设计、实施和验证基于传感器的精确喷气式喷雾器,以改进果园中的农药施用

IF 5.4 2区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Bernat Salas, Ramón Salcedo, Francisco Garcia-Ruiz, Emilio Gil
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引用次数: 0

摘要

设计并实施了一种果园喷雾器原型,它采用变速算法,可根据树冠特征(尺寸、形状和叶片密度)实时调整喷洒量。所开发的机器能够通过使用基于树行体积的算法,结合新定义的密度系数(Df)来修改喷洒量。使用六个超声波传感器(喷雾器每侧三个)对行间作物树冠特征的变化进行电子测量。通过合并超声波传感器数据和机载全球导航卫星系统接收到的前进速度信息,利用叶面结构的这些差异来调整喷嘴的流量。一套电动阀用于调节最终喷洒的液体量。利用人工树冠进行了实验室和实地测试,以校准和选择最能描述树冠物理特性的最佳超声波传感器配置(波束宽度和信号预处理方法)。结果表明,中等波束宽度的传感器设置能最恰当地描述树木的宽度和 Df。实验喷雾器还能根据目标树木的变化自动计算施药量。总的来说,电动阀在任何时候都有足够的能力提供和控制所需的液体压力,主要是在 4.0 至 14.0 兆帕的范围内进行喷洒时。还需要对设备做进一步的改进,如设计喷雾器的现场效率测试或改进 Df 的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Design, implementation and validation of a sensor-based precise airblast sprayer to improve pesticide applications in orchards

Design, implementation and validation of a sensor-based precise airblast sprayer to improve pesticide applications in orchards

An orchard sprayer prototype running a variable-rate algorithm to adapt the spray volume to the canopy characteristics (dimensions, shape and leaf density) in real-time was designed and implemented. The developed machine was able to modify the application rate by using an algorithm based on the tree row volume, in combination with a newly coefficient defined as Density Factor (Df). Variations in the canopy characteristics along the row crop were electronically measured using six ultrasonic sensors (three per sprayer side). These differences in foliage structure were used to adjust the flow rate of the nozzles by merging the ultrasonic sensors data and the forward speed information received from the on-board GNSS. A set of motor-valves was used to regulate the final amount of sprayed liquid. Laboratory and field tests using artificial canopy were arranged to calibrate and select the optimal ultrasonic sensor configuration (width beam and signal pre-processing method) that best described the physical canopy properties. Results indicated that the sensor setup with a medium beam width offered the most appropriate characterization of trees in terms of width and Df. The experimental sprayer was also able to calculate the application rate automatically depending on changes on target trees. In general, the motor valves demonstrated adequate capability to supply and control the required liquid pressure at all times, mainly when spraying in a range between 4.0 and 14.0 MPa. Further work is required on the equipment, such as designing field efficiency tests for the sprayer or refining the accuracy of Df.

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来源期刊
Precision Agriculture
Precision Agriculture 农林科学-农业综合
CiteScore
12.30
自引率
8.10%
发文量
103
审稿时长
>24 weeks
期刊介绍: Precision Agriculture promotes the most innovative results coming from the research in the field of precision agriculture. It provides an effective forum for disseminating original and fundamental research and experience in the rapidly advancing area of precision farming. There are many topics in the field of precision agriculture; therefore, the topics that are addressed include, but are not limited to: Natural Resources Variability: Soil and landscape variability, digital elevation models, soil mapping, geostatistics, geographic information systems, microclimate, weather forecasting, remote sensing, management units, scale, etc. Managing Variability: Sampling techniques, site-specific nutrient and crop protection chemical recommendation, crop quality, tillage, seed density, seed variety, yield mapping, remote sensing, record keeping systems, data interpretation and use, crops (corn, wheat, sugar beets, potatoes, peanut, cotton, vegetables, etc.), management scale, etc. Engineering Technology: Computers, positioning systems, DGPS, machinery, tillage, planting, nutrient and crop protection implements, manure, irrigation, fertigation, yield monitor and mapping, soil physical and chemical characteristic sensors, weed/pest mapping, etc. Profitability: MEY, net returns, BMPs, optimum recommendations, crop quality, technology cost, sustainability, social impacts, marketing, cooperatives, farm scale, crop type, etc. Environment: Nutrient, crop protection chemicals, sediments, leaching, runoff, practices, field, watershed, on/off farm, artificial drainage, ground water, surface water, etc. Technology Transfer: Skill needs, education, training, outreach, methods, surveys, agri-business, producers, distance education, Internet, simulations models, decision support systems, expert systems, on-farm experimentation, partnerships, quality of rural life, etc.
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