5 Uses of AI in Agriculture!

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5 Uses of AI in Agriculture!

5 Uses of AI in Agriculture! – Today we’re going to talk about five uses of AI in agriculture.

Fruit Picking

The first use of AI in agriculture is for fruit picking. Harvest Robotics uses a robot to pick strawberries. In just one day the robot can pick the same amount of fruits as 30 human workers. On top of that, the robot is equipped with camera systems that can do image recognition on the fruits to figure out whether or not they’re ready for picking.

Crop Analysis

The second use of AI in agriculture is crop analysis using drone and satellite imagery. So imagine a drone flies over your crops and takes pictures of your entire field. It then goes ahead and does an analysis on those images to create a detailed health report and that health report would also tell you whether or not your plants have been afflicted by any disease and whether they’re in need of herbicide.

SkySquirrel Technologies is doing just this. They claim to be able to scan 50 acres of fields in 24 minutes and providing a Health Report that’s 95% accurate. Similarly there’s a company called FarmShots that’s doing the same thing by combining drone imagery and satellite imagery.

Identifying and Eradicating Weeds

The third use of AI in agriculture is for identifying and eradicating weeds. A company called Blue River Technology does this by fitting a camera system on the back of a tractor as the tractor sweeps the fields the onboard computer system that are fitted on the camera run deep learning algorithms that’s able to recognize the weeds and spray herbicide wherever is needed.

This approach uses only 10% of the herbicides that would have been used following a conventional method and this is simply spraying the entire field with herbicide as you can imagine this results in higher efficiency, less wastage and safer produce for all of us.

Real-Time Weather Forecasting

The fourth use of AI in agriculture is for real-time weather forecasting to improve crop yield. 90% of crop losses result due to weather events and 25% of those losses could have been prevented by predictive weather modeling. Some of the things that affect crop yield or are temperature, rain, humidity and solar radiation.

So AI can be used to combine data from satellites, on-ground sensors and weather stations to give better predictions of the weather and this type of modeling can advise farmers on the best time to sow plants and harvest.

Detecting Soil Defects

The fifth-year survey on agriculture is for detecting soil defects. Trace Genomics, a company based in California analyzes your soil sample to give you an idea of the types of microbes present in your soil. Based on that data, they can make recommendations on what kind of fertilizers you can use to improve the quality of your soil and whether your soil contains any type of defects that needs to be treated.



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