In the digital soil mapping (DSM) framework, machine learning models quantify the
relationship between soil observations and environmental covariates. Generally, the most …

Crop yield is controlled by different environmental factors. Multi-source data for site-specific
soils, climates, and remotely sensed vegetation indices are essential for yield prediction …

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 …

Aggregate stability is a measurement of soil quality, as the presence of stable aggregates
relates to a wide range of soil ecosystem services. However, aggregates stability is not …

Rice is a major dietary source of the toxic metal cadmium (Cd). Concentration of Cd in rice
grain varies widely at the regional scale, and it is challenging to predict grain Cd …

Soil is an important resource worldwide with diverse physical, chemical, and biological
properties. These properties vary from place to place because ecological variables such as …

Water deficit stress is a frequent phenomenon that inhibits plant growth. This study explores
the performance of hyperspectral data for estimating the leaf water content of ten tree …

Abstract In northern Tunisia, Sidi Driss sulfide ore valorization had produced a large waste
amount. The long tailings exposure period and in situ minerals interactions produced an …

Machine learning can handle an ever-increasing amount of data with the ability to learn
models from the data. It has been widely used in a variety of disciplines and is gaining …

Highlights•Feature fusion based classifier can detect pathological situations in crops.•The
system can be used for automating detection of plant diseases or water stress.•Results show …