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

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Title Hyperspectral imaging for the determination of relevant cooking quality traits of boiled cassava
 
Creator Meghar, Karima
Tran, Thierry
Delgado, Luis Fernando
Ospina, Maria Alejandra
Moreno Alzate, Jhon Larry
Luna, Jorge
Londoño Hernandez, Luis Fernando
Dufour, Dominique
Davrieux, Fabrice
 
Subject dry matter content
texture
water extraction
consumer behaviour
high-throughput phenotyping
cassava
cooking quality
 
Description 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 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.
 
Date 2023-04
2023-06-28T08:41:48Z
2023-06-28T08:41:48Z
 
Type Journal Article
 
Identifier Meghar, 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
0022-5142
https://hdl.handle.net/10568/130907
https://doi.org/10.1002/jsfa.12654
 
Language en
 
Rights CC-BY-4.0
Open Access
 
Format application/pdf
 
Publisher Wiley
 
Source Journal of the Science of Food and Agriculture