agronomic and physiological effects of grazing on cereal

Agronomic and physiological effects of grazing on cereal 1

crop growth and grain yields: a review 2 3

4 Matthew T. HarrisonA, Andrew D. MooreA and John R. EvansB 5

6 ACSIRO Plant Industry, GPO Box 1600, Canberra ACT 2601, Australia 7 8 BThe Australian National University, Research School of Biology, Canberra ACT 0200, 9

Australia 10

11

Correspondence: M.T. Harrison. Telephone: +61 2 6246 4892; Fax: +61 2 6246 5166; 12

e-mail: [email protected] 13

14

Date submitted: March 2011 15

Target journal: Crop and Pasture Science 16

Number of tables: 1 17

Number of figures: 1 18

Running title: Effects of grazing on the agronomy and physiology of cereal crops 19

Keywords: Defoliation, herbivory, leaf area, radiation, soil water, transpiration 20

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Effects of grazing on the agronomy and physiology of cereal crops

2

List of abbreviations 34

35

Symbol Description Units

DM Dry matter g total dry matter m-2 groundDP Dual-purpose -G×E Genotype-by-environment

interaction -

GY Grain yield g grain m-2 groundHI Harvest index g grain DM g-1 SDMIPAR Intercepted PAR MJ PAR m-2 ground d-1

ΣIPAR Cumulative IPAR interception MJ IPAR m-2 ground LAI Leaf area index m2 leaf m-2 groundRUE Radiation-use efficiency g SDM MJ-1 IPARSDM Shoot dry matter g shoot dry matter m-2 groundSLA Specific leaf area m2 leaf g-1 leaf DMTE Transpiration efficiency g DM m-2 ground mm-1 transpiredWSC Water-soluble carbohydrate

concentration or content mg carbohydrate g-1 stem DM or g

carbohydrate m-2 groundWUE Water-use efficiency g DM m-2 ground mm-1 evapotranspirationYP Yield potential g grain m-2 ground


2

Abstract 1

2

The use of cereal crops for the dual purposes (DP) of animal forage and grain production has 3

been practised for over a century. DP cereal crops provide high quality forage during winter 4

when availability of other pastures is often lacking, and high-value grain at maturity. Most DP 5

crop experiments include quantification of biomass production and grain yield (GY) in 6

response to grazing. This review summarises these agronomic data and the reasons cited for 7

the differences in GYs. It then demonstrates how availability of physiological data would lead 8

to greater understanding of crop responses to grazing. 9

10

For a standardised comparison of the effects of defoliation on GY across studies, results from 11

the least intensive defoliation treatments from 33 separate experiments with DP wheat were 12

compiled and compared. Across studies the overall effect of defoliation on GY was –7 ± 25% 13

(mean ± SD, n = 276), with responses ranging from –36% to +75%. In many cases grazing 14

delayed crop phenological development. Delays increased as grazing severity increased or 15

when defoliation was conducted at later phenological stages, particularly after first node 16

appearance, but mechanistic explanations for delayed development were limited. Compared 17

with ungrazed crops, grazed crops were more prostrate, had more decumbent leaves and more 18

tillers, and were shorter at maturity. Physiological measurements of pasture grasses and grain-19

only cereal crops have shown that in general defoliation inhibits root growth, reduces N 20

uptake and carbohydrate production, promotes N remobilisation from roots to leaves, and 21

perturbs normal allocation of dry matter (DM) between roots and shoots. These changes have 22

important implications for canopy light interception, post-grazing growth rates and DM 23

accumulation, and thus assimilate available for retranslocation to grain. Physiological 24

measurements of grazed DP crops are rare but are an essential prerequisite in the development 25

of new dynamic crop-grazing models. Such models could be used to distinguish between the 26


3

effects of different grazing regimes on crop traits such as tillering and root growth, and their 1

respective implications for light interception, temporal soil water use and GY. Analysis of the 2

influence of abiotic variables on biotic variables over multiple seasons would help identify 3

genotype by environment by management interactions. Physiological data from field 4

experiments and application of crop-grazing simulation models should be conducive to (1) 5

better grazing management guidelines, (2) more appropriate trait targeting for breeding of 6

new DP cultivars and (3) better classification of the suitability of a DP cultivar to a given 7

environment. 8


4

Introduction 1

2

The use of cereal crops for the dual purposes (DP) of animal forage and grain production has 3

been practised for over a century (Shelton 1888; Georgeson et al. 1892), occurring in 4

countries such as Argentina (Arzadun et al. 2003), Australia (Kelman and Dove 2009), 5

Canada (Poysa 1985), Italy (Francia et al. 2006), Lebanon (Yau 2003), New Zealand (Scott 6

and Hines 1991), Spain (Royo 1997), Syria (Anderson 1985) and the United States (Winter 7

and Thompson 1987; Redmon et al. 1995). DP cereals include rye (e.g. Holliday 1956), oats 8

(e.g. Bortolini et al. 2005), triticale (e.g. Royo et al. 1994) and barley (e.g. Yau 2003), but the 9

most commonly DP cereal reported in the literature is winter wheat (e.g. Worrell et al. 1992; 10

Redmon et al. 1995; MacKown and Carver 2007). 11

12

DP cereal crops are typically sown in late autumn so that relatively warmer temperatures 13

promote growth and accumulation of large quantities of vegetative biomass by winter 14

(Davidson et al. 1990). Grazing may be commenced as soon as crop roots have sufficient 15

anchorage to prevent plant upheaval during defoliation, though grazing intensities and 16

durations differ from region to region. In the temperate, Mediterranean and semi-arid grazing 17

zones of Australia, Italy, West Asia and Africa, general practice is to graze crops for a single 18

continuous period of several days to weeks at relatively medium to high stocking rates 19

(Anderson 1985; Francia et al. 2006; Kelman and Dove 2009). In contrast standard practice in 20

the Central and Southern Great Plains of the United States is to graze crops for longer 21

durations at lower intensities (e.g. Khalil et al. 2002a; Holman et al. 2009). In most cases 22

grazing is terminated when vegetative development turns reproductive, a developmental stage 23

observed when the apical meristem becomes elevated above the soil surface (growth stage 30, 24

Zadoks et al. 1974). Management of grazing in this manner prevents decapitation of 25

developing spikes and potential loss of GY (Scott and Hines 1991). 26


5

DP cereal crops are a valuable resource and an attractive alternative to farmers for numerous 1

reasons. First, crop forage provides an alternative source of feed during winter when growth 2

of pastures is generally less than livestock requirements (Doole et al. 2009; Moore et al. 3

2009). Second, DP crop forage has high digestibility and crude protein content and is thus 4

conducive to high livestock weight gains (Dove et al. 2002; Dove and McMullen 2009). Third, 5

winter grazing of cereal crops in very productive environments may reduce stubble load and 6

facilitate ease of sowing in the following season (Baumhardt et al. 2009; Nuske et al. 2009). 7

8

As described by Virgona et al. (2006), commercial and scientific interest in DP wheat has 9

fluctuated with the relative profitability of grain and livestock systems and with the release of 10

new crop varieties. Grazing of wheat crops was common during the 1930-70 period (e.g. 11

