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Data science and the future of agriculture technologies

The rise of the data science courses has enabled data professionals to apply to new industries. Software companies that use data science applications have been growing at a very staggering rate. Agriculture is one of the software assisted industries that are witnessing digital farming development. Due to the rapid changes in the data science domains, it is worth knowing how data analysts and data scientists could be transforming the future of agriculture. More than 50 million farmers, big and small and some contractual, are employed in India, and their families are directly dependent on the returns from the cropping season. Despite mechanization and modernization of the farming world, agriculture continues to sit at the bottom of the rung as far as the use of data science is concerned. With so much scope available in the agrarian world, as demonstrated by the research done by data science academicians, things have been rather slow to move so far. But, as recent trends show, things could change very quickly in the next 4-5 years as farmers are adopting smart farming methods powered by data science and AI to meet the new norms of sustainability and continuity in the food industry.

Here are the top data science driven segments where agriculture technology professionals could be acquiring a lot of winning points.

Digital Farming

Farming is one of the world’s oldest occupations. With time, things have changed. Data science is enabling farmers to integrate newer data science and software supported technologies. 

For instance, digital farming or precision farming is a set of farming related activities that help farmers to plan their cropping methodologies. It uses technology built on data science and AI to gather information on soil, crop quality, pre-harvesting requirements, financial aids required, and marketing and supply chain management. Digital farming activities kind of activates all the major benefits of using data science in a conventional high inventory industry, and this could solve the major problems linked to droughts, food wastage, poor incentivization, and so on.

Fire control

Agriculture burning techniques are wreaking havoc around the world. Farmers in some parts of the world still burn their crop harvests and wastages once the product is supplied to the markets for retail or domestic consumption. Fire burning not only causes CO2 emissions that contribute more to the global warming but also inflicts damage at the mammoth levels on the livestock. Data scientists are using different AI and machine learning algorithms to detect and control agricultural fires. These include the use of clustering and data visualization techniques to demonstrate the role of data science in modernizing the agriculture occupation. 

Predictive Intelligence             

Weather conditions, soil change, pest attacks, natural calamities, and forest fires are some of the biggest reasons that govern the outcome of a farming practice. Billions of dollars are lost to uncertainties. Even the most fertile of lands and good harvest can’t assure a good return to farmers tilling the land. Reason; the outcomes are way too uncertain and we saw how the COVID situation aggravated the troubles for every farmer. Today, computer data is used to analyze how agriculture practices could be improved and conditioned based on weather forecasts. In-field sensors, historical data, and AI based weather forecasting algorithms are used to protect the crop from getting damaged. Predictive intelligence in farming is a big opportunity for data scientists and analysts certified in Python and R programming. These platforms are used to build real time predictive analytics tools that address the needs and demands of every farmer, expecting a profitable return and security from investing in a reliable AI based technology.

AI based consulting

AI could invariably help solve the global food problem by bringing zero carbon farming and financial planning together.

Farmers take loans to buy seeds and equipment required for cropping. As we already mentioned how farming remains an uncertain territory due to many factors, farmers often take big risks by acquiring loans. But, thanks to new age financial services tools and the power of fintech solutions that specifically focus on digitization of loans, user experience management, and rewards systems, farmers could enjoy the benefits of having an AI consultant supporting them on financial decisions pertaining to cropping and marketing. For example, AI systems could be used to measure the percentage of crop feed and fiber and thus reduce wastage. Also, it could be used to control food inventories and supply to retail markets which then would be used to feed impoverished regions of the world.

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