基于数字图像分析监测不同氮肥处理下加工番茄生长状况的初步研究

Tomato growth monitoring under different N treatments based on digital image analysis

利用数字相机获取田间加工番茄冠层影像,通过图像处理软件准确识别冠层和背景像素,分析了加工番茄不同施氮量下提取的地面覆盖度与生物学参数间的相关关系,其相关系数都达到0.96以上,呈极显著相关;分析了光谱参数—绿色深度指数(DGCI)与叶片叶绿素含量相关关系,二者表现出r=0.74以上的极显著直线相关。结果表明,利用地面覆盖度可在生长前期监控加工番茄生长量,预测生物学产量和叶面积系数;在果实膨大期预测吸氮量和经济产量。利用光谱参数DGCI可监测加工番茄叶片叶绿素含量。本结果可快速准确监测加工番茄生长发育,为加工番茄生产提供科学依据。

Tomato canopy and background pixel was identified by image processing software with CCD digital camera as a sensor. Percent ground cover of vegetation （PGCV） and tomato biological parameters were adopted for regression analysis. Empirical statistical showed that there was a significant correlation between these two parameters （r = 0.96）. The results of regression analysis showed that the optical parameters （Dark Green Color Index, DGCI） significantly linear correlated to tomato leaves＇ chlorophyll concentration （r = 0.74）. The results also indicated that image analysis is a promising method for monitoring growth rate of tomato at the prophase. The PGCV is a reliable indicator which can be used to evaluate both the biomass and the leaf area index （LAI） of tomato plant throughout the whole growth seasons. DGCI can be used to estimate the chlorophyll concentration in tomato＇s leaves. Therefore, color analysis provided a potential way for monitoring growth of tomato rapidly and accurately.