Hyperspectral imaging for the determination of relevant cooking quality traits of boiled cassava

Meghar Karima, Tran Thierry, Delgado Luis Fernando, Ospina Maria Alejandra, Moreno John Larry, Luna Jorge, Londoño Luis Fernando, Dufour Dominique, Davrieux Fabrice. 2024. Hyperspectral imaging for the determination of relevant cooking quality traits of boiled cassava. Journal of the Science of Food and Agriculture, n.spéc. Tropical roots, tubers and bananas: New breeding tools and methods to meet consumer preferences : 4782-4792.

https://doi.org/10.1002/jsfa.12654

Article de revue ; Article de recherche ; Article de revue à facteur d'impact

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Résumé : BACKGROUND: The purpose of this study was to investigate the potential of hyperspectral imaging for the characterization of cooking quality parameters, dry matter content (DMC), water absorption (WAB), and texture in cassava genotypes contrasting for their cooking quality. RESULTS: Hyperspectral images were acquired on cooked and fresh intact longitudinal and transversal slices from 31 cassava genotypes harvested in March 2022 in Colombia. Different chemometric methods were tested for the quantification of DMC, WAB, and texture parameters. Data analysis was conducted through partial least squares regression, K nearest neighbors regression, support vector machine regression and CovSel multiple linear regression (CovSel_MLR). Efficient performances were obtained for DMC using CovSel_MLR with, coefficient of multiple determination , root-mean-square error of prediction RMSEP = 0.96 g/100 g, and ratio of the standard deviation values RPD = 3.60. High heterogeneity was observed between contrasting genotypes. The predicted distribution of DMC within the root can be homogeneous or heterogeneous depending on the genotype. Weak predictions were obtained for WAB and texture parameters. CONCLUSIONS: This study showed that hyperspectral imaging could be used as a high-throughput phenotyping tool for the visualization of DMC in contrasting cooking quality genotypes. Further improvement of protocols and larger datasets are required for WAB and texture quality traits.

Mots-clés Agrovoc : génotype, manioc, Manihot esculenta, spectroscopie infrarouge, phénotype, teneur en eau, cuisson, teneur en matière sèche, propriété physicochimique, qualité de cuisson, qualité, vecteur de maladie

Mots-clés géographiques Agrovoc : Colombie, France

Mots-clés libres : Dry matter content, Water absorption, Texture, Chemometrics, High throughput phenotyping, Consumer preferences

Classification Agris : Q01 - Sciences et technologies alimentaires - Considérations générales
Q04 - Composition des produits alimentaires
U30 - Méthodes de recherche

Champ stratégique Cirad : CTS 3 (2019-) - Systèmes alimentaires

Agences de financement hors UE : Consortium of International Agricultural Research Centers, Centre de Coopération Internationale en Recherche Agronomique pour le Développement, Bill and Melinda Gates Foundation

Projets sur financement : (FRA) Breeding RTB Products for End User Preferences

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