AIMC Topic: Droughts

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Integration of remote sensing and machine learning algorithm for agricultural drought early warning over Genale Dawa river basin, Ethiopia.

Environmental monitoring and assessment Feb 4, 2025
Drought remains a menace in the Horn of Africa; as a result, the Ethiopia's Genale Dawa River Basin is one of the most vulnerable to agricultural drought. Hence, this study integrates remote sensing and machine learning algorithm for early warning id...
Algorithms Agriculture Environmental Monitoring Neural Networks, Computer Machine Learning Ethiopia Satellite Imagery Rivers Droughts Remote Sensing Technology
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A rapid method for assessing seed drought resistance using integrated ID-BOA-SVM.

Analytical methods : advancing methods and applications Dec 5, 2024
This study investigates the application of near-infrared spectroscopy (NIR) for assessing drought resistance in seeds, aiming to offer a rapid and efficient method suitable for large-scale primary screening. NIR spectroscopy is utilized to analyze fo...
Seeds Bayes Theorem Droughts Drought Resistance Zea mays Water Support Vector Machine Spectroscopy, Near-Infrared
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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...
Neural Networks, Computer Machine Learning Algorithms Support Vector Machine Crops, Agricultural Stress, Physiological Deep Learning Agriculture Droughts
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Integration of SPEI and machine learning for assessing the characteristics of drought in the middle ganga plain, an agro-climatic region of India.

Environmental science and pollution research international Oct 29, 2024
Drought, as a natural and intricate climatic phenomenon, poses challenges with implications for both natural ecosystems and socioeconomic conditions. Evaluating the characteristics of drought is a significant endeavor aimed at mitigating its impact o...
Climate Droughts Neural Networks, Computer Ecosystem India Machine Learning
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Genotype-specific responses to drought stress in myrtle ( L.): integrating machine learning techniques.

PeerJ Oct 7, 2024
BACKGROUND: Myrtle ( L.), native to the Mediterranean region of Türkiye, is a valuable plant with applications in traditional medicine, pharmaceuticals, and culinary practices. Understanding how myrtle responds to water stress is essential for sustai...
Stress, Physiological Droughts Machine Learning Myrtus Genotype
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Examining optimized machine learning models for accurate multi-month drought forecasting: A representative case study in the USA.

Environmental science and pollution research international Aug 13, 2024
The Colorado River has experienced a significant streamflow reduction in recent decades due to climate change, resulting in pronounced hydrological droughts that pose challenges to the environment and human activities. However, current models struggl...
Droughts Rivers Climate Change United States Machine Learning Models, Theoretical Forecasting
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Utilizing machine learning and bioinformatics analysis to identify drought-responsive genes affecting yield in foxtail millet.

International journal of biological macromolecules Jul 29, 2024
Drought stress is a major constraint on crop development, potentially causing huge yield losses and threatening global food security. Improving Crop's stress tolerance is usually associated with a yield penalty. One way to balance yield and stress to...
Gene Expression Regulation, Plant Droughts Genes, Plant Gene Expression Profiling Transcriptome Computational Biology Machine Learning Setaria Plant Plant Proteins Haplotypes Stress, Physiological
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Integrating non-invasive VIS-NIR and bioimpedance spectroscopies for stress classification of sweet basil (Ocimum basilicum L.) with machine learning.

Biosensors & bioelectronics Jul 17, 2024
Plant stress diagnosis is essential for efficient crop management and productivity increase. Under stress, plants undergo physiological and compositional changes. Vegetation indices obtained from leaf reflectance spectra and bioimpedance spectroscopy...
Machine Learning Spectroscopy, Near-Infrared Plant Leaves Salinity Stress, Physiological Biosensing Techniques Ocimum basilicum Dielectric Spectroscopy Support Vector Machine Droughts
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Enhancing drought resilience: machine learning-based vulnerability assessment in Uttar Pradesh, India.

Environmental science and pollution research international Jun 17, 2024
Drought is a natural and complex climatic hazard. It has both natural and social connotations. The purpose of this study is to use machine learning methods (MLAs) for drought vulnerability (DVM) in Uttar Pradesh, India. There were 18 factors used to ...
Machine Learning Droughts India
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Multimodal deep learning-based drought monitoring research for winter wheat during critical growth stages.

PloS one May 9, 2024
Wheat is a major grain crop in China, accounting for one-fifth of the national grain production. Drought stress severely affects the normal growth and development of wheat, leading to total crop failure, reduced yields, and quality. To address the la...
Stress, Physiological Deep Learning Droughts Triticum China Seasons
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