Crop yield is a significant factor in world income and poverty alleviation as well as food production through agriculture. Conventional crop yield forecasting approaches that employ subjective estimates including farmers' perceptions are imprecise an...
Urbanization and industrialization have led to widespread soil heavy metals contamination, posing significant risks to ecosystems and human health. Conventional methods for mapping heavy metal distribution, which rely on soil sampling followed by che...
Coal mining soils are highly susceptible to heavy metal pollution due to the discharge of mine tailings, overburden dumps, and acid mine drainage. Developing a reliable predictive model for heavy metal concentrations in this region has proven to be a...
Accurate prediction of maize yields is crucial for effective crop management. In this paper, we propose a novel deep learning framework (CNNAtBiGRU) for estimating maize yield, which is applied to typical black soil areas in Northeast China. This fra...
Global warming is one of the most pressing and critical problems facing the world today. It is mainly caused by the increase in greenhouse gases in the atmosphere, such as carbon dioxide (CO). Understanding how soils respond to rising temperatures is...
In this study, we introduce PFASorptionML, a novel machine learning (ML) tool developed to predict solid-liquid distribution coefficients () for per- and polyfluoroalkyl substances (PFAS) in soils. Leveraging a data set of 1,274 entries for PFAS in ...
Soil organic carbon (SOC) plays a crucial role in carbon cycle management and soil fertility. Understanding the spatial variations in SOC content is vital for supporting sustainable soil resource management. In this study, we analyzed the variability...
Soil contamination by potentially toxic elements (PTEs) poses substantial risks to the environment and human health. Traditional investigational methods are often inadequate for large-scale assessments because they are time-consuming, costly, and hav...
How to scientifically and efficiently quantify the impact and hazards of volatile organic compounds (VOCs) pollution and volatilization from complex groundwater systems on surface air environments is a critical environmental issue. This paper employe...
This study investigated the potential of using remote sensing indices with artificial neural networks (ANNs) to quantify the responses of dry bean plants to water stress. Two field experiments were conducted with three irrigation regimes: 100% (B100)...