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According to the Food and Agriculture Organization, the world's food production needs to increase by 60-70 percent by 2050 to feed the growing population. However, the EU agricultural workforce has declined by 35% over the last decade, and 54% of agriculture companies have cited a shortage of staff as their main challenge. This, among other factors, has led to an increased interest in advanced technologies in agriculture, such as IoT, sensors, robots, drones, digitalization, artificial intelligence, and many more. Artificial intelligence (AI) and machine learning have proven valuable for many agriculture tasks, including problems detection, crop health monitoring, yield prediction, price forecasting, yield mapping, optimization of pesticides and fertilizers usage, etc. In this article, we will explore various AI applications in agriculture and share our experience in this field.
