基于高光谱成像的蔬菜新鲜度检测初探
目的 利用高光谱成像技术对蔬菜新鲜度检测进行了初步探讨。方法 采集了小白菜、菠菜、油菜、娃娃菜这四种蔬菜的叶片, 分别在失水0、10、24、48 h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。结果 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变化, SPAD值预测模型的相关系数r=0.76。结论 利用高光谱成像来辨别蔬菜叶片新鲜度是可行的。
Objective To investigate the feasibility of determination of vegetable freshness by hyperspectral imaging. Methods Four kinds of vegetables including pakchoi cabbage, spinach, rape, and baby cabbage were analyzed. The hyperspectral images of vegetable leaves were collected at 0, 10, 24, and 48 h of water loss, respectively. Finally the characteristics of vegetable leaves were analyzed. Results Hyperspectral images could reflect the outer shape and inside chlorophyll changes of vegetables during the water loss. The correlation coefficient of the calibration model was 0.76. Conclusion It indicated that the detection of vegetable freshness by hyperspectral imaging was feasible.
标题：基于高光谱成像的蔬菜新鲜度检测初探
英文标题：Preliminary study on detection of vegetable freshness based on hyperspectral imaging
作者：
吴琼 北京农业信息技术研究中心
朱大洲 北京农业信息技术研究中心
王成 北京农业信息技术研究中心
马智宏 北京农产品质量检测与农田环境监测技术研究中心
陆安祥 北京农产品质量检测与农田环境监测技术研究中心
王纪华 北京农产品质量检测与农田环境监测技术研究中心
中文关键词:蔬菜,高光谱成像,新鲜度,无损检测,
英文关键词:vegetable,hyperspectral imaging,freshness,non-destructive detection,
发表日期：2012-11-12
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