AgTech Adoption for Irrigation Systems: A Review

Agriculture is the backbone of our country's economy, and irrigation is the major phase of agriculture throughout the crop life cycle and crop production. Many scientists and scholars are breaking their necks to hatch legitimate solutions in contemplation of enhancing the efficiency of water used for irrigation. This could be achieved using various AgTech adoption strategies. As per an estimate, around 70 percent of the freshwater on earth is consumed specifically for irrigation purposes. To reinforce the efficiency of freshwater management and slash water wastage in the act of irrigation, further advancements are being made in this field. It takes into consideration several environmental parameters, most commonly humidity, temperature, and soil moisture, thereby impacting crop production and water management simultaneously. The present paper reviews much of this research that incorporates the use of various IoT devices, such as microcontrollers, microprocessors, actuators, etc., together as a system for optimizing water requirements and usage. But deploying sensors in the field and collecting data takes considerable time, cost, and effort. To agree upon that, the paper has proposed the use of evapotranspiration as a parameter to measure water loss from crop fields. To calculate evapotranspiration using weather parameters, it is suggested to use the FAO 56 Penman-Monteith equation (PME). PME is considered a standard empirical method for the calculation of reference evapotranspiration. This method can further be used to measure the crop water requirements based on the crop coefficient of any particular crop. Also, machine learning and deep learning (ML/DL) models can be used for the predictive analysis of evapotranspiration. Thus, empirical as well as DL/ML models can replace the IoT-based models, or they can reduce the cost of existing IoT models by working simultaneously.