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Updated: Jun 19, 2026

Construction of Models for Nondestructive Prediction of Ingredient Contents in Blueberries by Near-infrared Spectroscopy Based on HPLC Measurements
Published on: June 28, 2016
[Study of simplification of prediction model for kiwifruit firmness using near infrared spectroscopy]
Qiang Lü1, Ming-Jie Tang, Jie-Wen Zhao
1School of Food & Biological Engineering, Jiangsu University, Zhenjiang 212013, China. lvqiang1111@gmail.com
Abstract:
To simplify the prediction model of kiwifruit firmness, SNV was used to preprocess the near infrared (NIR) spectra (1 000-2 500 nm)of kiwifruit. PLS model simplification by optimizing spectral intervals and decreasing the number of factors through net analyte preprocessing (NAP)was carried out. Results showed that the performance of NAP/PLS model is the best. It was achieved with 5 factors in five wavenumber ranges(5 189-5 370, 4 549-4 620, 6 049-6 230, 6 999-7 730, and 6 249-6 614 cm(-1)). The optimal model was achieved with R2 = 0.819 41 and RMSECV = 0.701 77 in the calibration set and R2 = 0.780 67 and RMSEP = 0.882 71 in the prediction set. This indicates that the model not only may efficiently simplify PLS model, but also may improve precision and predictive ability.
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