the post-harvest management of apples, from hot water ... van schaik.pdf · the post-harvest...
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The Post-harvest Management of Apples, from
Hot Water Treatment to Decision Support
System.
Alex van Schaik
Coordinator Paolo
Bertolini WP1
Ria Derkx WP2
Outline
� Non-destructive measurement of quality
� Sustainable prevention of postharvest rot
� Improved storage systems
� Quality prediction
Post Harvest Chain
Quality determined at harvest!!
- Ripening status
- Size/color/presentation
- Sustainable product
- Biochemical composition
- Potential taste (sugars)
- Sensitivity to defects
- Shelflife
Initial quality: DA meter
� NIR technique
� Portable
� Quality prediction (harvest and storage)
Research:
Golden Delicious, Red Delicious, Pink Lady
Galaxy, Elstar, Rubens
Harvest 4 Sept Harvest 2 Oct
IAD
0
0.5
1
1.5
2
2.5
650 750 850 950 1050
Wavelength (nm)
Ab
so
rba
nc
e (
A)
1.1
0.8
0.6
0.4
0.2
� The IAD is calculated as the difference in absorbance at the
wavelengths of 670 (chlorophyll-a absorbance peak) and 720 nm
(background of the spectrum)
� The IAD decreases throughout fruit development and ripening
Workin
g
DA-meter
� Ethylene production (left) and Starch content (right) in
relation with DA measurement at 3 harvest dates for
Red Delicious apples
0
0.5
1
1.5
2
2.5
1.65-1.55 1.55-1.5 1.5-1.4 1.4-1.3 1.3-1.2 <1.0
IAD
Ethylene emission
ppm h-1 kg-1
0
1
2
3
4
5
6
7
8
9
10
1.65-1.6 1.6-1.55 1.55-1.5 1.5-1.45 1.45-1.4 1.4-1.35 1.35-1 <1
Starch in
dex
DA meter: results
DA-classes for Gala Apples harvested at three times
4 Sept
0
5
10
15
20
25
30
35
40
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2
DA-index
%
11 Sept
0
5
10
15
20
25
30
35
40
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2
DA-index
%
19 Sept
0
5
10
15
20
25
30
35
40
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2
DA-index
%
25 Sept
0
5
10
15
20
25
30
35
40
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2
DA-index
%
2 Oct
0
5
10
15
20
25
30
35
40
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2
DA-index
%
Rubens - DA-index
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
19-9 29-9 9-10 19-10 29-10 8-11 18-11
Date
DA
-index 20
10
4
1
DA distribution at different harvest
dates for Rubens apples
Decline in DA-index during storage
at different temperatures
Pink Lady: badges of fruit
Elstar individual fruits
Relation DA and Firmness
Correlation between DA-index and
fruit firmness
y = 18.122x + 51.51
R2 = 0.58740
45
50
55
60
65
70
75
80
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
DA-index
Fru
it f
irm
ne
ss
, N
Tools in the chain: DA meter
� Promising technique for several varieties
� Reduction biological variation: selection at harvest
� Measurement in the orchard possible
� Application for more fruits
� Quality prediction (harvest and storage)
� Relationship with other quality attributes
� Must accepted as a standard tool?!
Safer Fruit and Environment
Replacing pesticide treatment against Postharvest rot
by:
- HWT Hot Water Treatment
- BCA Biological Control Agents (Antagonists)
- GRAS Generally Recognized Safe Substances
Hot Water Treatment
Results of Hot Water Treatment.
Example of results:
� Golden Delicious: 52°C for 40 seconds and 54°C/ 56°C for
20 seconds.
� Braeburn can be safely treated up to 56°C for 40 seconds
and 58°C for 20 seconds.
� Royal Gala can be safely treated up to 52°C for 40
seconds and 54°C for 20 seconds.
� Queen Cox can be safely treated up to 54°C for 20
seconds.
Results of Hot Water Treatment.
BUT:
� Variation in effects depending to season, orchard, growing
area and variety.
