期刊论文

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

中文

湖南农业大学学报(自然科学版)

1007-1032

2019

45

2

189-193

10.13331/j.cnki.jhau.2019.02.014

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

本校为第一机构

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、 0.683 1,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...

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 performan...