1Tribal Research cum Training Centre, Anand Agricultural University, Devgadhbaria, Gujarat, India

2Regional Research Station, Anand Agricultural University, Anand, Gujarat, India

3SMC Polytechnic in Agriculture, Anand Agricultural University, Anand, Gujarat, India

DOI : https://doi.org/10.21276/AATCCReview.2024.12.04.379

Keywords

depletion of available soil moisture (DASM), ET controller, iIntelligent strategies, Irrigation scheduling, rain sensor, soil moisture content (SMC), soil moisture sensor (SMS), Water saving

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Abstract

Agriculture being highest water consumer is responsible for two third of total withdrawals. The inspiration for this review study originated from developing countries particularly India where agriculture and climate conditions are crucial to the economy. In many parts of the India, irrigation water has been over-exploited, while freshwater shortage is becoming critical in the arid and semiarid areas. Profitability in production farming is dependent on making the proper and timely operational choice based on current conditions and previous records. Appropriate irrigation water management has gotten a lot of attention since it is critical to ensuring global water and food security. A smart irrigation system is used to make better use of water in agricultural fields and to increase crop productivity. As a result, the high demand forwater resources is lessened, as are the negative environmental effects of irrigation. Various irrigation systems have been developed to reduce over-irrigation by evaluating soil moisture content or crop water stress index. The purpose of this study is to examine smart irrigation technologies and describe how they affect water savings, production, and crop quality. According to an examination of important studies, the water consumption efficiency based on soil moisture sensors is dependent on the volumetric moisture content threshold value chosen by farmers. Soil moisture sensor controllers, evapotranspiration controllers, and rain sensors have all been found to save 40%-50%, 30%-40%, and 7%-26% of water while preserving crop growth and quality, respectively. The IoT-based approach outperformed on-site measurements in terms of assessing crop and soil variability in the field.

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