Identifying key wavenumbers that improve prediction of amylose in rice samples utilizing advanced wavenumber selection techniques.
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[1] A. Savitzky,et al. Smoothing and Differentiation of Data by Simplified Least Squares Procedures. , 1964 .
[2] B. D. Webb,et al. International Cooperative Testing on the Amylose Content of Milled Rice , 1981 .
[3] T. Fearn,et al. Near infrared spectroscopy in food analysis , 1986 .
[4] A HPLC method for specific determination ofα-amylase and glucoamylase in complex enzymatic preparations , 1989 .
[5] D. Sievert,et al. Determination of Amylose by Differential Scanning Calorimetry , 1993 .
[6] S. Engelsen,et al. Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .
[7] J. Roger,et al. CovSel: Variable selection for highly multivariate and multi-response calibration: Application to IR spectroscopy , 2011 .
[8] Dong-Sheng Cao,et al. A strategy that iteratively retains informative variables for selecting optimal variable subset in multivariate calibration. , 2014, Analytica chimica acta.
[9] Reinhold Carle,et al. On-line application of near infrared (NIR) spectroscopy in food production , 2015 .
[10] Qing-Song Xu,et al. Using variable combination population analysis for variable selection in multivariate calibration. , 2015, Analytica chimica acta.
[11] Dong-Sheng Cao,et al. A bootstrapping soft shrinkage approach for variable selection in chemical modeling. , 2016, Analytica chimica acta.
[12] P. Sampaio,et al. Dataset of Near-infrared spectroscopy measurement for amylose determination using PLS algorithms , 2017, Data in brief.
[13] Yunde Zhao,et al. Generation of High-Amylose Rice through CRISPR/Cas9-Mediated Targeted Mutagenesis of Starch Branching Enzymes , 2017, Front. Plant Sci..
[14] Ana Sofia Almeida,et al. Optimization of rice amylose determination by NIR-spectroscopy using PLS chemometrics algorithms. , 2018, Food chemistry.
[15] C. Pasquini. Near infrared spectroscopy: A mature analytical technique with new perspectives - A review. , 2018, Analytica chimica acta.
[16] Wenwen Yu,et al. High-amylose rice: Starch molecular structural features controlling cooked rice texture and preference. , 2019, Carbohydrate polymers.
[17] Dong-Sheng Cao,et al. A hybrid variable selection strategy based on continuous shrinkage of variable space in multivariate calibration. , 2019, Analytica chimica acta.
[18] Jean-Michel Roger,et al. New data preprocessing trends based on ensemble of multiple preprocessing techniques , 2020 .
[19] Puneet Mishra,et al. Improving moisture and soluble solids content prediction in pear fruit using near-infrared spectroscopy with variable selection and model updating approach , 2021 .