First Steps Towards The Realization Of Optical Sensors To Characterize Spray Deposits Of Pesticides On The Leaves Of Vine Plants

2017 19TH INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS (ICTON)(2017)

引用 0|浏览5
暂无评分
摘要
The reduction of inputs is a strategic stake for the wine industry, the main consumer of plant protection products. The development of research / experimentation and technical transfer on this topic over the past few years reflect this ambition shared by all actors. If efforts are mainly based on finding alternative products or developing decision support tools (DAOs) to reduce doses of applied products, optimizing the quality of spraying is also an important lever and can be directly mobilized by the winegrowers. The “spray deposit” is an indicator that reveals the dose received locally by the various organs of the plant that the treatment aims to protect. Thus, the “spray deposition” measure provides valuable information for optimizing the use of inputs. At present, the measurement of this surface quantity (surface covered, size of drops) is based on a constraining and tedious implementation based on artificial collectors. This operation requires to install and then retrieve all the collectors (more than a hundred in general) completely manually. Then, the analyzes are done in laboratory, which mobilizes time, manpower and consumables. Thus, automation of this measure would make it possible to acquire more references mobilizable by the manufacturers of sprayers to optimize their machines and the farmers themselves with a view to defining more precisely the optimal dose to be used thus causing a reduction in the use of plant protection products. In this context, our objective would be to develop optical sensors to characterize the quantity and distribution of a liquid spray. These optical sensors will have waveguides as basic bricks: the idea will be to analyze the impact of a liquid spray on the surface of the guides on their light guiding properties.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要