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Agriculture

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Deep learning-based rice pest detection research.

PloS one
With the increasing pressure on global food security, the effective detection and management of rice pests have become crucial. Traditional pest detection methods are not only time-consuming and labor-intensive but also often fail to achieve real-tim...

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence.

Journal of hazardous materials
Groundwater is vital for agricultural cities, but intensive farming and fertilizer use have increased contamination risks, particularly for non-carcinogenic health hazards. This study reveals the sources of contaminants in groundwater, their health i...

Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed.

Journal of environmental management
Prediction and quantification of nutrient concentrations in surface water has gained substantial attention during recent decades because excess nutrients released from agricultural and urban watersheds can significantly deteriorate surface water qual...

Sunflower mapping using machine learning algorithm in Google Earth Engine platform.

Environmental monitoring and assessment
The sunflower crop is one of the most pro sources of vegetable oil globally. It is cultivated all around the world including Haryana, in India. However, its mapping is limited due to the requirement of huge computation power, large data storage capac...

Integrating deep learning for visual question answering in Agricultural Disease Diagnostics: Case Study of Wheat Rust.

Scientific reports
This paper presents a novel approach to agricultural disease diagnostics through the integration of Deep Learning (DL) techniques with Visual Question Answering (VQA) systems, specifically targeting the detection of wheat rust. Wheat rust is a pervas...

Global meta-analysis and machine learning reveal the critical role of soil properties in influencing biochar-pesticide interactions.

Environment international
Biochar application in soils is increasingly advocated globally for its dual benefits in enhancing agricultural productivity and sequestering carbon. However, lingering concerns persist regarding its environmental impact, particularly concerning its ...

Downscaling MODIS evapotranspiration into finer resolution using machine learning approach on a small scale, Ribb watershed, Ethiopia.

Environmental monitoring and assessment
By monitoring evapotranspiration (ET), the exchange of water and energy between the soil, plants, and the atmosphere can be controlled. Routine estimations of ET on a daily, monthly, and seasonal basis can give relevant information on small-scale agr...

Assessment of groundwater quality variation characteristics and influencing factors in an intensified agricultural area: An integrated hydrochemical and machine learning approach.

Journal of environmental management
The decline in groundwater quality in intensive agricultural areas in recent years, driven by environmental change and intensified human activity, poses a significant threat to agricultural production and public health, requiring attention and effect...

Improving crop production using an agro-deep learning framework in precision agriculture.

BMC bioinformatics
BACKGROUND: The study focuses on enhancing the effectiveness of precision agriculture through the application of deep learning technologies. Precision agriculture, which aims to optimize farming practices by monitoring and adjusting various factors i...

Impacts of micro/nano plastics on the ecotoxicological effects of antibiotics in agricultural soil: A comprehensive study based on meta-analysis and machine learning prediction.

The Science of the total environment
Micro/nano plastics (M/NPs) and antibiotics, as widely coexisting pollutants in environment, pose serious threats to soil ecosystem. The purpose of this study was to systematically evaluate the ecological effects of the co-exposure of M/NPs and antib...