In the context of global sustainability challenges, precise soil characterization is pivotal for
informed soil management and land use planning as 'better measurement can only lead to …

Artificial intelligence has many applications in various industries, including agriculture. It can
help overcome challenges by providing efficient solutions, especially in the early stages of …

Hydrocarbon pollution is a major ecological problem facing oil-producing countries,
especially in the Niger Delta region of Nigeria. In this study, a site that had been previously …

Soil texture analysis is crucial for crop selection, fertilizer recommendation, and production.
Traditional soil testing in the lab using chemicals is highly time-consuming, expensive, and …

Soil texture classification is pivotal in diverse fields, such as agriculture, environmental
science, geology, civil engineering, and land management. Traditional approaches to soil …

This paper presents a novel study on soil image classification, leveraging the synergistic
potential of transfer learning and convolutional neural networks (CNNs). The proposed …

Organic carbon is probably the most important organic matter, which affects soil properties
and is a prime indicator of soil quality. In this letter, the electromagnetic sensor is designed …

Texture and color are fundamental visual descriptors, each complementing the other.
Although many approaches have been developed for color-texture analysis, they often lack …

Traditional practices in agriculture lack the proper guidance in regard to crop production and
yields, making the processes inefficient with Poor use of resources. To address the above …

This paper presents a new machine learning-based approach for nutrient deficiency
detection through literature shortcomings in advanced feature extractions and classification …