Storage Time as an Index for Varietal Prediction of Mango Ripening: A Systemic Approach Validated on Five Senegalese Varieties
2022
Mor Dieye | Nafissatou Diop Ndiaye | Joseph Bassama | Christian Mertz | Christophe Bugaud | Paterne Diatta | Mady Cissé
Mangifera indica species presents a wide varietal diversity in terms of fruit size and morphology and also of physicochemical and organoleptic properties of the pulp. In Senegal, in addition to the well-known export varieties, such as &lsquo:Kent&rsquo:, local varieties have been little studied particularly during ripening. This study aims to propose prediction models integrating variables deduced from varietal characteristics. Five mango varieties (&lsquo:Diourou&rsquo:, &lsquo:Papaye&rsquo:, &lsquo:Sierraleone&rsquo:, &lsquo:Boukodiekhal&rsquo: and &lsquo:Sewe&rsquo:) endemic to Senegal were characterized at harvest and followed during ripening storage. Caliber parameters were determined at green-mature stage as well as storage (25 °:C) weight losses. Considering the &lsquo:ripening storage time&rsquo: (RST) variable as ripeness level index, intra-varietal prediction models were built by multi-linear regression (R2 = 0.98) using pulp pH, soluble solid content (SSC) and Hue angle. In addition to these physicochemical parameters, variety-specific size, shape and weight loss parameters, were additional variables in multi-linear models (R2 = 0.97) for multi-varietal prediction of RST. Results showed that storage time, which was the most influential factor on the pH, SSC and Hue, can be used as a response for varietal prediction of mango ripening. As a decision support tool, theses statistical models, validated on two seasons, will contribute to reduce post-harvest losses and enhance mango value chain through a better ripening process monitoring.
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