The global artificial intelligence (AI) in agriculture market size is expected to be worth USD 2.6 billion by 2025 according to a report by Markets and Markets.  Agriculture is a major industry and plays a pivotal role in the economy of nations.  Population growth and climate changes have impelled the $5 trillion industry to look for sustainable and innovative solutions to improve growth.  AI has emerged as the industry’s technology arm

Agriculture is one of the most important professions for humanity. Irrespective of how the other sectors have grown, the demand for food has only increased. So, why not combine AI technology with agriculture and support both the sectors?  The rapid population growth and high demand for food combined with the scarcity of land certainly call for an efficient and effective method of farming to ensure better sustainability.

There are several terabytes of data from farms.  With the help of AI technologies and the Internet of Things, farmers can analyze real-time data on weather conditions, soil, temperature, and so on.  AI technologies also help in optimizing planning and utilization.  Farmer’s Weekly Magazine states that the use of AI-powered equipment based on the computer vision technology increases crop yields by about 30% and enables to predict weekly and seasonal crop yields with more than 90% accuracy.

The quality of crops can also be improved by identifying infected plants. Improving harvest quality and accuracy using AI systems, known as Precision agriculture technology, has been known to detect crop disease and pest damage with 98% accuracy with the help of GPS(  Global positioning system) and GIS (geographic information system) Guidance systems.  AI sensors can detect and target weeds and then decide which herbicides to apply. This not only reduces cost but also prevents excessive toxins that find their way in our food.  VRT (variable-rate technology) is automatic and can be used for a variety of farming activities. It sets the delivery of inputs depending on the soil condition noted by soil maps. Also, Rate controllers are used to control the delivery rate of a chemical (liquid/granular). These control speed, flow rate, and pressure of material in real-time.

Digital Soil mapping is a geographic representation showing the diversity of soil types in the interested area. It helps one determine what land use management will be sustainable at a particular site. These can estimate weather, soil conditions, temperature, and water usage to make better decisions. Farming can be made more cost-efficient by ensuring only the required inputs are used.

A yield map can be used to compare yield distribution within the field over a period of time. This allows farmers to know which area of the field needs improvement. With this, they can change their field management technique and develop nutrient strategies too. These yield records can support as proof to avail farmer loans.

Though all of this seems like a farfetched idea in a developing country, it has experimented. Large scale farmers use machinery for areas as large as 30 meters. However, the precision application of fertilizers and pesticides can be done in an area of 5-10 meters. Hence it will be only a one-time investment in the technology with better yields in subsequent times.