The Impact Of Big Data In Agriculture

Technological revolution that is currently happening in the agricultural sector became possible, among other things, due to big data. Collecting and analyzing big data can not only improve the productivity of individual farms but also help halt a global food crisis.

The significance of this lies in the growing need to produce more food while using less land for it. To reach this goal, policymakers and industry leaders seek assistance from technological innovations, including big data, IoT, analytics, and cloud computing.

Big Data in the Modern World

It's hard to imagine the modern world without data. More and more data is produced and used worldwide. But for the successful operation of an agricultural business, having an opportunity for big data analysis and management is key.

Agribusinesses are becoming larger and more diverse, which results in the growing volumes of complex data that has to be managed constantly. This includes external data from social media, supplier network channels, and sensor / machine data from the field. This leads to the agricultural sphere transformation, opening new opportunities.

Practical Application of Big Data in Agriculture

Ultimately, smart farming and precision agriculture practices help farmers to save costs and open new business opportunities. Here are the main possibilities that come with big data use in agribusinesses.

Meeting the food demand

The best way to satisfy the growing food demand without using more land and resources is to use the already existing farmland more efficiently with the purpose to increase yields. But how does big data help with that? Most importantly, it provides farmers with information on changes in weather, rainfall, soil moisture and other factors that affect crop yield. With all this data, the growers are able to make accurate and reliable decisions, ultimately improving farm yields.

Pesticides use optimization

Pesticides use is considered an issue due to its side effects on the ecosystem. Big data offers opportunities for smart and precise pesticides application, helping the farmer to easily make decisions on what pesticide to apply, when, and where.Such monitoring helps food producers to avoid the overuse of chemicals. Besides, it increases farmers' profits by cutting costs on unnecessary pesticides use.

Farm equipment management

Remote management of agricultural machinery helps large farms reduce costs. Thanks to big data applications that can process and analyze streams of data retrieved by a variety of sensors, ranging from satellites to farming equipment, farmers can remotely track their machinery in the field. This way they can eliminate all the unnecessary routes, considerably lowering spendings on fuel.  

Supply chain problems management

Big data makes it possible to achieve supply chain efficiency by offering tracking and optimization opportunities for delivery truck routes. As a result, food delivery cycles, from producer to the market, become much shorter, ensuring no food is wasted in the process. 

Yield prediction 

Yield prediction implies the use of technology and different algorithms to analyse information on weather, chemicals, vegetation, and more, with the aim of improving decision-making by growers. Different technologies help farmers to easily decide on where and when to plant seeds, how to space them, when to water, apply chemicals, and when to harvest. This significantly reduces the need for manual work thanks to remote and precise field management, with all the collected information available online.

Food safety

Food-related illnesses and diseases affect millions of people every year. And one of the tasks of modern farming is to enable instant detection of microbes and signs of contamination. This can be done by collecting data on temperature, humidity, and chemicals to assess the health of a growing plant.

So how do farmers "harvest" all these benefits offered by big data? The easiest way to receive access to previously analyzed information collected from the farm is via different online tools. They retrieve data from multiple sources, such as satellite imagery and ground sensors, often processing it on the fly. One of such tools, capable of processing and analyzing myriads of data in a very short time, is Crop Monitoring by EOS. The platform successfully leverages satellite imagery, applying a number of algorithms to visualize desired data about the field on one screen. The tool provides the following features among others:

• Field monitoring based on vegetation indices for tracking changes in vegetation health throughout the growing season

• Weather data (current, historical, and 14-day forecast)

• Field zoning to easily identify field's most productive areas and use the VRA methods to increase growth efficiency

• Field leaderboard to see fields sorted out by NDVI measurements of crop health

• Field activity log to easily track different activities performed on all fields and improve planning of future activities

• Remote scouting management, based on reliable information, to save time and effort

According to the study conducted by the Food and Agriculture Organization of the United Nations (FAO), approximately 1/3 of the food produced for human consumption is wasted or lost every year. However, the use of big data is revolutionizing agricultural practices, providing new opportunities to help harmers in battling this food crisis.