Swanson 1935; Stansel et al. 1937; Hubbard and Harper 1949) but popularity of DP crops 12

waned with the development of short-season and semi-dwarf cultivars (Pugsley 1983). These 13

varieties were developed as they enabled earlier sowing and tended to lodge less than older, 14

tall varieties (Redmon et al. 1995). However these semi-dwarf cultivars also had (1) shorter 15

coleoptiles and slower growth rates, (2) decreased seedling emergence (Allan 1980), (3) 16

greater developmental rates and therefore (4) earlier stem elongation than older varieties, 17

restricting the time allowed for grazing. Release of new semi-winter DP wheat varieties at the 18

end of the 20th century renewed farmer interest since these crops had high vernalisation 19

requirements (Dove et al. 2002) and potential to meet the high protein grain-milling category 20

(Khalil et al. 2002b; Holman et al. 2009). In 2003 a national program in Australia called 21

‘Grain & Graze’ was introduced to boost the viability and encourage the adoption of mixed-22

farming systems in southern Australia (Price and Hacker 2009; Price et al. 2009).The Grain & 23

Graze program aimed to increase farm profitability by 10% by filling feed gaps arising from 24

seasonal imbalances of forage demand and supply, maintain and improve catchment health, 25

and enhance the pride and social capital of participating farmers (Grain-and-Graze 2003; 26


6

Hacker et al. 2009). By 2008, nearly 3200 farms across nine regions in southern Australia had 1

adopted at least one strategy advocated by Grain & Graze since its outset in 2003 (Price et al. 2

2009). 3

4

Previous studies of DP cereals have focussed on variation in dry matter (DM) or GY with 5

grazing intensity or frequency (Hubbard and Harper 1949; Benjamin et al. 1978; Arzadun et 6

al. 2003), cultivar (Sprague 1954; Lovett and Matheson 1974; Davidson et al. 1990), 7

availability of soil nitrogen (Dann et al. 1983; MacKown and Carver 2007), sowing date 8

(Dann et al. 1977; Yau 2003), yield components (Sharrow and Motazedian 1987) or the 9

economics of meat, wool or grain production (Doole et al. 2009; Zhang 2010). Many studies 10

also document animal performance or in vitro digestibility of grazed cereals (e.g. Dann et al. 11

1983; Kelman and Dove 2007). There is less information on changes that grazing causes to 12

crop phenology and even fewer data on the effects of abiotic factors on physiological 13

mechanisms of crop recovery. These changes are important, since they may hold the key to 14

differences in DM accumulation and GY after grazing. For example, crop regrowth and GY of 15

grazed crops depends on the rate of leaf area development (Winter and Thompson 1987), 16

which in turn is contingent upon availability of soil water (Milroy and Goyne 1995) and soil 17

nitrogen (Gastal and Lemaire 2002). 18

19

This review summarises the agronomic and known physiological effects of grazing on crop 20

growth, phenology and GY. Depending on availability of information, examples in this review 21

relate first to DP wheat crops, second to other DP cereal crops, third to pasture grasses 22

subjected to grazing (effectively grazed cereals before stem elongation) and finally to 23

defoliation experiments performed under controlled conditions. Specifically, the aims of this 24

review are to 25


7

(1) Summarise the reported variation in the effects of grazing on GY and the abiotic reasons 1

ascribed for such variation; 2

(2) Show how a greater understanding of the physiological factors underlying the recovery of 3

DP cereals after grazing would facilitate design of future grazing regimes, breeding of DP 4

cereals and provide a better basis for comparison against ungrazed crops, and 5

(3) Underscore the need for and utility of crop simulation models in DP crop experiments. 6

7

Effects of grazing on grain yield 8

9

Overall effects 10

11

In general GYs decrease with increasing grazing intensities, longer grazing durations 12

(Holliday 1956; Miller et al. 1993) or later end dates of grazing (Stansel et al. 1937; Royo 13

1999). The GY penalty tends to be less if defoliation is completed before stem elongation or 14

appearance of first hollow stem (Swanson 1935; Redmon et al. 1996; Taylor et al. 2010). 15

Phenologically, these crop developmental stages coincide with Zadoks stage 30 (Zadoks et al. 16

1974) or Feekes stage 5.0 (Large 1954). With these factors in mind, the effects of defoliation 17

on GY in 34 experiments from a range of locations were reviewed and are shown in Table 1. 18

Studies were selected from published journal papers and agronomy-extension results, and 19

were only included in the survey if experiments (1) were conducted in the field in replicated 20

designs, (2) included an ungrazed control, (3) included valid statistical analyses for treatment 21

differences and (4) provided detailed site conditions including weather data. For consistency 22

across studies, values reported here are from the least intensive or earliest completed 23

treatments of DP wheat crops (n = 276). 24

25


8

Insert Table 1 near here 1

2

Overall, defoliation reduced GY by an average of 7%, with a standard deviation of 25%. 3

Results varied widely both within and across studies, ranging from -36 ± 11% after sheep 4

grazing in Victoria (Hacking 2006) to +75% following clipping near Perth (Dean et al. 2006). 5

6

Differences between the effects of defoliation in Table 1 arise because GY represents the 7

integration of crop processes over the entire growing season, from light interception, 8

radiation-use efficiency (RUE) and DM partitioning to grain filling. Possible approaches to 9

understanding effects of grazing on GY would be to examine each of these components 10

individually, or to use a dynamic model designed to simulate crop grazing. The first of these 11

methods is discussed below, and the second is examined later in this review. 12

13

Mode and rate of defoliation 14

15

Although there were no consistent differences between GYs of treatments subjected to 16

different defoliation methods in Table 1, 12 of the 15 reports of increased yield involved 17

livestock grazing as opposed to clipping. It may be that selective grazing by livestock avoided 18

removal of apical meristems (Virgona et al. 2006), in contrast to clipping treatments, which 19

were generally applied to a uniform crop height and may have removed apical meristems. On 20

the other hand many experiments designed to specifically compare differences between 21

grazing or clipping have shown otherwise. Francia et al. (2006: 163) comment that simulation 22

of grazing by cutting plots was highly comparable for crop growth and production with that 23

of the grazing of sheep. The experiments conducted by Francia et al. (2006) were carried out 24

under ‘crash’ conditions (342 sheep grazed plots over 1 hr), but other grazing studies 25


9

performed for longer periods have also found similar results (e.g. Dann 1968; Pumphrey 1970; 1

Dann et al. 1977; Dann et al. 1983). 2

Primary abiotic and biotic factors influencing the recovery of grazed crops 3

4

Causes ascribed by authors for the effects of grazing on GY in Table 1 are shown in Fig. 1. 5

Soil water content was the most common factor attributed to yield variation, having both 6

positive (e.g. Arzadun et al. 2003) and negative effects (e.g. Dann et al. 1983). Air 7

temperature was cited in 20% of studies and also had beneficial and detrimental effects on GY 8

