河南农业科学Issue(4)：181-184,4.DOI:10.15933/j.cnki.1004-3268.2015.04.040
基于近红外高光谱图像分析的麦粒硬度分类研究
Hardness Classification of Wheat Kernel Based on Near-infrared Hyperspectral Imaging Technology
摘要
Abstract
As the hardness of wheat may greatly influence the milling process,it is necessary to activate automatic detection of wheat hardness. To prepare for the research,the near-infrared hyperspectral images of wheat with different hardness were collected. The data were processed by derivation,and those in spec-tral range between 950—1 645 nm effective were extracted,after multiplicative scatter correction,with which a partial least squares discriminant analysis model(PLS-DA) was built. During the experiment,120 wheat kernels were used to train the model,and the remaining 90 kernels were used to predict. Conse-quently,the accuracy rate of the model was 99. 63% . The results showed that it was feasible to classify the hardness of wheat kernel based on near-infrared hyperspectral imaging technology.关键词
近红外高光谱图像/光谱分析/偏最小二乘判别分析/小麦硬度/分类Key words
near-infrared hyperspectral image/spectral analysis/partial least squares discriminant analysis/wheat hardness/classification分类
信息技术与安全科学引用本文复制引用
张红涛,田媛,孙志勇,母建茹,阮朋举,侯栋宸..基于近红外高光谱图像分析的麦粒硬度分类研究[J].河南农业科学,2015,(4):181-184,4.基金项目
国家自然科学基金项目(31101085) （31101085）
河南省基础与前沿技术研究计划项目(122300410145) （122300410145）
河南省高等学校青年骨干教师资助计划项目(2011GGJS -094) （2011GGJS -094）
华北水利水电大学教学名师培育项目(2014108) （2014108）
华北水利水电大学2014年大学生创新创业计划项目(HSCX2004143) （HSCX2004143）
