Agriculture is the most important sector of the world economy and the key to food security and economic growth. Agricultural production relies on a variety of inputs, including land, labor, capital, and information technology. In recent years, advances in artificial intelligence (AI) have led to significant improvements in agricultural productivity. AI used in agriculture can help farmers identify problems early, make better decisions about farming techniques, and optimize production strategies.
There are many reasons why farmers in developing countries should consider applying AI in their farming operations. For starters, it can significantly reduce transportation losses and unnecessary long storage and improve supply chains. The use of AI can also streamline the flow of information between suppliers and buyers. And that’s not all. A few other reasons might also justify using AI used in agriculture. Let’s look at some of them.
As the use of agricultural robots becomes more common, the employment of manual laborers is at risk. AI can do the work of two humans in just a fraction of the time. Similarly, AI can enhance crop yields by improving harvest efficiency and crop rotation. Furthermore, it can be used to see the field from a wider angle than human farmers. These benefits come at a price, but the potential costs of AI for agriculture are well worth the trade-off.
One of the most common costs of farming is the labor involved in manually detecting various diseases and pests. AI helps farmers reduce this expense by creating custom conditions for the crops. For example, farmers can now plant crops in containers inside their homes, and AI is capable of creating the right lighting and water conditions. This could reduce deforestation, especially in Latin America and the Caribbean, which rely heavily on using natural resources. Artificial intelligence also helps detect standing water, a major cause of crop loss.
Farmers are often wary of AI because they believe it is all about digital technology. As a result, they have difficulty visualizing how it can be applied to the farming industry. These new technologies can be expensive and confusing, and they often seem beyond their means. Furthermore, some AgriTech providers fail to adequately explain the benefits of their solutions and the proper ways to implement them. But, as we continue to develop AI technology, this problem is becoming less of a barrier. Currently, the most difficult part of fieldwork is manual detection.
Automation can solve that problem. For example, the process of apple picking can be made easier by robotic automation. This technology can identify ripe fruits and can be trained to look for them. Moreover, it can improve harvest efficiency, as it does not require humans to inspect and judge the crops. Furthermore, it can be replicated on a large scale.