Data Science Applications in Agriculture
Big Data and Data Science have already caused waves in all industries from IT to healthcare. Agriculture is another field where this revolutionary technology is being used in order to provide a betterment to the lives of struggling farmers.
Agriculture is the most vital sector in every country, but it lacks support from banks in terms of farmer welfare schemes and loans and in institutional attention. Those involved in the field receive very little support and have to face lots of disasters like climate change, floods, droughts, unfair policies in price fixing, etc. With more and more new problems coming up every year, it is high time that we resort to evolving technologies for solutions.
A breakthrough application of technology and science newly applied in the field of agriculture is called Smart farming. It is a network of complementing and interdisciplinary facilities and technologies. Technologies like Big Data, Internet of Things, Machine learning, Cloud computing, and analytics are applied to the agricultural field so as to enable farmers to gain more insights on the results of their actions and take better and learned decisions on the practices involved in farming.
The advantage of smart farming is not just limited to improving farming practices. The application of Data Science technologies has a significant impact in giving projective insights on farming operations and practices, as well as in helping to redesign business models, and in delivering real-time decisions, thus having a significant bearing on the entire supply chain. Data Analytics provides tremendous opportunity to significantly improve the initial cost to produce an output ratio, optimize or reduce input usage, improve product yield, offer timely advice for necessary actions, and more.
Improvements in Farming
Satellite-based monitoring, embedded sensors on fields and crops, fertilizer requirement reports, wind direction predictions, pest warnings, water cycles, tractors which are GPS -enabled, and many more facilities act as a rich data source for improvement in better agricultural methods. Monitoring and supervision for nutrient requirements and growth rates on per plant basis is also enabled by application of data science technologies. It also enables farmers to decide which crop to plant for the next harvest based on the available data like information on water availability, soil health, monsoon predictions etc.
Advantages in Marketing
Now that consumers are keen to know the source of food and how it is produced and processed and packaged, there is a need for transparency in the supply chain of the entire agricultural business. The technologies which provide efficient and strategic farming solutions also include usage of the app-based data extraction and generation, storage of data on the cloud, machine learning, real-time visualization of data, satellite monitoring, and so on.
The use of these technologies enables production forecast, output predictability, risk management, quality maximization, and increased sustainability to agriculture companies, financial institutions, and banks, insurance companies, seed manufacturing companies, farming enterprises, government bodies etc. Advice can be issued to farmers if supply is more than demand or even vice versa. This can help control food inflation to a great extent.