AIMC Topic: Crops, Agricultural

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Optimizing chickpea yield prediction under wilt disease through synergistic integration of biophysical and image parameters using machine learning models.

Scientific reports Feb 5, 2025
Crop health assessment and early yield predictions are highly crucial under biotic stress conditions for crop management and market planning by farmers and policy planners. The objective of this study was, therefore, to assess the impact of different...
Machine Learning Plant Diseases Plant Leaves Photosynthesis Cicer Crops, Agricultural Genotype
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Federated learning based reference evapotranspiration estimation for distributed crop fields.

PloS one Feb 5, 2025
Water resource management and sustainable agriculture rely heavily on accurate Reference Evapotranspiration (ETo). Efforts have been made to simplify the (ETo) estimation using machine learning models. The existing approaches are limited to a single ...
Plant Transpiration Federated Learning Pakistan Machine Learning Agriculture Crops, Agricultural Weather
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Integrating deep learning algorithms for forecasting evapotranspiration and assessing crop water stress in agricultural water management.

Journal of environmental management Jan 31, 2025
The increasing impacts of climate change on global agriculture necessitate the development of advanced predictive models for efficient water management in crop fields. This study aims to enhance the forecasting of evapotranspiration (ET), potential e...
Climate Change Crops, Agricultural Agricultural Irrigation Deep Learning Water Agriculture Algorithms Forecasting Neural Networks, Computer
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Application of machine learning and genomics for orphan crop improvement.

Nature communications Jan 24, 2025
Orphan crops are important sources of nutrition in developing regions and many are tolerant to biotic and abiotic stressors; however, modern crop improvement technologies have not been widely applied to orphan crops due to the lack of resources avail...
Genomics Crops, Agricultural Machine Learning Plant Breeding
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Using machine learning to predict selenium content in crops: Implications for soil health and agricultural land utilization in longevity regions.

The Science of the total environment Jan 21, 2025
Selenium (Se) is an indispensable trace element to human health, yet its biological tolerance threshold is relatively narrow. The potential application of machine learning methods to indirectly predict the Se content in crops across regional areas, t...
Crops, Agricultural Agriculture Environmental Monitoring Soil Pollutants Soil Selenium Neural Networks, Computer Machine Learning
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A Review of CNN Applications in Smart Agriculture Using Multimodal Data.

Sensors (Basel, Switzerland) Jan 15, 2025
This review explores the applications of Convolutional Neural Networks (CNNs) in smart agriculture, highlighting recent advancements across various applications including weed detection, disease detection, crop classification, water management, and y...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Agriculture Crops, Agricultural Machine Learning Deep Learning
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Understanding the spread of agriculture in the Western Mediterranean (6th-3rd millennia BC) with Machine Learning tools.

Nature communications Jan 15, 2025
The first Neolithic farmers arrived in the Western Mediterranean area from the East. They established settlements in coastal areas and over time migrated to new environments, adapting to changing ecological and climatic conditions. While farming prac...
Humans Crops, Agricultural Climate Mediterranean Region Agriculture Climate Change Machine Learning Archaeology Radiometric Dating History, Ancient Human Migration
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Improving early prediction of crop yield in Spanish olive groves using satellite imagery and machine learning.

PloS one Jan 15, 2025
In the production sector, the usefulness of predictive systems as a tool for management and decision-making is well known. In the agricultural sector, a correct economic balance of the farm depends on making the right decisions. For this purpose, hav...
Satellite Imagery Crop Production Crops, Agricultural Spain Machine Learning Seasons Olea Agriculture
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An efficient smart phone application for wheat crop diseases detection using advanced machine learning.

PloS one Jan 8, 2025
Globally, agriculture holds significant importance for human food, economic activities, and employment opportunities. Wheat stands out as the most cultivated crop in the farming sector; however, its annual production faces considerable challenges fro...
Crops, Agricultural Plant Diseases Triticum Pakistan Machine Learning Humans Smartphone Agriculture Mobile Applications Support Vector Machine
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Cropformer: An interpretable deep learning framework for crop genomic prediction.

Plant communications Dec 16, 2024
Machine learning and deep learning are extensively employed in genomic selection (GS) to expedite the identification of superior genotypes and accelerate breeding cycles. However, a significant challenge with current data-driven deep learning models ...
Genome, Plant Plant Breeding Zea mays Oryza Phenotype Genomics Solanum lycopersicum Deep Learning Crops, Agricultural Polymorphism, Single Nucleotide Genotype Triticum
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