Title: Determination of oil component in cottonseeds with Near Infrared Reflectance Spectroscopy
Abstract: This paper described the calibration and prediction of the oil components in 248 samples of cottonseed on a NIRS (Near Infrared Reflectance Spectroscopy). Using ISI software for scanning and data analysis, an oil calibration was obtained with modified partial least squares as the regression method. The calibration results showed that the coefficient of determination (RSQ) and standard error of calibration (SEC) were 0.9355 and 0.7955, with standard error of performance (SEP) and 1 minus the ratio of unexplained variance to total variance (1-VR) being 0.7905 and 0.9131,respectively. Validation results showed that the coefficient of determination (RSQ) was 0.978,which was higher than other methods with standard error of prediction (SEP) and standard error of prediction corrected for bias (SEP(C)) were 0.508 and 0.491,both the lowest among all used methods. This indicates that NIRS is comparable to chemical methods in both accuracy and prediction and is reliable in practical application.
Publication Year: 2001
Publication Date: 2001-01-01
Language: en
Type: article
Access and Citation
Cited By Count: 1
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot