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

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.