� Good result Nectria and Gloeosporium, not against
Botrytis.
� Longer immersion time and higher temperature: skin
damage.
� Standard protocol for every situation is problematic
� Logistic problems during harvest
� Large scale application is difficult
Hot Water Treatment on peaches
a
a
E I
84,38%
bE I
100%
b
0
25
50
75
peach "Rich Lady" nectarine "Big Top"
infe
cte
d f
ruit
s %
Control HW 60°C x 20"
Treatments with GRAS and Antagonists
� Effects of official EU registered Antagonists were
ineffective
� Some GRAS treatments were effective:
- Na-molybdate
- Peroxyacetic acid
- Alcohol ethoxylate
Registration is necessary and is time consuming in EU
1-MCP is blocking the ripening process
0 50 100 150 2000
200
400
600
800
1000
1200
time [hours]
ethylene production [pmol/kg/s]
receptor
C = C
receptor
C
C - C = C
ethylene
C = C
1-mcp
Storage systems
Storage techniques: 1-MCP treatment
0
10
20
30
40
50
60
70
80
90
100
0 48 75 103 138 175 0 43 70 98 133 170
storage days storage days
firm
ness [N
/cm
²]
firmness after shelf-life at 18°C
+ MCP - MCP
harvest 1 harvest 2
Kitteman, Bavendorf
Storage techniques: Dynamic Oxygen Conditions
Relative
respiration
0 % O2 21
ULO
DCS/DCA
Principle
Dynamic Storage Systems
DCA: Source A. Zanella, Italy
DCS: Source A. van Schaik, Netherlands
Dynamic Oxygen Systems Influence different technologies on scald Red Delicious
0
10
20
30
40
50
60
70
ULO DPA MCP DCA
Technology
% S
cald
Scald
Zanella,
Laimburg
Skinspots and DCS after 1 Week 18°C
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
11330 10412 10350 10069 avg
Orchard
SV-score (0-3)
ULO
DCS
Dynamic Control System (DCS)Distribution firmness of apples after 7.5 Month in storage direct en 1 wk shelflife
CA and DCS storage with and without 1-MCP (Elstar)
0
0.1
0.2
0.3
0.4
0.5
0.6
2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8
Firmness class (per 0.5 kg)
am
out of fr
uits (%
)
ULO shelflife Control
ULO shelflife SmartFresh
DCS shelflife Control
DCS shelflife SmartFresh
Interactive Storage systems
(DCA\DCS\ILOS)� Advantages
� Orchard related storage condition
� Retention of firmness and ground color in the chain
� Reduction of biological variation
� Reduction of physiological disorders
� Replacement of chemical treatments
� Allowed for organic fruits
� Necessary:
� More equipment
� Special sensors
� Gastight rooms
Peaple
Decision Support System for
Simulation of Postharvest Quality Changesin
Fruit Supply Chains
Pawel Konopacki et all
Peaple is a prototype Decision Support System to:
simulate quality changes
of apples and peaches
along different supply chains
to meet the demands of consumers
and consequently stimulate the increase of fresh fruit
consumption.
Peaple contains models for several apple and peach
quality indices:
firmness
acidity
soluble solids content
skin colour
disorders
helpsystem
1 Cultivars
2 Growth location
3 Harvesting time
4 Transport (conditions)
5 Storage: CA, 1 MCP, DCA, HWT
6 Distribution (conditions)
7 Shelflife
Included in Peaple:
35
40
45
50
55
60
65
70
0 30 60 90 120 150 180 210 240 270 300
Firmness
Time
RA storage
Transport
Retail
35
40
45
50
55
60
65
70
0 30 60 90 120 150 180 210 240 270 300Firmness
Time
CA storage
Transport
Retail
www.peaple-dss.eu
Conclusions
� Improvement Non Destructive measurement of
Quality
� Non Chemical treatments against Post Harvest Rot
in some cases possible.
� New storage systems successful on the market
� Prototype DSS system for quality
Thanks for your attention !