Li Tian-xin, Jia Shi-qiang, Liu Xu, Zhao Sheng-yi, Ran Hang, Yan Yan-lu, An Dong
Guang Pu Xue Yu Guang Pu Fen Xi. 2015 Dec;35(12):3388-92.
This article explore the feasibility of using Near Infrared Reflectance (NIR) and Transmittance (NIT) Spectroscopy (908.1-1677.2 nm wavelength range) to identify maize hybrid purity, and compare the performance of NIR and NIT spectroscopy. Principle Component Analysis (PCA) and Orthogonal Linear Discriminant Analysis (OLDA) were used to reduce the dimension of spectra which have been pretreated by first derivative and vector normalization. The hybrid purity identification model of Nonghua101 and Jingyu16 were built by SVM. Models based on NIR spectra obtained correct identification rate as 100% and 90% for Nonghua101 and Jingyu16 respectively. But NIR spectra were greatly influenced by the placement of seeds, and there existed significant difference between NIR spectra of embryo and non-embryo side. Models based on NIT spectroscopy yielded correct identification rate as 98% both for Nonghua101 and Jingyu16. NIT spectra of embryo and non-embryo side were highly similar. The results indicate that it is feasible to identify maize hybrid purity based on NIR and NIT spectroscopy, and NIT spectroscopy is more suitable to analyze single seed kernel than NIR spectroscopy.
本文探讨了利用近红外反射率(NIR)和透射率(NIT)光谱法(波长范围为908.1 - 1677.2 nm)鉴定玉米杂交种纯度的可行性,并比较了NIR和NIT光谱法的性能。采用主成分分析(PCA)和正交线性判别分析(OLDA)对经过一阶导数和向量归一化预处理后的光谱进行降维。利用支持向量机(SVM)建立了农华101和京玉16的杂交种纯度鉴定模型。基于近红外光谱的模型对农华101和京玉16的正确识别率分别为100%和90%。但近红外光谱受种子摆放位置影响较大,胚部和非胚部的近红外光谱存在显著差异。基于NIT光谱的模型对农华101和京玉16的正确识别率均为98%。胚部和非胚部的NIT光谱高度相似。结果表明,基于近红外和NIT光谱鉴定玉米杂交种纯度是可行的,且NIT光谱比近红外光谱更适合分析单粒种子。