November 30, 2022
Making Use of Artificial Intelligence in the Agriculture Industry

Making Use of Artificial Intelligence in the Agriculture Industry

It gives me great joy to witness the incorporation of cutting-edge research into commercial sectors that have a direct bearing on the daily lives of people all over the world. As an illustration, consider the extensive implementation of AI in the farming sector. University of California, Berkeley estimates that by 2050, the global food and agriculture sector would be worth $5 trillion. Despite the fact that the agricultural industry is often viewed as being less “digitized” than other parts of the economy, recent developments in areas like as artificial intelligence have sparked a renewed interest in the field.

The Importance of AI in Agriculture

Because of developments in AI, agricultural productivity is a win-win for both industrialized and developing nations (AI). Increased yields of greater quality with fewer inputs are now possible in agriculture as a result of these AI-enabled innovations. The average farm is predicted to create more than 4 million data points per day by 2050, with an estimated 75 million linked devices already in use on farms now, according to Science Direct. Thanks to AI’s rapid data processing, farmers can make better, more timely judgments on the weather, soil, and insects. In addition, it can pick up new information and skills as it goes along, allowing it to tackle new challenges in the future.

There are four main reasons for the rapid growth of AI in farming:

  1. With a growing global population comes a higher need for agricultural output.
  2. The efficiency of farming is currently being increased through the widespread use of various information management systems and technologies by farms.
  3. There is a pressing need to boost crop yields, and AI can do it in a timely and cost-effective manner.
  4. Governments throughout the world are actively promoting the use of cutting-edge farming methods like the incorporation of AI (AI).

The Application of Robotics in Agriculture for Weed Management

Farmers are increasingly worried about the development of herbicide resistance in several plant species, making weed management a top issue. According to research performed by the Weed Science Society of America, farmers lose an annual total of $43 billion due to the cost of weed treatment in only maize and soybeans.

Modern “See and Spray” machinery powered by AI can cut herbicide application by 80-90 percent thanks to advances in image processing and machine learning. In order to determine whether or not a given plant is a weed, a weed detection system employs cameras that combine computer vision and machine learning to perform instantaneous assessments. As it moves through a field, the equipment takes 20 pictures per second and instantly compares each one to a million-picture database. If it detects weeds, it will only spray the ones that need it based on their unique characteristics. It has experience with a wide variety of species and sizes, so it can eliminate wasteful human intervention and speed up the weed-control process.

Let’s move on to the next step in our investigation of A.I. in agriculture by looking into the many predictive weather apps available today.

Applications of Artificial Intelligence in Predictive Weather

As a result, weather monitoring is crucial for farmers everywhere, and AI is now being used to aid farmers in mitigating the effects of extreme weather. The following are the most significant pieces of meteorological information amenable to AI analysis:

Rainfall

Artificial intelligence can swiftly assess past rainfall patterns over a certain time period using analytical algorithms, allowing for accurate forecasting.

Temperature

By using AI algorithms, we can better analyze the data we collect on how temperatures rise and fall over the course of a day, month, or year and use that information to make informed decisions about the future.

Wind and Air Pressure

The wind’s direction and velocity, as well as the air’s pressure, are key indicators of impending storms and other severe weather.

Humidity

A vital indicator for planning ahead for anticipated precipitation and making better use of current water sources.

Farmers may track changes and create forward-looking agricultural strategies by collecting and centralizing data points from all these areas in a single hub. Better still, they can collaborate with other farmers to make regional predictions. Up to 90 percent of crop losses may be averted with the use of weather forecasting models, and another 25 percent may be prevented with more forethought.

Let’s have a look at how artificial intelligence can help with pest management as we continue our investigation into its applications in farming.

Killing Pests Cleverly

Artificial intelligence-enabled drones are increasingly being used to aid farmers in their fight against illness and pests. In Leones, Argentina, farmers are using a drone equipped with a camera to scan 150 acres of wheat stalk by stalk for symptoms of fungal infection, which might threaten the harvest. Computer vision, an AI technique commonly employed in security cameras, fuels the robot’s operations. Whether it’s a bug, fungus, or other form of risk, the AI engine can educate itself how to recognize it and categorize it. UAVs provide farmers with a bird’s-eye view of their fields, while AI and ML act as the “brains” of the operation.

Now, let’s examine how the plants themselves profit from the use of AI in farming.

Crop and soil health monitoring should be improved.

Artificial intelligence is rapidly becoming an important tool for monitoring soil on agriculture, which is essential for the health of crops. For instance, a Berlin firm has created a deep learning program that can identify soil flaws and nutritional deficits. Software algorithms have shown a correlation between certain types of foliage and the presence of soil deficiencies, as well as the effects of insects and disease on crops. Image recognition powered by AI may alert farmers to possible problems, at which point they can be given guidance on how to best address the situation.

The Growing Importance of Upskilling in Artificial Intelligence

Artificial intelligence (AI) is saving the global agriculture business and saving the lives of farmers everywhere. Take some classes in machine learning and deep learning to set yourself up for success in a tech job that will have a major influence in fields like agriculture and food processing.