AIMC Topic: Hordeum

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Artificial intelligence models to predict acute phytotoxicity in petroleum contaminated soils.

Ecotoxicology and environmental safety Mar 9, 2020
Environment pollutants, especially those from total petroleum hydrocarbons (TPH), have a highly complex chemical, biological and physical impact on soils. Here we study this influence via modelling the TPH acute phytotoxicity effects on eleven sample...
Petroleum Islands Soil Microbiology Soil Pollutants Hydrocarbons Russia Hordeum Artificial Intelligence Soil Models, Theoretical Neural Networks, Computer
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Computer Vision Classification of Barley Flour Based on Spatial Pyramid Partition Ensemble.

Sensors (Basel, Switzerland) Jul 4, 2019
Imaging sensors are largely employed in the food processing industry for quality control. Flour from malting barley varieties is a valuable ingredient in the food industry, but its use is restricted due to quality aspects such as color variations and...
Food-Processing Industry Algorithms Image Processing, Computer-Assisted Support Vector Machine Random Allocation Hordeum Flour Artificial Intelligence Machine Learning
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Physicochemical characterization of an arabinoxylan-rich fraction from brewers' spent grain and its application as a release matrix for caffeine.

Food research international (Ottawa, Ont.) Sep 18, 2018
The brewers' spent grain is a by-product generated during brewery process and is a potential source for arabinoxylans (AX) extraction. In the present work, the extraction and characterization of an arabinoxylan-rich fraction from brewers' spent grain...
Hordeum Plasticizers Waste Products Delayed-Action Preparations Edible Grain Drug Liberation Caffeine Drug Carriers Kinetics Xylans Glycerol Fermentation Viscosity Food Microbiology Solubility Central Nervous System Stimulants
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Evaluation of a miniaturized NIR spectrometer for cultivar identification: The case of barley, chickpea and sorghum in Ethiopia.

PloS one Mar 21, 2018
Crop cultivar identification is fundamental for agricultural research, industry and policies. This paper investigates the feasibility of using visible/near infrared hyperspectral data collected with a miniaturized NIR spectrometer to identify cultiva...
Spectroscopy, Near-Infrared Support Vector Machine Ethiopia Discriminant Analysis Image Interpretation, Computer-Assisted Humans Cicer Sorghum Hordeum
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phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds.

Plant physiology Sep 23, 2016
The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning ...
Arabidopsis Ecotype Hordeum Quantitative Trait Loci Seeds Robotics Automation Phenotype Imaging, Three-Dimensional
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Machine learning based prediction by PlantCdMiner and experimental validation of cadmium-responsive genes in plants.

Journal of hazardous materials Aug 15, 2025
Plants have evolved diverse adaptive mechanisms to sense and respond to environmental stimuli such as cadmium stress. The regulation of gene expression plays a critical role in plant responses to abiotic stress. However, homologous genes from differe...
Machine Learning Cadmium Stress, Physiological Genes, Plant Arabidopsis Avicennia Hordeum Nicotiana Gene Expression Regulation, Plant
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Identification of Fusarium sambucinum species complex by surface-enhanced Raman spectroscopy and XGBoost algorithm.

Food chemistry Jul 15, 2025
Rapid and reliable identification of Fusarium fungi is crucial, due to their role in food spoilage and potential toxicity. Traditional identification methods are often time-consuming and resource-intensive. This study explores the use of surface-enha...
Spectrum Analysis, Raman Fusarium Hordeum Boosting Machine Learning Algorithms
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Assessing the performance of generative artificial intelligence in retrieving information against manually curated genetic and genomic data.

Database : the journal of biological databases and curation Feb 17, 2025
Curated resources at centralized repositories provide high-value service to users by enhancing data veracity. Curation, however, comes with a cost, as it requires dedicated time and effort from personnel with deep domain knowledge. In this paper, we ...
Humans Artificial Intelligence Hordeum Databases, Genetic Data Curation Triticum Genome, Plant Data Mining Quantitative Trait Loci Genomics Generative Artificial Intelligence
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MRI-Seed-Wizard: combining deep learning algorithms with magnetic resonance imaging enables advanced seed phenotyping.

Journal of experimental botany Jan 10, 2025
Evaluation of relevant seed traits is an essential part of most plant breeding and biotechnology programmes. There is a need for non-destructive, three-dimensional assessment of the morphometry, composition, and internal features of seeds. Here, we i...
Algorithms Phenotype Deep Learning Hordeum Magnetic Resonance Imaging Seeds Triticum
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