AIMC Topic: Fabaceae

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Integrating multi-omics and machine learning for disease resistance prediction in legumes.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik Jun 27, 2025
Multi-omics assisted prediction of disease resistance mechanisms using machine learning has the potential to accelerate the breeding of resistant legume varieties. Grain legumes, such as soybean (Glycine max (L.) Merr.), chickpea (Cicer arietinum L.)...
Machine Learning Plant Diseases Disease Resistance Plant Breeding Multiomics Fabaceae Genomics
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Clustering and classification for dry bean feature imbalanced data.

Scientific reports Dec 28, 2024
The traditional machine learning methods such as decision tree (DT), random forest (RF), and support vector machine (SVM) have low classification performance. This paper proposes an algorithm for the dry bean dataset and obesity levels dataset that c...
Decision Trees Humans Fabaceae Cluster Analysis Algorithms Machine Learning Obesity Support Vector Machine
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ProTformer: Transformer-based model for superior prediction of protein content in lablab bean (Lablab purpureus L.) using Near-Infrared Reflectance spectroscopy.

Food research international (Ottawa, Ont.) Oct 1, 2024
Lablab bean (Lablab purpureus L.), known for its higher protein content provides a promising alternative to reduce reliance on animal-based proteins and support sustainable agriculture. Nowadays, traditional methods for nutritional profiling have bee...
Neural Networks, Computer Plant Proteins Least-Squares Analysis Spectroscopy, Near-Infrared Fabaceae Genotype Nutritive Value
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Nutritional, chemical and functional potential of Inga laurina (Fabaceae): A barely used edible species.

Food research international (Ottawa, Ont.) Dec 20, 2023
Inga laurina is a plant species which produces edible fruits, and until now there is little information available concerning its nutritional, chemical and bioactive composition. In this study, we evaluated for the first time the proximate composition...
Minerals Butanols Acetates Phenols Quercetin Antioxidants Fabaceae Plant Extracts
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Waste valorization as low-cost media engineering for auxin production from the newly isolated Streptomyces rubrogriseus AW22: Model development.

Chemosphere Mar 15, 2023
Indole-3-acetic acid (IAA) represents a crucial phytohormone regulating specific tropic responses in plants and functions as a chemical signal between plant hosts and their symbionts. The Actinobacteria strain of AW22 with high IAA production ability...
Neural Networks, Computer Reproducibility of Results Streptomyces Indoleacetic Acids Plant Growth Regulators Fabaceae Plants
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Modeling risk of Sclerotinia sclerotiorum-induced disease development on canola and dry bean using machine learning algorithms.

Scientific reports Jan 17, 2022
Diseases caused by the fungus Sclerotinia sclerotiorum are managed mainly through fungicide applications in canola and dry bean. Accurate estimation of the risk of disease development on these crops could help farmers make spraying decisions. Five ma...
Ascomycota Brassica napus Logistic Models Fungicides, Industrial Crops, Agricultural Temperature Neural Networks, Computer Plant Diseases Risk Assessment Machine Learning Fabaceae Agriculture
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Advances in for Abiotic Stress Resilience: From 'Omics' to Artificial Intelligence.

International journal of molecular sciences Sep 29, 2021
Legumes are a better source of proteins and are richer in diverse micronutrients over the nutritional profile of widely consumed cereals. However, when exposed to a diverse range of abiotic stresses, their overall productivity and quality are hugely ...
Fabaceae Artificial Intelligence Crops, Agricultural Quantitative Trait Loci Stress, Physiological Genomics Plant Breeding
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Morphological traits of drought tolerant horse gram germplasm: classification through machine learning.

Journal of the science of food and agriculture Jul 3, 2020
BACKGROUND: Horse gram (Macrotyloma uniflorum (Lam.) Verdc.) is an underutilized pulse crop with good drought resistance traits. It is a rich source of protein. Conventional breeding methods for high yielding and abiotic stress tolerant germplasm are...
Phenotype Genotype Fabaceae Stress, Physiological Seeds Machine Learning Algorithms Plant Breeding Quantitative Trait Loci Droughts
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Predicting Forage Quality of Warm-Season Legumes by Near Infrared Spectroscopy Coupled with Machine Learning Techniques.

Sensors (Basel, Switzerland) Feb 6, 2020
Warm-season legumes have been receiving increased attention as forage resources in the southern United States and other countries. However, the near infrared spectroscopy (NIRS) technique has not been widely explored for predicting the forage quality...
Calibration Animal Feed Seasons Reproducibility of Results Spectroscopy, Near-Infrared Fabaceae Machine Learning Temperature
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Assessment of CNN-Based Methods for Individual Tree Detection on Images Captured by RGB Cameras Attached to UAVs.

Sensors (Basel, Switzerland) Aug 18, 2019
Detection and classification of tree species from remote sensing data were performed using mainly multispectral and hyperspectral images and Light Detection And Ranging (LiDAR) data. Despite the comparatively lower cost and higher spatial resolution,...
Fabaceae Neural Networks, Computer Likelihood Functions Remote Sensing Technology Deep Learning Discriminant Analysis Photography
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