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...

תיאור מלא

מידע ביבליוגרפי
Main Authors: Luxiang Shen, Honghong Wang, Ying Liu, Yang Liu, Xiao Zhang, Yeqi Fei
פורמט: Article
שפה:English
יצא לאור: MDPI AG 2020-05-01
סדרה:Applied Sciences
נושאים:
green plum
SSC
hyperspectral
prediction
deep learning
SAE
גישה מקוונת:https://www.mdpi.com/2076-3417/10/11/3769

אינטרנט

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

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