稻米直链淀粉含量近红外检测模型的建立  

Establishment of near infrared analysis model for amylose content of rice powder

作　　者：刘红梅[1] 肖正午 申涛 蒋鹏[1] 单双吕 邹应斌[1] LIU Hongmei;XIAO Zhengwu;SHEN Tao;JIANG Peng;SHAN Shuanglyu;ZOU Yingbin(College of Agronomy,Hunan Agricultural University,Changsha,Hunan 410128,China)

机构地区：[1]湖南农业大学农学院,湖南长沙410128

出　　处：《湖南农业大学学报（自然科学版）》2019年第2期189-193,共5页Journal of Hunan Agricultural University(Natural Sciences)

基　　金：湖南省自然科学基金项目(2016JJ3072);湖南农业大学大学生创新性实验计划项目(XCX17088);湖南农业大学作物学科优秀人才基金项目(ZWKF201507)

摘　　要：以147份南方籼稻品种或组合的稻米为供试材料,利用偏最小二乘法(PLS),通过不同波长和不同预处方式建立稻米直链淀粉含量的近红外分析模型。结果表明:全谱段(950～1 650 nm)建模效果最好,其相关系数(R)、预测标准差(SEP)、校准标准差(SEC)分别为0.947 7,1.162 3、0.700 2;采用多元散射校正法(MSC)法对全谱图进行预处理的效果较好,优化后的模型相关系数(R)、预测标准差(SEP)、校准标准差(SEC)分别为0.981 9、0.100 9、0.6831,其相对分析误差(PRD)为3.6;将稻米直链淀粉含量的近红外光谱预测值与化学值进行配对T检验,P=0.356>0.05(置信区间为95%),表明近红外光谱法与化学分析法得到的检测结果无显著差异,即应用近红外光谱快速检测稻米直链淀粉含量是可行的。Using 147 southern japonica rice varieties or combinations as test materials, the near-infrared analysis model of rice amylose content was constructed by partial least squares (PLS) method. The results showed that the full spectral band (950-1 650 nm) was the best performance for modeling with the correlation coefficient (R), 0.947 7;prediction standard deviation (SEP), 1.162 3, and calibration standard deviation (SEC), 0.700 2, respectively. With different preprocessing methods, the models are adopted for the full spectrum. The multi-spectral correction (MSC) method showed the best performance. The resulted optimized model had correlation coefficient (R), prediction standard deviation (SEP) and calibration standard deviation (SEC) 0.981 9, 0.100 9 and 0.683 1, respectively. The relative analysis error (PRD) was 3.6. The results of paired T test showed that P=0.356>0.05 (confidence interval 95%) indicating that there was no significant difference between the predicted values of near infrared spectroscopy and the results of chemical values. It is feasible to detect the amylose content of rice by near-infrared spectroscopy.

关 键 词：稻米 直链淀粉含量 近红外分析 偏最小二乘法 

分 类 号：Q539.1[生物学—生物化学] O657.33[理学—分析化学]