AI in Agriculture: Strengthening the Future of Farming

AI in Agriculture: Strengthening the Future of Farming

Agriculture or farming is one of the most primitive and significant professions worldwide. However, in this sector, several food producers today are struggling to manage threats to their crops against disease and pests, which is made severe by climate change, monocropping, and prevalent pesticide use. The agriculture globally is a US$5 trillion industry, and now it is turning to Artificial Intelligence.

The AI-powered technologies can assist the agriculture sector to yield healthier crops, control pests, monitor soil, and growing conditions, organize data for farmers, aid with the workload, and advance a large range of agriculture-related tasks in the entire food supply chain. These innovations to farming have been considerably driven by climate change, population growth and food security concerns.

Farm Data Assessed by AI

On the ground, farms generate hundreds of thousands of data points daily. However, farmers can now analyze a variety of things in real-time, with the help of AI. They can assess weather conditions, temperature, water usage or soil conditions gleaned from their farm to better enlighten their decisions. For instance, Taranis, a leading precision agriculture intelligence platform, works with farms on four continents and flies high-definition cameras above fields to provides the eyes to farmers. So, AI-driven technologies assist farmers to optimize planning to create more generous yields by determining crop choices, the best hybrid seed choices and resource utilization.

Improving Harvest Quality 

AI systems today are helping farmers to improve harvest quality and accuracy using precision agriculture. It leverages AI to help in identifying diseases in plants, pests, and poor plant nutrition on farms. AI sensors can detect and target weeds and then decide which herbicides to apply within the right buffer zone. It assists to thwart applications of herbicides and extreme toxins that find their way in today's food. For example, a researchers' team developed an AI to detect diseases in plants. The team leveraged a method, transfer learning, to teach the AI to identify crop diseases and pest damage, and utilized TensorFlow, a Google's open-source library, which created a library of 2,756 images of cassava leaves from plants in Tanzania. In that case, AI was able to detect disease with 98% accuracy.

Computer Vision-Enabled Farming

Monitoring their farms, farmers are using Computer Vision and deep learning algorithms to capture data from drones flying over their fields. From drones, AI-powered cameras can take images of the entire farm and evaluate the images in near-real-time to recognize problem areas and potential improvements. Considering reports, several large industrial farms, for instance, tried using computer vision to detect and confiscate sick pigs at the outset of an African swine fever epidemic that is sweeping China. Thus, drones are able to capture far more land in much less time than humans.

Indoor Farming 

Nowadays, new techie farmers are ambitious and moving toward indoor farming. It is a technique of growing crops or plants, typically on a large scale, entirely in a packed environment. This way of farming often implements growing methods like hydroponics and leverages artificial lights to provide plants with the nutrients and light levels required for growth. AI-powered indoor agriculture is tempting a whole new breed of farmers now. For instance, 80 Acres Farms, a pioneer in indoor growing, opened the world's first fully-automated indoor growing facility last year. The company's AI-driven technologies monitor every step of the growing process.

So, the use of AI in agriculture is allowing farmers worldwide to run more efficiently, enabling farms of all sizes to operate and function with keeping the world fed.

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