NIRS-based prediction modeling for nutritional traits in Perilla germplasm from NEH Region of India: comparative chemometric analysis using mPLS and deep learning
Author:
Funder
CROPS4HD
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11694-024-02856-5.pdf
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3. T.B. Bagchi, S. Sharma, K. Chattopadhyay, Development of NIRS models to predict protein and amylose content of brown rice and proximate compositions of rice bran. Food Chem. 191, 21–27 (2016). https://doi.org/10.1016/j.foodchem.2015.05.038
4. J.M. Cáceres-Nevado, A. Garrido-Varo, E. De Pedro-Sanz, D. Tejerina-Barrado, D.C. Pérez-Marín, Non-destructive Near Infrared Spectroscopy for the labelling of frozen Iberian pork loins. Meat Sci. 175, 108440 (2021). https://doi.org/10.1016/j.meatsci.2021.108440
5. J. Chen, X. Ren, Q. Zhang, X. Diao, Q. Shen, Determination of protein, total carbohydrates and crude fat contents of foxtail millet using effective wavelengths in NIR spectroscopy. J. Cereal Sci. 58(2), 241–247 (2013). https://doi.org/10.1016/j.jcs.2013.07.002
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