浙江农业学报

• 作物科学 •    下一篇

基于高光谱图像的水稻种子活力检测技术研究

  

  1. 1 浙江农林大学 信息工程学院,浙江 杭州 311300; 2 浙江农林大学 农业与食品科学学院,浙江 杭州 311300; 3 浙江农林大学 浙江省林业智能监测与信息技术研究重点实验室,浙江 杭州 311300
  • 出版日期:2015-01-25 发布日期:2015-01-17

Study on detection technology of rice seed vigor based on hyperspectral image

  1. 1 College of Information Engineering, Zhejiang A&F University, Hangzhou 311300, China;2 School of Agricultural and Food Science, Zhejiang A&F University, Hangzhou 311300, China; 3 Key Laboratory of Forestry Intelligent Monitoring and Information Technology Research of Zhejiang Province, Zhejiang A&F University, Hangzhou 311300, China
  • Online:2015-01-25 Published:2015-01-17

摘要: 随着种子活力逐渐受到人们的重视,快速且不破坏种子的活力检测方法逐渐成为研究的热点。试验以不同老化程度的水稻种子为材料,采用高光谱成像技术结合PCA-SVM方法,研究比较了不同活力水平的水稻种子的活力差异。采集两个水稻品种在400~1000 nm范围的高光谱图像数据, 通过主成分分析法(PCA)获得主成分图像,确定特征波段;应用支持向量机(SVM)建立水稻种子活力鉴别模型。结果表明,预测的判别率可达100%,说明高光谱成像技术为快速准确无损测定种子活力提供了一条新的途径。

关键词: 种子活力, 高光谱, 支持向量机, 主成分分析

Abstract: As the seed vigor was gradually brought to the public attention, the rapid detection of seed vigor without destroying has been a research hot spot. The rice seeds with different aging degrees were used as experimental materials, PCA-SVM method and hyperspectral imaging technology were compared to study the difference in rice seed vigor. The hyperspectral image data of two rice varieties were collected in 400-1 000 nm range. In order to obtain principal component images, PCA was used to determine the feature band. SVM was adopted to build the model of seed vigor. The results showed that the prediction accuracy could reach 100%. A new way of rapid detection of seed vigor was proposed by hyperspectral imaging technology.

Key words: seed vigor, hyperspectral, support vector machine, principal component analysis