小型西瓜品质近红外无损检测的光谱信息采集
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国家自然科学基金资助项目(31071555);现代农业产业技术体系建设专项资金资助项目(CARS-26-22)


Information Collection of Mini Watermelon Quality Using Near-infrared Non-destructive Detection
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    摘要:

    为了实现小型西瓜生长过程中品质的快速无损检测,对其果实测定时的基础信息采集方式进行了定量分析研究。由PLS建模结果可知,无论是组织含水率还是可溶性固形物含量,在瓜顶部位和赤道部位处都可获得较好的效果。针对不同深度的化学基础信息,其建模效果存在一定差异。无论是组织含水率还是可溶性固形物含量,距瓜皮2~3cm的中层信息区域都能取得最佳的效果。其中瓜顶部位和赤道部位组织含水率的模型相关系数分别为0.953和0.924,RMSEP分别为0.510和0.766;瓜顶部位和赤道部位可溶性固形物含量的相关系数分别为0.952和0.929,RMSEP分别为0.666和0.732。整体说明小型西瓜果实(品种京秀)近红外检测的最佳基础信息区域为中层信息区。

    Abstract:

    In order to achieve the fast and non-destructive detection of mini watermelon quality during growth process, the basic information collection methods for fruit measuring were analyzed quantitatively. The PLS modeling results showed that both the tissue water content and soluble solids content could obtain good results at the top position and the equator. The modeling performance had some differences with basic chemical information at different depths, but both the tissue water content and soluble solids content could got the best results in the middle information area which was under 2~3cm from the rind. The correlation coefficients of tissue water content at the top location and the equator were 0.953 and 0.924, and the RMSEP were 0.510 and 0.766, respectively. The correlation coefficients of soluble solid content at the top location and the equator were 0.952 and 0.929, and the RMSEP were 0.666 and 0.732, respectively. For the mini Jingxiu watermelon, the best foundation information area for NIR detection was the middle area.

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韩东海,常冬,宋曙辉,蒋圣楠,赵洪卫.小型西瓜品质近红外无损检测的光谱信息采集[J].农业机械学报,2013,44(7):174-178.

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  • 在线发布日期: 2013-06-20
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