P. Vandôme, S. Moinard, G. Brunel, B. Tisseyre, C. Leauthaud, G. Belaud
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引用次数: 0
Abstract
This study presents the development and the evaluation of a low-cost sensor-based system to optimize the management of surface irrigation at the field level. During a surface irrigation event, water flows according to the slope of the field and it is difficult and time-consuming to predict the optimal time when inflow should be stopped. In such systems, measurement tools are uncommon and those existing are far too complex and expensive to be used as decision support tools on small farms. This article presents the development of an Open Source system, based on low-cost technologies, Internet of Things and LoRaWAN network, that allows: (i) detection of water at the sensor location in the field, (ii) sending an alert by phone to the user and (iii) remote control of surface irrigation gates. The metrological characteristics of the system and its suitability were tested in real conditions during one irrigation season of hay fields in the Mediterranean region. The results highlighted the reliability of the low-cost sensor system for detecting water and transmitting information remotely, with a 100% success rate. Remote control of irrigation gates was successful in 89% of trials carried out in the field, and adjustments resulted in a 100% success rate. The savings in labour time for the farmer and in irrigation water volumes made possible by the use of this system, as well as the inevitable trade-offs between accessibility, reliability and robustness of new technologies for agriculture, are finally discussed.
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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