN seems to substitute effectively for chill,
accelerating the attainment of chill-related developmental milestones in sweet cherry
(Wang et al., 2016), it is dangerous to use and not currently registered for pistachio.
Horticultural oil (also known as dormant oil) is the most commonly used DBA on
pistachios in both California and Iran. In California, although oil is licensed only for scale
insect control, recommended insect control timing overlaps with use as a potential DBA.
Uncertainty about application rate and timing hinder its more effective use, and lack of
knowledge about its mode of action impedes its improvement. Oil seems to function best
when applied near the time when trees fulfill their chilling requirement. Yet as winters
get warmer, it is taking longer for trees to accumulate the same amounts of chill. If
ongoing climatic trends continue, late-winter oil treatments may become more relevant.
Going forward, the California pistachio industry needs updated decision support for the
use of horticultural oil as well as new DBAs that are less sensitive to application time, are
more effective in late winter, or substitute for chill in contributing to adequate winter rest.
In this experiment, we applied several plant growth regulators in late winter and
screened for ability to advance and narrow the female bloom window without adverse
yield effects. The tested candidates were ethephon, aminoethoxyvinylglycine (AVG), and
gibberellic acid (GA3).
Ethephon was reported to delay budbreak and bloom when applied to 'Kaleh-
Ghouchi' pistachios in late winter in Iran (Askari et al., 2011). However, the relationship
of the delay length with dose is complicated, with higher doses not necessarily giving
longer delays. Based on their previous results, we expected 500 mg/l ethephon to give 10-
14 days of delay. No trial has yet examined the effect of pre-bloom ethephon on 'Kerman'
pistachio in California.
56 56
AVG is an ACC synthase inhibitor that suppresses cyanogenic ethylene
biosynthesis. Because late-winter ethephon was reported to delay budbreak and bloom,
we hypothesized that AVG would have the opposite effect and might advance those
events.
GA3 was included in this study as a likely positive control. GA3 is known to
substitute for chill and advance bud break and bloom when applied in early winter
(Tzoutzoukou et al., 1998). Higher doses were associated with more advancement.
Previous results strongly suggest that earlier application may be more effective than later
application, even though no trial has examined multiple GA3 application times in the
same year.
Because several DBAs have previously been shown to affect respiration, we
hypothesized that DBAs may affect bloom quality through respiration and carbohydrate
depletion. To our knowledge, no one has previously determined how applying DBAs
affects the allocation of energetically available non-structural carbohydrates (NSCs) to
buds and in turn affects bud development, dormancy breaking and bloom quality. We
speculated that interference with carbohydrate mobilization to breaking buds might
explain why some DBAs' effectiveness is so sensitive to their application timing.
Thus, we investigated how the application of DBAs to pistachio during
ecodormancy influences the movement, consumption, and transformation of stored
carbohydrates by monitoring changes of bud respiration and NSC content in twigs and
female floral buds. We also sought to identify links between DBA effects on
carbohydrate mobilization and DBA effects on bloom quality and yield.
57 57
Methods
Study Site and Treatments
This study took place over two years in the 25-acre commercially managed
pistachio orchard (36.828 N, 119.752 W) located on the CSU Fresno University
Agricultural Laboratory grounds. The study orchard consists of 16th-leaf (in 2018)
pistachio trees, 'Kerman' females and 'Peters' males on 'UCB-1' rootstock, with every fifth
tree of every fifth row being male in a rectangular pattern. The soil has low EC. The trees
are minimally hand-pruned every year, only to remove crossing or downward branches as
well as branches in the way of machinery.
Pistachio trees tend to bear alternately. In 2018, we scouted the pistachio orchard
for ON trees (predicted to have a heavy crop). 20 ON trees were selected for treatment
and were organized into an RCBD: 5 treatments × 4 single-tree replications/treatment.
Selected trees had at least 12-15 non-whip shoots within easily sampled height range with
4-5 flowering buds each. On 2018-03-06, trees were sprayed to the point of drip, ~1
gallon per tree, with water (control), 6% (w/v) IAP 440 oil, 500 mg/l ethephon, 125 mg/l
AVG (applied as 830 ppm Retain™), and 2000 mg/l GA3.
After scouting in winter 2019 confirmed that the trees treated in 2018 were all the
most OFF of the trees in the test orchard, we established a new RCBD consisting of 4
blocks, each block containing 7 treatment plots, each plot containing 3 female trees and 1
male tree. Plots were only located in rows with males, and individual plots were
separated by a single buffer tree in the row.
AVG was dropped from the 2019 trials because it did not seem to function as a
DBA in 2018. The 7 treatments in 2019 comprised 3 chemicals × 2 application dates plus
1 untreated control. Prior to spraying, a GA3 dose-response bioassay for endodormancy
completion was conducted (Hatch & Walker, 1969; see Chapter IV) to verify that the
trees would be ecodormant on the first spray date. Using a motorized backpack sprayer,
58 58
trees were sprayed to the point of drip (~16 l per 4 trees) with 500 mg/l ethephon, 200
mg/l GA3, or 6% (w/v) IAP 440 oil on either 2019-02-10 or 2019-02-26.
By those dates, 55 and 65 Chill Portions (CP) had accumulated at the study site,
respectively. In the Dynamic Model of chill accumulation (Fishman et al., 1987),
cultivars and species are assumed to differ in the number of CP they must accumulate to
break dormancy. The 'Kerman'/'Peters' system in California has a yield-based chilling
requirement of ~65 CP (Pope et al., 2015). As individual cultivars, 'Kerman' and 'Peters'
are thought to have chilling requirements of ~59 CP and ~69 CP respectively (ibid.).
Bud Respiration Measurements
Bud respiration was measured in both 2018 and 2019. In 2018, we first measured
every 5 days after spray, but seeing no changes after the first few measurements, we
reduced frequency to every 10 days until we saw buds start to swell. We then took
measurements every 3 days. Following analysis of the 2018 data, we realized that we had
undersampled the most pronounced period of increase in bud respiration about 20-27
days before bloom. Thus, in 2019, bud respiration measurements were taken twice per
week from the first week of March until the beginning of April.
Bud respiration measurements were taken with an LI-6800 photosynthesis
machine outfitted with an insect respiration chamber (LI-COR Biosciences, Lincoln,
NE). The measurement protocol was adapted from the one described by Tzoutzoukou et
al. (1998). Four buds (collected from NSEW quadrants of the chosen tree) were detached.
The four buds were placed in the insect respiration chamber and the chamber was
screwed sealed. Measurement was taken one minute after the chamber was sealed.
Samples were measured in the field and weighed when taken back to the laboratory. In
2019, respiration was reported directly by the instrument. In 2018, respiration was
computed on fresh weight basis as:
59 59
Respiration (μg CO2 min-1 g FW-1) =
2.64E-3 * ΔCO2 (μmol mol-1) * Flow (μmol s-1) / sample FW (g)
Overview of Carbohydrate Analysis
Because we were interested in how DBAs affected the movement of energy-rich
metabolites, we chose to monitor soluble hexoses and starch as primary energy reserves.
We were also interested in levels of non-hexose sugars because activation of the
oxidative pentose phosphate pathway has long been implicated in the process of
dormancy release (Simmonds and Simpson, 1971).
Accordingly, we developed a tandem H2SO4-UV/anthrone method to separately
quantitate hexose and non-hexose soluble sugars. Beginning with a standard sample
preparation, extraction, digestion, and hexose quantitation protocol from the California
Carbohydrate Observatory (Sperling et al., 2019), we elected instead to use hot ethanol
extraction and sequential enzymatic digestion as recommended by a recent review
(Landhäusser et al., 2018). For quantitation, samples were digested with H2SO4 to
convert all soluble sugars to furfurals and their UV absorbance was measured
(Albalasmeh et al., 2013). Subsequently, visibly colored dyes were formed by
condensation of hexose-derived 5-hydroxymethyl furfural with added anthrone, and
visible absorbance was measured (Bailey, 1958). Soluble sugars data from the H2SO4-UV
method were thereby collected alongside data from the hexose-specific anthrone method
for minimal additional effort.
A detailed protocol for this novel method, as well as a discussion of its
development, is given in Appendix A.
In both 2018 and 2019, starting in the first week of March, and about every week
thereafter, one ON shoot and one OFF shoot were taken from the east and west sides of
the most ON tree in each experimental plot, making 4 shoot samples per plot per week
60 60
total. Shoots with at least 2 floral buds remaining were considered "ON", and shoots with
at least 4 floral buds were preferentially chosen to represent this category; only shoots
with 0 floral buds were considered "OFF". Material from the 2 ON shoots and 2 OFF
shoots from opposite sides of the same tree were each pooled. Shoots were typically
taken between 10 AM and 12 noon.
Hexose, non-hexose sugar, and starch contents were quantitated in bud and bark
fractions of the sampled shoots as described in Appendix A.
Bloom Rating
For bloom monitoring in 2018, we tagged 4 branches/tree, one on each aspect
(NSEW). Field survey on 2018-03-30 observed no bloom underway, but returning on
2018-04-04, some of the treatments had begun blooming already. Thus, beginning on
2018-04-05 and every three days thereafter, the stage of the most advanced bud on each
tagged shoot was recorded. The bloom stages used in the rating were: tight, swollen,
green tip, elongated, differentiated, open, and fruit set.
Using the routine polr in the package MASS of the statistical software suite R,
2018 bloom data were analyzed with proportional odds cumulative logistic regression, a
technique suitable for the evaluation of transitions between phenological stages. By
dividing the treatment main coefficients by the day coefficient we obtained an estimate of
the advancement associated with each treatment over water control.
Bloom monitoring in 2019 used a different rating system. On 2019-04-10, 04-14,
and 04-18, the percentage of flowering shoots in each stage of bloom on every tree in the
trial was visually estimated. The bloom stages used in the rating were: bud swell, pre-
bloom, bloom, post-bloom, and fruit set (this last category for females only).
We supposed that every shoot on a tree is subject to at least three important
effects that act as sources of variation in its bloom timing:
61 61
Advancement of its whole tree.
The height of the shoot relative to the canopy crown. Pistachio shoots in
this study seemed to bloom in acropetal order (from bottom to top),
inducing what we refer to as acropetal variation.
Differential accumulation of light and heat as a function of shoot aspect
(the direction of the shoot's facing relative to the tree crown). We refer to
this variation as aspect variation.
In 2019, whole-tree advancement, acropetal variation, and aspect variation were
assessed on each date for each treatment, but we could only produce statistics for whole-
tree advancement. Proportional odds cumulative logistic regression models were fit to the
2019 bloom data using R. Bloom stage was modeled as a function of ordinal date *
treatment (i.e. ordinal date, treatment and their interactions.) The observed percentage of
each stage of bloom was used as a weight in the fitting of the regression model, so that
each observed tree had equal total weight.
Yield and Quality Components
Our 2018 study design (4 single-tree plots per treatment) successfully captured
differences in bloom date, but not in yield or quality. In an attempt to address the latter
deficiencies, the larger 2019 study block was established. The 2019 block contained six
times as many trees per treatment, split among two application dates. No power
calculation was performed beforehand.
