The application of Artificial Intelligence (AI) has been evident in the agricultural sector
recently. The sector faces numerous challenges in order to maximize its yield including …

Agricultural production systems play a crucial role in global societal sustenance as they
provide the world's food, fuel, and fiber supplies. However, these systems face numerous …

Sustainable agricultural development is a significant solution with fast population
development through the use of information and communication (ICT) in precision …

Soil pH and carbonates (CaCO 3) are important indicators of soil chemistry and fertility, and
the prediction of their spatial distribution is critical for the agronomic and environmental …

This study was conducted to evaluate the efficacy of the ensemble machine learning model
to predict the spatial variation of soil organic carbon (SOC) concentration in a deciduous …

Soil water content (SWC) estimation is a crucial issue of agricultural production, and its
mapping is an important task. We aimed to study the efficacy of UAV-based thermal (TH) and …

Accelerated urbanization has resulted in the accumulation of considerable amounts of
heavy metals (HMs) in urban soils. It is important to identify correlations between the …

The efficiency of different digital and conventional soil mapping approaches to produce
categorical maps of soil types is determined by cost, sample size, accuracy and the selected …

The variability of soil properties plays a critical role in soil and water conversation
engineering. In this study, different machine learning techniques were applied to identify the …

In the current study, the use of regression-kriging (RK), artificial neural networks (ANN),
support vector machines (SVM), and random forest (RF) methods from machine learning …