AIMC Topic: Phaseolus
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Detection of kidney bean leaf spot disease based on a hybrid deep learning model.
Scientific reports
Apr 1, 2025
Rapid diagnosis of kidney bean leaf spot disease is crucial for ensuring crop health and increasing yield. However, traditional machine learning methods face limitations in feature extraction, while deep learning approaches, despite their advantages,...
Research on variety identification of common bean seeds based on hyperspectral and deep learning.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Sep 24, 2024
Accurate, fast and non-destructive identification of varieties of common bean seeds is important for the cultivation and efficient utilization of common beans. This study is based on hyperspectral and deep learning to identify the varieties of common...
Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI.
Scientific reports
Jul 6, 2024
Common beans (CB), a vital source for high protein content, plays a crucial role in ensuring both nutrition and economic stability in diverse communities, particularly in Africa and Latin America. However, CB cultivation poses a significant threat to...
Robotic Sensing and Stimuli Provision for Guided Plant Growth.
Journal of visualized experiments : JoVE
Jul 1, 2019
Robot systems are actively researched for manipulation of natural plants, typically restricted to agricultural automation activities such as harvest, irrigation, and mechanical weed control. Extending this research, we introduce here a novel methodol...
Determination of soyasaponins in Fagioli di Sarconi beans (Phaseolus vulgaris L.) by LC-ESI-FTICR-MS and evaluation of their hypoglycemic activity.
Analytical and bioanalytical chemistry
Dec 21, 2017
Soyasaponins are oleanene-type triterpenoid saponins, naturally occurring in many edible plants that have attracted a great deal of attention for their role in preventing chronic diseases. The aim of this study was to establish the distribution and t...
Artificial intelligence in the selection of common bean genotypes with high phenotypic stability.
Genetics and molecular research : GMR
Apr 28, 2016
Artificial neural networks have been used for various purposes in plant breeding, including use in the investigation of genotype x environment interactions. The aim of this study was to use artificial neural networks in the selection of common bean g...
Environment ensemble models for genomic prediction in common bean (Phaseolus vulgaris L.).
The plant genome
Jun 1, 2025
For important food crops such as the common bean (Phaseolus vulgaris, L.), global demand continues to outpace the rate of genetic gain for quantitative traits. In this study, we leveraged the multi-environment trial (MET) dataset from the cooperative...
Water status and plant traits of dry bean assessment using integrated spectral reflectance and RGB image indices with artificial intelligence.
Scientific reports
May 14, 2025
This study investigated the potential of using remote sensing indices with artificial neural networks (ANNs) to quantify the responses of dry bean plants to water stress. Two field experiments were conducted with three irrigation regimes: 100% (B100)...
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