While sectors like healthcare and transportation have embraced technological advancements, agriculture, the backbone of our survival, has been slower to catch up. In many regions, farming remains bound by local customs and traditions. Yet, both smallholder and large-scale farms are under immense pressure to increase their output to feed the expanding global population.
Big data offers a powerful solution. By leveraging real-time data on soil health, weather conditions, and crop growth, farmers can make more informed decisions about irrigation, fertilisation, and harvesting.
In this article, we’ll explore how big data is shaping the future of farming and why it holds the key to feeding the world.
What is Big Data ?
Big Data has emerged as a transformative force across industries, and agriculture is no exception. At its core, Big Data refers to extremely large and complex data sets that traditional processing software cannot effectively manage. Bernard Marr, a prominent tech author, aptly describes it as “the digital trace we leave behind as we move through the world,” encompassing everything from web searches and credit card transactions to social media posts and GPS data from our phones.
The scale of Big Data is impressively high. Forbes reports that 90% of the world’s data has been created in the last two years alone, while IDC predicts that by 2025, the global datasphere will grow to 175 zettabytes. This exponential growth is driving a booming market, with Statista projecting the market to reach $103 billion by 2027.
Ways Big Data can Optimise Agricultural Yield
The potential impact of Big Data on global food production is significant. It has the potential to add value across the entire agricultural value chain, from precision farming to improved forecasting and risk management. Let’s take a look at some of the ways Big data can transform agriculture.
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Predictive Analytics
Predictive Analytics for Crop Management takes the guesswork out of farming by using sophisticated algorithms to forecast crop performance under various conditions. This approach allows farmers to make informed decisions about crop selection, planting times, and harvest schedules, significantly reducing the risks associated with agriculture. A report by Meticulous Research predicts that the global agricultural analytics market sise will reach $2.27 billion by 2027, growing at a CAGR (Compound Annual Growth Rate) of 17.5% from 2020 to 2027. This growth is largely driven by the increasing adoption of predictive analytics in agriculture.
A case study by IBM showed that their Watson Decision Platform for Agriculture helped farmers increase yield by up to 10% while reducing water usage by 20%. These data-driven models can even predict which crop varieties are likely to perform best in specific microclimates within a farm, allowing for hyper-localised optimisation of crop selection and management practices.
Precision Agriculture
Precision Agriculture has revolutionised farming practices by leveraging big data to optimise resource allocation and boost crop yields. This approach utilises a wealth of data sources, including soil sensors, satellite imagery, and weather stations, to provide farmers with unprecedented insights into their fields.
Precision agriculture enables farmers to do more with less – less water, less fertiliser, less herbicide – all while improving yields.” For instance, a study published in the journal “Computers and Electronics in Agriculture” found that variable-rate fertiliser application, guided by precision agriculture, can reduce fertiliser use by up to 30% while maintaining or even improving crop yields.
Pest and Diseases Management
Pest and Disease Management has been transformed by the integration of big data systems, offering farmers powerful tools to predict and prevent crop losses. These systems analyse complex patterns in weather, crop health, and pest populations to forecast potential outbreaks with remarkable accuracy.
 Dr. David Hughes, a researcher at Penn State University, emphasises the potential of this technology: “By harnessing the power of data and AI, we can detect plant diseases and pests before they become visible to the human eye. This will allow for early intervention and potentially saving millions in crop losses.” A notable example is the PlantVillage project, which uses machine learning algorithms to identify plant diseases from smartphone images with over 98% accuracy. This technology enables farmers to rapidly diagnose and respond to emerging threats, significantly reducing the risk of widespread crop damage.
Soil health management
Dr. Rattan Lal, a renowned soil scientist and World Food Prise laureate, emphasises the importance of soil health. ‘Soil is the essence of all terrestrial life, and soil life-support capacity depends on its health, quality or functionality’. Soil Health Management has been revolutionised by the application of big data analytics. It provides farmers with unprecedented insights into the complex ecosystem beneath their crops. By analysing vast amounts of information on soil composition, microbial activity, and crop management. Farmers can now implement highly targeted soil management practices.
The impact of big data on soil health management is exemplified by initiatives like the Soil Health Institute’s North American Project to Evaluate Soil Health Measurements. This project is collecting and analysing data from over 124 long-term agricultural research sites. The aim is to develop robust soil health indicators and management recommendations.Â
Market Intelligence
Market Intelligence powered by data analytics has become an indispensable tool for modern farmers, enabling them to make informed decisions about crop selection and timing of sales. This can help farmers navigate increasingly volatile global markets. For instance, during the COVID-19 pandemic, farmers using data-driven market intelligence platforms were better able to adapt to rapid shifts in demand and supply chains. This demonstrates how big data is not only optimising day-to-day decisions but also enhancing the resilience of agricultural businesses in the face of unprecedented challenges.
Big Data: Analysing The Future Of Global Food Production
Big Data is revolutionising agriculture by providing farmers with unprecedented insights and tools. As we move forward, the integration of data into farming practices promises to enhance productivity, sustainability, and profitability in an increasingly complex and challenging global food system. The agricultural sector stands on the brink of a data-driven transformation that could reshape how we produce food for generations to come.
