Big Data in agriculture: Can it prove to be a shot in the arm ​of dwindling farm growth?

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Have you ever wondered why agriculture is being thought of as a low profitability venture? After the green revolution, what would be the next precursor for increasing agriculture productivity? Further, how can we increase small farmers’ income? Nevertheless, With the advent of technology, we seem to have found an answer in terms of ‘Big data’.

Gone are the days when agriculture was considered a layman’s job. Nowadays, it is being realized that the business of agriculture production and management is as complex as tech-based companies. The primary reason for the complex nature of agriculture is associated with the involvement of too many independent parameters such as weather, pest infestation, resource availability and best resource combinations. The world is now thinking of developing ways to make accurate predictions of these independent parameters and use them as a tool for future agriculture.

What is Big Data?

Features of big data
This picture depicts the different components of big data.

The term “big data” is the latest tech buzzword and its exact definition is still foggy. However,  it is generally referred to as an enormous amount of data about something that can be studied and analyzed to evaluate current trends and patterns. Also, we can analyze it to make predictions for futures. Primarily, this type of data generally can be explained by the five characteristics:

  1. Volume: The amount of data to be stored and analyzed is enormous and require special considerations.
  2. Variety: It includes various types of data potentially from different sources.
  3. Velocity: The new data is produced at high rates and operating on ‘stale’ data is not valuable.
  4. Value: The data has perceived and quantifiable benefit to the individual, enterprise or organization using it.
  5. Veracity: It means that reliability and correctness of the data can be assessed and tested.

Scope of big data in agriculture

In the recent past, there has been a significant trend to consider the use of large dataset techniques and methods to agriculture. Its applications in farming are not strictly about primary production, but also have a significant role in enhancing the efficiency and sustainability of effectiveness of the entire supply chain and alleviating food security concerns.

Opportunities for applications big data in agriculture include:

  1. Sensor deployment
  2. Input prediction models
  3. Yield prediction models
  4. An accurate weather prediction model
  5. Drive real-time operational decisions

Currently, large data or cloud-based applications are being applied primarily in Europe and North America however, however, the number of applications is expected to increase in other countries like China, India, and Brazil.

How can big data revolutionize agriculture?

Its impact on our society and businesses is often depicted through anecdotes and success stories of methods and technology implementations. The existing large data applications are many and expected to grow: hence, their systematic description constitutes a promising development area for those willing to contribute to the scientific progress in this field.

Do you think Big data application in agriculture can boost the productivity of small farmers?

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