Deep learning (DL) has emerged as a powerful subset of machine learning (ML) and
artificial intelligence (AI), outperforming traditional ML methods, especially in handling …

Proximal soil sensing is a highly advanced and rapidly evolving technique for predicting soil
chemical properties. NIR spectroscopy is expected to offer an easier and more cost-effective …

Soil, a non-renewable resource, requires continuous monitoring to prevent degradation and
support sustainable agriculture. Visible-near-infrared (Vis-NIR) spectroscopy is a rapid and …

Soil moisture content plays a vital role in agricultural production, significantly influencing
crop growth, development, and yield. Thoroughly understanding the specific soil moisture …

With the increasing demand for precision agriculture and sustainable land management, it is
crucial to quickly and accurately predict soil properties. However, there are still challenges in …

This study is focused on evaluating the potential of deep neural networks for assessing soil
properties based on VIS–NIR spectroscopy with spectral wavelength ranges of 350–2500 …

There are few reports on soil pollution caused by long-term mining of Mojiang gold mine in
Yunnan Province. This study took the contaminated farmland soil around the gold mine in …

This work proposes exploring the discrimination model by near-infrared (NIR) spectroscopy
(FT-NIR and Micro-NIR) for geographical source areas of coconut milk in tandem with the …

Many soil functions and processes are controlled by the soil particle size distribution.
Accordingly, nationwide geoinformation on this soil property is required to enable climate …

Accurate prediction of soil properties is essential for sustainable land management and
precision agriculture. This study presents an LSTM-CNN-Attention model that integrates …