AIMC Topic: Triticum

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Predicting wheat yield using deep learning and multi-source environmental data.

Scientific reports Jul 21, 2025
Accurate forecasting of crop yields is essential for ensuring food security and promoting sustainable agricultural practices. Winter wheat, a key staple crop in Pakistan, faces challenges in yield prediction because of the complex interactions among ...
Neural Networks, Computer Forecasting Soil Triticum Pakistan Crops, Agricultural Deep Learning Agriculture
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Modeling impacts of climate-induced yield variability and adaptations on wheat and maize in a sub-tropical monsoon climate - using fuzzy logic.

Scientific reports Jul 16, 2025
Climate change is causing more frequent and extraordinary extreme weather events that are already negatively affecting crop production. There is a need for improved climate risk assessment by developing smart adaptation strategies for sustainable fut...
Adaptation, Physiological Rain Triticum Seasons Crops, Agricultural Bangladesh Climate Change Models, Theoretical Temperature Fuzzy Logic Zea mays
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AI-Accelerated Identification of Novel Antimicrobial Peptides for Inhibiting .

Journal of agricultural and food chemistry Jul 1, 2025
Fusarium head blight caused by threatens global wheat production, causing substantial yield reduction and mycotoxin accumulation. This study harnessed machine learning to accelerate the discovery of antifungal peptides targeting this phytopathogen. ...
Fungicides, Industrial Molecular Dynamics Simulation Plant Diseases Antimicrobial Peptides Fusarium Machine Learning Triticum
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Evaluation of different spectral indices for wheat lodging assessment using machine learning algorithms.

Scientific reports Jul 1, 2025
Wheat lodging is a recurrent phenomenon that significantly affects grain yield and impedes the harvesting efficiency. Therefore, the precise and rapid assessment of wheat lodging is crucial in minimizing its impact on grain yield and quality. Recentl...
India Support Vector Machine Triticum Machine Learning Algorithms
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Enhanced wheat yield prediction through integrated climate and satellite data using advanced AI techniques.

Scientific reports May 24, 2025
Wheat plays a vital role in Pakistan's economy and food security, making accurate yield forecasting essential for planning and resource management. Traditional approaches-such as manual field surveys and remote sensing-have been widely used, but thei...
Agriculture Remote Sensing Technology Pakistan Climate Crops, Agricultural Machine Learning Forecasting Triticum Satellite Imagery Deep Learning
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Predicting land suitability for wheat and barley crops using machine learning techniques.

Scientific reports May 7, 2025
Ensuring food security to meet the demands of a growing population remains a key challenge, especially for developing countries like Ethiopia. There are various policies and strategies designed by the government and stakeholders to confront the chall...
Agriculture Ethiopia Crops, Agricultural Triticum Hordeum Machine Learning
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Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.

Plant biotechnology journal Apr 20, 2025
Big data, combined with artificial intelligence (AI) techniques, holds the potential to significantly enhance the accuracy of genome-wide predictions. Motivated by the success reported for wheat hybrids, we extended the scope to inbred lines by integ...
Genome, Plant Plant Breeding Genomics Polymorphism, Single Nucleotide Triticum Artificial Intelligence Genotype Feasibility Studies Phenotype Genome-Wide Association Study
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Novel hybrid transfer neural network for wheat crop growth stages recognition using field images.

Scientific reports Apr 7, 2025
Wheat is one of the world's most widely cultivated cereal crops and is a primary food source for a significant portion of the population. Wheat goes through several distinct developmental phases, and accurately identifying these stages is essential f...
Image Processing, Computer-Assisted Agriculture Crops, Agricultural Neural Networks, Computer Triticum
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Enhancing the application of near-infrared spectroscopy in grain mycotoxin detection: An exploration of a transfer learning approach across contaminants and grains.

Food chemistry Mar 17, 2025
Cereals are a primary source of sustenance for humanity. Monitoring, controlling, and preventing mycotoxins in cereals are vital for ensuring the safety of the cereals and their derived products. This study introduces transfer learning strategies int...
Triticum Edible Grain Mycotoxins Spectroscopy, Near-Infrared Food Contamination Arachis
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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...
Agriculture Plant Diseases Smartphone Support Vector Machine Humans Mobile Applications Pakistan Triticum Machine Learning Crops, Agricultural
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