How big data can boost agricultural growth

August 2, 2019

Data tools can help determine changes required to maintain yields and meet food demands.

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.

 

Data mining is the computing process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning statistics and database system.

 

Precision agriculture’s main objective is to ensure profitability, efficiency, and sustainability using the big data gathered to guide both immediate and future decision-making. This could cover everything — from when it is best to apply fertilisers, chemical and seeds, to where in the field it is best to apply a rate.

 

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.

 

To achieve this, advanced algorithms are needed to swiftly unlock the highly valuable insights for products to perform well on an ongoing basis despite changing conditions. The development of highly-specific customer segmentation set has become possible to tailor product offerings to meet customer needs.

 

Benefits include faster unearthing of valuable insights and the ability to develop and adapt products that meet specific customer needs on an ongoing basis.

 

Robots can play an important role in control, but it can be expected that the role of humans in analysis and planning is increasingly assisted by machines so that the cyber physical cycle becomes almost autonomous.

 

Autonomous vehicle devices placed in the ground can measure soil moisture and nutrients, while predictive weather stations and image-capturing drones can map out land and measure 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.

 

Information is power, and the industry can now have access to it for more informed decision making. These are the ways in which data analysis can help:

 

  • Development of new seed traits - Access to the plant genome with new ways to measure, map and drive information betters products.

  • Precision farming - Big data takes advantage of information derived through precision farming in aggregate over many farms. The resulting analytics, insights and better decisions can then be deployed through precision farming techniques

  • Food tracking - Use of sensors and analytics to prevent spoilage and food-borne illnesses

  • Effect on supply chains - Seismic shifts in the supply chain of seed, crop inputs and food driven by the democratisation of technology and information

 

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.

 

Source: Down To Earth

 

 

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