Prediction of Soluble Solids Content in Green Plum by Using a Sparse Autoencoder

Prediction of Soluble Solids Content in Green Plum by Using a Sparse Autoencoder

The soluble solids content (SSC) affects the flavor of green plums and is an important parameter during processing. In recent years, the hyperspectral technology has been widely used in the nondestructive testing of fruit ingredients. However, the prediction accuracy of most models can hardly be imp...

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Bibliografiska uppgifter
Huvudupphovsmän: Luxiang Shen, Honghong Wang, Ying Liu, Yang Liu, Xiao Zhang, Yeqi Fei
Materialtyp: Artikel
Språk:English
Publicerad: MDPI AG 2020-05-01
Serie:Applied Sciences
Ämnen:
green plum
SSC
hyperspectral
prediction
deep learning
SAE
Länkar:https://www.mdpi.com/2076-3417/10/11/3769

Internet

https://www.mdpi.com/2076-3417/10/11/3769

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