Trees in the 2018 block were harvested in both years using a single 5-second
shake from an almond shaker. Nuts were shaken onto tarps, non-nut material was
removed, and their fresh weight was recorded. To comply with a regulatory requirement
to destroy any crop treated with non-registered products and ensure that none of it entered
62 62
commerce, all of the crop from the 2018 block was destroyed. Nut samples from each
tree weighing ~10 kg each were shipped to Horizon Nut Co. (Lost Hills, CA) for grading.
In the 2019 block, two separate harvests were conducted, which unfortunately
compromised the study. Trees in crop-destruct treatments were shaken for 5 seconds with
an almond shaker onto tarps, and the samples cleaned and weighed as before. The other
treatments were harvested using a 6-second shake from a standard commercial catch
frame. Nut samples from each plot were shipped for grading.
Results
Bud Respiration Increases and Peaks Before Bloom
In 2018, no immediate changes in respiration (on fresh weight basis) were
detected in the field following any treatment. About 1 month before bud break,
endogenous respiration began to increase. This respiration increase was followed by a
gain in fresh bud mass (bud swell) that drove an apparent decrease in respiration. As
shown in Figure 1, respiration reached a peak ~2-4 weeks before bloom in 2018;
unfortunately, our sampling coverage of this period was minimal. Respiration then
decreased to a temporary minimum during bloom before increasing again as the
inflorescences developed into clusters.
Apparent respiration differences observed on day 84 of 2018 were correlated with
bloom advancement. The more respiration on that date, the more advanced the bloom.
But owing to having undersampled that period, two theories remained plausible: 1) that
the respiration onset was advanced by DBAs, leading to significant differences that we
happened to capture; or 2) that DBAs altered the peak respiration rates before bloom.
Thus, in 2019 we altered our sampling scheme to observe what effects DBAs had on the
endogenous pre-bloom increase in respiration. We observed (Fig. 2) that respiration
63 63
Figure 1. Chronology of bud respiration increase before bloom, 2018.
Each point represents averaged respiration (FW basis) of 4 buds/tree, 1 collected from
each quadrant (NESW). Respiration peaked ~3 weeks prior to bloom.
remained close to a dormant baseline level of < 10 μg/min-g FW at first, then increased
towards a maximum, just as we hypothesized. Induced elevated dormant respiration was
detected in the later oil treatment. Neither ethephon nor GA3 immediately induced any
changes in respiration.
Respiration began to increase around day 70. Every DBA seems to advance the
onset of the respiration increase, although the respiration data contains so much variance
that differences between treatments at any given time point are not significant. We
applied linear regression to a truncated dataset containing only the increasing portion of
the respiration curve to look for acceleration of the onset of respiration increase, but this
approach yielded only marginal significance for the intercepts. Our 2019 data can neither
support nor rule out the alternate prediction that the pre-bloom respiration maximum
indicates DBA effectiveness. Unfortunately, we stopped taking respiration data only one
week too soon to evaluate the hypothesis.
64 64
Figure 2. (upper) Chronology of bud respiration increase before bloom, 2019.(lower)
Daily temperature highs and lows, same period.
65 65
Carbohydrate Levels in Twigs Respond to Bud Activity
TSS, hexose, and starch levels in twigs all declined before day 75-80. The rate of
sugar stock decline seems to be constant with time, as shown by cubic regression fits with
hardly visible curvature (Fig. 3). NHS content in twigs remained constant; all of the
decline in TSS was due to decline in hexose.
Figure 3. Absolute TSS, hexose, starch, and computed non-hexose sugar (NHS) content
in twigs during the month of March, 2019.
Each point represents one tree at one sampling time. Trendlines are cubic polynomial fits.
Points from all DBA treatments are shown and are not differentiated. NHS values for
each bud sample were obtained by subtracting Hexose from TSS.
Starch in twigs initially declined at the same proportional rate as hexose.
However, starting at day ~75-80, coinciding with the beginning of endogenous bud
respiration increases, twigs began to accumulate starch, even as TSS and hexose levels
continue to drop at their previous rates (Fig. 4).
66 66
Figure 4. Relative TSS, hexose, and starch content in twigs during the month of March,
2019.
Each point represents one tree at one sampling time. Trendlines are cubic polynomial fits.
Points from all DBA treatments are shown and are not differentiated. Standard material
was a mixture of pistachio twigs from the first and second sampling dates.
67 67
Omnibus MANOVA of starch, TSS, and hexose in day 77 twigs revealed
significant effects for shoot ON/OFF status (p<0.001) after accounting for residual batch-
to-batch, treatment, and application date effects. Post hoc univariate ANOVA showed
that in ON shoots, TSS and hexose were lower (p<0.05) and starch was higher (p<0.01)
than in OFF shoots. These results indicate that twig starch accumulation upon growth
initiation is a process initially driven by the floral buds present on the shoot (Fig. 5).
Figure 5. Boxplot of differences in twig starch accumulation (day 77) between ON and
OFF shoots shortly after growth initiation.
Samples from day 77 were re-run in as few batches as possible to reduce batch-to-batch
variance.
68 68
In buds, the patterns of carbohydrate content show different patterns than in twigs
(Fig. 6). The hexose contents of buds and of twigs were almost identical throughout the
month of March, starting at just under 50 mg/g and decreasing linearly with time to 40%
the initial value by the end of March. Starch content increased slowly at first, then began
to fall near day ~75-80. NHS content remained constant, then increased after day ~75-80.
Figure 6. Absolute TSS, hexose, starch, and computed non-hexose sugar (NHS) content
in floral buds during the month of March, 2019.
Each point represents one tree at one sampling time. Trendlines are cubic polynomial fits.
Points from all DBA treatments are shown and are not differentiated. NHS values for
each bud sample were obtained by subtracting Hexose from TSS.
69 69
GA3 and Oil Can Induce Premature Carbohydrate Mobilization to Buds
Omnibus MANOVA to predict hexose, NHS, and starch content in buds
identified significant treatment effects (p < 0.01), and post-hoc ANOVA on each bud
carbohydrate measure identified significant treatment effects for all three (p<0.05), as
well as a significant (p<0.05) interaction effect on starch content between spray date and
the natural spline basis of sampling date (3 degrees of freedom), which we interpret as a
change in the timing of peak bud starch accumulation due to DBA spray date.
Figure 7 presents the DBA-induced differences in bud carbohydrate content.
Hexose in buds declined throughout the study period as it did in twigs (Figs. 6,
7a). Hexose levels in buds and twigs declined by a similar proportion (~60%) over the
whole monitoring period. Both applications of GA3 may have elevated hexose
concentrations, and both applications of oil may have accelerated hexose decline during
early ecodormancy. Ethephon's effects on hexose were minimal.
NHS levels in unsprayed buds first remained constant, then increased rapidly
(Fig. 7b). The onset of NHS content increase seemed most advanced for the oiled shoots.
Oiled shoots appeared to have higher NHS content at the beginning of March. This
excess was depleted in early ecodormancy. GA3 appeared to induce an additional early
peak in bud NHS (near day 70) before the endogenous increase. Ethephon's effects on
NHS were minimal.
In unsprayed buds, starch levels started low, increased to a peak at ~day 75-80,
then fell afterwards (Fig. 7c). Bud starch content was the only measure for which spray
date was statistically significant. Oil and GA3 applied in late February induced a starch
peak near the same time as the control, but the maximum level of starch accumulated was
higher. Oil and GA3 applied in early February (day 41) induced an earlier peak in starch
content (~day 60), and starch content decreased thereafter. Both applications of ethephon
had minimal effect on bud starch content. DBA application did not seem to affect the rate
of NHS accumulation in buds after ~day 75-80.
70 70
Figure 7. Relative hexose (a), non-hexose sugar (b), and starch (c) contents in female
pistachio floral buds throughout the month of March, 2019.
71 71
Overall, ethephon tended to have minimal effects on carbohydrate dynamics,
whereas GA3 and oil may increase carbohydrate content of tissue. GA3 and oil induced
anomalous NHS and starch content peaks in the period before respiration increase that
had no analog in the unsprayed trees.
Bloom Advancement and Compaction
2018 bloom observations indicated that GA3-treated trees (2000 mg a.i./l) were the
first to break bud and bloom, followed by oil-treated trees. GA3-treated trees also tended
to break more evenly than other treatments, with shoots facing different directions closer
to each other in bloom stage, which is important as buds receiving more sunlight and
warmth during the dormancy period emerge from dormancy later. Oiled trees broke next,
but irregularly. Ethephon gave slight advancement, but not more than oil, and 125 mg/l
AVG had an insignificant main effect, but is likely retarding, as a statistically significant
retarding interaction of AVG treatment with South aspect suggests that 125 mg/l AVG
may interfere with the accumulation of budbreak-promoting heat.
Bloom advancement and compaction results from 2018 are plotted and
summarized below (Figure 8). In 2018, synchrony was not evaluated because male trees
were not observed.
In 2019, unsprayed female trees had a bloom window lasting from day 104 to
107. Unsprayed male trees had a bloom window lasting from day 101-105. Bloom in
unsprayed trees of both sexes was first led by the shoots facing southeast, then spread to
the east side, with the west side trailing the east side by 1 or 2 days.
Oiled trees were the most advanced in 2019, but also had the widest bloom
window. Increases in both aspect and acropetal variation seemed to contribute to the
wider bloom window. Each shoot's response to oil seems strongly influenced by its
microclimate. Oil was the only treatment in which the west sides were more advanced
72 72
than the east sides of the same trees. Lower regions of the trees were also more advanced
than the high tips, a pattern shared with GA.
Figure 8. Bloom window hindcasts for crop year 2018.
DBAs were sprayed on March 6th (day 57). Day 100 = April 10th.
Ethephon induced the second-quickest and narrowest bloom of all the treatments.
Application of ethephon on day 41 resulted in a narrower bloom window than application
on day 57. Ethephon-treated trees seemed to retain the aspect variation of control trees,
but acropetal variation seemed to have been decreased. Ethephon was the only treatment
that seemed to regularize acropetal variation.
GA3 trees in 2019 were treated with a 10-fold lower concentration of 200 mg
a.i./l, a more economical dose for commercial production. We hoped that the lower dose
would avoid side effects while retaining the advancement effect of the higher dose, but
our hopes were not met. Instead, the lower dose of GA3 failed to induce advancement as
great as was seen in 2018, and still induces adverse side effects. Bud death and abscission
73 73
were induced on OFF trees treated on day 41, especially the more OFF trees in the block.
Abscission was concentrated in the lower branches of the tree. Additionally, although
GA3 regularized the directional variation in both 2018 and 2019, it magnified acropetal
variation. As with oil, lower branches of GA3-treated trees were more advanced. Overall,
the use of GA3 to advance or compact the bloom window cannot be recommended,
because GA3 seems to induce bud drop, reducing cluster number (data not shown) and
thereby reducing yield.
2019 bloom and synchrony observations are summarized in Figure 9. In
unsprayed trees, male trees bloomed 1 or 2 days earlier than the females; late-blooming
female clusters received poor coverage. The tested DBAs advanced female bloom by 1-4
days, and delayed bloom in male trees by 1-2 days. DBA-treated females bloomed sooner
than the DBA-treated males. Pollen can stay in the air for several days while remaining
viable, but ovule quality declines quickly after bloom, so it is usually desired for male
flowers to be shedding pollen 1-2 days before female flowers become receptive. In this
light, the results represent no improvement over the control, and DBAs may actually have
worsened the males' coverage of the earliest female shoots.
