Artificial Intelligence (AI) plays a key role in advancing sustainable agriculture by improving productivity and enhancing environmental resilience. AI enables precision farming through data-driven decisions on irrigation, fertilization, and planting. It supports early detection of pests and diseases, predicts crop yields, and optimizes water usage through smart irrigation systems. AI also powers autonomous machines, helps breed climate-resilient crops, and offers decision support tools for farmers and policymakers. Additionally, AI contributes to climate adaptation and sustainable land use planning.

Dear Simranpreet Kaur ,

By integrating historical yield data, weather patterns and remote sensing inputs, the AI models generate yield forecasts for wheat crop. These predictions help farmers plan their planting schedules, allocate resources efficiently and anticipate potential challenges.

https://journals.openedition.org/factsreports/7898#:~:text=By%20integrating%20historical%20yield%20data,efficiently%20and%20anticipate%20potential%20challenges.

Regards,

Shafagat

AI in remote Sensing promotes in advanced crop production with seasonality, improvement in weather implementation in accordance with crop

so long as the ai is monitored and set on an algorithm (eg, do this at this time in the morning and afternoon) it can be used effectively (you can use automated sprinklers as well)

I fully agree with the importance of precision agriculture used through AI. The ability to maximise, and thus optimise, the use of water, fertilisers and all other inputs not only increases agricultural productivity, but can significantly reduce the environmental impact of agriculture in general. For example, the variable application of fertilisers based on real-time soil data analysis can minimise the dispersion of nutrients in the soil and thus in the surrounding environment, which leads to an improvement in biodiversity and an increase in the quality of water resources, which are becoming increasingly scarce today especially in arid climates.

Initially, it can predict and alert the occurrence of abiotic stresses (drought, excessive rain with flooding, excessive cold with frost and also excessive heat).

It can also issue alerts about favorable conditions for the proliferation of pests and especially bacterial diseases, indicating the exact time to apply pesticides, whether preventively or curatively.

Finally, it can be an auxiliary tool in genetic, molecular and metabolomic selection for conditions that are adverse to plant productivity.