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Quantification of leaf greenness and leaf spectral profile in plant diagnosis using an optical scanner

机译:使用光学扫描仪对植物诊断中的叶片绿度和叶片光谱进行定量

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Observation of leaf spectral profile (color) enables suitable management measures to be taken for crop production. An optical scanner was used: 1) to obtain an equation to determine the greenness of plant leaves and 2) to examine the power to discriminate among plants grown under different nutritional conditions. Sweet basil seedlings grown on vermiculite were supplemented with one-fifth-strength Hoagland solutions containing 0, 0.2, 1, 5, 20, and 50 mM NH4+. The 5 mM treatment resulted in the greatest leaf and shoot weights, indicating a quadratic growth response pattern to the NH4+ gradient. An equation involving b*, black and green to describe the greenness of leaves was provided by the spectral profiling of a color scale for rice leaves as the standard. The color scale values for the basil leaves subjected to 0.2 and 1 mM NH4+ treatments were 1.00 and 1.12, respectively. The other treatments resulted in significantly greater values of 2.25 to 2.42, again indicating a quadratic response pattern. Based on the spectral data set consisting of variables of red-green-blue and other color models and color scale values, in discriminant analysis, 81% of the plants were correctly classified into the six NH4+ treatment groups. Combining the spectral data set with the growth data set consisting of leaf and shoot weights, 92% of the plant samples were correctly classified whereas, using the growth data set, only 53% of plants were correctly classified. Therefore, the optical scanning of leaves and the use of spectral profiles helped plant diagnosis when biomass measurements were not effective.
机译:观察叶片光谱图(颜色)可以采取适当的管理措施来生产农作物。使用光学扫描仪:1)获得确定植物叶片绿色度的方程式,以及2)检查在不同营养条​​件下生长的植物之间进行区分的能力。在ver石上生长的甜罗勒幼苗中加入五分之一强度的Hoagland溶液,其中含有0、0.2、1、5、20和50 mM NH4 +。 5 mM处理导致最大的叶片和枝条重量,表明对NH4 +梯度的二次生长响应模式。通过以稻叶色阶为标准的光谱分析,提供了一个包含b *,黑色和绿色的方程式来描述叶片的绿色度。罗勒叶经过0.2和1 mM NH4 +处理的色标值分别为1.00和1.12。其他处理导致的值明显更大,为2.25至2.42,再次表明是二次响应模式。根据由红,绿,蓝和其他颜色模型的变量以及色标值组成的光谱数据集,在判别分析中,将81%的植物正确分类为六个NH4 +处理组。将光谱数据集与包括叶重和枝条重量的生长数据集相结合,可以正确分类92%的植物样品,而使用生长数据集,仅可以正确分类53%的植物。因此,当生物量测量无效时,叶片的光学扫描和光谱图的使用有助于植物诊断。

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