(Cutler et al. 1949). For example, yield penalties were observed when temperatures were 9

either sub-optimal during winter months, limiting crop growth rates (e.g. Lyon et al. 2001), or 10

supra-optimal at the end of the growing season, inducing premature ripening, damage during 11

pollination or a truncation of the kernel filling duration (Royo and Tribo 1997; Kelman and 12

Dove 2009). Around 7% of studies in Table 1 ascribed yield penalties to crops experiencing 13

frost damage during regrowth or at anthesis (e.g. Davidson et al. 1990). In summary, almost 14

60% of studies in Table 1 attributed yield differences after grazing to soil water availability or 15

air temperature. 16

17

Insert Fig. 1 near here 18

19

In many cases in Table 1, GY of grazed crops increased compared with controls due to 20

reduced lodging (Fig. 1). Lodging was primarily reported in American studies (e.g. Swanson 21

1935; Christiansen et al. 1989) and generally occurred as a result of prolific biomass 22

accumulation in early development. Compared with ungrazed crops, grazed crops generally 23

have less shoot dry matter (SDM) and reduced height at maturity (Winter et al. 1990). These 24

characteristics reduce plant mass and the magnitude of over-turning moments generated by 25

wind (Berry et al. 2003; Sylvester-Bradley and Riffkin 2008), decreasing the likelihood of 26


10

lodging and enabling more spikes to be gathered by machine harvesters at maturity (Winter et 1

al. 1990). 2

3

Mitigation of disease was another reason attributed to increased GY after grazing in the 4

studies reported in Table 1. Dann et al. (1977) observed that grazing reduced the incidence of 5

septoria leaf spot (Septoria tritici), leaf and stem rust (Puccinia triticina, P. graminis 6

respectively), but did not explain why. Miller et al. (1993) commented that damage to 7

unclipped triticale by bacterial streak (Xanthomonas campestris), septoria glume blotch 8

(Stagonospora nodorum) and barley yellow dwarf virus (BYDV, Luteovirus spp.) was rife in 9

seasons with high rainfall. They noted that defoliation reduced leaf damage due to (1) 10

repeated removal of disease inoculum and (2) delayed spike development. It is worth noting 11

here that the chances of disease transmission (e.g. wheat-streak mosaic virus and BYDV) 12

from volunteer cereals and weeds (Hawkes and Jones 2005; Coutts et al. 2008) may be 13

enhanced in DP cereals (compared with grain-only cereals) due to their requirement for 14

earlier sowing. 15

16

Other factors implicated with differences in GY of grazed crops in Table 1 included livestock 17

trampling (Christiansen et al. 1989), smothering of weeds (Davidson et al. 1990), hailstone 18

damage (Lyon et al. 2001), and sub-optimal photoperiod (Royo et al. 1994). Many of these 19

factors were associated with delays in phenological development (see following section). 20

Effects of leaf area and light interception on regrowth and GY are discussed later in this article. 21

22

Effects of defoliation on grain yield components 23

24

Over the 276 treatments in Table 1 there were no consistent effects of defoliation on yield 25

components. Of the studies reporting positive effects on GY, 78% were due to increased 26


11

kernels per unit ground area and the remainder were caused by increased kernel weight. Only 1

the study by Sprague (1954) reported increased GY due to increases in both yield components. 2

Reports of decreased GY after grazing in Table 1 were almost equally attributed to changes in 3

kernel weight (52%) and kernels per unit ground area (48%). 4

5

Effects of defoliation on the number of fertile tillers or spikes per unit ground area at maturity 6

were variable. Del Moral (1992) observed that yields were mainly decreased after cutting due 7

to reduced number of spikes, while El-Shatnawi et al. (2004) found that grazing increased the 8

number of fertile tillers per unit ground area. Many studies also noted that defoliation did not 9

significantly affect the number of fertile spikes per unit ground area or that this yield 10

component was the least affected by defoliation (e.g. Dunphy et al. 1982; Royo 1997; 11

Virgona et al. 2006). 12

13

Yield components are determined temporally, with tiller number first, followed by spikelets 14

per spike, kernels per spikelet and finally kernel weight (Evans et al. 1975). Since the 15

developmental stage of crops during defoliation and the weather conditions following 16

defoliation in the studies above were diverse, it is not surprising that defoliation acted on 17

different yield components, even when the overall effects of defoliation on GY were similar. 18

19

Phenological delays associated with grazing 20

21

Flowering time has been suggested as the single most important factor influencing GY in rain-22

fed environments (Richards 1991), so understanding the effects of grazing on crop 23

development and the timing of flowering will be crucial if yield penalties are to be mitigated. 24

In most cases in Table 1, delayed development after grazing or clipping was associated with 25

decreased GY or reduced grain quality. These effects were particularly evident in experiments 26


12

that were rain-fed or experienced dry finishes to the growing season (Hacking 2006; Virgona 1

et al. 2006). 2

In general later maturity delays harvest and prolongs grain exposure to the environment, 3

increasing chances of weather damage to grain. Amjad et al. (2006) found that grain quality 4

traits such as screenings, fungal staining and falling numbers were a major problem in long-5

season winter wheats when their development was delayed. 6

7

Although the effects of delayed development on GY were primarily negative in studies 8

reported in Table 1, there were some cases when the delay was beneficial. A case in point is 9

that anthesis of grazed crops were less likely to experience late frosts (Dann et al. 1977). 10

Dean et al. (2006) reported large yield losses of unclipped Mackellar wheat due to a frost 11

event that occurred during late spike emergence; in contrast the development of clipped 12

Mackellar was sufficiently delayed so that the effect of frost on GY was relatively small. The 13

outcome of the study by Dean et al. (2006) was that clipped crops yielded around 75% more 14

than those of controls (114 cf. 65 g m-2 respectively). Frost during grain filling may damage 15

developing florets, causing yield penalty and loss of grain quality (Boer et al. 1993; Cromey 16

et al. 1998). Grazed crops were also more capable of using late rainfall (Holliday 1956), and 17

later ripening lowered the susceptibility of pre-harvest grain sprouting (Holman et al. 2009). 18

19

Causes of delayed development 20

21

The question of how defoliation delays crop development in a mechanistic sense remains to 22

be conclusively answered. Some authors postulate that decreased photosynthetic activity 23

reduces the supply of assimilate to the developing apex (Davidson et al. 1990; Virgona et al. 24

2006). Evans (1960) suggested that laminae area remaining after defoliation may be 25

insufficient to generate the long-day stimulus required to accelerate development. Royo et al. 26


13

(1994) attributed delays in anthesis to lower radiation interception and sub-optimal 1

photoperiod. Insufficient day length has also been associated with delayed development in 2

ungrazed crops (Slafer and Rawson 1994) and pasture grasses (Evans 1960). Virgona et al. 3

(2006) commented that the delay may be caused by cooler temperatures surrounding the 4

developing apex, though other studies have revealed that grazing tends to elevate soil 5

temperature maxima (Fahnestock and Knapp 1994) which increases development rates (Rice 6

and Parenti 1978), particularly when apical meristems are close to the soil surface (Stone et al. 7

