Ready2Eat Avocado Development of improved ripening protocols Ernst Woltering Wageningen-UR Food & Biobased Research 1
Global sourcing Avocado/Mango 2
Avocado/Mango chain Generally fruit are transported over sea in refrigerated containers Sometimes under Controlled Atmospheres Transport times 3 4 weeks 100.000 tons Avocado s imported, 80% re-exported 150.000 tons Mango s imported, 75% re-exported The Netherlands is important player in Avocado/Mango trade On arrival: Storage/ripening further transport in refrigerated trucks Ripening: ripening rooms Ready2Eat fruit in supermarkets Challenges Huge variability! Huge variability! 3
The challenge For Avocado & Mango coming into the Netherlands, main challenge is to produce homogeneously ripened batches of fruit (Ready-to-Eat, tasty fruit, free from internal and external disorders) Our aim is to better understand the ripening behaviour of these fruit and the factors that affect ripening 4
Ripening protocols We are developing ripening protocols for mango and avocado to assist the industry in making Ready2Eat fruit Hass Avocado s Keitt & Kent mango s The challenge: How to deal with the variability Variability within and between batches Research questions Can we determine the future ripening behaviour at arrival Can we design, based on the initial state, the optimal ripening protocol (temperature, ethylene) to have R2E fruit within.. days Can we predict whether the fruit will become R2E or R2N R2E (ready to eat): the fruit is soft (eatable) R2N (ready to enjoy): the fruit is soft, sweet, tasty aromatic 5
Comparing apples and oranges? Hass Avocado and Keitt/Kent Mango have similar ripening behaviour Both have strong tree factor Can be stored in the tree Ripening starts only after picking Ethylene plays important role in ripening No ripening in the tree (mango) Delayed picking does not affect the ripening behaviour The tree blocks the ripening of the fruit 6
ethylene production (pmol/kg.s) firmness/colour/co2 02-12-2014 Ethylene and avocado ripening 1000 800 coloring ethylene production firmness index colour index CO2 (%) 5 4 600 softening 3 400 2 200 1 0 0 0 2 4 6 8 10 12 Time (days) Comparing apples and oranges? Despite obvious differences between Avocado and Mango, the ripening behaviour seems similar and may be regulated by similar processes Both Avocado and Mango were used in our ripening studies 7
Firmness (0-5 scale) 02-12-2014 Variability in the tree Fruit harvested from one individual tree Fruit had uniform size and color and felt (hand) all firm Some avocadoes/mango s ripen very fast and others very slow or not at all 6 5 Hass Avocado 4 3 2 1 Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 0 0 5 10 15 20 25 days at room temperature Pedreschi et al., 2014 Variability... The variability in future ripening behaviour is already present in the tree This variability still exists after long distance transport Measuring firmness by hand is not predictive for future ripening behaviour Are there other ways to predict the future ripening behaviour? Can we measure the variation? 8
Approach: Initial firmness measurement Although at harvest (or at arrival) all fruits are rock hard (when judged by squeezing by hand) there are differences measurable using machines Limited compression Acoustic spectrum Can we use initial firmness measured by a machine as a measure for future ripening behaviour? Firmness measurement Measure force required to compress the fruit 2 mm Measure the acoustic spectrum after gently ticking the fruit 9
Acoustics and limited compression Acoustics and limited compression 10
Acoustics and limited compression Acoustics and limited compression 11
Acoustic spectrum tomato mango How to measure firmness Zwick (limited compression) AFS (acoustics) good correlation with Zwick Generally good correlation between these methods Three batches of Mango s 12
Avocado Hand versus machine Avocado s that were all judged rock hard by hand showed huge variation when measured by limited compression or by acoustics hard 13
Huge variation after harvest Firm fruit ripens more fast! At t=0 all mango s were rock hard Firm fruit ripens more fast 14
Firm fruit ripens more fast Initial firmness determines softening speed Within a batch: Fruit have different initial firmness Time to soften completely is about similar for all fruit Firm fruit soften faster than less firm fruit 15
