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Plant Breeding

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DeepSort: deep convolutional networks for sorting haploid maize seeds.

BMC bioinformatics
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
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
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...

Post-composing ontology terms for efficient phenotyping in plant breeding.

Database : the journal of biological databases and curation
Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored to diverse use cases, post-composing user-defined terms reconciles the demands for standardization on...

WheatGP, a genomic prediction method based on CNN and LSTM.

Briefings in bioinformatics
Wheat plays a crucial role in ensuring food security. However, its complex genetic structure and trait variation pose significant challenges for breeding superior varieties. In this study, a genomic prediction method for wheat (WheatGP) is proposed. ...

Integration of machine learning and genome-wide association study to explore the genomic prediction accuracy of agronomic trait in oats (Avena sativa L.).

The plant genome
Machine learning (ML) has garnered significant attention for its potential to enhance the accuracy of genomic predictions (GPs) in various economic crops with the use of complete genomic information. Genome-wide association studies (GWAS) are widely ...

Tasselyzer, a machine learning method to quantify maize anther exertion, based on PlantCV.

The Plant journal : for cell and molecular biology
Maize anthers emerge from male-only florets, a process that involves complex genetic programming and is affected by environmental factors. Quantifying anther exertion provides a key indicator of male fertility; however, traditional manual scoring met...

SoyDNGP: a web-accessible deep learning framework for genomic prediction in soybean breeding.

Briefings in bioinformatics
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...

Multi-modal deep learning improves grain yield prediction in wheat breeding by fusing genomics and phenomics.

Bioinformatics (Oxford, England)
MOTIVATION: Developing new crop varieties with superior performance is highly important to ensure robust and sustainable global food security. The speed of variety development is limited by long field cycles and advanced generation selections in plan...