1999). Various authors have suggested that an increased ratio of red to far-red (R-FR) light at 8

the base of the canopy after defoliation may inhibit the onset of stem elongation (Hofstede et 9

al. 1995; Gautier et al. 1999), but others have observed that exposure of young tissues to 10

increased R-FR light ratios after defoliation tends to advance inflorescence development 11

(Wan and Sosebee 1998). 12

13

Such information indicates that the defoliation-induced phenological delay may be governed 14

by a suite of abiotic variables and that effects of defoliation on crop development cannot 15

simply be generalised across studies. To adequately predict the delay in development caused 16

by grazing and possible consequences for flowering time, further research needs to be carried 17

out on each of the mechanisms discussed above, preferably first as single variates under 18

controlled conditions, then as multivariate systems in the field. 19

20

Effects of grazing on crop water-use efficiency and transpiration efficiency 21

22

Knowledge of grazing regimes that allow crops to better utilise soil water would be 23

advantageous since most DP crops are grown under rain-fed conditions (e.g. Bonachela et al. 24

1995a; Doole et al. 2009). Two indices commonly used to assess crop productivity per unit 25

water used are water-use efficiency (WUE) and transpiration efficiency (TE) (Richards 1991), 26


14

calculated as crop DM produced per unit evapotranspiration or transpiration, respectively 1

(Fischer 1979). The upper limit of WUE for grain of well-managed disease-free water-limited 2

cereal crops is 2.0-2.2 g grain/m2.ground mm (French and Schultz 1984; Sadras and Angus 3

2006). However WUE for grain is often much lower due to stresses caused by weeds, diseases, 4

poor nutrition or inhospitable soils (Passioura 2006), with typical values for rain-fed wheat 5

ranging from 0.53 g/m2.mm in the US Great Plains to 1.0 g/m2.mm in southern Australia 6

(Sadras and Angus 2006). Given the body of literature on WUE and TE in rain-fed crops 7

grown only for grain, computation of these indices for grazed crops would allow useful 8

comparisons between the effectiveness of grain-only and DP systems in terms of biomass 9

production per unit water used. 10

11

Despite their utility, however, published values of WUE and TE of grazed crops are rare, and 12

conclusions from available reports have been unclear. Bonachela et al. (1995b) contrasted the 13

effects of forage removal on the water-use of barley and triticale crops and found no 14

significant differences in evapotranspiration or soil water depletion at maturity between 15

genotypes, sowing date or growing season. In the first of three experiments they showed that 16

clipping increased WUE for DM and for grain by 10 and 26% respectively, yet in the 17

remaining two seasons clipping reduced WUE for DM and for grain by an average of 19 and 18

26% respectively. They attributed differences in WUE to weather conditions and crop water-19

use between seasons. In the first growing season they suggested that a prolonged drought 20

period between the end of clipping and anthesis heightened water stress of unclipped crops. 21

Forage removal conserved soil water and decreased crop water stress. Prolific biomass 22

accumulation at the beginning of a growing season followed by a lack of rainfall leading to 23

premature leaf area senescence generally results in lower GYs for a given vegetative biomass 24

(van Herwaarden 1996). 25

26


15

A generally accepted notion for the conservation of soil water caused by crop grazing is that 1

leaf area removal reduces transpiration and decreases the rate of soil water use (Bonachela et 2

al. 1995b; Virgona et al. 2006; Kelman and Dove 2009). However, other than the study of 3

Bonachela et al. (1995b) there are few reports that provide numerical evidence of concurrent 4

changes to leaf area, SDM and soil water content during and after defoliation. Since the 5

effects of crop defoliation on soil water content in past experiments are inconsistent, ranging 6

from a conservation of soil water (Zhu et al. 2004; Virgona et al. 2006) to using more soil 7

water than undefoliated plots (Kelman and Dove 2009), the notion that grazing conserves soil 8

water should receive further attention. 9

10

In temperate rain-fed environments the rate at which soil water is depleted over the growing 11

season is fundamental to the effects of grazing on WUE and TE. Management of grazing to 12

manipulate the timing of soil water depletion poses an intriguing dilemma, however. On the 13

one hand, WUE is increased the earlier full canopy closure is established (Passioura 2006). 14

Rapid canopy closure reduces water lost to soil evaporation and allows more growth during 15

winter when temperatures are cool and vapour pressure deficits are low (Richards et al. 2002; 16

Dunin and Passioura 2006). On the other hand, conserving soil water before anthesis so that 17

more water is available during grain filling can increase DM partitioned to kernels and 18

ultimately GY (Richards et al. 2002). Studies of temporal soil water extraction by wheat crops 19

have demonstrated that conversion efficiencies of water into grain are high after anthesis, with 20

TE values as high as 5.9 g grain/m2.mm being recorded (Condon et al. 1993; Kirkegaard et al. 21

2007). High TE values after anthesis occur because most post-anthesis assimilate is 22

partitioned directly to grain (Fischer 1979) and pre-anthesis stem assimilates are remobilised 23

to grain (Ehdaie et al. 2006), even though high late season vapour pressure deficits can reduce 24

photosynthesis through stomatal closure, leaf rolling and senescence (Kemanian et al. 2005). 25

26


16

Grazing reduces canopy cover and increases evaporation of water from the soil surface 1

(Murphy et al. 2004). However, since grazing generally delays crop growth (phenological 2

development section) and reduces transpiration, it is possible that grazing may lead to more 3

water available for use at, and after, anthesis. This could enhance GY, but there appears to be 4

only one study that has numerically confirmed this phenomenon (see Bonachela et al. 1995b). 5

Removal of shoot biomass also reduces assimilate supplied to roots (see water-soluble 6

carbohydrate section below), resulting in reduced root biomass and root length density (Trent 7

et al. 1988), and potentially reduced soil water uptake (Garwood and Sinclair 1979). 8

Assimilate translocated to roots increases as plant available water decreases, but decreases 9

with increasing defoliation severity, so defoliation and soil water stress have opposing effects 10

on root growth (Sosebee and Wiebe 1971). In summary, rates of soil water use by grazed 11

crops will depend on (1) rainfall distribution and soil water availability, (2) the severity of 12

defoliation and its affect on assimilate partitioned to roots, and (3) the rate of canopy closure 13

after grazing. It is therefore difficult to predict whether grazing will decrease or increase WUE. 14

Further work is necessary to help identify the trade-offs between soil water conservation and 15

reduced interception of sunlight on growth for different distributions of growing-season 16

rainfall. 17

18

Effects of grazing on canopy light interception, radiation-use efficiency and 19

DM partitioning 20

21

The yield potential (YP) formula (Eqn. 1) can be used to better understand the effects of 22

grazing on crop physiology and its consequences for GY. YP is often defined as the attainable 23

GY of a cultivar grown in environments to which it is adapted, with nutrients and water non-24

limiting, and with pests, diseases, weeds, lodging and other stresses effectively controlled 25

(Evans and Fischer 1999). YP is often expressed as the product of cumulative intercepted 26


17

photosynthetically active radiation, (ΣIPAR, MJ IPAR.m2 ground), radiation-use efficiency 1

