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Non-destructive growth measurement by machine vision for cabbage plug seedlings population with missing plants

机译:白菜塞幼苗人口与缺失植物的机器视觉无损生长测量

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This report examines an adaptation of a non-destructive growth measurement system for plug seedlings populations with various planting patterns that vary according to missing plants. A three-layered neural network was used to model the relationship between the total leaf area of a cabbage plug seedlings population and growth indices that were obtained by machine vision. It was confirmed that the growth indices of the plug seedlings populations with missing plants varied similarly to the growth indices of plug seedlings populations without missing plants. The predicted total leaf areas for the plug seedlings population with missing plants fitted well with the actual total leaf areas.
机译:本报告探讨了一种适应无损生长测量系统,用于塞子幼苗种群,各种种植模式可根据缺失植物而变化。三层神经网络用于模拟通过机器视觉获得的白菜塞幼苗种群和生长指标之间的关系。据证实,塞子幼苗种群的生长指数与缺失植物的吞噬群相似地变化,没有缺失植物的塞子幼苗种群的生长指标。预计塞子幼苗种群的总叶区域,缺失植物与实际的总叶区域很好。

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