叶菜失水条件下的高光谱图像特征分析研究  

Research on the Leafy Vegetables Under the Condition of Water Loss Detection Based on the Hyperspectral Imaging

作　　者：吴琼[1,2] 陆安祥 朱大洲[3] 王成[3] 方晶晶[1] 纪建伟[1] 

机构地区：[1]沈阳农业大学信息与电气工程学院,辽宁沈阳110866 [2]北京农业质量标准与检测技术研究中心,北京100095 [3]北京农业智能装备技术研究中心,北京100097

出　　处：《北方园艺》2015年第8期5-9,共5页Northern Horticulture

基　　金：公益性行业(农业)科研专项资助项目(201003008);国家自然科学基金资助项目(31201125);北京市自然科学基金资助项目(4142019)

摘　　要：通过采集小白菜、菠菜、油菜、娃娃菜这4种蔬菜的叶片,分别在失水0、10、24、48h的状态下,利用成像光谱仪采集其光谱图像,对蔬菜叶片进行对比分析,利用高光谱成像技术对蔬菜新鲜度检测进行了初步探讨。结果表明:蔬菜在失水过程中,高光谱图像能反映其外观形态及内部叶绿素的光谱曲线变化,并利用主成分分析(PCA)方法实现对不同品种蔬菜叶片的分类定性判别的划分。从而说明利用高光谱成像来辨别蔬菜叶片新鲜度是可行的。Four kinds of vegetables were compared to analyze,including pakchoi cabbage, spinach, rape, and baby cabbage. The vegetable leaf was stored for water loss. The hyperspectral images were collected at 0 hours water loss, 10 hours water loss, 24 hours water loss, 48 hours water loss, respectively. The freshness change in the process of the vegetable storage by hyperspectraI imaging was preliminary explored. The results showed that hyperspectral image could reflect the outer shape and inside chlorophyll change of vegetables during the water loss. And the result of the principal component analysis （PCA） method for the classification of different varieties of vegetables leaf showed that the differences of the spectral were increasing within the degrees of the water loss. The study provided a technical support for the quality management in the process of the vegetable storage and transportation.

关 键 词：蔬菜 高光谱成像 失水 新鲜度 无损检测 

分 类 号：TN911.73[电子电信—通信与信息系统]