(RUE, g DM/MJ IPAR), and harvest index (HI, the ratio of grain DM to SDM at crop 2

maturity), such that 3

4

YP = ΣIPAR × RUE × HI (1) 5

6

Increasing any term on the right-hand side of the identity in Eqn. 1 should increase YP, 7

assuming the other terms remain constant. Eqn. 1 provides a framework of readily measured 8

parameters that can be used to describe how the relative contributions from light interception, 9

RUE and DM partitioning affect YP or GY. The following sub-sections review how changes in 10

crop physiology and morphology affect each component on the right-hand side of Eqn. 1, the 11

effects of grazing on these attributes, and thus the pathways that grazing is likely to influence 12

GY. 13

14

Leaf area indices, canopy light interception and crop growth rates 15

16

Leaf area index (LAI) and the light extinction coefficient of the canopy, k, govern intercepted 17

photosynthetically active radiation (IPAR) (Simpson and Culvenor 1987). LAI and IPAR 18

represent two of the most important physiological parameters underlying crop responses to 19

grazing since they determine crop growth rate (Atwell et al. 1999) and the rate of recovery 20

after defoliation. Around 14% of studies in Table 1 attributed differences in GY of grazed 21

crops to sub-optimal LAI (and by inference IPAR) in the grazed crops (e.g. Swanson 1935; 22

Royo and Pares 1996), as shown in Fig. 1. Winter and Thompson (1987) found that later 23

grazing of wheat limited regrowth of leaf area, biomass accumulation in spring and 24

consequently GY. Ramos et al. (1996) similarly concluded that spring triticale needed to be 25


18

capable of regenerating leaf area rapidly after cutting to prevent GY penalty. Dunphy et al. 1

(1984) also suggested that reduced leaf area of wheat crops at anthesis was strongly correlated 2

with reduced GY. Finally, Winter and Musick (1991) observed that green leaf area removal 3

beyond certain limits could cause abortion of primary culms, reduced growth rate, delayed 4

morphological development and reduced kernel filling duration. In summary these studies 5

have indicated that later and/or more severe defoliation limits leaf area recovery and crop 6

development, and in many cases growth rates following defoliation and GYs. 7

8

The crucial knowledge gap for nearly all DP crop studies is quantification of IPAR. 9

Measurement of IPAR would allow better linkage between changes in LAI and resultant 10

growth rates. Such analyses are already well documented for pasture grasses and have 11

provided good guidelines to grazing management. Simpson and Culvenor (1987) defined the 12

LAI at which maximum growth rate was obtained as the ‘critical LAI’. For best management 13

practice of pasture grasses, Matches (1992) stipulated that (1) LAIs should not be allowed to 14

develop beyond the critical value, (2) LAIs should not be reduced excessively by defoliation, 15

and (3) grazing intensities should be regulated so as to maintain leaf area for maximum 16

growth rates throughout the season (though they conceded that in practice such management 17

may be difficult to achieve). 18

19

Effects of grazing on crop traits that influence cumulative radiation interception (ΣIPAR) 20

21

Specific leaf area 22

23

Many grassland experiments have shown that grazed swards have greater specific leaf area 24

(SLA, leaf area per unit leaf dry mass) compared with ungrazed swards (Rotundo and Aguiar 25

2008; Zhao et al. 2009). Since the product of SLA and green leaf biomass determines LAI and 26


19

ultimately IPAR, it is possible that increased SLA over an extended duration after defoliation 1

may increase ΣIPAR. Richards (2000) indicated that SLA was a primary determinant of early 2

vigour in young wheat plants, as crops with high SLA generally have higher IPAR prior to 3

canopy closure. However, grazing reduces LAI, so the trade-off between decreased IPAR due 4

to leaf area removal and increased IPAR due to greater SLA would largely depend on the rate 5

of canopy closure after grazing and the duration over which SLA was perturbed. 6

7

Canopy architecture 8

9

IPAR is also influenced by light distribution within canopies (Hammer and Wright 1994; 10

Whaley et al. 2000) which depends on leaf angle distribution (Duncan 1971; Campbell 1986), 11

canopy height (Miralles and Slafer 1997; Muurinen and Peltonen-Sainio 2006) and tiller 12

number (Duggan et al. 2005). Grazing can alter any or all of these morphological traits. First, 13

leaf angles may become more decumbent after grazing (Hofstede et al. 1995; de Mello and 14

Pedreira 2004) depending on grazing frequency (Smith 1998). Second, defoliation often 15

reduces canopy height at maturity (Dann 1968; Winter and Thompson 1987) by decreasing 16

the length of the main stem (Royo 1999), resulting in more prostrate canopies (MacKown and 17

Carver 2005). Third, the number of tillers per unit ground area may increase or decrease after 18

grazing (Royo 1999; Kelman and Harrison 2010). 19

20

Green area duration 21

22

Extending the duration with which SDM remains green (the ‘green area duration’) may also 23

increase ΣIPAR. Jenner and Rathjen (1975) and later Borrell et al. (2000) showed that DM 24

accumulation of wheat and sorghum, respectively, were improved by maintaining IPAR 25

during later stages of kernel filling, leading to greater ΣIPAR. Since grazing typically delays 26


20

crop development, grazing may also affect the duration of growth and green area duration in 1

late development (Royo 1997). Under these circumstances it can be postulated that grazing 2

would increase ΣIPAR provided sufficient resources were available. Whether such increases 3

were due to delayed leaf senescence or growth of more leaves and tillers in later development 4

is yet unknown. 5

6

Radiation-use efficiency 7

8

Positive linear correlations are often found between DM and ΣIPAR for crops grown under 9

favourable conditions (Sinclair and Muchow 1999). The slope of this relationship is the RUE 10

(Monteith 1977), generally expressed as g total biomass/MJ IPAR. Since RUE is linked with 11

photosynthetic activity, factors affecting photosynthesis should also alter RUE (Monteith 12

1977; Sinclair and Muchow 1999; Fischer 2007). However, studies of both photosynthesis 13

and RUE in DP cereals are limited and the effects of defoliation on the photosynthesis of 14

grass species vary (e.g. see Nowak and Caldwell 1984; Fahnestock and Detling 2000). 15

Harrison et al. (2010) indicate that there are generally three pathways by which 16

photosynthesis may increase after defoliation. These include (1) improved leaf water status, (2) 17

increased leaf nitrogen content and/or (3) increased activity of photosynthetic enzymes. In one 18

of the few studies examining the effects of grazing on the photosynthesis of DP cereals, 19

Harrison et al. (2010) showed that grazed winter wheat transiently increased photosynthesis 20

by 33-68% over a 2-4 week period after grazing ended. Harrison et al. (2010) attributed 21

changes in photosynthesis to increased Rubisco activity which in turn was associated with a 22

partial alleviation of leaf water stress. 23

24

Other stresses or adverse conditions influencing photosynthesis are also likely to affect RUE. 25

These include water-, temperature- or nitrogen-stresses (Sinclair and Horie 1989; Whaley et 26


