A deep learning approach to improving spectral analysis of fruit quality under interseason variation

Model updating for developed calibrations is critical for robust spectral analysis in fruit quality control. Existing methods have limitations that usually need sufficient samples for model recalibration and are mainly designed for conventional linear models. This study proposes a model fine-tuning...

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Bibliographic Details
Main Author: Yang, Jie (author)
Other Authors: Luo, Xuan (author), Zhang, Xiaolei (author), Passos, Dário (author), Xie, Lijuan (author), Rao, Xiuqin (author), Xu, Huirong (author), Ting, K.C. (author), Lin, Tao (author), Ying, Yibin (author)
Format: article
Language:eng
Published: 2022
Subjects:
Biological variability
Visible/near-infrared spectroscopy
Deep learning
Convolutional neural network
Model updating
Fruit quality
Online Access:http://hdl.handle.net/10400.1/18594
Country:Portugal
Oai:oai:sapientia.ualg.pt:10400.1/18594

Internet

http://hdl.handle.net/10400.1/18594

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