光散射学报, 2015, 27 (4): 0384, 网络出版: 2016-01-20
基于近红外光谱技术的水稻种子成分分析模型的建立
Construction of Analysis Model of Rice Seed Components Based on Near Infrared Reflectance Spectroscopy
近红外光谱 成分预测 偏最小二乘回归 光谱预处理 单粒种子 NIR spectroscopy component prediction PLSR spectral preprocessing single grain
摘要
对单粒种子样品成分进行快速无损检测,对于作物遗传育种研究有着重要意义。本文采用近红外光谱技术(NIR)和偏最小二乘回归法(PLSR),研究了水稻种子的近红外光谱特性及其与直链淀粉、蛋白质含量的关系,建立了基于NIR的水稻种子成分快速检测模型。通过比较几种不同的光谱预处理方法对于单粒和群体样品模型的效果,对模型进行了优化。结果显示,多元散射校正(MSC)对单粒样品模型的优化作用显著,而一阶导数对单粒和群体样品模型改善都有明显的效果。模型评价参数显示,预测效果良好,为基于NIR的水稻单粒种子成分分析提供技术支撑。
Abstract
In crop genetics and breeding researches,great significance has been attached to nondestructive testing of the components of a single grain sample. In this essay,the relationship between the spectra of a single rice grain and its content of amylose and protein was studied,where near infrared reflectance spectroscopy and partial least-squares regression were applied,and a model for rapid testing of the rice seed components based on near infrared reflectance spectroscopy was set up. The effects of different kinds of spectral preprocessing methods on the model of both single and group seed samples were compared and the model was optimized. According to the results,multiplicative scatter correction had great effect on the model optimization of single seed samples,while first derivative was useful for model optimization of both single and group seed samples. Good prediction results were achieved according to the model evaluation parameters,which provided technical supports for the component analysis of single rice grains based on near infrared reflectance spectroscopy.
余鼎, 程维民, 王琦, 宋乐, 刘斌美, 陶亮之, 吴跃进. 基于近红外光谱技术的水稻种子成分分析模型的建立[J]. 光散射学报, 2015, 27(4): 0384. YU Ding, CHENG Wei-min, WANG Qi, SONG Le, LIU Bin-mei, TAO Liang-zhi, WU Yue-jin. Construction of Analysis Model of Rice Seed Components Based on Near Infrared Reflectance Spectroscopy[J]. The Journal of Light Scattering, 2015, 27(4): 0384.