prediction of juice quality from fruit analysis · Æble temadag taastrup, 14-11-2012 slide 1 mabel...

Æble temadag Taastrup, 14-11-2012Slide 1

Mabel Martínez Vega

PhD Student

Supervisors:

Brian Grout

Torben Toldam-Andersen

Dvoralai Wulfsohn

Prediction of juice quality from fruit analysis


Fruit Material

LevelsMeasurement

Dates Cultivars

Aroma

Rajka

HolsteinerCox

Ingrid Marie

1

1

2

2

1

2

• Sugar• Firmness• Acidity• Sug/acid• Starch• Color• Aroma• sensory

Quality traits


Apple orchard

Variability

The Pometum, Taastrup- Denmark


Sugar content, 10 trees (Pometum)

Variety: 'Aroma'. Date 1

Tree

0 1 2 3 4 5 6 7 8 9 10 11

SS

C (

%B

rix)

0

2

4

6

8

10

12

14

16

18

Sug

arC

onte

nt (

%B

rix)

Variety: 'Rajka'. Date 1

Tree

0 1 2 3 4 5 6 7 8 9 10 11S

SC

(%

Brix

)

0

2

4

6

8

10

12

14

16

18

Sug

arC

onte

nt (

%B

rix)


Science and Variability

Author/s Method Area of study

Barrit et al. 1987, Krishnaprakash et al. 1983

Random sampling Effects of fruit position and light

De Silva et al. 2000, Kainer et al. 2001, Skrede et al. 2011, Woodward et al. 2011),

Random sampling Fruit variation

Gutrie and Walsh 1999, McGlone et al. 2002, Hernández et al. 2003, Chauchard et al. 2004, Qing and Zude 2007, Mendoza et al. 2012

Random sampling Fruit quality prediction

H.J. Gundersen, 1987 The fractionator , systematic sampling

Medicine

Gardi et al. 2006, 2007; Dorph- Petersen et al. 2000,

Different uses of Systematic Uniform Random sampling

Medicine,


What is sampling about?

Sample Population


Applications of SUR sampling: The fractionator

Number of flowers in a tree, fruit yieldSource: (Maletti et al. 2004, Wulfsohn et al. 2011)


Objectives

1. To obtain representative samples in order to study the

quality variability of early and late season apple varieties

2. To explore relationships between fruit and juice quality

3. To evaluate feasibility of non-destructive methods to predict

fruit and juice quality


Sugar content, 10 trees (Pometum)


Tree

0 1 2 3 4 5 6 7 8 9 10 11

SS

C (

%B

rix)

0

2

4

6

8

10

12

14

16

18

Sug

arC

onte

nt (

%B

rix)

Variety: 'Rajka'. Date 1

Tree

0 1 2 3 4 5 6 7 8 9 10 11S

SC

(%

Brix

)

0

2

4

6

8

10

12

14

16

18

Sug

arC

onte

nt (

%B

rix)


Sugar Content and fruit position on the tree

Variety: Rajka D1

low high

SS

C (

%B

rix)

0

2

4

6

8

10

12

14

16

18


low high

SS

C (

%B

rix)

0

2

4

6

8

10

12

14

16

18

Low = apples under 1.56 m High = apples over 1.56 m

(In agreement with: Barritt et al. 1987, Volz et al. 1995, Warrington et al. 1996)


An example of skin color and sugar content

9,2 11 11,1 11,3 11,4 11,5 11,7 11,9 12,1 12,3 12,4 12,5 12,7 13,3 13,5 14,1 15,1

‘Aroma 2010’


Commercial Orchard: ‘Fuji’ Chile (7.6ha)

Distribution of Caliber (18.2 kg box)

0%

5%

10%

15%

20%

25%

30%

135 120 110 100 90 80 70 60 50 40

Caliber

Fre

quen

cy

Sample

Packing Export

N= 70 apples

Distribution of fruit size class

Size class (mm)

Parameter Standard Range in sample % of exportquality

Firmness (kg) 6.4-9-1 5.9-10-4 86%

Sugar content(%Brix)

> 12% 12.1 – 18.6 100%

Starch index (10 scale)

5-7 4 - 10 43%


• The Samples who showed extreme values of sugar seem to

come from the upper part of the trees

• No clear relationships between internal quality and skin

color were found

• It was possible to produce an early fruit quality evaluation

for a commercial apple plantation


Objectives







Fruit Quality

Quality

Aroma Rajka Holsteiner Cox Ingrid Marie

5 days 10 Days 5 days 10 Days 5 days 10 Days 5 days 10 Days

No. 102 94 96 90 111 115 105 76

Sugar/acid 15.8 16.9 21.9 24.5 17.7 19.7 18.2 20.7

Streif 0.13 0.04 0.07 0.06 0.08 0.06 0.18 0.08

Juice Quality

Quality

Aroma Rajka Holsteiner Cox Ingrid Marie

5 days 10 Days 5 days 10 Days 5 days 10 Days 5 days 10 Days

Sugar/acid 14.3 17.1 20.3 23.8 17.8 20.5 18.5 25.76


Juice quality


Aroma Rajka H. Cox Ingrid Marie

‘normal applesmell’

‘fresh apple flavor’ ‘Complex applesmell’

‘complex fruittones’

Date 1Cis-3-hexenolEthyl-2-methylpropanoate

Date 22-propanoneButyl 2 methyl butanoateEthyl-2-butenoate

Date 1Methyl propanoateEthyl-2-methylpropanoate

Date 2Cis-3-hexenol

Date 11-pentanol Hexanol2-methyl-1-propanol2-methyl-1-propanolPentanal 2-pentanone2-nonanone2-heptanoneMethyl acetate*Ethyl acetate*

Date 2Propanol2-butanol2-methyl butanal2-butanonePropyl acetateButyl propanoate

Date 1ButanalHexanal*t-2-hexenalpentil acetatemethyl butanoateethyl butanoatepropyl butanoatebutyl butanoatemethyl hexanoate

Date 11-pentanol Hexanol2-methyl-1-propanol2-methyl-1-propanolPentanal 2-pentanone2-nonanone2-heptanoneMethyl acetate*Ethyl acetate*

Harvest date


• Apple varieties collected at the end of the harvest season

developed more complex and appealing aroma taste after

a postharvest period

• sugar/acidity ratio between fruit and their juice was similar


Objectives







VIS/NIR spectroscopy

? ?


VIS/NIR Spectroscopy


Variety ‘Aroma’

5 days

10 days


Fruit sugar content calibration model (%Brix)

Actual (%Brix)

Predicted (%Brix)Variety ‘Aroma’

R=0.78SEC=0.66 (%Brix)


Predictive spectral regions for sugar content . Variety ‘Aroma’

Fruit sugar content bands of interest (%Brix)


The juice calibration model for sugar content obtained from fruit spectra

5 6 7 8 9 10 11 12 13 14

5

6

7

8

9

10

11

12

13

14

Hcox B-2 Hcox B-1

Ingrid A-2 Ingrid A-1

Ingrid B

Hcox A-2

Rajka B-1 Hcox A-1

Predicted PC#4

Rajka A-1

Aroma B-2

Rajka B-2

Aroma B-1 Rajka A-2 Aroma A-1 Aroma A-2

Actual Brix (%)

Predicted Brix (%)

R = 0.92 SEC= 0.95


Conclusions

• It was possible to model fruit quality from sets of representative samples

• Postharvest results in juice quality enhancement but betterquality control of quality in the field is necesary to avoidpost harvest fruit disorders (e.g. Patulin)

prediction of juice quality from fruit analysis · Æble temadag taastrup, 14-11-2012 slide 1 mabel...

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