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

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dc.creatorMeghar, Karima
dc.creatorTran, Thierry
dc.creatorDelgado, Luis Fernando
dc.creatorOspina, Maria Alejandra
dc.creatorMoreno Alzate, Jhon Larry
dc.creatorLuna, Jorge
dc.creatorLondoño Hernandez, Luis Fernando
dc.creatorDufour, Dominique
dc.creatorDavrieux, Fabrice
dc.date2024-06
dc.date2023-06-28T08:41:48Z
dc.date2023-06-28T08:41:48Z
dc.date.accessioned2026-06-27T13:35:29Z
dc.descriptionBACKGROUND: 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 R2p =0:94, 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.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/130907
dc.identifier.urihttp://hdl.handle.net/123456789/64195
dc.languageen
dc.publisherWiley
dc.rightsOpen Access
dc.sourceMeghar, K.; Tran, T.; Delgado, L.F.; Ospina, M.A.; Moreno, J.L.; Luna, J.; Londoño, L.; Dufour, D.; Davrieux, F. (2023) Hyperspectral imaging for the determination of relevant cooking quality traits of boiled cassava. Journal of the Science of Food and Agriculture, Online first paper (22 April 2023). ISSN: 0022-5142
dc.subjectdry matter content
dc.subjecttexture
dc.subjectwater extraction
dc.subjectconsumer behaviour
dc.subjecthigh-throughput phenotyping
dc.subjectcassava
dc.subjectcooking quality
dc.titleHyperspectral imaging for the determination of relevant cooking quality traits of boiled cassava
dc.typeJournal Article

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