TY - JOUR
T1 - Artificial intelligence for fostering sustainable agriculture
AU - Kusumavathi, Konathala
AU - Konatala, Ramesh
AU - Lal, Priyanka
AU - Sarkar, Smritikana
AU - Banerjee, Hirak
AU - Bandopadhyay, Pintoo
AU - Sethi, Debadatta
AU - Upendar, Konga
PY - 2025
Y1 - 2025
N2 - Agriculture intensification has a paradoxical effect, as it increases food production and productivity by increasing farmer's return on investment while instantaneously posing a serious threat to long-term sustainability like depletion of resources, soil degradation, water scarcity and finally environmental pollution. All these challenges have flickered concerns about the quality of life. To bash all these concerns, the precise and judicious use of agricultural inputs is necessary. Bespoke solutions (Site-Specific) tailored to specific problems can optimize resource utilization while minimizing negative impacts. Integrating advanced technologies like automation by the use of sensors, drones and robotics guarantees solutions in the context of availability and efficiency of agricultural labour decline. This technology-driven approach can reform agriculture. So, the holistic approach of using technological advancements with sustainable practices is necessary for a long-term ecological balance with enhancement in productivity. The integration of driven solutions allows farmers to obtain real-time insights into soil health, water availability and nutrient status facilitating sustainable farming practices. The main goal of this manuscript is to review the applications of AI in agriculture for crop monitoring with sustainable use of resources such as soil, water, and nutrients, as well as to elevate food production with better quality maintenance. This article scrutinizes the findings of several researchers to get a brief outline of the subject of the recent execution of automation in agriculture and compares it with conventional methods followed by the farmer.
AB - Agriculture intensification has a paradoxical effect, as it increases food production and productivity by increasing farmer's return on investment while instantaneously posing a serious threat to long-term sustainability like depletion of resources, soil degradation, water scarcity and finally environmental pollution. All these challenges have flickered concerns about the quality of life. To bash all these concerns, the precise and judicious use of agricultural inputs is necessary. Bespoke solutions (Site-Specific) tailored to specific problems can optimize resource utilization while minimizing negative impacts. Integrating advanced technologies like automation by the use of sensors, drones and robotics guarantees solutions in the context of availability and efficiency of agricultural labour decline. This technology-driven approach can reform agriculture. So, the holistic approach of using technological advancements with sustainable practices is necessary for a long-term ecological balance with enhancement in productivity. The integration of driven solutions allows farmers to obtain real-time insights into soil health, water availability and nutrient status facilitating sustainable farming practices. The main goal of this manuscript is to review the applications of AI in agriculture for crop monitoring with sustainable use of resources such as soil, water, and nutrients, as well as to elevate food production with better quality maintenance. This article scrutinizes the findings of several researchers to get a brief outline of the subject of the recent execution of automation in agriculture and compares it with conventional methods followed by the farmer.
KW - Artificial intelligence
KW - Drones
KW - Robots
KW - Sensors
KW - Sustainable agriculture
UR - http://www.scopus.com/inward/record.url?scp=105001026095&partnerID=8YFLogxK
U2 - 10.1016/j.cpb.2025.100476
DO - 10.1016/j.cpb.2025.100476
M3 - Review article
AN - SCOPUS:105001026095
SN - 2214-6628
VL - 42
JO - Current Plant Biology
JF - Current Plant Biology
M1 - 100476
ER -