Please wait a minute...
浙江大学学报（农业与生命科学版）
浙江大学学报(农业与生命科学版)  2011, Vol. 37 Issue (3): 307-311    DOI: 10.3785/j.issn.1008-9209.2011.03.011
农业科学     
稻叶瘟染病程度的可见-近红外光谱检测方法
程术希,邵咏妮,吴迪,何勇
浙江大学生物系统工程与食品科学学院,浙江 杭州 310029
Determination of rice leaf blast disease level based on visible near infrared spectroscopy
CHENG Shu-xi,SHAO Yong-ni,WU Di,HE Yong
College of Biosystems Engineering and Food Science , Zhejiang University , Hangz hou 310029 , China
 全文: PDF(447 KB)   HTML ( ) 
摘要： 基于可见‐近红外光谱技术,并采用偏最小二乘算法对不同水稻稻叶瘟染病程度的叶片进行化学计量学分析,分别建立基于全波段、特征波段和特征波长的稻叶瘟染病程度定量检测模型.结果表明:全波段建模的叶瘟病染病程度检测正确率达到９６ .７％ ;通过偏最小二乘算法的回归系数选择５ 个特征波段,分别为５５２ ～ ５５８ 、６７２ ～ ６８２ 、７１９ ～ ７２６ 、７５６ ～ ７６８ 和９９０ ～ ９９８ nm ,基于特征波段的模型正确率也达到了９０％ ,说明该５ 个特征波段与叶瘟病染病程度有很好的相关性;基于特征波段结果,选择５ 个特征波长,对叶瘟病染病程度的检测正确率为８０％ .说明基于可见‐近红外光谱技术方法具有较好的预测能力,为稻叶瘟染病程度的快速鉴别提供了一种新方法.
Abstract: A rapid determination of rice leaf blast disease based on visible-near-infrared spectroscopy was proposed . Chemometric analysis was executed on the spectra of the rice leaves with different disease level by using partial least square regression ( PLSR) . Three PLSR models were established based on fullrange spectra ( model １ ) , spectra at feature wavebands ( model ２ ) and spectra at feature wavelengths (model ３) . The determination correct rate of the disease detection level was ９６ .７％ for model １ . By using the obtained regression coefficients of PLSR model , five feature wavebands were selected , which were at ５５２‐５５８ , ６７２‐６８２ , ７１９‐７２６ , ７５６‐７６８ and ９９０‐９９８ nm . The determination correct rate was ９０％ for model ２ . The result showed that there was a good correlation between the disease detection level and the five selected feature wavebands . Five feature wavelengths were further selected based on the feature wavebands . The determination correct rate was ８０％ for model ３ . It is concluded that the visible-nearinfrared spectroscopy gives a good determination result and is a new way to fast determine rice leaf blast disease level .
出版日期: 2011-05-20
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　
邵咏妮
吴迪
何勇
程术希

引用本文:

程术希,邵咏妮,吴迪,何勇. 稻叶瘟染病程度的可见-近红外光谱检测方法[J]. 浙江大学学报(农业与生命科学版), 2011, 37(3): 307-311.

CHENG Shu-xi,SHAO Yong-ni,WU Di,HE Yong. Determination of rice leaf blast disease level based on visible near infrared spectroscopy. Journal of Zhejiang University: Agric. & Life Sci., 2011, 37(3): 307-311.

链接本文:

http://www.zjujournals.com/agr/CN/10.3785/j.issn.1008-9209.2011.03.011    或    http://www.zjujournals.com/agr/CN/Y2011/V37/I3/307

No related articles found!