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 !