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Convolutional neural network allows amylose content prediction in yam (Dioscorea alata L.) flour using near infrared spectroscopy

Background: Yam (Dioscorea alata L.) is the staple food of many populations in the intertropical zone where it is grown. The lack of phenotyping methods for tuber quality hinders the adoption of new genotypes from the breeding programs. Recently, near infrared spectroscopy (NIRS) has been used as a...

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Main Authors: Houngbo, M.E., Desfontaines, L., Diman, J.L., Arnau, G., Mestres, C., Davrieux, F., Rouan, L., Beurier, G., Marie-Magdeleine, C., Meghar, K., Alamu, E.O., Otegbayo, B., Cornet, D.
Format: Journal Article
Language:Inglés
Published: Wiley 2024
Subjects:
amylose
consumers
acceptability
phenotypes
infrared spectrophotometry
yams
food production
yields
Online Access:https://hdl.handle.net/10568/131744

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