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. 2022 Nov 22;11(23):3759.
doi: 10.3390/foods11233759.

Storage Time as an Index for Varietal Prediction of Mango Ripening: A Systemic Approach Validated on Five Senegalese Varieties

Mor Dieye  1   2 , Nafissatou Diop Ndiaye  1 , Joseph Bassama  3 , Christian Mertz  4   5 , Christophe Bugaud  4   5 , Paterne Diatta  6 , Mady Cissé  2
Affiliations

Storage Time as an Index for Varietal Prediction of Mango Ripening: A Systemic Approach Validated on Five Senegalese Varieties

Mor Dieye et al. Foods. .

Abstract

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 'Kent', 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 ('Diourou', 'Papaye', 'Sierraleone', 'Boukodiekhal' and 'Sewe') 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 'ripening storage time' (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.

Keywords: Boukodiekhal; Diourou; Papaye; Senegalese mango varieties; Sewe; Sierra Leone; multi-linear regression; ripening storage time; varietal prediction.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
Digital photo of the three dimensions (Lmax, lmax and emax) of mango.
Figure 2
Figure 2
Correlation between the fruit weight and the equivalent volume V(cm3) = Lmax × lmax × emax. The line Y = 0.528X (R2 = 0.96) is the linear regression on all observations of the scatterplot, all varieties combined (n = 240). The lines y = Cc.x are the linear regressions per variety (n = 40).
Figure 3
Figure 3
Physicochemical parameters of the five local varieties pulp during ripening storage. (a) SSC, (b) DM, (c) pH, (d) TA, (e) Hue. Each point represents mean value of n = 5 mango fruits × 2 trials per fruit with standard deviation bars.
See this image and copyright information in PMC

References

    1. Sarron J. Estimation Spétialisée des Rendements d’une Culture Pérenne en Afrique de l’Ouest: Le cas du Manguier au Sénégal. Université de Montpellier/Montpellier Supagro; Montpellier, France: 2019.
    1. Siddiq M., Brecht J.K., Sidhu J.S. Handbook of Mango Fruit: Production, Postharvest Science, Processing Technology and Nutrition. John Wiley & Sons; Hoboken, NJ, USA: 2017.
    1. FAOSTAT FOASTAT Data—Crops and Livestock Products—Production Quantity. [(accessed on 12 November 2021)]. Available online: https://www.fao.org/faostat/fr/#data/QCL.
    1. Cirad Statistiques Mondiales Mangue 2019–2020. Fruitrop Online. 2021;274:78–79.
    1. Ndiaye O., Diatta U., Nibaly M., Djiba S., Badji K., Ndiaye S. Caractérisation des Vergers de Manguiers (Mangifera indica L.) en Basse Casamance, Sénégal. Eur. Sci. J. ESJ. 2020;16:338. doi: 10.19044/esj.2020.v16n12p338. - DOI