Figure 9. Bloom window hindcasts for crop year 2019.
74 74
Yield and Quality Components
In the past, oil treatments have been shown to accelerate the onset of nut fill and
enable earlier harvests in adequately chilled trees (Beede et al., 2002). We detected no
difference in harvest readiness between our treatments in 2018. Selected yield and quality
results from 2018 are presented in Table 2. The largest difference was between the
ethephon and the control treatments, but this difference was not statistically
significant. Despite our efforts to select uniform ON trees for the study, the selected trees
varied enough in the strength and position of their alternation to compromise any
conclusions that could be drawn from a single year's yield data.
Table 2: Yield and quality summary* for the field trial, crop year 2018.
Treatment 1st shake
dry weight
Open in
shell %
Closed
edible %
Blanks % Payout per
tree**
GA3 0.2% 39 lbs. 66 20 6 $47
Oil 6.25% 45 lbs. 62 26 4 $54
Ethephon
500 mg/l
46 lbs. 62 25 6 $54
AVG 125 mg/l 36 lbs. 67 21 6 $45
Control 36 lbs. 61 27 6 $43
*Not included: split shelling stock (<4%), very small open in-shell, insect damage and
other internal defects.
**Payouts estimated at $1.60/dry lb for open in-shell and $0.80/dry lb for closed edible.
2019 yield data for the block established in 2018 (shown in Table 3) showed that
any yield increases suggested in the first year were compensated for in the second year by
alternate bearing. These findings suggest that observed yield differences in 2018 may in
fact have been primarily due to variations in alternate bearing status in the tested trees,
despite our having scouted the trees ON. A mixed-model ANOVA with treatment as a
75 75
fixed factor and block as a random factor suggested that 2-year cumulative yields were
not significantly different across all treatments (F= 0.155 on 4 and 12 df, p > 0.95).
Table 3: 1st-shake fresh weights from 2018 and 2019, block established 2018.
Treatment 2018 average
fresh weight
(lbs.)
2019 average
fresh weight
(lbs.)
2-year total
fresh weight
(lbs.)
GA3 0.2% 91 29 120
Oil 6.25% 98 39 137
Ethephon
500 mg/l
105 30 135
AVG 125 mg/l 86 39 125
Control 85 48 133
Unlike in the 2018 block, trees in the larger 2019 block were not first scouted ON,
and so this block should be more representative of production conditions. Only one year’s
yield data is available from the experimental block established 2019. The block
established in 2019 was harvested using two different apparatuses due to the need to
remove and destroy crop from GA3- and ethephon-treated trees prior to commercial
harvest of the rest of the field. Hence, we analyzed the fresh weights as if they had come
from a nested design. The commercial shaker removed significantly (p < 0.01) more crop
from the trees. Unfortunately, the difference in shaking prevents the GA/ethephon
treatments from being compared directly with the control/oil treatments. Yields from oil-
treated and control trees were negligibly different, and GA3 at 200 mg a.i./l yielded
insignificantly more than ethephon-treated trees. Yield data from this block are
summarized in Table 4.
76 76
Table 4: Average 1st-shake fresh weights (lbs.) from 3-tree plots, block established 2019.
Treatment Shaking procedure Not sprayed Sprayed
February 10
(day 41)
Sprayed
February 26
(day 57)
Control Commercial shaker,
6-second shake
263 - -
Oil 6.25% Commercial shaker,
6-second shake
- 266 253
Ethephon
500 mg/l
Almond shaker,
5-second shake
- 180 175
GA3 200 mg/l Almond shaker,
5-second shake
- 226 214
Discussion
Study Limitations
The weather provided the trees with adequate winter rest in both the test years, so
we were unable to test any of our treatments for chill-substituting effects.
The chemicals in this study were sprayed up into the canopy using a backpack
sprayer on foot, so incomplete coverage might complicate the interpretation of any
putative acropetal effect, especially regarding our observations of bloom advancement in
the lower branches of oil- and GA3-treated trees. Spraying instead using either a high-
boom sprayer or by air could remove that confounding factor in young trees. However, in
commercial orchards, spray coverage in the upper portion of the canopy is often less than
desired due to the interference of the canopy and the current limitations of spray
equipment, so this limitation is not unknown in commercial orchards.
The 2018 block had a water-sprayed control to account for evaporative cooling
caused by the spray itself. Evaporative cooling in spring delays bloom in pistachio
(Muller, 2008). In the 2019 block we instead used an unsprayed control to focus on the
77 77
effect of the spraying decision itself. Because it was the 2019 block's data that showed
that DBA application reverses the normal order of bloom, we cannot exclude the
possibility that evaporative cooling during ecodormancy may have contributed to this
undesirable outcome.
Endogenous Carbohydrate Mobilization Patterns During Ecodormancy
As measured by GA3 response (see Chapter IV), endodormancy in these trees
ended in mid-February. After buds accumulate enough chill to complete endodormancy,
they should become susceptible to heat. A critical accumulation of heat should lead to
growth initiation.
In pistachio pistillate flower buds, growth initiates in early March with gynoecium
differentiation, which finishes by April (Hormaza and Polito, 1996). As shown in Figure
2, after growth resumed in mid-March, bud respiration was no longer responsive to
external temperature, which fluctuated, but continued to increase steadily on the plant's
own schedule. By day 79 of 2019, respiration had doubled from its pre-day-70
ecodormant baseline. On that day, based upon our 2018 observations, we issued a
prediction that bloom would follow in 3.5 weeks (~25 days). On day 104, control trees
achieved 10% bloom. Our successful prediction of bloom date based on the timing of
elevated respiration suggests that the time span from discernable respiration increase to
bloom may be tightly constrained.
Endogenous bud respiration increase is accompanied by a suite of changes in
carbohydrate dynamics: bud NHS begins increasing, bud starch begins decreasing, and
twig starch begins accumulating. The rate of hexose depletion in both buds and shoots
seems steady through all of March, which spans late ecodormancy and early pre-bloom
growth. As shown in Figure 7, the rate of NHS accumulation in buds (~50-75 mg/g in 2
weeks) exceeds the sum total of hexose depletion (~20 mg/g in 2 weeks) and starch
78 78
depletion (~10 mg/g in 2 weeks). Mass balance implies that enough NSC is being
transported into the buds to account for TSS accumulation plus the demands of increased
bud respiration, and an additional amount also to the shoots to account for concurrent
starch accumulation in the twigs.
Based on the preceding observations, our view is that increased bud respiration is
a sign of growth initiation. By definition, growth initiation is the physiological event that
ends ecodormancy, so bloom time should be less sensitive to environmental temperature
after growth has begun. It remains unknown exactly how temperatures in late February
and early March promote growth initiation. We suggest that by the time a floral bud's
respiration first starts to increase in mid-March, its physiology may be entirely committed
to emerge from dormancy, and either proceed to bloom or terminate in abscission. Some
older heat accumulation models might be improved if they integrated not all the heat that
accumulates before bloom, but only the heat that has accumulated before growth initiates
at a fixed time before bloom.
The long span of time, almost an entire month, between endodormancy release in
mid-February and growth initiation in mid-March suggests that ecodormancy may
substantially decouple the timing of endodormancy release from the timing of bloom.
Thus, although low-chill winters can lead to both inadequate chilling to complete
endodormancy and uneven emergence from ecodormancy, perhaps these physiological
problems should be considered and solved separately.
Predictions of the C-T Model
The newest model of dormancy completion is the C-T model (Sperling et al.,
2019), which posits that in plant tissue, temperature history is translated into a
biochemical signal through temperature effects on starch-to-sugar interconversion. The
C-T model predicts that NSC transport to satisfy the high carbohydrate demands of
79 79
elevated floral bud respiration may cause the accumulation of starch in less quickly
respiring twig tissue (ibid.). Thus, higher rates of bud respiration before bloom should
produce a twig starch surge (ibid.). We did detect a starch surge in both ON and OFF
twigs eventually, and we detected the starch surge in ON twigs first. A starch surge in
ON twigs first would be explained if floral bud respiration in pistachio increases before
vegetative bud respiration, as it does in peach (Hatch and Walker, 1969). Vegetative bud
respiration was not measured in this study. Overall, our findings substantiated the starch
surge prediction of the C-T model.
Our other findings suggest one slight but important modification to the C-T
model, concerning its prediction of bloom soon after soluble sugar levels sharply decline.
As originally conceived (Sperling et al., 2019), the C-T model's key idea is that
temperature history is sensed through the polymerization and depolymerization of starch.
Starch is a polymer of hexose subunits, and Sperling et al. accordingly used an anthrone
method for carbohydrate quantitation that was specific for hexoses and does not respond
to pentoses. All of their data and analyses thus are based on hexoses alone. Consequently,
we suggest that the logic and model presented by Sperling et al. remain valid as long as
soluble hexose levels, and not soluble sugar levels, are considered.
During ecodormancy, twig starch and twig/bud hexose decline in the same
proportion with time. This pattern suggests that these NSC pools are in relatively fast
equilibrium with each other and are being depleted together. In contrast, the results from
tandem carbohydrate quantitation show that NHS concentrations in buds and twigs are
maintained at constant levels throughout ecodormancy. These observations suggest that
NHS are not easily catabolized and may function as soluble structural carbohydrates.
Furthermore, bud NHS levels increase upon growth initiation. Strangely, even though a
link between oxidative pentose phosphate pathway activation and dormancy release has
80 80
long been known and is well attested in the literature, our observation of bud NHS
increase in late ecodormancy before bloom seems to be novel.
It has been proposed (Kaufmann and Blanke, 2017) that the hexose:starch ratio
can be used as a potential biomonitor of dormancy in buds, or even acts as a trigger of
physiological changes. Our findings suggest that changes in the relative abundance of
hexose to NHS may function similarly as biomarker and trigger. This avenue warrants
further study. Our tandem acid method is capable of resolving these changes, but more
excitingly, if starch levels need not be quantitated, then NSC quantitation techniques
based on near-infrared reflectance, whose main weakness seems to be starch quantitation,
may hold promise for dormancy monitoring in the field.
DBA Effects on Respiration
Our preliminary studies on cuttings in growth chambers (Syverson et al., 2018)
showed that DBAs can have immediate effects on respiration as well as delayed effects
on the endogenous respiration increase. Those studies led us to believe that only a DBA's
effects on the endogenous respiration increase are reliably indicative of a DBA's strength:
in other words, immediate DBA effects on respiration seem generally unrelated to their
dormancy-breaking strength.
Our graphical analysis of the respiration time series strongly suggests that DBAs
advance the initiation of growth by a similar length of time as they advance bloom itself.
This unexpected finding substantiates a link between DBA-induced bloom advancement
and DBA effects on the endogenous pre-bloom respiration increase. Now that we
consider the onset of endogenous respiration increase itself as a sign of growth initiation,
a question presents itself: how can we tell if a DBA's immediate effects on respiration are
part of its mode of action or not? A drug-drug interaction study between the DBA and
81 81
specific inhibitors of cytochrome c-dependent and alternative oxidase-dependent
respiration could reveal those answers, i.e., the approach of Malyshev et al. (2016).
