Моделі штучного інтелекту оцінки родючості ґрунтів для ефективного вирощування сільськогосподарських культур

Abstract

The purpose of this article is to explore the progress of artificial intelligence models in the field of agriculture. Using a dataset as an example, it will explore what data can currently be used to improve crop production and the possibility of integration with existing soil research methods, such as laboratory experiments, etc. The article will focus on the assessment of soil fertility using artificial intelligence, which will allow agronomists and farmers to make informed decisions about fertilization, irrigation, and other aspects of land cultivation. It will be discussed how the integration of these technologies with existing soil analysis methods can improve the accuracy of fertility assessment and contribute to sustainable agricultural development.