基于叶面叶绿素分布特征的黄瓜叶片氮钾元素亏缺诊断

利用高光谱图像技术无损表征黄瓜叶片的叶绿素分布特征,并将其作为N、K元素亏缺诊断依据。采集黄瓜叶片的高光谱图像数据,利用高效液相色谱法分析黄瓜叶片的叶绿素含量,利用遗传算法建立叶片高光谱图像信号与叶绿素含量的对应关系,进而实现黄瓜叶片叶绿素分布图的无损检测。与对照组叶片的叶绿素分布图相比,缺N叶片主要表现为叶片中心区域叶绿素含量偏低,而缺K叶片主要表现为叶片边缘的局部区域叶绿素含量偏低。据此分别提取缺N、缺K叶片及对照组叶片的叶绿素及其分布特征(叶片中心区域所有像素点的叶绿素含量均值、叶片边缘区域叶绿素含量偏低的像素点数量),并借助提取的特征参数建立了N、K元素亏缺诊断方法,其正确诊断率为95%。研究结果表明,叶绿素叶面分布特征可有效实现黄瓜植株N、K元素的亏缺诊断。

Nondestructive Diagnostics of Nitrogen and Potassium Deficiencies Based on Chlorophyll Distribution Features of Cucumber Leaves

The deficiencies of essential macronutrients of nitrogen (N) and potassium (K) usually affect the production of chlorophyll, cause imbalances in plant growth and drastically most importantly affect the quality and yield of agricultural products. A new N/K deficiency diagnostics method was proposed based on chlorophyll distribution features of the whole cucumber leaf. N/K deficient cucumber plants and control plants were grown under non soil conditions with special nutrient supply. Chlorophyll distribution maps of N deficient leaves, K deficient leaves and control leaves were determined by using hyperspectral imaging technology and genetic algorithm, and distribution features extracted from the chlorophyll distribution maps were employed to diagnose N/K deficiencies. Chlorophyll distribution features (the mean value of all pixels in leaf center region and the number of pixels with low chlorophyll content in the leaf edge region) were extracted. A diagnostic method based on these features were obtained with total diagnostics rates of 95% for N/K deficiencies. The result indicated that the extracted chlorophyll distribution features could be employed to diagnose N and K deficiencies in cucumber plants.