Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Non-destructive detection strategy of maize seed vigor based on seed phenotyping and the potential for accelerating breeding.

Journal of advanced research - 1 Oct 2025

Tu Keling, Wen Shaozhe, Xu Yanan, He Hongju, Li He, Xu Rugen, Guo Baojian, Sun Chengming, Gu Riliang, Sun Qun

Abstract excerpt

INTRODUCTION: Seeds are fundamental to agricultural production, and their vigor affects seedling quality, quantity, and crop yield. Accurate vigor assessment methods are crucial for agricultural productivity. OBJECTIVES: Traditional seed vigor testing and phenotypic trait acquisition methods are complex, time-consuming, or destructive. Thus, this study aims to develop a non-destructive method for assessing maize...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Germination
Share to Phenotype

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Plant Breeding

Share to Zea mays

Source

Open in PubMed Open full text

Identifiers

PMID: 39725006
DOI: 10.1016/j.jare.2024.12.022
PMCID: PMC12793759

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Non-destructive detection strategy of maize seed vigor based on seed phenotyping and the potential for accelerating breeding.PMID 39725006Read ↗

Combining Hyperspectral Techniques and Genome-Wide Association Studies to Predict Peanut Seed Vigor and Explore Associated Genetic Loci.Semantic proximity Read ↗

QTLs for seed vigor-related traits identified in maize seeds germinated under artificial aging conditions.Semantic proximity Read ↗

SeedGerm-VIG: an open and comprehensive pipeline to quantify seed vigor in wheat and other cereal crops using deep learning-powered dynamic phenotypic analysis.Semantic proximity Read ↗

Dissecting the genetic architecture of seed-related traits in Brassica napus by integrating multi-omics analysis and VIS-NIR hyperspectral imaging.Semantic proximity Read ↗

Construction of High-Density Genetic Map and Identification of QTLs Associated with Seed Vigor after Exposure to Artificial Aging Conditions in Sweet Corn Using SLAF-seq.Semantic proximity Read ↗

Pollen Germination as a High-Throughput Phenotyping Tool for Assessing Heat Tolerance in SoybeanSemantic proximity Read ↗

A genome-wide association study uncovers a ZmRap2.7-ZCN9/ZCN10 module to regulate ABA signalling and seed vigour in maize.Semantic proximity Read ↗

Seed coat color genetics and genotype × environment effects in yellow beans via machine-learning and genome-wide association.Semantic proximity Read ↗

A multivariate approach to the physical and physiological quality of hybrid corn seeds affected by Molicutes and MRFVSemantic proximity Read ↗

SUnSeT: spectral unmixing of hyperspectral images for phenotyping soybean seed traits.Semantic proximity Read ↗

Integrated multi-omics approach to reveal the molecular networks underlying the seed germination of Polygonatum cyrtonemaSemantic proximity Read ↗

Towards the Development, Maintenance and Standardized Phenotypic Characterization of Single-Seed-Descent Genetic Resources for Chickpea.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.