AIMC Topic: Glycine max

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Rapid characterization of metabolites in soybean using ultra high performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS/MS) and screening for α-glucosidase inhibitory and antioxidant properties through different solvent systems.

Journal of food and drug analysis Jun 15, 2017
This work was the first to investigate on the simultaneous characterization of metabolite profiles in soybean using UPLC-ESI-Q-TOF-MS/MS. Twenty two compositions were observed within 14 min from the methanol extract and confirmed as twelve isoflavone...
Glycine max Metabolome Spectrometry, Mass, Electrospray Ionization Phytochemicals Isoflavones Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization Solvents Molecular Structure Antioxidants Glycoside Hydrolase Inhibitors Chromatography, High Pressure Liquid Tandem Mass Spectrometry Plant Extracts Metabolomics
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Computer vision and machine learning for robust phenotyping in genome-wide studies.

Scientific reports Mar 8, 2017
Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic stu...
Image Processing, Computer-Assisted Stress, Physiological Genome-Wide Association Study Glycine max Quantitative Trait Loci Artificial Intelligence Machine Learning Phenotype
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Clustering of soybean genotypes via Ward-MLM and ANNs associated with mixed models.

Genetics and molecular research : GMR Aug 5, 2016
The objectives of this study were to use mixed models to confirm the presence of genetic variability in 16 soybean genotypes, to compare clusters generated by artificial neural networks (ANNs) with those created by the Ward modified location model (M...
Glycine max Models, Genetic Cluster Analysis Genotype Neural Networks, Computer
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Application of self-organising maps towards segmentation of soybean samples by determination of amino acids concentration.

Plant physiology and biochemistry : PPB May 13, 2016
Soybeans are widely used both for human nutrition and animal feed, since they are an important source of protein, and they also provide components such as phytosterols, isoflavones, and amino acids. In this study, were determined the concentrations o...
Neural Networks, Computer Amino Acids Glycine max
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Virtual screening of umami peptides during sufu ripening based on machine learning and molecular docking to umami receptor T1R1/T1R3.

Food chemistry Sep 15, 2025
Umami peptides might significantly contribute to the taste of sufu. However, the inefficiencies of traditional identification methods had great limitations. This study explored a new approach for umami peptides characterization in sufu. Combining pep...
Receptors, G-Protein-Coupled Humans Amino Acid Sequence Machine Learning Peptides Glycine max Molecular Docking Simulation Soy Foods Taste Flavoring Agents
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SoyDNGP: a web-accessible deep learning framework for genomic prediction in soybean breeding.

Briefings in bioinformatics Sep 22, 2023
Soybean is a globally significant crop, playing a vital role in human nutrition and agriculture. Its complex genetic structure and wide trait variation, however, pose challenges for breeders and researchers aiming to optimize its yield and quality. A...
Humans Phenotype Genome, Plant Genomics Deep Learning Plant Breeding Glycine max
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Use of in vitro dry matter digestibility and gas production to predict apparent total tract digestibility of total dietary fiber for growing pigs.

Journal of animal science Dec 1, 2017
In vitro DM disappearance (IVDMD) and gas production methods have been developed and used to measure in vivo nutrient digestibility of feed ingredients, but further validation is needed for ingredients containing high concentrations of insoluble fibe...
Zea mays Triticum Dietary Fiber Animal Feed Diet Swine Animals Digestion Glycine max Fermentation Gastrointestinal Tract
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