“Big data” often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and not just to a particular size of data set.  Data tools can help determine changes required to maintain yields and meet food demands

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Potential of Big Data in agriculture:

• The availability of data is on the grow because they are increasingly gathered by cheap and numerous information-sensing mobile devices, aerial (remote sensing), software logs, cameras, microphones, radio-frequency identification (RFID) readers and wireless sensor networks.
• In agriculture, big data is often viewed as a combination of technology and analytics that can collect and compile novel data and process it in a more useful and timely way to assist decision making.
• Real-time insights to help performance optimisation advance analytics can show how farmers are utilising their inputs and what adaptations are required to take account of emerging weather events or disease outbreaks.
• For instance, if Black Grass becomes problematic in a given region, suppliers can deploy big data techniques such as real-time micro-segmentation of customers to target promotional and marketing activities, thus facilitating better utilisation of marketing spends.
• Benefits include faster unearthing of valuable insights and the ability to develop and adapt products that meet specific customer needs on an ongoing basis.
• In this range, we can encounter autonomous vehicle devices farmers place in the ground to measure soil moisture and nutrient, predictive weather stations and image-capturing satellites and drones mapping out land and measuring crop health.
• These insights are extremely important since they tell the farmer when and how much to irrigate a field, crop health, weather predictions, pest infestations and even drought conditions.
• Considering the increasing labour shortages in the sector the capacity for big data analysis that lessens the need for physical manpower is of great advantage for agriculture.

Role of Big data in Agriculture:

• Development of new seed traits: Access to the plant genome with new ways to measure, map and drive information betters products.
• Seed Selection: Big-data businesses can analyse varieties of seeds across numerous fields, soil types, and climates and select the best.
• Crop disease: Similar to the way in which Google can identify flu outbreaks based on where web searches are originating, analysing crops across farms helps identify diseases that could ruin a potential harvest.
• Irrigation: Precision agriculture aids farmers in tailored and effective water management, helping in production, improving economic efficiency and minimising waste and environmental impact.
• Weather: Advanced analytics capabilities and agri-robotics such as aerial imagery, sensors help provide sophisticated local weather forecasts can help increasing global agricultural productivity over the next few decades.
• Climate change: Since, climate change and extreme weather events will demand proactive measures to adapt or develop resiliency, Big Data can bring in the right information to take informed decisions.
• Food tracking: Use of sensors and analytics to prevent spoilage and food-borne illnesses
• Food processing: They help in streamlining food processing value chains by finding the core determinants of process performance, and taking action to continually improve the accuracy, quality and yield of production. They also optimise production schedules based on supplier, customer, machine availability and cost constraints.
• Effect on supply chains: Seismic shifts in the supply chain of seed, crop inputs and food driven by the democratisation of technology and information
• Loss control: In India, every year 21 million tons of wheat is lost, primarily due to scare cold-storage centres and refrigerated vehicles, poor transportation facilities and unreliable electricity supply. Big Data has the potential of systematisation of demand forecasting thus reducing such losses.
• Pricing: A trading platform for agricultural commodities that links small-scale producers to retailers and bulk purchasers via mobile phone messaging can help send up-to-date market prices via an app or SMS and connect farmers with buyers, offering collective bargaining opportunities for small and marginal farmers.

Conclusion:

The big data revolution is in its early days and most of the potential for value creation is still unclaimed. But it has set the industry on a path of rapid change and new discoveries. Stakeholders committed to innovation will likely be the first to reap rewards. If the farmers would have been concerned about the infirmities in terms of data-based farming, production could be increased.