DBA Effects on Carbohydrate Mobilization and Bloom Synchrony
Our results suggest that in floral buds, the endogenous timings of starch
accumulation and of respiration increase are synchronized. Starch accumulates to a peak
just as respiration begins to increase.
We had hypothesized that DBAs applied at ineffective times would disrupt any
endogenous bud carbohydrate dynamics. We expected deleterious effects of DBAs to
manifest as reduced NSC transport into buds or as increased rate of NSC depletion, both
of which would induce starvation, but our data did not support our presumption. Only oil
may have accelerated the endogenous rate of bud sugar depletion in early ecodormancy,
and this effect was not statistically significant. Nor did any DBA change the rate of sugar
accumulation upon growth initiation.
Instead, we observed that carbohydrate levels were generally higher in DBA-
treated buds than in control buds. Inducing early carbohydrate mobilization may remove
resource support from growing floral buds, resulting in a wider bloom window. For
instance, it seems that GA3 and oil treatment can advance the starch accumulation in buds
while minimally affecting the timing of the endogenous respiration increase. Figure 7c
suggests that the treatments (GA3 and oil applied on day 41) that elevated bud starch
content before growth initiated had lower bud starch content by late March approaching
bloom. GA3 and oil treatments also had wider bloom windows than ethephon or the
control. In contrast, ethephon treatment maintained natural bloom window narrowness
and induced the smallest changes in carbohydrate levels relative to the control.
Thus, we suggest that any DBA-induced increases in carbohydrate content that
are not synchronized with growth initiation may be disruptive to bloom. While we agree
82 82
with Sperling et al. (2019) in observing that many existing DBAs appear to affect NSC
transport and consumption, we believe that carbohydrate mobilization is not a good
system to target when developing new DBAs.
In California, pistachio growers have often considered oil as a possible remedy
for uneven bloom induced by low chill accumulation. But while there is evidence that oil
is an effective growth accelerant when applied near the time that trees achieve complete
winter rest (Beede, 2007), there is minimal or no evidence that oil is effective in years
with marginal chill. Although this study did not directly examine the effect of applying
oil in inadequately chilled trees, our data do suggest that oil may accelerate the
endogenous rate of hexose depletion during ecodormancy. This finding gives credence to
Beede's (pers. comm.) and Ferguson's (pers. comm.) earlier suspicions that using oil in a
warm winter is likely to reduce yield because warm winters and oil both deplete available
energy stores. In this respect, ethephon is potentially superior in that its mode of action
does not seem to target carbohydrate mobilization at all.
Possible DBA Modes of Action
In this study we considered GA3 as a positive control, because it had earlier been
reported (Tzoutzoukou et al., 1989) that GA3 advances bud break in pistachio and
substitutes for chill. In seed germination, light promotes GA biosynthesis and enhances
sensitivity to GAs, so exogenous GA substitutes effectively for light (Derkx and Karssen,
1993). ABA is the key hormone that maintains dormancy, and GA represses ABA
biosynthesis. GAs also promote glucanase synthesis, which restores symplastic
connections between plant cells and enables the bud meristem to utilize imported NSC as
fuel for growth. GAs also encourage the degradation of glucose through the pentose
phosphate pathway (Simmonds and Simpson, 1971). In this study, 200 mg/l GA3 applied
in early February (day 41) indeed induced an early peak in NSC accumulation in buds as
83 83
starch. Exogenous GAs likely trigger multiple modes of action, likely not only promoting
dormancy release but also causing side effects.
Our group earlier discovered (Syverson et al., 2018) that oil immediately
increases respiration from buds to which it is applied. It is tempting to propose that oil's
primary mode of action may be to deplete available hexose to force earlier bloom and
simultaneously enhance sensitivity to environmental heat. However, it is difficult to see
why oil would cause bloom and leaf-out on the west side to not only catch up to the east
side, but overtake it. Because the west side is strongly lit in the warmer afternoon,
whereas the east side is more strongly lit in the morning when it is colder, we speculate
that oil may synergize with environmental warmth and light to advance bud phenology.
The role that light plays in this interaction is unclear. Sunlight heats the buds to warmer
than ambient air (Doll et al., 2018). Alternatively, the photodegradation of certain oils
releases ethylene and induces ethylene production in the plant (Saad et al., 1969), but we
do not know whether such oils are present in the oil we applied.
Ethephon is an ethylene prodrug. Our field observations suggest that ethephon
applied during ecodormancy may counteract the pistachio tree's endogenous acropetal
gradient in budbreak. Acropetal bloom order in trees is often maintained by gradients
decreasing from top to bottom of auxins, which inhibit bud break, e.g. in apples (Jackson,
2005). California pistachios are very apically dominant (Ferguson et al., 2005), so this
auxin-based explanation is likely to hold. Ethylene inhibits basipetal auxin transport by
gravity in tomato and pepper leaves (Lyon, 1970), and applying ethephon to grapes
reduces their apical dominance (Bautista et al., 1991). Thus, ethephon's ability to
counteract endogenous acropetal variation in pistachio suggests that the dormancy-
breaking mechanism of ethephon/ethylene involves inhibiting auxin transport, thereby
promoting both budbreak and bloom uniformity.
84 84
Interestingly, our study seems to be the first to report any ethephon-induced
advancement of dormancy release phenology in tree crops. Shahba (2019) reported that
ethephon could promote the germination of seeds of black calla lily (Arum palaestinum
Boiss). But most studies on dormant tree crops with ethephon have applied it in autumn,
when dormancy is being induced, often resulting in delayed spring phenology, e.g. in
peaches (Sloan and Matta, 1996). The literature even includes an Iranian study on cv.
'Kaleh-Ghouchi' pistachio (Askari et al. 2011) that applied a range of ethephon doses
including 500 mg/l (this study's rate) on February 10, March 1, and at both times. Their
late-winter application delayed budbreak by between 7 and 16 days depending on dose
and application time. In contrast, after applying 500 mg/l ethephon in late winter to cv.
'Kerman', we obtained 2-3 days of advancement in both trial years.
It is difficult to reconcile our results with those of Askari et al. (2011). Their
control trees began to bloom on March 24-25, which would be extraordinarily early for
'Kerman' in California. Their applications were 43 days and 24 days before bloom; in
contrast, our applications were 63 and 47 days before bloom in 2019, and 31 days before
bloom in 2018. Our two groups' testing thus overlapped the range ~40-30 days before
bloom as well as the calendar date range February through March. Lastly, Askari et al.
did not describe their edaphic conditions nor their pruning or irrigation regimens, so we
cannot compare on those bases. We can only suggest that both results may be cultivar-
dependent, in which case further work with ethephon in the newer California female
pistachio cultivars 'Golden Hills', 'Lost Hills', and 'Gumdrop' might be necessary.
We note that the more effective dormancy-breaking agents for which we have two
years' data (i.e., oil and ethephon) seem to have modes of action linked to ethylene, which
itself plays some unclear role in dormancy release. The most reliable DBA used on other
plants, H2NCN, has a mode of action that involves inducing prolonged ethylene
biosynthesis and release (Nee, 1986; Shi et al., 2018). The amino acid asparagine is a
85 85
common detoxification byproduct of cyanogenic ethylene biosynthesis. In pistachio buds,
levels of asparagine that increase throughout the dormant season suggest gradually
increasing rates of ethylene biosynthesis over the same period (Durzan, 1996). Ethylene
seems to act pleiotropically and in conjunction with other growth regulators (such as GA)
in dormancy release.
It is likely worth distinguishing between rest-breaking agents (RBAs), which
substitute for chill and promote the completion of endodormancy, and quiescence-
breaking agents (QBAs), which ensure regular emergence from ecodormancy. Although
hormonal studies of the control of dormancy-breaking have tended to focus on the
antagonism between GA and ABA (Liu and Hou, 2018; Pham et al., 2018), genome-wide
association studies of bloom time QTLs have tended to find links to photosynthetic
genes, phytochrome responses, and auxin transport, e.g., the work of Porto et al. (2015).
We suggest that ABA/GA antagonism may be closer related to endodormancy, whereas
light response and auxin may be closer related to ecodormancy. In this analysis
framework, ethephon, which releases ethylene that inhibits the basipetal transport of
auxin, likely functions primarily as a QBA. Thus, the roles that ethylene and its
biosynthetic coproduct cyanide may play during ecodormancy warrant further attention.
It may be a challenge to identify and amplify those modes of ethylene action that
positively affect yield.
Regarding the effect of DBA application time, higher yields were obtained for all
three tested DBAs in mid-February than in late February. Although these differences
were not significant, mid-February in 2019 coincided with measured release from
endodormancy, and physiological signs of enhanced sensitivity at this time were
observed with each DBA. When applied in mid-February, oil induced the greatest bloom
spread, ethephon induced the most compact bloom, and GA3 induced the most bud death
in OFF trees. Considering that oil has previously been reported most effective when chill
86 86
has almost completely accumulated (Beede, 2007), we suggest that the transition from
endodormancy to ecodormancy may indeed be a special time to target for DBA
applications and is worth monitoring for.
DBAs, Synchrony, and Yield
We finally discuss the question of whether DBA applications can improve yields
by advancing and synchronizing bloom. Although bloom synchrony is obviously a
potential limiting component of yield, bloom date itself is not thought to be a similarly
limiting factor. What we call "early virgin" shoots may be especially important to
monitor. Early virgin shoots are those female shoots that are so phenologically advanced
that they yield poorly because of minimal pollinizer overlap. A disproportionately large
number of early virgin shoots were seen in the lower branches of oil- and GA3-treated
trees. Because they are so advanced compared to other shoots on the same tree, floral
buds on early virgin shoots develop into large yet useless clusters that take up valuable
early-season carbohydrates.
Focusing on the early virgin shoots helps explain why none of the tested DBAs
outperformed the untreated control in the 'Kerman'/'Peters' system with adequate chill.
DBAs advanced female bloom and delayed male bloom. Together, these effects reversed
the order of bloom and led to loss of synchrony. These results suggest that a next
approach could be to try treating trees of one sex alone. Because 'Peters' has a higher
chilling requirement than 'Kerman', treating the male trees only might be a cost-effective
management strategy to assure adequate winter rest in marginal-chill years and mitigate
the risk of losing synchrony to uneven or delayed male bloom.
Alternatively, DBAs that narrow the female bloom window without advancing it
could be sought. Narrowing the bloom window seems to function mainly by delaying the
earliest shoots, helping more of the female flower clusters overlap with male bloom.
87 87
This trial presumptively took a black-box approach towards the relationship
between pollinizer synchrony and yield. DBA treatments generally resulted in yield
losses relative to the control that could be explained by synchrony loss; however, our
yield data also suggest the existence of other treatment differences that would have to be
attributed to processes other than pollination synchrony. Closer attention needs to be paid
to how yield components (i.e., cluster count, # nuts/cluster, proportion of nuts blank,
filled, and split) and processes affecting yield components (e.g., fruit set and fruit
abscission, timing of kernel fill and nut maturity) are associated with pollinizer
synchrony and are affected by DBA treatment.
