Using VIS-NIR hyperspectral imaging and deep learning for non-destructive high-throughput quantification and visualization of nutrients in wheat grains-Reference-Cited by-同舟云学术

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Using VIS-NIR hyperspectral imaging and deep learning for non-destructive high-throughput quantification and visualization of nutrients in wheat grains

Published:2024-12 Issue: Volume:461 Page:140651
ISSN:0308-8146
Container-title:Food Chemistry
language:en
Short-container-title:Food Chemistry

Author:

Shi Taotao,Gao Yuan,Song Jingyan,Ao Min,Hu Xin,Yang Wanneng,Chen Wei,Liu Yanyan,Feng Hui

Publisher

Elsevier BV

Reference72 articles.

1. Yellowness index: An application of spectral second derivatives to estimate chlorosis of leaves in stressed vegetation;Adams;International Journal of Remote Sensing,1999

2. Factor analysis and AIC;Akaike;Psychometrika,1987

3. Genetic improvement of grain protein content and other health-related constituents of wheat grain;Balyan;Plant Breeding,2013

4. Early disease detection in wheat fields using spectral reflectance;Bravo;Biosystems Engineering,2003

5. The development of hyperspectral distribution maps to predict the content and distribution of nitrogen and water in wheat (Triticum aestivum);Bruning;Frontiers in Plant Science,2019

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