AUTOMATION, SENSOR TECHNOLOGY AND GENOMIC TOOLS FOR IMPROVING NUTRIENT- AND WATER-USE EFFICIENCY IN CROPS: A REVIEW

Abstract

Enhancing nutrient and water use efficiency is critical to ensuring sustainable crop production amidst growing climate variability, loss of soil fertility, water scarcity, and high input costs of farming. Traditional agriculture usually involves blanket fertilization and irrigation practices that may lead to inefficient nutrient utilization, water utilization, pollution, and reduced yields. Modern developments in automation, sensing, and genomics technologies present possibilities to improve resource utilization through precision farming practices and creation of resource-efficient crops. Automation technologies include variable-rate fertilizers application, automatic irrigation, robotic technology, and artificial intelligence (AI) decision-making support tools that allow for timely and location-specific crop management. The sensing technologies include soil moisture sensors, canopy temperature sensors, chlorophyll sensors, multispectral imaging, remote sensing, and Internet of things (IoT). Alongside this, genomics techniques, which include QTL mapping, GWAS, marker assisted selection, genomic selection, and genome editing using CRISPR-Cas technology aid in the detection and enhancement of traits related to nutrient and water uptake, root physiology, stomata control, and stress tolerance. The integration of these techniques can aid in linking field-based observations with automated decision-making and genetic improvement techniques. However, the use of these techniques is hindered by high costs of initial investments, low digital infrastructure, issues related to interoperable data collection, required skills, and gene-by-environment interactions. This review highlights the principles, applications, opportunities, and limitations of automation, sensors, and genomics technologies for improving nutrient and water use efficiency in crops.