The consistency of 2-year cumulative yields from our 2018 trial block raises the
question of how alternate bearing may limit the yield gains or losses that can be achieved
from dormant-season events. Yield gains in one year from successful dormant
management may be offset by lower yields in the following year. We suggest that future
exploratory efficacy trials of DBAs should seek improved single-year yields, a practice
that would avoid conflation of a DBA's ability to protect a given year's crop with a DBA's
presumed inability to improve cumulative yields. Such trials would ideally take place in
strongly alternating orchards on blocks of trees previously scouted ON. Multi-year
efficacy trials of more mature treatments could be analyzed by extending the method of
Kallsen (2017) and examining how regular DBA use affects the influence of winter chill
on yield.
A major goal of this project was to identify a single best candidate for further
trials. No clearly best candidate has emerged. The horticultural and regulatory tradeoffs
between ethephon and GA3 will have to be evaluated by the industry. Neither product is
registered, but only ethephon should require budgeting for crop destruction; GA3 is
federally exempt from the requirement of a tolerance (40 CFR § 180.1098), so lawfully
treated nuts from research trials may enter commerce. Both ethephon and GA3 seem to
88 88
carry the risk of yield loss in conditions of adequate chill. Ethephon performed well in the
female-only 2018 trial but poorly in the 2019 trial that included trees of both sexes. GA3
had the lowest 2-year cumulative yield in the 2018 trial and induced bud drop, so it does
not seem suitable for use during ecodormancy. However, endodormant application of
2500 mg a.i./l GA3 increased yield in "Ohadi" pistachio (Kashanizade et al., 2017), so
using lower concentrations (5 to 200 mg a.i./l) during endodormancy to substitute for
chill in marginal-chill years could be a promising strategy. In support of product
registration, further trials remain to be conducted of either ethephon or GA3 to determine
the effective dose ranges and application times, as well as their efficacy on other
commercial pistachio cultivars, in chill-deficient situations, in saline soils, and with
repeated use.
Conclusions
In pistachio pistillate floral buds, growth is initiated several weeks before visible
bud swell. Initiation of growth is indicated by accumulation of NHS in buds and starch in
twigs, as well as a continuous increase in bud respiration. Once growth has been initiated,
NSC transport to buds is critical to sustain high assimilatory and catabolic demands for
carbohydrates. Depending on application time, DBAs such as GA3 and oil may induce
premature mobilization and dissipation of stored carbohydrates, likely extending the
bloom window.
Although low-chill winters can lead to both inadequate chilling to complete
endodormancy and uneven emergence from ecodormancy, perhaps these physiological
problems should be considered and solved separately. The transition from endodormancy
to ecodormancy is an important physiological event that likely structures the effective
application time range of any DBA.
89 89
A two-year study with adequate chill in both years found no significant effect of
any DBA on cumulative yield. In both years, 500 mg/l ethephon applied in early
ecodormancy successfully advanced female bloom in 'Kerman' pistachio while
maintaining natural bloom window narrowness. Ethephon's mode of action does not seem
to involve altered carbohydrate dynamics. AVG does not act as a DBA, and GA3 cannot
be recommended for ecodormant use.
90 90
References
Albalasmeh, A.A., A.A. Berhe, and T.A. Ghezzehei. 2013. A new method for rapid
determination of carbohydrate and total carbon concentrations using UV
spectrophotometry. Carbohydr. Polym. 97(2): 253–261. doi:
10.1016/j.carbpol.2013.04.072.
Askari, E., S. Irani, and K. Razmjoo. 2011. Bloom, maturity, and fruit set of pistachio in
response to early season application of ethephon. Hortic. Environ. Biotechnol.
52(1): 29–34. doi: 10.1007/s13580-011-0029-4.
Bailey, R.W. 1958. The reaction of pentoses with anthrone. Biochem. J. 68(4): 669–672.
Baldocchi, D., and E. Waller. 2014. Winter fog is decreasing in the fruit growing region
of the Central Valley of California. Geophys. Res. Lett. 41(9): 3251–3256. doi:
10.1002/2014GL060018.
Bautista, A.D., G. Vargas, and J.C. Colmenares. 1991. Influencia del etefon sobre la
brotacion y fertilidad de tres cultivares de vid. Agron. Trop. 41(5–6): 225–235.
Beede, R.H. 2007. Chilling, Cold Injury, and Dormant Oil Research in Pistachio (Kerman
and Peters cv.). http://cekings.ucanr.edu/files/19104.pdf.
Beede, R.H., C. Nichols, J. Starling, B. Lahorn, Z. Heath, et al. 2002. Growth, Yield, and
Nut Quality Responses in a Commercial Pistachio Orchard from Dormant Applied
Horticultural Mineral Oil. Calif. Pist. Comm. Res. Rep. 2002: 153–164.
Derkx, M.P.M., and C.M. Karssen. 1993. Effects of light and temperature on seed
dormancy and gibberellin-stimulated germination in Arabidopsis thaliana: studies
with gibberellin-deficient and -insensitive mutants. Physiol. Plant. 89(2): 360–368.
doi: 10.1111/j.1399-3054.1993.tb00167.x.
Doll, D., J. Coelho, M. Zwieniecki, L. Zhang, L. Ferguson, et al. 2018. The evaluation of
winter kaolin clay and dormant oil applications on chill accumulation and yield in
the California pistachio ( Pistacia vera ) cultivars ‘Kerman’ and ‘Peters.’ Acta
Hortic. (1219): 111–118. doi: 10.17660/ActaHortic.2018.1219.19.
Durzan, D.J. 1996. Nitrogen reallocation during female bud abscission in alternate
bearing of pistachio. Adv. Hortic. Sci. 10(4): 219–225.
Ferguson, L., V. Polito, and C. Kallsen. 2005. The pistachio tree; botany and physiology
and factors that affect yield. Pist. Prod. Man. 4th Ed Davis CA USA Univ. Calif.
Fruit Nut Res. Inf. Cent.: 31–39.
91 91
Fishman, S., A. Erez, and G.A. Couvillon. 1987. The temperature dependence of
dormancy breaking in plants: Computer simulation of processes studied under
controlled temperatures. J. Theor. Biol. 126(3): 309–321. doi: 10.1016/S0022-
5193(87)80237-0.
Hatch, A.H., and D.R. Walker. 1969. Rest intensity of dormant peach and apricot leaf
buds as influenced by temperature, cold hardiness and respiration. J Amer Soc Hort
Sci 94: 304–307.
Hormaza, J.I., and V.S. Polito. 1996. Pistillate and staminate flower development in
dioecious Pistacia vera (Anacardiaceae). Am. J. Bot. 83(6): 759–766. doi:
10.1002/j.1537-2197.1996.tb12765.x.
Jackson, J.E. 2005. The Biology of Apples and Pears. Cambridge University Press.
Kallsen, C.E. 2017. Temperature-related Variables Associated with Yield of ‘Kerman’
Pistachio in the San Joaquin Valley of California. HortScience 52(4): 598–605. doi:
10.21273/HORTSCI11775-17.
Kashanizade, S., Sh. Hajivand, N. Jalilvand, A. Mohammadbeigi, and V. Rasoli. 2017.
The effects of GA3 on some qualitative and quantitative characters of Pistacia vera
Var. “Ohadi.” Int. J. Agric. Environ. Res. 3(1): 2114–2120.
Kaufmann, H., and M. Blanke. 2017. Changes in carbohydrate levels and relative water
content (RWC) to distinguish dormancy phases in sweet cherry. J. Plant Physiol.
218: 1–5. doi: 10.1016/j.jplph.2017.07.004.
Landhäusser, S.M., P.S. Chow, L.T. Dickman, M.E. Furze, I. Kuhlman, et al. 2018.
Standardized protocols and procedures can precisely and accurately quantify non-
structural carbohydrates. Tree Physiol. 38(12): 1764–1778. doi:
10.1093/treephys/tpy118.
Liu, X., and X. Hou. 2018. Antagonistic Regulation of ABA and GA in Metabolism and
Signaling Pathways. Front. Plant Sci. 9: 251. doi: 10.3389/fpls.2018.00251.
Luedeling, E., M. Zhang, and E.H. Girvetz. 2009. Climatic Changes Lead to Declining
Winter Chill for Fruit and Nut Trees in California during 1950–2099. PLOS ONE
4(7): e6166. doi: 10.1371/journal.pone.0006166.
Lyon, C.J. 1970. Ethylene inhibition of auxin transport by gravity in leaves. Plant
Physiol. 45(5): 644–646. doi: 10.1104/pp.45.5.644.
Malyshev, R.V., M.A. Shelyakin, and T.K. Golovko. 2016. Bud dormancy breaking
affects respiration and energy balance of bilberry shoots in the initial stage of
growth. Russ. J. Plant Physiol. 63(3): 409–416. doi: 10.1134/S1021443716030092.
92 92
Muller, A.M. 2008. The effects of rest breaking agents, pruning and evaporative cooling
on budbreak, flower bud formation and yield of three pistachio (Pistacia Vera L.)
cultivars in a climate with moderate winter chilling.
Nee, C.-C. 1986. Overcoming bud dormancy with hydrogen cyanamide: timing and
mechanism. Ph.D. thesis, Oregon State University.
Pham, A.T., R. Kumar, P.K. Rehal, P.K. Toora, and B.T. Ayele. 2018. Molecular
Mechanisms Underlying Abscisic Acid/Gibberellin Balance in the Control of Seed
Dormancy and Germination in Cereals. Front. Plant Sci. 9: 668. doi:
10.3389/fpls.2018.00668.
Pope, K.S., V. Dose, D. Da Silva, P.H. Brown, and T.M. DeJong. 2015. Nut crop yield
records show that budbreak-based chilling requirements may not reflect yield
decline chill thresholds. Int. J. Biometeorol. 59(6): 707–715. doi: 10.1007/s00484-
014-0881-x.
Porto, D.D., M. Bruneau, P. Perini, R. Anzanello, J.-P. Renou, et al. 2015. Transcription
profiling of the chilling requirement for bud break in apples: a putative role for
FLC-like genes. J. Exp. Bot. 66(9): 2659–2672. doi: 10.1093/jxb/erv061.
Saad, F.A., J.C. Crane, and E.C. Maxie. 1969. Timing of olive oil application and its
probable role in hastening maturation of fig fruits. J Amer Soc Hort Sci.
Shahba, M.A. 2019. Seed Germination, Drought, and Salinity Tolerance of the
Endangered Black Calla Lily (Arum palaestinum Boiss) Endemic in Mediterranean
Coast. Presented at ASHS Annual Conference 2019, August 25 2019, Las Vegas,
NV.
Shi, Z., T. Halaly-Basha, C. Zheng, M. Weissberg, R. Ophir, et al. 2018. Transient
induction of a subset of ethylene biosynthesis genes is potentially involved in
regulation of grapevine bud dormancy release. Plant Mol. Biol. 98(6): 507–523.
doi: 10.1007/s11103-018-0793-y.
Simmonds, J.A., and G.M. Simpson. 1971. Increased participation of pentose phosphate
pathway in response to afterripening and gibberellic acid treatment in caryopses of
Avena fatua. Can. J. Bot. 49(10): 1833–1840. doi: 10.1139/b71-258.
