化学计量学
稳健性(进化)
计算机科学
生化工程
质量评定
质量(理念)
工艺工程
环境科学
农业工程
生物技术
机器学习
评价方法
化学
可靠性工程
工程类
生物化学
哲学
认识论
基因
生物
作者
Zhenjiao Du,Wenfei Tian,Michael Tilley,Donghai Wang,Guorong Zhang,Yonghui Li
标识
DOI:10.1111/1541-4337.12958
摘要
Wheat is one of the most widely cultivated crops throughout the world. A great need exists for wheat quality assessment for breeding, processing, and products production purposes. Near-infrared spectroscopy (NIRS) is a rapid, low-cost, simple, and nondestructive assessment method. Many advanced studies associated with NIRS for wheat quality assessment have been published recently, either introducing new chemometrics or attempting new assessment parameters to improve model robustness and accuracy. This review provides a comprehensive overview of NIRS methodology including its principle, spectra pretreatments, spectral wavelength selection, outlier disposal, dataset division, regression methods, and model evaluation. More importantly, the applications of NIRS in the determination of analytical parameters, rheological parameters, and end product quality of wheat are summarized. Although NIRS showed great potential in the quantitative determination of analytical parameters, there are still challenges in model robustness and accuracy in determining rheological parameters and end product quality for wheat products. Future model development needs to incorporate larger databases, integrate different spectroscopic techniques, and introduce cutting-edge chemometrics methods. In addition, calibration based on external factors should be considered to improve the predicted results of the model. The NIRS application in micronutrients needs to be extended. Last, the idea of combining standard product sensory attributes and spectra for model development deserves further study.
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