Abstract Machine learning (ML) has become an important technology for the development of
prediction models for crop yield. Predictive modeling using ML is rapidly growing as …

Pistachio production is an economically important crop that grows in arid environments. To
predict yield and sustainably manage the use of natural resources such as soil and water …

With the aid of models used in artificial intelligence, a wide range of data can be processed
quickly with high accuracy. The quality of rapeseed oil from 40 genotypes cultivated during …

Pigeon pea is the second most important grain legume in India, primarily grown under
rainfed conditions. Any changes in agro-climatic conditions will have a profound influence …

Pesticides are essential for agriculture, but because of their residues in crops, produce and
soil, they have become a major concern. Traditional pesticide detection methods …

Pistachio is one of the most important and valuable orchard products in Iran and some other
places in the world. Because it is adaptable to adverse environmental conditions, especially …

Using remote sensing combined with machine learning (ML) techniques is a promising
approach to classify soybean cultivars. Therefore, the objectives of this study are (i) to verify …

Over half the world population relies on rice for energy, but being a carbohydrate-based
crop, it offers limited nutritional benefits. To achieve nutritional security targets in Asia, we …

Enhancing the crop yield predictability in intercropping systems is important for optimizing
agricultural productivity. However, accurately predicting yield in such systems is quite …

Crop yield predictions are important for crop monitoring and agronomic management. The
traditional methods for yield predictions are complicated and resource consuming. With the …