AIMC Topic: Plant Breeding
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Computer vision-based phenotyping for improvement of plant productivity: a machine learning perspective.
GigaScience
Jan 1, 2019
Employing computer vision to extract useful information from images and videos is becoming a key technique for identifying phenotypic changes in plants. Here, we review the emerging aspects of computer vision for automated plant phenotyping. Recent a...
DeepSort: deep convolutional networks for sorting haploid maize seeds.
BMC bioinformatics
Aug 13, 2018
BACKGROUND: Maize is a leading crop in the modern agricultural industry that accounts for more than 40% grain production worldwide. THe double haploid technique that uses fewer breeding generations for generating a maize line has accelerated the pace...
A heuristic method for fast and accurate phasing and imputation of single-nucleotide polymorphism data in bi-parental plant populations.
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Aug 4, 2018
Key message New fast and accurate method for phasing and imputation of SNP chip genotypes within diploid bi-parental plant populations. This paper presents a new heuristic method for phasing and imputation of genomic data in diploid plant species. Ou...
Image set for deep learning: field images of maize annotated with disease symptoms.
BMC research notes
Jul 3, 2018
OBJECTIVES: Automated detection and quantification of plant diseases would enable more rapid gains in plant breeding and faster scouting of farmers' fields. However, it is difficult for a simple algorithm to distinguish between the target disease and...
Cotton genotypes selection through artificial neural networks.
Genetics and molecular research : GMR
Sep 27, 2017
Breeding programs currently use statistical analysis to assist in the identification of superior genotypes at various stages of a cultivar's development. Differently from these analyses, the computational intelligence approach has been little explore...
Artificial neural networks as auxiliary tools for the improvement of bean plant architecture.
Genetics and molecular research : GMR
Jun 29, 2017
Classification using a scale of visual notes is a strategy used to select erect bean plants in order to improve bean plant architectures. Use of morphological traits associated with the phenotypic expression of bean architecture in classification pro...
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...
A review of the journey of field crop phenotyping: From trait stamp collections and fancy robots to phenomics-informed crop performance predictions.
Journal of plant physiology
Aug 1, 2025
Crop phenotyping encompasses methodologies for measuring plant growth, architecture, and composition with high precision across scales, from organs to canopies. Field-based phenotyping is pivotal in bridging genomic data with crop performance, offeri...
Genomics-assisted breeding for designing salinity-smart future crops.
Plant biotechnology journal
Aug 1, 2025
Climate change induces many abiotic stresses, including soil salinity, significantly challenging global agriculture. Salinity stress tolerance (SST) is a complex trait, both physiologically and genetically, and is conferred at various levels of plant...
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...
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