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Precision agriculture
What is precision agriculture?
Precision agriculture involves using data-driven technology to improve farming outcomes. Leveraging tools like GPS, sensors, and data analytics, growers can monitor and manage field variability in their crops. They can also use this information to make smarter decisions around their use of inputs such as water and crop protection products.
By being more precise with how they farm and the products they use, growers can use precision agriculture to reduce their environmental impact while boosting productivity.
Using tools such as satellite data, sensors, weather prediction tools, drones and GPS systems, farmers can monitor their crops and soil in granular, up-to-the-minute detail.
They can then use that information to tailor their farming practices to the specific needs of their crops and soil and apply precise amounts of input – like water, fertilizer or crop protection products – at specific times.
By using only how much input is needed, when and where it is required, growers are able to use smaller amounts of product, more effectively. That means farmers can use their land and resources, such as water, fuel and fertilizer more efficiently, reducing unnecessary costs.
Mitigating the negative impacts of conventional farming practices, precision agriculture optimizes land use. That means farmers can use less to grow more – and so, it is growing in popularity as an efficient method of modern farming.
Where is precision agriculture used?
Precision agriculture can be used anywhere that a farmer wants to use cutting-edge technology to better understand their environment and make deliberate, data-driven decisions to improve their farming.
And because it is so flexible and beneficial for growers, helping them to maximize their yields, minimize resource consumption and farm sustainably, precision agriculture is becoming more popular around the world.
How did precision agriculture come about?
Precision agriculture is as old as the technologies it uses – meaning it’s quite recent. The emergence of technologies like GPS, remote sensing, and data analytics in the late 20th century gave farmers the opportunity to have a more in-depth understanding of what, how and where they grow their crops.
The concept of precision agriculture emerged in the tech boom of the 1980s, when it was used to develop the first input recommendation maps for farmers.
New technologies, including GPS receivers and yield sensors, have enhanced the efficacy of this future-focused farming system.
The rapid development of Artificial Intelligence (AI) over the past decade has accelerated the types of technology farmers can utilize for precision agriculture and the accuracy of it.
What is the difference between precision agriculture and conventional agriculture?
The key difference between the two is found in the specificity that precision agriculture offers - hence its name.
Conventional agriculture often takes a blanket approach to fields and crops, relying on uniform and broad applications of inputs, like crop protection products, fertilizers and water. While this approach allows farmers to grow at scale and over many hectares of land, it does not account for the variability that is found in each row of crop, or handful of soil. Just as the microorganisms found in the soil differ from one field to the next, the pests and diseases that attack crops can vary and often don’t affect the entire field at the same time.
The difference that precision agriculture offers is in the scale and detail of the data itself that farmers can access. By learning about the moisture levels of an individual crop and the composition of the soil it grows in, farmers can then prescribe the plant exactly what it needs to thrive. This means growers can go from a field-by-field, bird’s eye view of their crops to a plant-by-plant approach throughout the crop’s growing cycle.
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What machinery does precision agriculture use?
Alongside high-tech equipment such as drones and satellites, precision agriculture also utilizes farm machinery equipped with technology to improve overall farming practices.
From tractors equipped with GPS and sensor systems, to irrigation systems that automatically switch on in certain conditions, this machinery gives farmers the information they need to make better decisions.
This machinery helps them to use their resources more efficiently too, as they can use precise amounts of crop protection products, when and where they are needed.
For example, farmers can use GPS technology to produce tailored maps with specific fertilizer needs – and then use the GPS to steer the tractor around their fields, following the map.
AI and precision agriculture
Artificial intelligence (AI) has supercharged the effectiveness of precision agriculture, giving farmers more data than ever before to grow healthy crops.
From predicting on-farm weather patterns, to tracking key sustainability emissions, to monitoring disease and pest pressures, AI-enabled systems give growers the real-time data they need to make effective decisions. The ability of AI to process and categorize vast amounts of this data, from multiple sources, means it can offer farmers practical advice on inputs and crop management.
Syngenta’s Cropwise AI tool is one example of this. Blending decades of agronomic expertise with cutting-edge data analytics and machine learning algorithms, the tool offers growers advice to suit their needs. These recommendations include input applications and pest and disease management methods.
This helps farmers to improve their yields, while reducing their environmental footprint.
With rapid advancements in AI, future iterations of the app are expected to include the ability to detect and identify pests and diseases early, for proactive and precise management strategies, alongside sustainability analytics that measure the environmental impact of farming and offer tips to reduce a grower’s carbon footprint.
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Optimized resource management
AI in precision agriculture optimizes the use of resources like water, fertilizers, and crop protection products by providing precise recommendations based on data analysis.
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Enhanced crop monitoring
AI-powered drones and sensors allow for real-time monitoring of plant health, spotting early signs of pests and diseases.
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Data-driven decision making
Machine learning algorithms analyze field data, supporting growers to make better decisions that enhance their outcomes.
AI-powered precision agriculture offers remarkable benefits. But can every farmer access these advantages?
Recent research by Syngenta and IPSOS reveals a growing digital divide between smallholders and larger operations. Learn more about the challenges smallholder farmers face in adopting this technology.
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