Predicting moisture content during maize nixtamalization using machine learning with NIR spectroscopy
Author:
Funder
Directorate for Biological Sciences
PepsiCo
Iowa Agriculture and Home Economics Research Station
USDA-ARS base funds
Publisher
Springer Science and Business Media LLC
Subject
Genetics,Agronomy and Crop Science,General Medicine,Biotechnology
Link
https://link.springer.com/content/pdf/10.1007/s00122-021-03926-8.pdf
Reference38 articles.
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3. Balabin RM, Lomakina EI (2011) Support vector machine regression (SVR/LS-SVM)—an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data. Analyst 136:1703. https://doi.org/10.1039/c0an00387e
4. Barratt S, Sharma R (2018) Optimizing for generalization in machine learning with cross-validation gradients. ArXiv180507072 Cs Stat
5. Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67. https://doi.org/10.18637/jss.v067.i01
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