21

al. 2000), frost, pests, diseases or senescence (Gallagher and Biscoe 1978; Siddique et al. 1

1989; Gregory et al. 1992), prolonged periods of high vapour pressure deficit (Stockle and 2

Kiniry 1990) and low proportions of diffuse to total solar radiation (Sinclair et al. 1992). 3

4

From the above it is apparent that grazing may have positive (e.g. increased SLA) or negative 5

(e.g. decreased LAI) impacts on ΣIPAR and RUE, which makes the overall effect of 6

defoliation on crop productivity difficult to predict. The physiological parameters discussed 7

above underpin crop growth rate and biomass accumulation, and their quantification in a crop 8

grazing scenario would reveal their relative importance for crop recovery and GY. The other 9

main pathway that grazing may influence GY is through HI (Eqn. 1), which is examined next. 10

11

Effects of defoliation and grazing on dry matter partitioning during reproductive 12

development 13

14

HI may be increased by allocating a greater proportion of SDM to spikes, particularly in the 15

weeks around anthesis (Richards 2000). SDM partitioned to kernels is derived from (1) 16

carbohydrate produced after anthesis and translocated directly to kernels, (2) carbohydrate 17

produced after anthesis, stored temporarily in the stem then retranslocated to kernels, or (3) 18

carbohydrate produced before anthesis, stored mainly in the stem then retranslocated during 19

kernel filling (Ehdaie et al. 2006). Mode 3 depends on the assimilate storage capacity of the 20

crop, thought to be largely a function of stem DM (Austin et al. 1980). Assimilate used during 21

kernel filling in modes 1 and 2 is mainly derived from current photosynthesis and therefore 22

depends on green area duration and activity after anthesis (Welbank et al. 1966; Garcia del 23

Moral 1992). 24

25


22

The extent to which defoliation alters the DM accumulation of individual crop organs, and by 1

implication the size of the assimilate pool available for retranslocation (mode 3), depends on 2

the severity and time of defoliation, as well as the crop species. Noy-Meir and Briske (2002) 3

showed that a single severe clipping of vegetative wild wheat (Triticum dicoccoides) reduced 4

spike and spikelet numbers and total reproductive biomass compared with unclipped wild 5

wheat. A second severe clipping reduced not only survival to reproduction, but also 6

reproductive biomass, GY and grain quality of plants that did become reproductive. 7

Defoliation of barley or triticale crops similarly caused reductions in the DM of leaves, stems 8

and spikes at anthesis relative to unclipped controls (Royo 1999). In this study the 9

contribution of pre-anthesis assimilate to kernels of clipped barley was lower than that of 10

unclipped barley, but the opposite was true for triticale (Royo 1999). 11

12

Defoliation of DP crops has resulted in (1) increased (+58%, Kelman and Dove 2009), (2) no 13

change (Royo et al. 1997) or (3) decreased (-28%, Bonachela et al. 1995a) HI relative to 14

controls. More work is needed to clarify how grazing affects HI. For example HI of grazed 15

crops may be greater than controls due to greater GY, lower SDM or both. Moreover nearly all 16

DP crop studies cite HI values that have been estimated as the ratio of kernel DM to SDM at 17

maturity, as is the convention for grain-only systems. A more informative approach would be 18

to also cite ‘apparent HI’, i.e., to include an estimation of the SDM removed by defoliation 19

since this would demonstrate how above-ground productivity was affected by grazing. 20

Greater understanding of how SDM allocated to developing spikes changes with crop species 21

and with the timing and severity of defoliation should lead to grazing management strategies 22

that mitigate the effects of grazing on GY. 23

24

25

26


23

The need to study water-soluble carbohydrates in grazed cereal crops 1

2

Water-soluble carbohydrates in grazed pastures and grain-only crops 3

4

Concentrations of water-soluble carbohydrates (WSCs) in plant tissues have been extensively 5

studied in pasture grasses (Matches 1992; Fulkerson and Donaghy 2001) and grain-only crops 6

(Shearman et al. 2005) for a number of reasons. First, WSCs relate to a plant’s ability to 7

recover from defoliation. If the duration of grazing is excessive or defoliation is too severe, 8

WSC concentrations may fall to a level that suppresses regrowth and hinders long term 9

persistence (Fulkerson and Donaghy 2001). In ryegrass (Lolium spp.), WSC reserves decline 10

after defoliation as WSCs are used to regrow new shoots, whilst root growth slows and may 11

cease completely (Morvan-Bertrand et al. 1999). It is not until about 75% of a new leaf or 12

tiller has regrown that the plant has enough photosynthetic capacity to support growth and 13

maintenance, and only then does WSC concentrations increase and root growth recommence 14

(Fulkerson and Donaghy 2001). Second, studies of WSC have provided useful guides to 15

grazing management of pasture grasses. Based on relationships between biomass removal, 16

WSCs and regrowth, Fulkerson and Donaghy (2001) suggested that successive grazings of 17

ryegrass should not occur before at least two leaves per tiller were established. If grazing was 18

conducted before the two leaf/tiller stage of regrowth, recovery was severely suppressed. 19

Third, WSCs stored in stems provide a buffer for assimilate supply to kernels when adverse 20

environmental conditions occur after anthesis, so WSCs can potentially have a large influence 21

on final GY (Richards et al. 2010; also see DM partitioning section). Genetic gains in the 22

yield potential of wheat varieties over time have also been associated with increased WSCs in 23

stems and leaf sheaths at anthesis (Shearman et al. 2005). 24

25


24

Water-soluble carbohydrates in DP crops 1

2

Despite extensive studies of WSC dynamics in grazed pastures and grain-only cereals, 3

information on WSC in grazed cereal crops is limited and appears contradictory. Some reports 4

suggest that grazing depletes WSC content (i.e. g/m2), but not WSC concentrations (i.e. g/g), 5

and that the implications of this depletion for GY may be major (Trent et al. 1988). For 6

example Trent et al. (1988) found that total WSC contents in live shoots, leaves and stem 7

bases of grazed wheat were lower than WSC contents measured in ungrazed shoots for about 8

four months after the end of grazing. By physiological maturity, total WSC contents of grazed 9

wheat were similar to those of ungrazed wheat, but the GY of grazed wheat was 16% less than 10

that of the controls. Although other studies have also shown that grazing of wheat crops 11

reduces WSC content of stems at anthesis and does not affect WSC concentrations (average 12

0.38 g g-1), they have also found that effects of grazing on GY were minimal (Muir et al. 13

2006). It is possible that GYs in the study conducted by Muir et al. (2006) were not as 14

dependent on WSCs stored in stems as GYs in the study by Trent et al. (1988). Further 15

investigation of the effect of grazing on DP crop WSCs is required to clarify such 16

discrepancies and to determine how WSC concentrations and contents change temporally, not 17

only to help understand the relationship between regrowth rates and crop persistence, but also 18

to determine how grazing affects WSC accumulation in crop stems and its implications for GY. 19

20

Soil nitrogen uptake and nitrogen metabolism in DP crops 21

22

Grazing or defoliation of pasture grasses may reduce N uptake by roots (Davidson and 23

