AI & farm analytics strengthen the future of food production

According to the United Nations (UN), it is expected that the world population will grow from the current about 6.9 billion to 9.7 billion by 2050. The unprecedented demand for food will grow more quickly as the incomes and standards of nutrition rise and populations move towards more land and water-intensive diets. With the increasing demand for food, food safety concerns have compelled farmers to ensure the early detection and control of crop diseases. The farmers should precisely record and analyze the varying crop parameters and make wise decisions from time to time.

AI & farm analytics revolutionize farming

Artificial Intelligence (AI) and farm analytics today have revolutionized the agriculture industry. The introduction of these technologies has the potential to turn smallholders into successful producers. By digitalizing and optimizing several farm functions, these emerging technologies can map an upward trajectory for the agriculture sector.

Climate change, crop failure possibilities, pest-attacks, and soil degradation are compelling farmers to embrace smart farming. The growing need to produce more with fewer resources also forces farmers to adopt data-driven and precision farming techniques. AI-driven farming and farm analytics can assist farmers with image-based insights, pest-risk forecasts, and weather pattern information.

Farmers can carry out data-intensive farming techniques efficiently with the aid of tech-driven approaches. AI and farm analytics can help secure producers' profit margins and better visibility to crop failure risks. AI-driven farming can assist farmers in detecting and mapping crop diseases, pests and identifying plants with poor nutrition. The apt use of fertilizers is essential to get rid of these pests and diseases. The farmers can now maintain the desired quality of their agriproducts and predict the precise requirement of fertilizer application with advanced farm analytics as their aid.

Processes of farm planning, pest detection, water conservation, and fertilizer management can be more data-driven with the integration of smart technology. The incorporation of AI and farm analytics has made it possible to increase farm productivity per area through a data-driven approach.

It is possible to constantly track the fields as well as indoor growing environments through AI. Analysis and monitoring of numerous aspects of agriculture have become a reality, thanks to image-based insights. Farmers can make crucial decisions effectively with end-to-end agricultural operations with the help of tech-driven methods that scan the farms.

Farmers can use drones along with AI for monitoring crops and in-depth analysis of field parameters. Further, implementing farm analytics on the data captured through these monitoring practices can be beneficial in determining problematic areas in real-time.

Image processing techniques used by AI-driven tools can monitor soil and identify potential defects and nutrient deficiencies in the soil. Pre-processing images of leaves can help in analyzing and detecting crop diseases precisely. Image-based insights can also help categorize the crops or fruits depending upon the different levels of their readiness.

Farm analytics and AI-based agriculture can enable farmers to gather data accurately and analyze water usage, weather conditions, and soil health. It can also help assess process requirements and allocating resources accordingly for maximum efficiency. AI and farm analytics encourage data-based farm management to provide producers with economic and fruitful outcomes.

Farm management platforms empower farmers to respond promptly and accurately to extreme weather events. Farmers can increase their yields and profits with minimum risks of crop failure with the help of weather forecast data provided by AI-driven technologies.

As opposed to making decisions based on intuition, data-driven farming boosts agricultural productivity. AI and farm analytics can help derive maximum value from the large datasets of complex farm information.

Many farmers fail to capitalize on the benefits of smart farming. Analysis of the huge database garnered for the various operations can help streamline processes and enhance agricultural productivity. Farm analytics and AI-driven farming are emerging as potential approaches that can spearhead the future of agriculture, food production, and smart farming.

Santosh Shinde is a chief operating officer and co-founder of Shivrai Technologies and FarmERP, a technology platform.