Data Science is a newly emerging interdisciplinary science which is impacting almost all the global business sectors. The application of data science offers a huge potential in the field of agriculture as well. The more the farmers can understand and see what is happening in the fields, the more they are able to make the right as well as strategic choices, both as a business owner and in making better use of land resources.

Digital technology helps farmers to collect various information from the field. It can also enable them to closely monitor each piece of land so that they can precisely determine what is needed for a particular crop to thrive, while at the same time enabling them to avoid or reduce the resources which are not essential for the crop. Farmers can use data science to determine how much fertilizer, water, and other inputs are needed to harvest the best crop. It can also help them to decide how much seeds to be planted in order to get maximum seed performance.

Inter-disciplinary Field

Agricultural science is a complex field which merges together many disciplines. Fundamentals of biology, chemistry, mathematics, physics, statistics, business management, and economics are being used here. Just like in any other industry, the role of an agriculture data scientist is very complex and responsible and requires experts with versatile skill sets. Aspiring data scientists in the field of agriculture need an exposure to plant biotechnology, plant science, animal science, and soil science in order to make an impact and so that they can make sense out of the sets of unstructured data from various resources.

Currently, interactions with farmers prove that they are ready for any technology which can help in improving farm economics. Now they need to be educated regarding the possible risk mitigation and other potential upsides of data science technologies. Farmers are open to accepting new technology, in general. Agricultural ‘data is currently a precious commodity in the global agricultural market and it can impact agriculture in different ways.

Helps to Control of Food inflation

The usual cause of the unpredictable and sudden sharp increase in food inflation is a lack of timely supply. Even though demand patterns are more or less predictable, the challenge is to estimate supply in the food category. Perishable crops usually have price volatility, which is a major setback for farmers. Timely availability of data for sowing, harvest, and production is the only solution for this.

Helps to Reduce wastage of farm produce

Major loss in agriculture comes from wastage of produce, the reasons of which can be lack of proper storage, handling, and planning. If factors which cause wastage can be monitored using remote sensors or devices during storage and transportation, that will be one way to solve the problem. Data science technology can be used to alert farmers if supply is much more than current market demand. Thus stocks can be retained or sowing can be controlled to reduce criminal wastage of crops, which is a boon for farmers.