AIMC Topic: Triticum

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TrG2P: A transfer-learning-based tool integrating multi-trait data for accurate prediction of crop yield.

Plant communications May 15, 2024
Yield prediction is the primary goal of genomic selection (GS)-assisted crop breeding. Because yield is a complex quantitative trait, making predictions from genotypic data is challenging. Transfer learning can produce an effective model for a target...
Genotype Zea mays Phenotype Crops, Agricultural Plant Breeding Oryza Triticum Machine Learning Neural Networks, Computer
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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...
Droughts Triticum Stress, Physiological Seasons Deep Learning China
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Estimation of wheat protein content and wet gluten content based on fusion of hyperspectral and RGB sensors using machine learning algorithms.

Food chemistry Mar 22, 2024
The protein content (PC) and wet gluten content (WGC) are crucial indicators determining the quality of wheat, playing a pivotal role in evaluating processing and baking performance. Original reflectance (OR), wavelet feature (WF), and color index (C...
Machine Learning Algorithms Glutens Plant Proteins Triticum
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Precision in wheat flour classification: Harnessing the power of deep learning and two-dimensional correlation spectrum (2DCOS).

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Mar 5, 2024
Wheat flour is a ubiquitous food ingredient, yet discerning its various types can prove challenging. A practical approach for identifying wheat flour types involves analyzing one-dimensional near-infrared spectroscopy (NIRS) data. This paper introduc...
Algorithms Flour Triticum Deep Learning Least-Squares Analysis Spectroscopy, Near-Infrared
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The use of Multispectral Radio-Meter (MSR5) data for wheat crop genotypes identification using machine learning models.

Scientific reports Nov 14, 2023
Satellite remote sensing is widely being used by the researchers and geospatial scientists due to its free data access for land observation and agricultural activities monitoring. The world is suffering from food shortages due to the dramatic increas...
Triticum Machine Learning Neural Networks, Computer Logistic Models Agriculture
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Discrimination of wheat flour grade based on PSO-SVM of hyperspectral technique.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jun 19, 2023
Rapid detection of wheat flour grade played an important role in the food industry. In this work, hyperspectral technology was used to detect five types of wheat flour. An analysis model was established based on the reflectance of samples at 968 ∼ 25...
Algorithms Support Vector Machine Spectroscopy, Near-Infrared Triticum Least-Squares Analysis Flour
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Evaluation of AquaCrop and intelligent models in predicting yield and biomass values of wheat.

International journal of biometeorology Feb 28, 2023
AquaCrop is one of the dynamic and user-friendly models for simulating different conditions governing plant growth in the field. But this model requires many input parameters such as plant information, soil, climate, groundwater, and management facto...
Climate Biomass Triticum Algorithms Neural Networks, Computer
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Determination of Wheat Heading Stage Using Convolutional Neural Networks on Multispectral UAV Imaging Data.

Computational intelligence and neuroscience Nov 24, 2022
The heading and flowering stages are crucial for wheat growth and should be used for fusarium head blight (FHB) and other plant prevention operations. Rapid and accurate monitoring of wheat growth in hilly areas is critical for determining plant prot...
Triticum Support Vector Machine Neural Networks, Computer Diagnostic Imaging
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Uncertainty and spatial analysis in wheat yield prediction based on robust inclusive multiple models.

Environmental science and pollution research international Oct 20, 2022
Reliable prediction of wheat yield ahead of harvest is a critical challenge for decision-makers along the supply chain. Predicting wheat yield is a real challenge for better agriculture and food security management. Modeling wheat yield is complex an...
Spatial Analysis Uncertainty Algorithms Triticum Neural Networks, Computer
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Online Detection System for Wheat Machine Harvesting Impurity Rate Based on DeepLabV3.

Sensors (Basel, Switzerland) Oct 8, 2022
Wheat, one of the most important food crops in the world, is usually harvested mechanically by combine harvesters. The impurity rate is one of the most important indicators of the quality of wheat obtained by mechanized harvesting. To realize the onl...
Online Systems Triticum Neural Networks, Computer
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