Performance enhancement in hydroponic and soil compound prediction by deep learning techniques.

ABSTRACT: The soil quality plays a crucial role in providing essential nutrients for crop growth and ensuring a bountiful yield. Identifying the soil composition, which includes sand, silt particles, and the mixture of clay in specific proportions, is vital for making informed decisions about crop selection and managing weed growth. Furthermore, soil pollution from emerging contaminants presents a substantial risk to water resource management and food production. Developing numerical models to comprehensively describe the transport and reactions of chemicals within both the plants and soil is of utmost importance in crafting effective mitigation strategies. To address the limitations of traditional models, this paper devises an innovative approach that leverages deep learning to predict hydroponic a

SUBMITTER: Abidi MH 

PROVIDER: S-EPMC11636990 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature