AIMC Topic: Agriculture

Clear Filters Showing 1 to 10 of 409 articles

Towards practical AI for agriculture: A self-supervised attention framework for Spinach leaf disease detection.

PloS one
Malabar spinach is a nutrient-dense leafy vegetable widely cultivated and consumed in Bangladesh. Its productivity is often compromised by Alternaria leaf spot and straw mite infestations. This work proposes an efficient and interpretable deep learni...

Geospatial modeling and forecasting of urban land use change using Google Earth Engine and machine learning.

PloS one
Urban expansion and Land Use Land Cover (LULC) change pose critical challenges for sustainable urban planning and risks to food security. This study analyzes multi-temporal Landsat imagery from 1990 to 2020 for five major cities, Islamabad, Karachi, ...

A novel agricultural commodity price prediction model integrating deep learning and enhanced swarm intelligence algorithm.

PloS one
The volatility of agricultural commodity prices significantly affects market stability and financial market dynamics, especially during periods of economic uncertainty and global shocks. Accurate price prediction, however, remains challenging due to ...

Land use change and soil salinization in the Sundarbans: a machine-learning based analysis of long-term transformation and future projections.

Environmental monitoring and assessment
Quantitative data on coastal land use changes are essential for effective resource management and sustainable development. In this study, we examined land use and land cover (LULC) changes, along with erosion and accretion, in the climate-sensitive S...

High-performance parallel multi-scale attention network with explainable AI for intelligent diagnosis of leaf diseases in agricultural systems.

Scientific reports
Detecting leaf diseases is crucial for ensuring crop health and boosting agricultural productivity. An advanced deep learning-based framework is introduced for cassava and groundnut leaf disease detection, incorporating a suite of innovative techniqu...

Explainable AI-driven interpretation of environmental drivers of tomato fruit expansion in smart greenhouses using IoT sensing.

Scientific reports
Tomato fruit expansion is a key physiological process that determines fruit size, marketability, and yield, yet its quantitative and threshold-based response to microclimatic factors in smart greenhouses has been insufficiently studied. This study de...

An AI-powered smart Agribot for detecting locusts in farmlands using IoT and deep learning.

Scientific reports
In many countries, locusts have significantly harmed agricultural production. To prevent their spread, the Agriculture Robot (Agribot) with cutting-edge technologies like the Internet of Things (IoT) and Machine Learning (ML) can be a possible soluti...

Impact of agricultural subsidy on chemical fertilizer use: Empirical evidence of China's Organic-Substitute-Chemical-Fertilizer policy based on double machine learning.

PloS one
The sustainable development of agriculture hinges on effective fertilizer management, and China's experience with chemical fertilizer overuse highlights the challenges and opportunities in this domain. This study examines the impact of agricultural s...

A novel integrated framework for long-term assessment of ecosystem service degradation and restoration prioritization in a semi-arid rift valley landscape.

Environmental monitoring and assessment
Wetland ecosystems in Africa's semi-arid rift valleys are crucial for supporting biodiversity, regulating water systems, and sustaining livelihoods; however, they are rapidly deteriorating due to agricultural expansion and urbanization. Previous asse...

Computer intelligence based model for mental health detection among Indian farming communities.

Scientific reports
Mental health challenges among Indian farmers are a critical yet under reviewed public health problem, especially in rural areas where access to men's health professionals is limited. Stress from crop failure, fluctuating prices, debt, and poor socia...