Artificial Intelligence in Agriculture


Artificial Intelligence in Agriculture


Eight billion people now inhabit this globe, a doubling of the population since 1974. Despite the fact that population growth has halted, if things continue as they are, we should reach 9 billion in 15 years. How much food must be provided for everyone? Could John McCarthy, who first used the phrase "artificial intelligence" in 1955 to describe "the science and engineering of making intelligent machines," have foreseen how technology would impact our ever-increasing demand for food? Share your thoughts with us on the Artificial Intelligence Write For Us category.

Role of Artificial Intelligence in Agriculture 

The quantity and quality of the yield, as well as the health of the crop, are directly influenced by the micro- and macronutrients in the soil. In order to maximise production efficiency after crops are planted in the soil, it is also crucial to keep track of their developmental stages. To make changes for better crop health, it's essential to comprehend how crop growth and the environment interact. Now, historically, human observation and judgement were used to assess the health of the soil and the crops. However, this approach is neither precise nor timely. Instead, we can now acquire aerial image data with drones (UAVs) and train computer vision models to use it for informed crop and soil status monitoring.

The kind of labour-intensive task that manual observation of wheat head growth stages falls under is exactly the kind that AI can assist with in precision agriculture. Researchers were able to construct a "two-step coarse-to-fine wheat ear detection mechanism" by gathering photos of wheat over the course of three years and in various lighting conditions at various "heading" phases. The farmers no longer needed to make daily trips out into the fields to inspect their crop because this computer vision model could then more precisely identify wheat growth stages than human observation.Or picture having to manually assess the maturity of tomatoes on a large scale. Well. That can also be assisted by AI!

You may use this to enhance all facets of production, operations, and distribution. For instance, drones may train computer vision models and give visual data, enabling continuous information about crop development and the surroundings. With AI, farmers are better equipped to keep an eye on their crops and respond instantly to situations like the recent rainstorms in California or drought conditions by changing their watering practises or erecting canopies. 

The Bottom Line

Today's farmers are under pressure and require expertise in a variety of areas, including soil and fertiliser science, crop-specific pesticides, planting and irrigation cycles, and the effects of the weather. Farmers must now produce more food while using less energy and water since pests alone can ruin up to 40% of the world's crops every year. Farmers must lessen their reliance on a workforce because there has been a global lack of farm labour for years due to urbanisation, immigration challenges, and a generational shift away from farming. Never before has technology been more essential to a successful crop cycle. 

Post a Comment


Ad Code

Responsive Advertisement