Predicting ripening behaviour of mango fruit through an understanding of ripening events

The aim of this project is to understand the molecular mechanisms behind mango ripening, and develop a predictive model to ensure nutritional and physiological quality across the supply chain, to reduce waste.

DatesSeptember 2020 – September 2023
SponsorOrchard House Foods and Cranfield University

Cranfield University and Orchard House Foods have joint efforts to predict mango ripening behaviour through the understanding of the progression of ripening events in different cultivars. This will be achieved by elucidating the mechanisms underlying the differential ripening patterns between ‘Kent’ and ‘Keitt’ cultivars, and evaluating the potential use of non-destructive techniques to predict ripening through the supply chain.

The aim of this project will be achieved through the following objectives:

To investigate the biochemical processes, and elucidate the differential molecular mechanisms, that control ripening patterns in ‘Keitt’ and ‘Kent’ mangoes.
To evaluate the potential for near-infrared spectroscopy (NIRS) and Laser Doppler Vibrometry (LDV) coupled with chemometrics to classify ‘Kent’ and ‘Keitt’ mangoes into different ripening stages.
The best non-destructive technique (NIRS or LDV) will be selected (based on year 1) and ripening prediction models (e.g., PSL-DA, Random Forest) will be developed based on the selected biomarkers from first objective.

The knowledge gained will allow the industry to adopt informed and targeted postharvest management practices to improve ready-to-eat mango quality and reduce waste.