AIMC Topic: 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...
Machine Learning Forecasting Remote Sensing Technology Triticum Pakistan Deep Learning Agriculture Satellite Imagery Crops, Agricultural Climate
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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...
Crops, Agricultural Hordeum Machine Learning Ethiopia Triticum Agriculture
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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...
Phenotype Genome, Plant Artificial Intelligence Genome-Wide Association Study Plant Breeding Triticum Polymorphism, Single Nucleotide Genomics Feasibility Studies Genotype
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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...
Crops, Agricultural Agriculture Triticum Neural Networks, Computer Image Processing, Computer-Assisted
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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...
Humans Mobile Applications Agriculture Machine Learning Pakistan Crops, Agricultural Support Vector Machine Smartphone Plant Diseases Triticum
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Prediction of Deoxynivalenol contamination in wheat kernels and flour based on visible near-infrared spectroscopy, feature selection and machine learning modelling.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 7, 2025
Contamination of wheat by the mycotoxin Deoxynivalenol (DON), produced by Fusarium fungi, poses significant challenges to the quality of crop yield and food safety. Visible and near-infrared (vis-NIR) spectroscopy has emerged as a promising, non-dest...
Food Contamination Algorithms Triticum Trichothecenes Spectroscopy, Near-Infrared Machine Learning Flour
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Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models.

Sensors (Basel, Switzerland) Jan 7, 2025
Wheat is a globally cultivated cereal crop with substantial protein content present in its seeds. This research aimed to develop robust methods for predicting seed protein concentration in wheat seeds using bench-top hyperspectral imaging in the visi...
Plant Proteins Spectroscopy, Near-Infrared Convolutional Neural Networks Seeds Neural Networks, Computer Triticum Image Processing, Computer-Assisted Machine Learning Hyperspectral Imaging Support Vector Machine
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An effective method for detecting the wheat freshness by integrating biophotonics and machine learning algorithm.

Scientific reports Dec 30, 2024
The accurate and timely assessment of wheat freshness is not only a complex scientific endeavor but also a critical aspect of grain storage safety. This study introduces an innovative approach for evaluating wheat freshness by integrating machine lea...
Support Vector Machine Machine Learning Triticum Algorithms
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Wheat disease recognition method based on the SC-ConvNeXt network model.

Scientific reports Dec 30, 2024
When utilizing convolutional neural networks for wheat disease identification, the training phase typically requires a substantial amount of labeled data. However, labeling data is both complex and costly. Additionally, the model's recognition perfor...
Neural Networks, Computer Algorithms Triticum Plant Diseases
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