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Artificial Intelligence in Agriculture: What Awaits Us Until 2030

In recent years, technology is slowly entering agriculture to help farmers provide the best conditions for plant growth. Moving away from the old ways of farming is difficult, but the early adopters of modern technologies report noticeable changes in profit. 

Artificial intelligence (AI), machine learning (ML), and IoT sensors are powerful technologies used in many industries. For example, in agriculture, they can enable farmers to increase their yield but only when used with other technologies. However, AI cannot solve all the problems in the industry overnight. 

According to research, agriculture is predicted to grow from $1 billion in 2020 to $4 billion in 2026 and triple its revenue.

In this article, we want to focus on ML and AI’s influence on agriculture in the next decade. We will also share some of our predictions on how agriculture can benefit from using machine learning and artificial intelligence to ensure the stability of the food supply.

How AI and ML Can Be Used in Agriculture

Traditional farming revolves around the farmer being present in the fields as it’s the only way to understand what is happening. However, as the market pressure grows, farmers will have to turn to novel approaches to match the market’s needs. 

Agriculture involves different processes and development stages that require a lot of manual labor. AI is there to collect big data, process it, and provide farmers with enough information to make thought-through decisions. It gathers soil health insights, fertilizer recommendations, weather prognosis, and whether the crops are ready for harvesting. 

All this enables farmers to keep a close eye on their crops and make better decisions at every step. Here’s what AI will bring to the industry:

  • Detailed analysis of market demand
  • Predictive analysis that reduces risks
  • Soil health monitoring
  • Automated harvesting
  • Protecting and feeding crops system

Saving Costs by Using Agriculture Technology

Farmers are exploring many approaches to achieve better yields with fewer resources. However, the lack of knowledge in every stage of plant development can lead to problems in irrigation, improper use of pesticides and creates additional costs. 

In the next decade, one of the best ways to save costs will be precision farming. It allows farmers to use water and fertilizers in the right amounts, decrease their production costs and optimize water usage. Optimal water usage is incredibly important as by 2030, the water supply will fall 40 percent short of what global agriculture would require to produce more food than today.

AI will collect data from the fields and process everything from flow, soil moisture, freeze, and rain sensors. Then, using an application, farmers will quickly identify areas that require more water, a special irrigation regime, and fertilization to restore optimal growth conditions. 

Another benefit of using ML and AI in agriculture is better resource management, especially for farmers with big fields. With enough data planning and purchasing seeds, fertilizers, and additional equipment, farmers can have their expenses under control.

Minimizing Manual Work

Farming is time-consuming and often stressful. In addition, large-scale agricultural businesses rarely have access to a large workforce to distribute fertilizers or drive tractors and other machinery. This problem will become even more pressing as fewer people are interested in working in the fields. Programming self-driving tractors and additional ML and AI-based harvesting machines can provide security for everyone in the agricultural business.

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Machine Learning and Artificial Intelligence enable farmers to produce more quality crops.

Machines can reach remote locations and distribute fertilizers to improve yields. As the sophistication of robots grows, they are more capable of doing more complex fieldwork. 

Machines are more reliable, faster, and more accurate, and farmers will know that everything will be done precisely as planned. And research proves that when farmers combine precise irrigation with nutrient management can significantly reduce the environmental impact of fertilizers. 

Embracing More Sustainable Farming

Sustainability is one of the critical issues in agriculture. For example, finding irrigation leaks and measuring water usage contribute to building more efficient and more sustainable future farms

Sustainable agriculture is the key to creating a better future where farmers will use their resources mindful of their environmental impact. By maintaining sustainable plant cycles, farmers can reduce erosion, maintain the soil quality and preserve valuable water sources.

Also, certain AI apps and software can help farmers predict output yield of crops and calculate potential profit. That allows better planning and timely reactions if, for example, optimizing the irrigation process by upgrading the system can help generate a better outcome.

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Improving the Crops’ Quality

Machine learning and artificial intelligence in agriculture can also help grow higher-quality crops and improve the overall quality of the food we all eat. AI and ML are already in use for such crop-protection purposes:

  • Disease recognition
  • Pest detection
  • Plant species recognition
  • Crop security, and more.

By recognizing images and determining patterns and correlations, ML can help farmers protect their crops without them being present on the land at all times. Combined with precision irrigation and fertilization and crop prediction, these AI features can (and will) truly revolutionize food production.

Rising to the High Expectations of the Industry

The future of agriculture is closely connected to technology. Those willing to adopt new technologies might produce high-quality crops with lower risks.

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