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<p>Performance Evaluation of Chemometric Prediction Models—Key Components of Wheat Grain</p>

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Title Statement <p>Performance Evaluation of Chemometric Prediction Models—Key Components of Wheat Grain</p>
 
Added Entry - Uncontrolled Name Joe, A Anne Frank; Sathyabama Institute of Science and Technology, Tamil Nadu
Gopal, A ; CSIR-CEERI, Taramani, Chennai 113, India
Pandian, R ; Sathyabama Institute of Science and Technology, Tamil Nadu
 
Uncontrolled Index Term Near infrared spectrometer, Quality parameters, Support vector machine, Wheat 
 
Summary, etc. <p class="Abstract"><span lang="EN-GB">The present study was aimed to evaluate the accuracy of using near-infrared spectroscopy (NIRS) for predicting protein, moisture, starch and ash content values of wheat. The physiochemical properties of wheat were predicted using twelve prediction models of preprocessing coupled with regression tools. The performance measure of SVM aided with extended multiplicative scatter correction gave confident prediction results of protein, moisture, ash and starch content with R<sup>2</sup> values of 0.989, 0.987, 0.976, 0.998 and RMSECV values of 0.263, 0.285793, 0.369 and 0.03 respectively. These results indicate the practical applicability of NIRS in wheat grain quality profiling.</span></p><br />
 
Publication, Distribution, Etc. Journal of Scientific & Industrial Research
2022-11-17 06:32:00
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/JSIR/article/view/68470
 
Data Source Entry Journal of Scientific & Industrial Research; ##issue.vol## 79, ##issue.no## 2 (2020): Journal of Scientific & Industrial Research
 
Language Note en