不同含水量劣变燕麦种子活力的近红外光谱分析  

Analysis of Vigour Level of Deteriorated Oat Seeds Containing Different Moisture with Near Infrared Spectroscopy

作　　者：阴佳鸿[1] 毛培胜[1] 黄莺[1] 孔令琪[1] 朱萍[1] 于晓娜[1] 

机构地区：[1]中国农业大学草地研究所,北京100193

出　　处：《红外》2010年第7期39-44,共6页Infrared

基　　金：北京市自然科学基金项目(6082009);现代牧草产业体系项目(nycytx-037)

摘　　要：以不同含水量的燕麦种子为材料,将近红外光谱技术与主成分-马氏距离识别方法相结合,研究比较了经控制劣变处理后的燕麦种子的活力差异。结果表明,在选取4000cm^(-1)～5050cm^(-1)、5200cm^(-1)～6790cm^(-1)和7192cm^(-1)～10000cm^(-1)波长范围内的光谱数据和含水量为4.0%、10.0%、16.0%、22.0%时,用多元散射校正(MSC)预处理方法对选取的8个主成分进行预测的效果最佳,对校正样本和预测样本的鉴别率均可达到100%;在含水量为22.0%、28.0%、34.0%、40.0%时,用标准归一化预处理方法对选取的8个主成分进行预测的效果最佳,但仍有较高的误判数。在确定的种子含水量范围内,利用近红外技术可以准确地区别不同活力水平的燕麦种子。Using the oat seeds containing different moisture as test samples,the different vigour levels of oat seeds treated by the controlled deterioration are studied by combining near infrared spectroscopy （NIRS） with a principal component analysis-Mahalanobis distance model.The result shows that when the wavelength ranges of 4000-5050cm^（-1）,5200-6790cm^（-1） and 7192 10000cm^（-1） and the moisture of 4.0%,10.0%,16.0%and 22.0%are selected,the multiplicative scatter correction（MSC） is most effective for preprocessing the eight selected principal components and has a 100%identification rate for all of the correction samples and prediction samples.For the samples with moisture of 22.0%,28.0%,34.0% and 40.0%,the normalized preprocessing method is most effective for preprocessing the eight selected principal components but it still has a higher misclassification rate.In the given moisture range,NIRS can identify the oat seeds with different vigour levels correctly.

关 键 词：近红外技术 马氏距离 种子活力 燕麦 

分 类 号：O433.4[机械工程—光学工程]