Milthorp 1966; Thornton and Millard 1997) which in turn (1) reduces plant N supply, (2) 24

causes proteolysis and remobilisation of soluble N compounds from roots and/or stubble to 25


25

establish growth of new laminae (Thornton and Millard 1997), and (3) reduces synthesis of 1

new protein-N compounds (Ourry et al. 1988). Despite the advanced physiological 2

understanding of N metabolism in pasture grasses, knowledge of N-relations in DP crops is 3

still in its infancy. The few available reports focus mainly on N uptake and appear to be 4

inconsistent. Virgona et al. (2006) suggested that N-uptake of grazed crops did not differ from 5

that of ungrazed crops, even though grazing caused a net loss of N (38 kg N ha-1; estimate 6

does not account for recycling of N in urine or faeces). In contrast Thomason et al. (2002) 7

found that more fertiliser N was recovered by forage wheat than grain-only wheat, and Zhu et 8

al. (2006) showed that defoliating wheat at the mid to late tillering stages increased total N 9

removal and N uptake relative to controls (provided adequate fertiliser was applied and crops 10

were sown early). 11

12

Since the majority of soluble leaf N in C3 crops is invested in Rubisco, grazing-induced 13

perturbations to leaf N may affect photosynthesis and therefore have consequences for DM 14

accumulation (see RUE section). Although increases in shoot N concentrations have been 15

observed after defoliation of pasture grasses (Fulkerson and Donaghy 2001), this may reflect 16

a change in SLA or decreasing WSC rather than increasing N content (Davidson and Milthorp 17

1966). Indeed when expressed per unit leaf area, changes in leaf N content after grazing are 18

less frequently observed (Harrison et al. 2010). In one of the few studies examining the 19

changes in leaf N after grazing, Harrison et al. (2010) showed that although grazed crops had 20

significantly elevated leaf photosynthesis, there were no systematic temporal effects of 21

grazing on total leaf N content. 22

23

Because grazed DP crops tend to remain greener than ungrazed crops in later phenological 24

phases (see phenological development section), grazed crops may have increased competition 25

between leaves and grain for N. After anthesis, up to one half of grain N may be sourced from 26


26

retranslocation from leaves and stems (Harper et al. 1987) depending on plant N status and 1

water stress (Borrell and Hammer 2000). If soil N is insufficient to meet N demand of 2

developing kernels, N requirements of kernels are met first through retranslocation from 3

stems and second from leaves (van Oosterom et al. 2010). When the latter occurs, delayed 4

leaf senescence may inhibit leaf N retranslocation, potentially limiting grain protein (Triboi 5

and Triboi-Blondel 2002). Indeed since grazing removes N and delays phenological 6

development it is not surprising that grain protein is often reduced by grazing or defoliation 7

(Asghar and Ingram 1993; Virgona et al. 2006). On the contrary, others have found that 8

defoliation during early vegetative stages has little effect (Francia et al. 2006) or even 9

increases grain protein (Pumphrey 1970). Again these inconsistencies indicate that a more 10

systematic approach is required to disentangle the interactions between phenology, leaf N, N 11

retranslocation and grain protein after crop defoliation. 12

13

Use of models to enhance understanding and forecasting of crop responses 14

to grazing 15

16

Complex interactions and effects of physiological traits in DP systems could be better 17

understood using simulation models 18

19

A crop-grazing simulation model could be used to classify crop traits that are conducive to 20

both forage and grain production, since there are likely to be many traits that are beneficial to 21

one aspect of DP productivity yet detrimental to another (MacKown and Carver 2005). For 22

instance, crops with more erect leaves and vertical growth habits allow a more uniform 23

distribution of light within the canopy, potentially leading to greater GY (see light interception 24

section). However such cultivars are also likely to elevate meristematic zones in early 25


27

development (Noy-Meir and Briske 2002), making apical meristems more prone to 1

decapitation by grazing. In fact pasture grass species most tolerant of grazing are generally 2

those with delayed elevation of meristematic zones (Branson 1953). Crop cultivars with more 3

erect growth habits may also have more rapid accumulation of biomass earlier in the season 4

than more prostrate cultivars, altering the timing of forage availability (MacKown and Carver 5

2005). Effects of other traits (such as tillering and WSC contents) or aspects of DP systems 6

(such as crop soil water use or N status) on the trade-offs between forage and grain production 7

could also be examined using an appropriately designed and calibrated crop-grazing model. 8

9

Simulating grazing of DP crops over multiple seasons and nutritional levels 10

11

A key advantage of a mechanistic crop-grazing model would be the ability to simulate crop 12

responses to defoliation over multiple growing seasons and/or nutritional states. In contrast to 13

one or two years of expensive and labour intensive field experimentation, in silico 14

experiments can be conducted over decades of weather data and multiple nutritional states, to 15

formulate best management practices over the long-term. Such analyses would be beneficial 16

since many physiological processes occurring after grazing are governed by weather, abiotic 17

conditions or endogenous N levels (Fig. 1, N metabolism section, respectively). In fact, 18

abiotic factors often have greater influence on regrowth and GY in DP systems than grazing 19

treatment per se (Christiansen et al. 1989; Brelsford et al. 1998). More recent case studies 20

have suggested that use of forecast-derived decision information to predict differences in 21

forage production and cattle liveweight gains would be a valuable tool for beef producers, 22

provided seasonal forecasts were both timely and strong (Garbrecht et al. 2010). 23

24

Simulation of DP crop responses to grazing over many seasons could also help interpret crop 25

or animal genotype by environment interactions (G×E). In grain-only systems, models have 26


28

been used to investigate three main areas of crop G×E (Chapman 2008). These include (1) 1

using models as ‘environmental integrators’ to interpret G×E observed in the field, (2) model 2

simulation of G×E in multi-environment trials to understand how GY is driven by different 3

combinations of traits, and (3) interpretation of changes in G×E with actual or simulated 4

breeding programs (Chapman 2008). Published model analyses of G×E for grazed pastures 5

are more limited than those of grain-only systems, but are also more diversified. Reports have 6

provided information on, for example, expected livestock phenotypes under different 7

environments (Bryant et al. 2005) or economic outcomes under different stocking rates over 8

many growing seasons (Salmon and Donnelly 2008). Similar analyses conducted for DP 9

cereals would provide information of use to farmers (e.g. risk management associated with 10

grazing different cultivars under different conditions), crop or animal breeders (e.g. suitability 11

of a proposed trait in a target environment, for examples in grain-only systems see Hammer et 12

al. 2005) and policy-makers (e.g. long-term economic outcomes caused by introducing DP 13

crops into new regions). Currently it appears that most analyses of G×E in DP systems are 14

restricted to field experiments over a relatively small number of seasons (e.g. Krenzer et al. 15

1992). 16

17

The need for more dynamic crop-grazing simulation models 18

19

Currently there are only two published models capable of simulating DP crop grazing 20

(Rodriguez et al. 1990; Zhang et al. 2008), but these models have restricted applicability for 21

several reasons. First, both models were designed for winter wheat simulation. Different 22

cultivars and species respond differently to grazing (Redmon et al. 1995; Kelman and Dove 23