Sloan, R.C.J., and F.B. Matta. 1996. Peach bloom delay and tree responses to fall
applications of ethephon. Bull. Miss. Agric. For. Exp. Stn. USA.
http://agris.fao.org/agris-search/search.do?recordID=US9709949 (accessed 27
October 2019).
Sperling, O., T. Kamai, A. Tixier, A. Davidson, K. Jarvis-Shean, et al. 2019. Predicting
bloom dates by temperature mediated kinetics of carbohydrate metabolism in
deciduous trees. Agric. For. Meteorol. 276–277: 107643. doi:
10.1016/j.agrformet.2019.107643.
93 93
Syverson, D., P. Gordon, M. Khezri, J. Bushoven, L. Ferguson, et al. 2018. Efficacy trials
of new dormancy-breaking treatments in pistachio. Calif. Pist. Res. Exec. Summ.
2018: 23–24.
Tzoutzoukou, C.G., C.A. Pontikis, and A. Tolia-Marioli. 1998. Effects of gibberellic acid
on bloom advancement in female pistachio ( Pistacia vera L.). J. Hortic. Sci.
Biotechnol. 73(4): 517–526. doi: 10.1080/14620316.1998.11511008.
Wang, L., L. Zhang, C. Ma, W. Xu, Z. Liu, et al. 2016. Impact of chilling accumulation
and hydrogen cyanamide on floral organ development of sweet cherry in a warm
region. J. Integr. Agric. 15(11): 2529–2538. doi: 10.1016/S2095-3119(16)61341-2.
Zhang, L. 2018. Studies of Pistachio Flower Quality and Development as influenced by
Low Chill in California. Presented at CA Statewide Pistachio Day, January 19
2018, Visalia, CA.
http://lecture.ucanr.edu/Mediasite/Play/c8fa0c86a441459996ae1c07849ee1aa1d.
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Appendix: Methodology of NSC measurements
Operating Principles of the Acid Methods
Recent literature has raised the issue of inter-laboratory reliability in the
measurement of non-structural carbohydrate (NSC) from plant samples. Quentin et al.
(2015) challenged different labs to analyze an identical set of intentionally challenging
samples. They concluded that inter-lab variability made NSC measurements from
different labs difficult to compare. Landhausser et al. (2018) countered with an inter-lab
comparison of a small set of standardized protocols and demonstrated that inter-lab
variability could be mostly eliminated by protocol standardization, but that begs the
question: upon what protocols should labs standardize, and why?
NSC measurement protocols entail both extraction and quantitation; we discuss
only quantitation.
As reviewed by both Quentin et al. and Landhausser et al., laboratory methods for
NSC quantitation include ion-exchange chromatography (IC), enzymatic scintillation
methods, and acid methods based on a digestion. The acid methods are of greatest
relevance to agricultural research/development and grower decision support due to their
high potential throughput, low per-sample cost, low laboratory fixed cost, and low
minimum sample volume. IC and enzymatic methods have higher fixed and variable cost,
and while near-infrared reflectance (NIRR) measurements involving no wet chemistry are
even faster and cheaper, at the moment NIRR for NSC quantitation is not quite mature.
Inaccurate starch determination seems to be the main hurdle for NIRR to overcome.
Owing to historical scientific emphasis on the physiology of alternate bearing in
pistachio, most of the effort that has gone to measuring NSC levels in pistachios has
focused on the active growth season, with special emphasis on the induction of bud
abscission and postharvest carryover into the dormant season (Nzima et al., 1997; Spann
et al., 2008). Building on this work, the California Carbohydrate Observatory (CCO) is a
95 95
crowdsourced statewide carbohydrate monitoring effort for tree crops that accepts twig
samples year-round, including during the dormant season.
The CCO uses the anthrone method to quantitate soluble hexose and starch levels
(Sperling et al., 2019). The anthrone method begins with sulfuric acid (H2SO4) digestion.
H2SO4 is the acid most commonly used for the digestion step in carbohydrate
quantitation, and the phenol-H2SO4 method, the resorcinol method, the anthrone method,
and the H2SO4-UV method all begin with H2SO4 digestion. A persistent concern with
these methods is that H2SO4 digestion is not specific to NSCs. H2SO4 readily attacks
glycoproteins and structural carbohydrates as well. Consequently, H2SO4-based methods
are less suited than IC or enzymatic methods to the quantitation of metabolically active
sugar pools (Landhäusser et al., 2018).
In our experience, most of the difficulty in NSC measurement lies in process
control of sample preparation and extraction. Given an extract, quantitating its sugar
content by acid methods is relatively straightforward. When concentrated sulfuric acid is
added to a dilute aqueous solution of sugar, the dehydrating action of the acid converts
hexoses into 5-hydroxymethyl-furfural and pentoses into furfural. Anthrone, resorcinol,
and phenol are all developing reagents that then bind to these furfurals and give them
visible color.
Differential reactivity of the coloring agents with the various furfurals gives each
colorimetric assay distinctive specificity. For example, the anthrone assay as usually
practiced (~3-6 mg anthrone reacted with ~20-100 μg carbohydrate in 4 ml assay volume
of 75% (v/v) H2SO4) is specific for hexoses (Bailey, 1958); lowering the concentration of
anthrone increases the sensitivity to pentoses at the cost of sensitivity to hexoses (ibid.).
Resorcinol is specific for ketoses. Phenol has the broadest spectrum of reactivity, reacting
equally with furfurals derived from hexoses and pentoses.
96 96
The H2SO4-UV method, recently proposed as a standalone method (Albalasmeh
et al., 2013) but actually developed much earlier as a diagnostic for the phenol-sulfuric
acid method (Rao and Pattabiraman, 1989), differs from all the other acid methods in that
it uses no developing reagent. Instead, the furfurals formed from sugars are directly
detected by their absorbance in the UV range (peak at 315 nm in the presence of sulfuric
acid). Because this method uses no developing reagent, the experiments generate only
waste salts, which are easily disposed of. But the H2SO4-UV method necessarily has the
least specific response of all the acid methods because no developing reagent is used. The
H2SO4-UV method is thus most likely to replace the phenol-sulfuric acid test as the most
nonspecific carbohydrate test. Yet the H2SO4-UV method has mainly been tested on pure
chemicals and does not have a long history of being used on plant samples.
As Landhausser et al. (2018) pointed out in the Supplementary Material to their
article, any acid method that uses a developing reagent should be run in parallel with an
acid-only blank on each sample to correct for any chromogenic interference arising from
acid reacting with the matrix. Rao and Pattabiraman (1989) demonstrated that the color-
developing condensation reactions in the acid analyses can proceed at room temperature.
In that context, a question naturally arises; is a tandem assay valid in which
furfurals are first formed by acid digestion, measured, then a developing reagent added
and the sample measured again? Can the order of addition be safely changed? The answer
seems to be yes.
The Order of Addition
Regarding the order of addition, there are four reagents: carbohydrate, acid, heat,
and developing reagent. The conversion of sugar to furfural and vice versa under acidic
conditions at high temperature have been extensively explored in literature due to interest
in the chemical utilization of biologically derived feedstocks. A review is beyond the
97 97
scope of this Appendix. Three dehydrations are necessary to form furfural from sugar; the
rate-limiting reaction in the assay is likely the initial dehydration of the sugar which can
only occur at high temperature, so heat itself is usefully considered a reagent.
In what is often referred to as the "traditional" order of addition in the phenol-
sulfuric acid assay, all the chemical reagents are kept on ice and mixed on ice; only after
mixing is a known amount of heat then applied. At first glance, this method seems to
have the advantage of not relying upon the heat of dilution of H2SO4 to provide heat for
the assay. But closer examination reveals problems.
The first problem is differential sensitivity. Three dehydrations are necessary to
form furfural from sugar; the partially dehydrated intermediates are poorly characterized.
Some of these intermediates are more reactive with phenol (or other color-developing
agents) than the furfurals themselves, and it is not clear which intermediates exist/are
formed from any given sugar's dehydration reactions. Thus, assays with this order of
addition are unpredictably and differentially sensitive to particular monosaccharides. This
order of addition seems to persist in the literature largely because glucose sensitivity
happens to be enhanced by this order of addition. Some researchers interested in a
glucose signal who prefer to remove interference from other sugars have considered this
order of addition superior.
A second problem with this order of addition is that it exposes the developing
agent to heat, which induces two processes that confound the development of color (Rao
and Pattabiraman, 1989). The first process is the deactivation of developing reagent by
sulfonation. The second process is destruction of dye by thermal instability. The decision
of how much heat to apply then becomes subject to an artificial trade-off between the
necessity of forming furfurals and the desire to preserve the developing reagent's potency.
For all those reasons, Rao and Pattabiraman (1989) suggested that developing reagent
should be added after heating. The dye-forming reactions are facilitated by temperature
98 98
but do not require high temperature. Color will develop at room temperature with phenol
(Rao and Pattabiraman, 1989) and on ice with anthrone (Su and Ho, 1955) developing
agents. To our knowledge, no efforts have been made to optimize assay conditions for
maximum color stability when developed at room temperature.
Towards Automation
The acid assays for carbohydrate are not easy to automate. The primary challenge
of automation is how to deal with the heating in the reaction to achieve a precise result
(Ruhmann et al., 2015). A comparative analysis of various procedures conducted by Rao
and Pattabiraman (1989) concluded that any heating step reduces the precision of the
assay in general. For example, Albalasmeh et al. (2013) solved the problem by adding
sulfuric acid to sugar and timing the vortexing of the tube, stopping the reaction by
transferring the sample to ice, then reading the furfurals directly at 315 nm. By depending
entirely on the heat of dilution and exposing the sample for a known amount of time,
precision was achieved. This procedure cannot be automated for 96-well format easily
unless both a 96-channel pipette were used, and a way of cooling the whole plate at once
were available.
In our own attempts to automate that assay, using an 8-channel pipette to fill a 96-
well plate, we verified that the heat of dilution from the wells to which acid is first added
changes the thermal environment in the adjacent wells, resulting in higher readings for
later wells as well as lower readings for edge wells. Thermal position effects in 96-well
plates introduced systematic error in the standard curve, with a coefficient of variation as
high as 40%. For this reason, we were forced to abandon the 96-well format, and we
chose to adhere to the practice of Albalasmeh et al. (2013), i.e., we individually,
independently, and sequentially processed samples at ~1 ml volume.
99 99
Thus, the tandem method used in this study was conceived; it uses timed exposure
to the heat of dilution to assure precision in furfural formation, and makes use of a room-
temperature anthrone development step. Details of its implementation are provided in the
main text.
To achieve reliable automation of the tandem method in a 96-well plate format in
the future, a method is needed of converting sugars to furfurals without using the heat of
dilution to supply the necessary heat. The following schematic procedure is proposed. To
a very small volume of relatively concentrated carbohydrate extract, add acid pre-diluted
to the concentration of the assay mixture, approximately 71-75% (v/v). Heat the whole
plate for a known period of time to synthesize furfurals, and read the plate's UV
absorbance; then let cool to room temperature and mix in developing agent. Cover plate
and develop color at room temperature; read visible absorbance after development is
complete. This procedure would avoid the usual tradeoff in the selection of heating time
between converting sugar completely to furfural and deactivating the developing agent or
destroying the formed dye, because the developing agent is not present when the heat is
applied. This method was not prototyped for the present investigation.
