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

<0.8) for predicting amylose content from yam flour, while the CNN proved reliable and efficient method. With the application of deep learning method, this study established the proof of concept that amylose content, a key driver of yam textural quality and acceptance, could be predicted accurately using NIRS as a high throughput phenotyping method. This article is protected by copyright. All rights reserved.