Making smart, data-driven decisions for farmers with precision farming tools
BookMyCrop
Nov 03, 2022
How resilient farmers can use precision farming tools
Zero hunger, the second Sustainable Development Goal of the United Nations, cannot be attained without adequate access to food. A Nature Food research that looked at 57 estimates for global food security came to the conclusion that by 2050, there will be a 35% to 56% increase in global food demand. However, the increasing population, the scarcity of arable land, and climate change have a significant impact on the world's food production.
Natural disasters, pests, and diseases have grown due to rapid climate and environmental change. Floods, forest fires, droughts, and salinization have all ruined crops and arable land. Due to rising urbanization, the area of arable land is also drastically decreasing. Future food shortages can be avoided by digitalizing agriculture and creating climate-resilient, smart agricultural models with precision farming. Responsiveness, the cornerstone of resilience, will be heralded by these developments.
The benefits of precision farming for farms
Farmers made decisions over a large portion of agricultural history using knowledge that was passed down verbally through generations, as well as memory and observation of the seasons and local and regional weather. This approach, however, has a number of drawbacks.
- Recollection and observation are not always reliable because they are not based on recorded facts or data.
- Climate change has made things like seasons, rainfall, temperature, etc. unpredictable and unreliable.
- Most of the time, soil fertility varies between and within fields, yet farmers nevertheless apply agri-inputs consistently based on their experience.
- Agri-input resources are under- and over-applied when they are applied uniformly.
- Overuse of inputs pollutes the ecosystem, affecting the soil, groundwater, and surface and drain-off water.
Smart farming improves responsiveness by providing timely information and useful insight.
Thankfully, there are now crop and site-specific management solutions available to farmers, providing them with rapid access to real-time data for data-driven decision-making. Some of the farming digitization technologies used to produce the knowledge inputs required by farmers include global positioning and geographic information systems, variable rate technology, grid sampling, yield maps, remote and proximate sensors, unmanned aerial vehicles, automation and robotics, micro-irrigation systems, and data analytics software. The fact that these inputs are readily available whenever and wherever needed is a major bonus.
Big data, artificial intelligence (AI), and machine learning (ML) are all used in precision farming to assist farmers in maintaining process control. For inputs, it makes use of precise data gathered by distant sensors, satellite pictures, and historical data. Together, these make a significant improvement to agricultural operations long-term planning and real-time strategy adjustment for unforeseen circumstances.
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