Tissue Sampling, Extraction, and Digestion for Carbohydrate Analysis
Shoots were oven-dried for 24 to 48 hours at 65°C. Their floral buds were
removed and ground separately with mortar and pestle. An identical length of the two
shoots, the longer of 15 cm or two years' growth, was cut up and pooled. The cut pieces
of twig and wood were ground in a large Wiley mill and then sieved through household-
quality tea strainer balls (Mainstays™; Walmart) placed in beakers in an orbital shaker.
Samples for carbohydrate quantitation were processed in batches of 23 samples +
1 internal standard. For twigs, the internal standard was a mixture of the twig material
100 100
derived from the 1st and 2nd weeks of collection. A mixture of ground pistachio buds
was composed for use as a bud internal standard.
~25 mg ± 4 mg of dry ground sample was weighed out into a microcentrifuge
tube. Soluble sugars were extracted in 600-800 μl of boiling 80% ethanol. Samples were
returned to the 80°C water bath for 10 minutes, and the supernatant soluble sugar extracts
were then decanted away. The extracts were diluted to a volume of 25 ml with deionized
(DI) water, and 320 μl were used for the soluble sugar and hexose assays.
Pellets were washed twice with 50% (v/v) ethanol before being evaporated to
dryness in an oven at 65°C. Pellets were resuspended in α-amylase working solution (60
U/ml in DI water) and allowed to digest at room temperature overnight.
The completed α-amylase digests were centrifuged, and 100 μl supernatants were
each added to 500 μl amyloglucosidase working solution (12 U/ml in 0.1 N pH 4.8
acetate buffer) and incubated at 65°C for 30 minutes. The final dilution was to add 243 μl
DI water to 77 μl completed amyloglucosidase digest, making 320 μl total for the starch
assays. The total dilution factor for the starch assay is the same as that for the soluble
sugar assay: 1 ml assayed extract / mg sample, subject principally to weighing error.
Tandem H2SO4-UV/Anthrone Method
DI water and 100 μg/ml D-glucose solution were assayed as external standards.
To each 320 μl sample in a microcentrifuge tube, ~ 1 ml 95% H2SO4 was added. Each
tube was capped and vortexed for 30 seconds (timed with a stopwatch), then immediately
put into an ice-water bath. After all the assay mixtures had cooled down, 200 μl of each
was transferred three times to a flat-bottom polystyrene 96-well plate and their
absorbance at 315 and 620 nm was read in triplicate. The readings at 315 nm were used
to calculate total soluble sugar or starch concentration by the H2SO4-UV method.
101 101
For hexoses, the readings at 620 nm were used as a reagentless blank for a
modified anthrone assay. After 600 μl was transferred to make the first assay plate, 20 μl
anthrone developing reagent (40 mg anthrone in 1.5 ml of 75% (v/v) H2SO4) was added
to the remaining assay liquid in each tube, and the tubes were vortexed. The whole batch
was bathed for several seconds at 80°C and then left at room temperature to develop
color for 20 min. Assay liquids were then loaded into a 96-well plate in triplicate.
Absorbance of this second plate at 620 nm was recorded and used to calculate the hexose
concentration.
Despite effort, we could not eliminate high variability in extraction efficiency
between batches. To quantitatively correct for this variability, an extraction factor (EF)
was calculated for each batch: (sugar concentration of extract from internal standard
sample / internal standard sample weight). For each other sample in the batch, we then
calculated the quotient [(sugar concentration of sample extract / sample weight) / batch
EF]. Thus, the content of hexose, TSS and starch in each sample were expressed relative
to the content of the internal standard.
Relative contents were converted back into absolute values by multiplying by the
average carbohydrate content determined for the standard. Non-hexose sugar (NHS)
content was estimated by subtracting absolute hexose content from absolute TSS content.
102 102
References
Albalasmeh, A.A., A.A. Berhe, and T.A. Ghezzehei. 2013. A new method for rapid
determination of carbohydrate and total carbon concentrations using UV
spectrophotometry. Carbohydr. Polym. 97(2): 253–261. doi:
10.1016/j.carbpol.2013.04.072.
Bailey, R. 1958. The reaction of pentoses with anthrone. Biochem J. 68(4): 669-72.
Landhäusser, S.M., P.S. Chow, L.T. Dickman, M.E. Furze, I. Kuhlman, et al. 2018.
Standardized protocols and procedures can precisely and accurately quantify non-
structural carbohydrates. Tree Physiol. 38(12): 1764–1778. doi:
10.1093/treephys/tpy118.
Nzima, M.D.S., G.C. Martin, and C. Nishijima. 1997. Seasonal Changes in Total
Nonstructural Carbohydrates within Branches and Roots of Naturally “Off” and
“On” `Kerman’ Pistachio Trees. J. Am. Soc. Hortic. Sci. 122(6): 856–862. doi:
10.21273/JASHS.122.6.856.
Quentin, A.G., E.A. Pinkard, M.G. Ryan, D.T. Tissue, L.S. Baggett, et al. 2015. Non-
structural carbohydrates in woody plants compared among laboratories. Tree
Physiol. 35(11): 1146–1165. doi: 10.1093/treephys/tpv073.
Rao, P., and T.N. Pattabiraman. 1989. Reevaluation of the phenol-sulfuric acid reaction
for the estimation of hexoses and pentoses. Anal. Biochem. 181(1): 18–22. doi:
10.1016/0003-2697(89)90387-4.
Ruhmann B., J. Schmid, and V. Sieber. 2015. Methods to identify the unexplored
diversity of microbial exopolysaccharides. Front. Microbiol. 2015(6): 565.
Spann, T.M., R.H. Beede, and T.M. DeJong. 2008. Seasonal carbohydrate storage and
mobilization in bearing and non-bearing pistachio (Pistacia vera) trees. Tree
Physiol. 28(2): 207–213.
Sperling, O., T. Kamai, A. Tixier, A. Davidson, K. Jarvis-Shean, et al. 2019. Predicting
bloom dates by temperature mediated kinetics of carbohydrate metabolism in
deciduous trees. Agric. For. Meteorol. 276–277: 107643. doi:
10.1016/j.agrformet.2019.107643.
Su, J.-C., and H.-K. Ho. 1955. Microdetermination of Pentose and Furfural by Anthrone
Reaction. J. Chin. Chem. Soc. 2(2): 132–153. doi: 10.1002/jccs.1955000
IV. VALIDATING A BIOASSAY OF ENDODORMANCY DEPTH FOR CALIFORNIA PISTACHIO (PISTACIA VERA CV.
'KERMAN')
Abstract
Dormancy-breaking agents (DBAs) are used to enable or extend cultivation of
trees with high chilling requirements in low-chill areas. Many DBAs, including dormant
oils, have narrow windows of application times in which they are effective, so science-
based DBA-timing decision support is highly sought. Oil applications are best targeted
near the transition from endodormancy to ecodormancy, but that transition is a difficult
event to forecast. Following recent mixed results from using GA3 directly as a DBA, I
conducted a modified bioassay experiment to answer two questions: whether single doses
of GA3 can break endodormancy in pistachio shoots, and whether the minimum effective
dose (MED) that breaks endodormancy can be used as a proxy measure for dormancy
depth in pistachio. My 2019 results confirmed both hypotheses: 2000 ppm GA3 sprayed
on pistachio shoots broke even deep endodormancy in January, and the MED to break
endodormancy decreased 3-fold per week until mid-February, when endodormancy was
endogenously released. This year's data suggest that a bioassay using the tested range of
GA3 concentrations would have a working range between 15-25 days before transition.
Thus, bioassay experiments of this or like design can provide timely estimates of
dormancy depth and forecasts of endodormancy completion, useful for DBA-timing
decision support, without requiring noxious chemicals or specialist equipment.
Introduction
The physiology of winter dormancy in perennial plants is complicated and
involves many unelucidated processes. Key physiological unknowns include the
mechanisms by which environment is translated into physiological response at the
cellular or tissue level, as well as the factors that limit the effectiveness of exogenous
104 104
dormancy-breaking agents (DBAs). In particular, many DBAs are known to have narrow
windows of effective application times, but predicting these windows is difficult, e.g.
(Beede, 2007). Grower standard practice is to use calendar-based or chill-based
recommendations, and it remains unknown which of these methods are better, or how to
effectively combine both. Science-based DBA-timing decision support is highly sought.
Winter dormancy consists of two generally recognized stages: endodormancy
followed by ecodormancy (Lang et al., 1987). Endodormancy is defined as that period of
time where buds are prevented from bursting by factors contained within the buds
themselves, whereas during ecodormancy the buds are ready to burst and are waiting for
the right environment. Chilling is thought to advance buds out of endodormancy, and
heat and light advances buds out of ecodormancy. Ecologically, the requirements for first
chill then heat correspond to the plant sensing that winter has come and passed.
Owing to the inherently different physiologies of endodormant and ecodormant
plant tissue, some DBAs may only work on one or the other stage. For example, in
pistachio, horticultural oil is used as a DBA to extend the growing season in spring and
improve bloom synchrony between male and female trees. Oil applications seem best
targeted around the onset of ecodormancy. Thus, to advise growers of their trees' DBA-
readiness, it is important to identify the completion of endodormancy and transition to
ecodormancy, but the timing of this event is difficult to assay until after it has already
happened.
In other high-chill crops, such monitoring is carried out by means of flower bud
dissection. For example, peach farmers in the southeastern US will look for the
development of yellow structures inside the bud to determine whether it is too late to
apply hydrogen cyanamide. But these methods are predicated on tracking some
continuous development of floral structures throughout dormancy, which does not occur
105 105
in pistachio. Consequently, a reliable tissue-testing method to assay whether pistachio
trees are ready for DBA application is desired.
As part of the Brar lab's research into new DBAs, I had some success applying
GA3 in late winter 2018 to pistachios to advance bloom, but I became concerned about
adverse yield effects we observed. To mitigate those effects, I decided to experiment with
lower and earlier doses of GA3. Regarding the optimization of GA3 dose and time, I was
primarily interested in two questions:
1. how the dose response of GA3 varies with application time during endodormancy;
particularly, whether there exists a minimal effective dose (MED) of GA3
required to break endodormancy, and how that MED varies with application
time;
2. whether cuttings' dose response to GA3 can itself be used as an assay of progress
towards endodormancy completion, to support pistachio growers' oil application
decisions as well as efforts to breed new cultivars with lower chilling
requirements.
I addressed these two questions by conducting an experiment on the effect of
single doses of GA3 applied at different times to endodormant pistachio cuttings. I
hypothesized that the MED of GA3 changes as a function of accumulated chill, and I
sought to use the MED itself as a measure of the tissue's depth of dormancy.
Methods
Cuttings were taken from a single block of 17-year-old 'Kerman'/'UCB-1'
pistachio trees located on the grounds of the CSU Fresno University Agricultural
Laboratory. Only ON shoots (with intact terminal vegetative buds and at least 4 lateral
floral buds) at least 30-35 cm long from female trees were cut, to assure similar situation
with regard to carbohydrate reserves and the alternate bearing cycle (Nzima et al., 1997).
