Estimated reading time: 2 minutes, 45 seconds

Since time immemorial, farmers across the world have depended mainly on rain-fed agriculture in their activities. This has significantly affected production due to climate change and unpredictable environmental or weather patterns. Consequently, the sector which was the backbone of many countries has continually experienced dwindling fortunes not only for the farmers but also for the economies which depended on agriculture as the main contributor to the GDP. Technology is beginning to offer solutions to many problems that have haunted the agriculture sector.

Big data is addressing various problems facing farming and agriculture at large. For instance, farmers now depend on cloud and big data technologies for information which will offer insights that can make a huge difference on how farmers carry out their activities. With the availability of reliable well-analyzed information, farmers can access huge volumes of data for accurate decision making. The emergence of big data tools and platforms such as that created by CGAR allows farmers to solve complex problems regardless of where they are in the world. Small farmers in the developing world, where agriculture is the primary source of income and livelihood are benefiting from this technology as well. These countries have for long been left behind and are facing massive challenges from climate change. The entry of big data and its associated technologies is transforming not only how research is being done but also how farming is carried out.

Big data is speeding up the process of collection and analysis of trends. These trends are enhanced by the availability of satellite imaging data, cheap remote sensors, mobile phones, and distributed computer networks. The availability of mobile phones in almost every household and their use in different areas such as education, business, and other areas has made access to information easy. Capitalizing on the availability of these devices and networks, researchers can share data with farmers or receive crucial information from farmers that increase accuracy and offer guidance to scientific research activities.

With machine learning and mathematical models used in the analysis of big data, prediction of various aspects such as yield, chemicals, biomass index, and weather has become easier and more accurate. These statistics ease decision making. For instance, the prediction of yields allows a farmer to extract knowledge concerning what, when and where to plant. With the use of sensors, less manual effort is needed to gather data that can be analyzed and used as critical decision making information which will guarantee better farm returns and profits in the long run. Through Advanced Weather Information System, spatial information can be accessed, and farmers given feedback that can enable them to make informed choices.

With big data, problems that show up in the supply chain are reduced. The technology allows oversight with regard to the harvesting of crops each season and eases the interaction between the farmer, retailers, packagers, suppliers and other players in the industry. The data shared among these individuals can help them prepare their processes well which reduces waste and increases accuracy.

Summing it up, big data in agriculture is working towards increasing opportunities and enhancing the tools that can help farmers prosper in their operations around the world. By offering empowerment through access to information, the right kind of animals can be kept and the correct plant grown which reduces risk and enhances profit.

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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief


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