Smart Phone Evapotranspiration-Based App for Optimal Irrigation Scheduling for Thai Crops

D. Simonet
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Abstract

Thailand is known as a top producer of many essential agricultural commodities including canary seeds, cassava, mango, mangosteen, guava, and chili pepper. Due to global warming and population growth, droughts are increasing and water is becoming scarce, which have a direct impact on agriculture. Farmers are therefore facing difficulties in supplying their crops with sufficient water due to water scarcity and the increasing irrigation cost. This situation calls for optimal use of irrigation water in agriculture, which is sufficient to avoid crop water stress and at the same time help to sustain water and reduce irrigation expenses. Methodolgy/approach: With the number of smartphone users in the world exceeding 3.5 billion, this app uses geospatial data and the Water Balance Approach to estimate the optimal irrigation cycle in the current month in Thailand using Java. Result: This app would result in significant water savings and a less costly irrigation process for both large farms and private gardens in subsistence agriculture. Conclusion: The proposed smartphone app captures the unique characteristics of the weather and soil conditions of any location in Thailand to determine the optimal average daily amount of water required to prevent crop water stress in the current month.
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基于智能手机蒸散发的应用程序为泰国作物优化灌溉调度
泰国是许多重要农产品的顶级生产国,包括金丝雀种子、木薯、芒果、山竹、番石榴和辣椒。由于全球变暖和人口增长,干旱日益严重,水资源日益匮乏,这对农业产生了直接影响。因此,由于缺水和灌溉成本的增加,农民在为作物提供足够的水方面面临困难。这种情况要求在农业中最佳地利用灌溉水,这足以避免作物缺水,同时有助于维持用水和减少灌溉费用。方法/方法:随着全球智能手机用户数量超过35亿,该应用程序使用地理空间数据和水平衡方法来估计泰国当月使用Java的最佳灌溉周期。结果:这款应用程序将为自给农业中的大型农场和私人花园带来显著的节水和成本更低的灌溉过程。结论:提出的智能手机应用程序捕捉泰国任何地点的天气和土壤条件的独特特征,以确定当月防止作物水分胁迫所需的最佳平均每日水量。
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