106 106
Shoots were cut to 30-35 cm length, then taken into lab and sprayed with GA3 solutions
spanning a range of concentrations. 15-24 cuttings per treatment per date were used.
Depending on the treatment date, different concentrations were applied. Initially, I had
planned to test a range of concentrations 2000-2 ppm in factor steps of 10, but changes
were made following the receipt of peer-review feedback to decrease the step size
between treatments from a factor of 10 to a factor of ~3 and focus on the higher end of
the range to be explored. The formulation of GA3 I used was Falgro 2X LV (Fine
Americas, Inc.), which contains 2 g GA3/fl oz solution. Table 5 summarizes the
preparation of the treatments and the dates on which each treatment was applied.
Table 5: Concentrations and dates of GA3 applications in the bioassay experiment.
Dates applied
Concentration Prepared as 2019-01-13 2019-01-26 2016-02-13
2000 ppm 15 mL Falgro 2X LV
diluted to 500 mL solution
yes yes yes
670 ppm 3× dilution of 2000 ppm no yes yes
200 ppm 10× dilution of 2000 ppm yes yes yes
67 ppm 3× dilution of 200 ppm no yes yes
20 ppm 10× dilution of 200 ppm yes no yes
2 ppm 10× dilution of 20 ppm yes no no
0 ppm (control) DI water yes yes yes
Treated cuttings were incubated out on the lab bench at constant ambient
laboratory temperature (74 degrees Fahrenheit) in plastic beakers with 3-5 cm of water at
the bottom. Between 5 and 12 cuttings were placed in each beaker; the number of
cuttings per beaker was reduced later into the experiment, and the number of beakers per
treatment increased, because it seemed as if coincubation compromised the independence
107 107
of each cutting's advancement. Every 3 or 4 days, the water was changed and the bottom
1 cm of each cutting was pruned off to prevent xylem blockage.
11-15 days after treatment, each cutting was rated on the following scale: all bud
scales tight (T), at least one bud swollen (S), terminal vegetative bud green tip (V), at
least one floral bud green tip (G). Terminal vegetative green tip always precedes lateral
floral green tip in pistachio. Some intermediate ratings (e.g. "S/V") were used when
appropriate.
The experiment was repeated every two weeks until cuttings in the control
treatment broke bud. Graphs were drawn using the software package R. Ordinal
regressions were conducted using R, but were judged minimally informative and are not
reported.
Results
The first notable difference between treated cuttings was odor of the incubation
water. The incubation water of cuttings that later broke bud more often smelled fresh or
resinous, whereas the incubation water of cuttings that failed to break bud often smelled
putrid or spoilt, or was slimy.
The raw advancement ratings data are given in Table 6 and are plotted as Figure
10. As expected, the proportion of cuttings that attained more advanced budbreak stages
increased with sampling date.
As Figure 10 shows, although treatment with high concentrations of GA3 did not
guarantee that cuttings would achieve budbreak, cuttings that were treated with less than
a minimum effective dose of GA3 never achieved budbreak. The estimated minimum
effective dose, denoted by the dashed line in Figure 1, decreased with time approximately
3-fold per week. Control cuttings collected on 2019-02-14 broke bud unaided and the
experiment was then stopped.
108 108
Figure 10. The budbreak response to applied GA3 concentrations shows a decreasing
minimum effective dose with time.
The use of log( 1+ [concentration] ) as the ordinate serves to rescale the plot and allow
plotting the control concentration of 0 ppm on the graph. Cuttings rated "S", swollen,
excluded from this graph.
109 109
Table 6: Contingency table of advancement ratings in the bioassay experiment. Cuttings rated S/V, V, or G Date cut
ppm GA applied Jan 13 Jan 26 Feb 13
Row Total
2000 10 19 7
36
670
9 13
22
200 4 14 4
22
67
11 7
18
0
8
8
Column Total 14 53 39
106
Cuttings rated S Date cut
ppm GA applied Jan 13 Jan 26 Feb 13
Row Total
2000 5 5 1
11
670
14 2
16
200 3 7 7
17
67
6 7
13
20 6
15
21
2 1
1
0 1 5 18
24
Column Total 16 37 18
103
Cuttings rated T or T/S Date cut
ppm GA applied Jan 13 Jan 26 Feb 13
Row Total
2000 4
7
11
670
1
1
200 12 3 4
19
67
7 1
8
20 10
10
2 17
17
0 17 19 3
39
Column Total 60 30 15
105
# total cuttings 314
110 110
Discussion
The key idea in this work is the use of an applied PGR to extend the working
range of the budburst bioassay for endo-to-ecodormant transition. It has always been
possible, by definition, to assay the timing of the transition from endodormancy to
ecodormancy by taking cuttings in from the field, incubating them in warm surroundings,
and observing if the buds push by themselves. That assay has a working range limited to
the transition itself or after, and so only gives meaningful results after they become
useless for scheduling a dormant spray. By applying GA3 and determining its MED, the
working range of the defining assay is extended back into the endodormant period and
estimation of the time to endo-to-ecodormant transition (TtT) becomes possible.
A GA3-based bioassay has been used before to measure rest depth in dormant
peach buds (Hatch & Walker, 1969). My report is the first of adapting Hatch & Walker's
methodology to pistachio. The 1969 work was reviewed unfavorably by Dennis (2003),
who wrote that green-tip or bud swell was "a questionable criterion for the breaking of
dormancy". Dennis preferred that the assay material should ideally be followed to full
bloom (floral buds) or leaf-out (vegetative buds). In my experience, to do as Dennis
recommended is not reliably possible for assays using cuttings, because resource
limitation within the cuttings often causes malformation in bloom or leaf-out.
Because my method of estimating both the MED and its change with time is
purely graphical, I need to justify the transformation I applied to the ordinate. The
transformation consists of adding a truncation threshold to the concentration of applied
GA3, then taking the logarithm. Endogenous concentrations of bioactive GA are typically
determined by the dynamic equilibrium between biosynthesis and degradation.
Exogenous application preempts biosynthesis, so degradation kinetics dictate the
transformation that should be used. An assumption of first-order bioactive GA
degradation kinetics justifies the logarithmic transformation. The truncation threshold
111 111
value should correspond to the concentration below which the degradation of GA3 stops
being first-order and the transformation should no longer be biochemically valid.
According to one available mathematical model (Middleton et al., 2012), the intracellular
concentration of GA3 needed to saturate a plant cell is approximately 1-4 ppm, so I set
the truncation threshold at the lower saturation concentration of 1 ppm.
My results confirmed both that single GA3 doses applied to endodormant
pistachio shoots can break their endodormancy, and that the MED to break
endodormancy changes with time. Denoted by the dashed line in Figure 1, the MED
decreased with time approximately 3-fold per week. Cuttings collected and treated on day
13 (January 13) required at least 200 ppm GA3 to achieve budbreak; by day 44 (February
13), collected cuttings required no exogenous GA3 to break bud.
The precision of the estimated MED is constrained by the size of the
multiplicative steps between the applied GA3 concentrations. Theoretically, one might
use a regression to improve the precision of the data analysis in the transitional range
where there are some cuttings that burst and some cuttings that fail, but as described
before, coincubation (forced by logistics) compromises the independence of the cuttings
from the same beaker. Furthermore, cuttings can fail to achieve budbreak even when the
dose of applied GA3 far exceeds the MED. Consequently, I judged the primitive
graphical method most robust.
The precision of estimated rate of MED change was restricted by sample
collection and treatment only once every two weeks, which is not quite frequent enough.
In hindsight, repeating the experiment once per week would have been preferable.
Additionally, it appears that the biological response of the second sampling date was not
fully explored; a more reliable estimate of the change in MED with time might have been
obtained if I had adhered to the original plan of exposing cuttings to the range 2000-2
ppm in steps of 10 instead of 2000-200 ppm in steps of 3.
112 112
The detection limit of this assay would be the TtT corresponding to the smallest
concentration of GA sufficient to induce budbreak when the control does not yet break.
While this value theoretically exists, in practice, a detection limit less than 10 days for an
assay that takes 11 days to conduct is not useful. If the time response to the logarithm of
applied concentration were linear, then 10 days TtT would probably correspond to a
MED between 6 and 20 ppm GA3, but my data do not exclude the possibility of
significant nonlinear response in this range.
The working range would be bounded by the maximum and minimum TtT
detectable by the assay, which the presently available data are insufficient to establish.
My results this year suggest that the tested assay concentrations from 2000 to 200 ppm
would be effective at least in the 15-25 day TtT range, which, assuming that the assay
takes 11 days, would let a grower know of likely endo-to-ecodormant transition between
half a week and two weeks in advance. Of course, the timing of the actual transition will
be a product of environmental forcing endured by the tree over the period following
sample collection. Viewed in that light, this technique's long assay period of 11 days is a
significant weakness. Measures to shorten the assay period should be sought.
Conclusion
My results confirmed both that single GA3 doses applied to endodormant
pistachio shoots can break their endodormancy, and that the MED to break
endodormancy changes with time. Bioassay experiments of this or like design can
provide useful estimates of dormancy depth and time to endodormancy completion with
minimal use of specialist equipment. Efforts to repeat this study in the future should
collect samples weekly and apply a range of GA3 doses from 2000-20 ppm in steps of 3.
After that, the next step would be to test this assay using samples from multiple orchards
113 113
in multiple years, or with other cultivars significant in commercial production (especially
'Golden Hills').
In a professional laboratory context, developing a more rapid screen to shorten the
assay period after treatment would be desirable. Using a tetrazolium test to screen for a
bud respiration increase after GA3 application is one possible method. Using rt-PCR on
mRNA extracts from GA3-treated cuttings should also be considered. The next step in the
latter approach would be to identify diagnostic mRNAs.
114 114
References
Hatch, A.H. and Walker, D.R. 1969. Rest intensity of dormant peach and apricot leaf
buds as influenced by temperature, cold hardiness and respiration. J. Am. Soc.
Hortic. Sci. 94:304-7.
Beede, R.H. 2007. Chilling, Cold Injury, and Dormant Oil Research in Pistachio (Kerman
and Peters cv.). http://cekings.ucanr.edu/files/19104.pdf.
Lang, G.A., J.D. Early, G.C. Martin, and R.L. Darnell. 1987. Endo-, para- and
ecodormancy: physiological terminology and classification for dormancy research.
HortScience 22: 371–77.
Middleton, A.M., S. Úbeda-Tomás, J. Griffiths, T. Holman, P. Hedden, et al. 2012.
Mathematical modeling elucidates the role of transcriptional feedback in gibberellin
signaling. Proc. Natl. Acad. Sci. U. S. A. 109(19): 7571–7576. doi:
10.1073/pnas.1113666109.
Nzima, M.D.S., G.C. Martin, and C. Nishijima. 1997. Seasonal Changes in Total
Nonstructural Carbohydrates within Branches and Roots of Naturally “Off” and
“On” `Kerman’ Pistachio Trees. J. Am. Soc. Hortic. Sci. 122(6): 856–862. doi:
10.21273/JASHS.122.6.856.
Dennis, F.G. Jr. 2003. Problems in standardizing methods for evaluating the chilling
requirements for the breaking of dormancy in buds of woody plants. HortScience
38(3): 347–5.
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