Normalizing trick 24C ripening Important facts Limited compression or acoustic can classify the fruit into firmness classes Different firmness classes show different ripening behaviour Within a batch, the time to fully ripe seems about similar for all fruit at a given temperature The speed of ripening depends on the initial firmness Firm fruit ripen more fast than less firm fruit This information is used to design models to predict the ripening behaviour of individual fruit from within a batch 16
Temperature and ripening Mean of 30-40 fruit 10C 12C 30C 24C 17C Temperature and ripening 5C 18C 13C 9C 17
Temperature, ethylene production and ripening Ethylene production 20C 15C softening 10C 5C Temperature and ripening reversibility 12C 12C 20C 20C 18
Temperature and ripening reversibility Softening speed dependent on Temperature and initial Firmness Firm fruit FI 60 Medium FI 45-50 Soft FI 30 temperature 19
Decrease variability within batches Both initial firmness and temperature affect the ripening speed The ripening process can be easily modelled To better control ripening: sort out different firmness classes and use different ripening protocols to produce homogeneous batches of fruit The effect of adding extra Ethylene on ripening speed at different temperatures is still under investigation Ready to Enjoy (R2N)? Will the fruit become R2N? Generally initial Dry Matter is important factor Mango: starch + sugars (correlate with DM) Avocado: Fatty acids (correlate with DM) Near Infrared Spectroscopy (NIR) can non-destructively measure te DM of the fruit 20
Sorting and ripening protocols Sort fruit after harvest (or at arrival) NIR DM high Firmness classes Different ripening protocols DM low Firmness classes Acoustics Different ripening protocols Ripening Models Ready to Enjoy Ready to Eat Alternatively.. When measuring each individual fruit is not possible, one can take a representative sample A firmness distribution can be made of a random sample and the ripening protocol that is best for most of the fruit can be applied Firmness 21
AWETA firmness tester for mango/avocado Biomarkers? Using the protocols we can tackle the variation within batches Variation between batches and through the season still hard to tackle Late season fruit generally ripen faster We would like to have a BIOMARKER that could predict the ripening behaviour of the fruit A BIOMARKER should preferably be measurable nondestructively in-line A Biomarker may be a combination of product features 22
Current BIOMARKER research Avocado C7 sugars (perseitol, mannoheptulose) Role as ripening inhibitors? contradictory results! Low levels of C7 sugars >>> fast ripening? Perseitol Current BIOMARKER research Avocado No relation between initial content of C7 sugars and time to ripen Pedreschi et al., 2014 23
Current BIOMARKER research Avocado Dry Matter? No relation between DM and time to ripen Low DM Medium DM High DM Days to ripen Pedreschi et al., 2014 Current BIOMARKER research Avocado Fatty acids? Linoleic acid (C18:2) >> low in slow ripening fruit Pedreschi et al., 2014 24
The search goes on.. Currently ripening behaviour of Avocado and Mango is studied in relation to soluble and volatile (aroma) compounds Primary & secondary metabolites (sugars, phenolics) Lipids, fatty acids (aroma) volatiles NIR spectroscopy (dry weight, sugars,..) This will hopefully generate new markers, that can be measured non-destructively, to further improve ripening protocols New instruments Proton Transfer Mass Spectroscopy PTR-MS Within a second, a spectrum of the aroma volatiles can be made, very low levels, non-destructively Differences in volatile spectrum between fruit may reflect differences in physiological state The usefulness of this technique will be evaluated on mango and avocado 25
PTR-MS Air flow in Air flow 0ut Mass spectrum Tomatoes Artificial chewing m/z 83 Release of aroma volatile mass 83 900 800 700 600 500 INTACT FRUIT 400 300 AIR 200 100 CHEW 0-10 -100 10 30 50 70 90 110 130 150 170 190 210 230 Sec Aroma fingerprint Cocktail and Round tomato round cocktail 26
Thanks for your attention Contributers: Bruno Defilippi Chile Sebastian Rivera Rob Schouten Eelke Westra Harmannus Harkema Netherlands Els Otma Romina Pedreschi Ric de Vos MSc students: Devika, Tim, Shuang, Thijs, Jolien, Ruxin 27