关键词: 农药, 在线混合, 图像处理, 混合均匀性

Abstract: Pesticide spraying is an effective way to control pest damage and increase crop yields. Because of the behindhand pesticide spraying technology, the problems of pesticides wast and environmental pollution are getting worse and worse. In order to improve the use efficiency of pesticide, it is worthwhile to study the mixing uniformity of pesticide online. Because there were remarkable differences between water and pesticides containing fluorescent substance, image processing technology was adopted to analyze the uniformity of pesticide on-line-mixing. In this study, an online mixed image collection system for pesticides was set up. The image with maximum percentage of pesticides area in the ROI (region of interest) was chosen after subtraction preprocessing of all acquired images, then the axial and radial pixel analysis method and RMSE statistic were used to quantify the uniformity index. Additionally, the data analysis software was written by Matlab, and the mixing uniformity of 3 different kinds of pesticide were analyzed. The RMSE percentage （β） of water-soluble pesticides was 13.389%, which was higher than 9.280% of emulsified pesticides and 9.996% of liposoluble pesticides, indicating that the mixing uniformity of water-soluble pesticides was better than that of emulsified and liposoluble pesticides. Experiments on 7 groups with finit concentration but different quantity of flow were carried out data processing on liposoluble pesticide images. When the flow rate decreased from 1 390 mL/min to 880 mL/min, the RMSE percentage dropped from 11.029% to 8.737%, and uniformity became worse gradually. The results revealed that image processing technology was feasible for analyzing uniformity of pesticide on-line-mixing. It could be easily and intuitively adopted to analyze the influence of chemical mixer structure and performance parameters on mixing effect, thus laying a foundation for pesticide on-line-mixing image processing, and quantitative analysis of pesticide on-line-mixing effect.

Key words: pesticide, in-line-mixing, image processing, mixing uniformity