Applicability of Near Infrared Reflectance Spectroscopy to Predict Amylose Contents of Single-Grain Maize
文献类型： 外文期刊
作者： Dong, Qing 1 ; Xu, Qianqian 1 ; Wu, Jiandong 1 ; Cheng, Beijiu 1 ; Jiang, Haiyang 1 ;
作者机构： 1.Anhui Agr Univ, Natl Engn Lab Crop Stress Resistance, Hefei 230036, Peoples R China
2.Anhui Acad Agr Sci, Maize Res Ctr, Hefei 230031, Peoples R China
关键词： NIR spectra; Zea mays; amylose; optimal model
期刊名称：AGRONOMY-BASEL （ 影响因子：3.949； 五年影响因子：4.117 ）
ISSN：
年卷期： 2021 年 11 卷 12 期
页码：
收录情况： SCI
摘要： Near infrared reflectance spectroscopy (NIRS) and reference data were used to determine the amylose contents of single maize seeds to enable rapid, effective selection of individual seeds with desired traits. To predict the amylose contents of a single seed, a total of 1069 (865 as calibration set, 204 as validation set) single seeds representing 120 maize varieties were analyzed using chemical methods and performed calibration and external validation of the 150 single seeds set in parallel. Compared to various spectral pretreatments, the regression of partial least squares (PLS) with mathematical treatment of Harmonization showed the final optimization. The single-seed amylose contents showed the root mean square error of calibration (RMSEC) of 2.899, coefficient of determination for calibration (R-2) of 0.902, and root mean square error of validation (RMSEV) of 2.948. In external validations, the coefficient of determination in cross-validation (r(2)), root mean square error of the prediction (RMSEP) and ratio of the standard deviation to SEP (RPD) were 0.892, 2.975 and 3.086 in the range of 20-30%, respectively. Therefore, NIRS will be helpful to breeders for determining the amylose contents of single-grain maize.
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