Measuring and predicting mango quality from harvest at Brazil till RTE stage in the Netherlands: GreenCHAINge WP1 – Mango

The general objective in GreenCHAINge Work package 1, is to develop a more generic quality control system for the AH supply chain that will improve the assurances for consistent quality. One of the subprojects is the study of mangoes, being one of the exotic products delivered to Albert Heijn and serving as a model for other exotic products with the AH fresh food logistics. Mangoes produced in Brazil are transported in reefer containers to the Netherlands. To obtain uniform and RTE (Ready to Eat) mangoes on the shelf in supermarkets, it is essential to:
• Harvest mangoes at an optimal maturity stage
• Transport mangoes at optimal conditions
• Ripe mangoes at optimal temperature and time
• Deliver uniform and RTE mangoes at the right moment
The aim of this study is to predict mango quality based on several destructive and nondestructive measurements. This will enable Albert Heijn, Bakker Barendrecht, MAERSK LINE and VEZET to define optimal harvest, transport and ripening conditions, and to select the best raw material for the processing of cut fruit salads. The results of this study are promising:
• Measuring firmness at different moments in the mango supply chain enabled us to develop a model to predict firmness in a future stage
• Quality measurements over time allow prediction of RTE stage to a certain extent • Quality characteristics like internal color and internal defects are measured using “classical subjective phenotyping” as well as using “novel objective phenotyping” methods. Measuring in an objective way reduces variation due to human error and allows standardization of measurements in a continuous scale, throughout the whole world wide supply chain
• Non-destructive measurements of firmness and NIR (Near-infrared) spectra correlate to quality, the capture of NIR spectra in a value might enable the use of each NIR spectrum as a marker to track maturity
• Volatile esters may be used as non-destructive biomarkers to detect ripe mangoes
• Quality measurements over time allow acquirement of suitable raw material for making cut fruit salads
• Precooling has a positive effect on quality of mangoes, while transport to the harbour with or without genset has no significant effect
Accurate prediction of quality allows sorting of mangoes during the chain to finally deliver uniform and RTE mangoes to the supermarkets. To allow proper sorting of mangoes, further optimization of predictive models is required.