AIMC Topic: Agriculture
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Advancing food security: Rice yield estimation framework using time-series satellite data & machine learning.
PloS one
Dec 12, 2024
Timely and accurately estimating rice yields is crucial for supporting food security management, agricultural policy development, and climate change adaptation in rice-producing countries such as Bangladesh. To address this need, this study introduce...
Comprehensive Investigation of Machine Learning and Deep Learning Networks for Identifying Multispecies Tomato Insect Images.
Sensors (Basel, Switzerland)
Dec 9, 2024
Deep learning applications in agriculture are advancing rapidly, leveraging data-driven learning models to enhance crop yield and nutrition. Tomato (), a vegetable crop, frequently suffers from pest damage and drought, leading to reduced yields and f...
Integrating Sentinel-1 data and machine learning for effective paddy field monitoring in Cauvery Delta Zone, Tamil Nadu, India.
Environmental monitoring and assessment
Dec 5, 2024
Paddy crop mapping is essential for agricultural monitoring, ensuring food security, and enhancing resource allocation. This study observes the Cauvery Delta Zone (CDZ), recognized as the rice bowl of Tamil Nadu and a crucial area for paddy farming i...
Smart agriculture: utilizing machine learning and deep learning for drought stress identification in crops.
Scientific reports
Dec 3, 2024
Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep learning. This is a significant step toward sustainable agriculture. Innovative insights into the ph...
Enhanced forecasting of rice price and production in Malaysia using novel multivariate fuzzy time series models.
Scientific reports
Dec 2, 2024
A significant portion of the world's population relies on rice as a primary source of nutrition. In Malaysia, rice production began in the early 1960s, which led to the cultivation of the country's most significant food crop up till the present day. ...
Developing novel spectral indices for precise estimation of soil pH and organic carbon with hyperspectral data and machine learning.
Environmental monitoring and assessment
Nov 26, 2024
Accurate soil pH and soil organic carbon (SOC) estimations are vital for sustainable agriculture, as pH affects nutrient availability, and SOC is crucial for soil health and fertility. Hyperspectral imaging provides a faster, non-destructive, and eco...
Artificial intelligence-driven assessment of critical inputs for lead adsorption by agro-food wastes in wastewater treatment.
Chemosphere
Nov 25, 2024
Due to environmental concerns and economic value, the adsorption process using agricultural wastes is one of the promising methods to remove lead (Pb) from contaminated water. The relationships between agricultural waste properties, adsorption condit...
Deployment of intelligent irrigation monitoring system with Android app for machine learning prediction.
Environmental monitoring and assessment
Nov 21, 2024
Water is a fundamental necessity for humans and a critical resource in agriculture. However, water scarcity poses a significant challenge, especially considering that agriculture accounts for a substantial portion of freshwater usage. The inadequate ...
Towards efficient IoT communication for smart agriculture: A deep learning framework.
PloS one
Nov 21, 2024
The integration of IoT (Internet of Things) devices has emerged as a technical cornerstone in the landscape of modern agriculture, revolutionising the way farming practises are viewed and managed. Smart farming, enabled by interconnected sensors and ...
Fuzzy multi-objective optimization for sustainable agricultural water management of irrigation networks.
Journal of environmental management
Nov 20, 2024
Sustainable water resource management in arid and water deficit regions requires optimal use of water resources due to competition among different water sectors. The purpose of this study is to model uncertainties in economic and hydro-climatic varia...
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