2009) so it is unlikely that models developed for winter wheat would produce realistic results 24

for other crop species. Second, both models simulate cattle grazing, but DP crops are also 25

commonly grazed by sheep (e.g. Virgona et al. 2006; Dove and McMullen 2009). Third, 26


29

neither model was calibrated with temporal measurements of LAI, and since key processes 1

such as light interception and transpiration are predominantly driven by LAI, it is crucial that 2

effects of grazing on LAI over the course of the growing season are used in model calibration. 3

Fourth, neither model included the delay in phenological development commonly observed 4

after grazing, which has important ramifications on post-grazing DM accumulation and 5

partitioning, the time-course of LAI and GY (Garcia del Moral 1992; Royo et al. 1999; also 6

see phenological development section). Finally, and most importantly, both models used 7

empirical factors directly linking grazing to observed GY reductions. Such empiricisms 8

severely restrict understanding of crop behaviour after grazing since they blur the distinction 9

between the extent to which GYs are reduced by removal of shoot biomass and inhibition of 10

carbohydrate supply or by removal of apical meristems. Clearly, development of new 11

dynamic crop-grazing simulation models is now required. 12

13

14

Conclusions 15

16

The emphasis of future crop-grazing experiments could profitably shift away from agronomic 17

effects of grazing on GYs towards phenological and physiological recovery of DP crops after 18

grazing. Questions relate to the effects of grazing on leaf angles, SLA, canopy height, tillering 19

potential and rates of canopy closure, since these traits govern light interception, post-grazing 20

growth rates and DM accumulation. It will be important to elucidate the mechanisms 21

underlying delayed phenological development, for crop ontogeny determines the time of 22

anthesis and green area duration after anthesis, both of which strongly affect allocation of 23

assimilate to kernels and ultimately GY. Radiation- and transpiration-use efficiencies are 24

useful indices for contrasting the light- and water-use of grazed crops to those of grain-only 25

crops, yet without field data the complexities implicit in these indices make the effects of 26


30

grazing difficult to project. Grazing reduces leaf area and assimilate supplied to roots, which 1

can inhibit or interrupt root growth, resulting in reduced water and N uptake. Depending on 2

the quantity and frequency of growing season rainfall this may slow soil water use and 3

conserve deep soil water, in turn mitigating terminal crop water stress and increasing the 4

duration of kernel filling. Reduced N uptake caused by grazing has several important 5

consequences in grain-only crops and pasture grasses, ranging from decreased leaf N content 6

and effects on photosynthesis and DM accumulation, changes in forage quality and dry matter 7

digestibility, and increased source-sink competition between leaves and kernels for soluble N 8

compounds after anthesis. Whether such effects occur in grazed cereal crops remains to be 9

seen. Future field experiments should be designed to determine how the severity or frequency 10

of grazing affects the aforementioned physiological variables and thus identify the thresholds 11

with which each variable becomes limiting to productivity. 12

13

Interactions between physiological variables and feedbacks from abiotic factors on post-14

grazing crop recovery are equally important since they often govern whether crop 15

productivity is increased or decreased by grazing. Documented interactions will need to be 16

obtained from field data and from simulations using appropriately calibrated DP crop-grazing 17

models. Information from field data and modelling will further understanding of each other. 18

Simulation models will be a pivotal component for progress in physiological understanding of 19

DP crops as they will allow simulation of grazing systems under multiple seasons and in 20

different environments, hopefully enabling insights into the trade-offs between (1) forage 21

removal and GY, and (2) specific crop traits on recovery rates and GY. Knowledge from field 22

experiments and simulation models would aid risk management planning by farmers, 23

facilitate future breeding of DP crops by scientists and enable better planning of changes in 24

farming enterprises by policy-makers. 25

26


31

Table 1 1 GY ± SD (%)

Contrasts Defoliation Method

Location Reference

-36 ± 10 4 S VIC Nicholson (2006) -28 ± 14 11 C Texas Winter and Musick (1991) -26 ± 6 2 Cl, C, S Oregon Pumphrey (1970) -25 ± 19 4 S ACT Kelman and Dove (2007) -21 ± 27 29 S, Cl ACT Dann et al. (1977) -19 ± 27 36 C Oklahoma Khalil et al. (2002a) -18 ± 11 13 C Texas Winter and Thompson (1990) -17 ± 17 6 Cl ACT Davidson et al. (1990) -17 ± 13 6 Cl Texas Dunphy et al. (1982) -17 ± 12 12 Cl VIC Hacking (2006) -16 ± 15 8 S ACT Dann et al. (1983) -16 ± 13 2 Cl NSW Dann (1968) -7 ± 29 6 Cl Indiana Cutler et al. (1949) -6 ± 3 2 S VIC Nuske et al. (2009) -5 ± 9 24 S Kansas Holman et al. (2009) -5 1 Cl QLD Asghar and Ingram (1993) -4 ± 12 4 Cl QLD Zhu et al. (2004) -3 ± 4 6 Cl Nebraska Lyon et al. (2001) -1 1 S NSW Muir et al. (2006) 1 ± 18 10 C Texas Winter, Thompson and Musick (1990) 1 ± 17 19 Cl Oklahoma Hubbard and Harper (1949) 2 ± 3 2 S ACT Dove et al. (2002) 5 ± 22 3 C Oklahoma Christiansen et al. (1989) 6 ± 17A 24 S NSW McMullen and Virgona (2009) 7 ± 12 10 H Kansas Swanson (1935) 13 ± 28 3 S ACT Harrison et al. (2010) 14 ± 15 10 S NSW Virgona et al. (2006) 16 ± 33 3 S ACT Kelman and Dove (2009) 17 ± 9 3 C Oregon Sharrow and Motazedian (1987) 17 1 C Argentina Arzadun et al. (2003) 18 ± 29 4 C New Jersey Sprague (1954) 23 ± 4 4 S TAS Miller (2010) 51 ± 21 2 Cl Louisiana Miller (1993) 75 1 Cl WA Dean et al. (2006) A Grazed winter wheat compared with ungrazed spring wheat 2


32

Soil watercontent31%

Airtemperature20%

Other 11%

Disease7%

Leaf area14%

Frost damage7%

Lodging11%

1

Fig. 1 2


33

Table 1 1

2

Percentage change in grain yield (GY) of wheat crops relative to undefoliated controls. 3

‘Contrasts’ column shows the number of experiments conducted in each study. Data are mean 4

± one standard deviation (SD) and were calculated for the earliest or least intensive treatments 5

(C = cattle grazing, Cl = mechanical clipping, H = horse grazing and S = sheep grazing). 6

7

Figure 1 8

9

Primary reasons ascribed to differences in grain yield after defoliation as a proportion of the 10

total number of treatments in Table 1. Note that ‘differences’ refer to both positive and 11

negative effects of defoliation (see text for details). ‘Other’ fraction includes livestock 12

trampling, competition with weeds and photoperiod. 13


34

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agronomic and physiological effects of grazing on cereal

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