Genetic Diversity Assessment and Phenotypic Characterization of Crops—2nd Edition

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Crop Genetics, Genomics and Breeding".

Deadline for manuscript submissions: 30 April 2026 | Viewed by 102

Special Issue Editors


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Guest Editor
Faculty of Agrobiotechincal Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia
Interests: nutritional quality; wheatgrass; in vitro digestion; phenotypic diversity; genetic diversity
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Guest Editor
Institute of Field and Vegetable Crops, 21000 Novi Sad, Serbia
Interests: genetics; plant breeding; molecular biology; biotechnology; plant phenotyping; cereal and oil crops
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Special Issue Information

Dear Colleagues,

Genetic diversity assessment involves studying the genetic variations that are present within a crop species, which can help us understand their potential for adaptation and resilience and identify unique traits that may be beneficial for breeding purposes. Phenotypic characterization, on the other hand, focuses on observing and measuring the physical traits of crops such as yield, disease resistance, nutritional content, etc., providing valuable information on their performance in different environments. By combining genetic diversity assessment with phenotypic characterization, researchers can better understand the relationship between genotypes and phenotypes, leading to the development of improved crop varieties. This integrated approach allows for the selection of crops with desirable traits, such as a high yield, disease resistance, and nutritional quality, contributing to sustainable agriculture and food security. Both genetic diversity assessment and phenotypic characterization are crucial areas of research in crop improvement efforts, and ongoing studies in these fields aim to address the challenges of sustainable agriculture, food security, and climate change.

Topics of interest for this Special Issue include, but are not limited to, the following:

  • Investigating the role of genetic diversity in crop adaptation to changing environments;
  • Utilizing advanced technologies such as genomics and bioinformatics for more accurate and efficient assessment;
  • Evaluating the performance of crops under different environmental conditions;
  • Assessing the nutritional quality and health benefits of crop varieties;
  • Studying the interactions between genotypes and phenotypes;
  • Exploring the potential of precision agriculture techniques for phenotypic data collection;
  • Integrating phenotypic data with genomic information for a more comprehensive understanding of crop traits.

Prof. Dr. Andrijana Rebekić
Dr. Ankica Kondić-Špika
Guest Editors

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Keywords

  • genetic diversity
  • genomic analysis
  • phenotypic diversity
  • high-throughput phenotyping
  • crop improvement
  • crop adaptation
  • crop resilience
  • nutritional quality
  • big data analysis
  • bioinformatics

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Published Papers (1 paper)

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Research

20 pages, 3159 KB  
Article
Photosynthetic and Canopy Trait Characterization in Soybean (Glycine max L.) Using Chlorophyll Fluorescence and UAV Imaging
by Harmeet Singh-Bakala, Francia Ravelombola, Jacob D. Washburn, Grover Shannon, Ru Zhang and Feng Lin
Agriculture 2025, 15(24), 2576; https://doi.org/10.3390/agriculture15242576 - 12 Dec 2025
Abstract
Photosynthesis (PS) is the cornerstone of crop productivity, directly influencing yield potential. Photosynthesis remains an underexploited target in soybean breeding, partly because field-based photosynthetic traits are difficult to measure at scale. Also, it is unclear which reproductive stage(s) provide the most informative physiological [...] Read more.
Photosynthesis (PS) is the cornerstone of crop productivity, directly influencing yield potential. Photosynthesis remains an underexploited target in soybean breeding, partly because field-based photosynthetic traits are difficult to measure at scale. Also, it is unclear which reproductive stage(s) provide the most informative physiological signals for yield. Few studies have evaluated soybean PS in elite germplasm under field conditions, and the integration of chlorophyll fluorescence (CF) with UAV imaging for PS traits remains largely unexplored. This study evaluated genotypic variation in photosynthetic and canopy traits among elite soybean germplasm across environments and developmental stages using CF and UAV imaging. Linear mixed-model analysis revealed significant genotypic and G×E effects for yield, canopy and several photosynthetic parameters. Broad-sense heritability (H2) estimates indicated dynamic genetic control, ranging from 0.12 to 0.77 at the early stage (S1) and 0.20–0.81 at the mid-reproductive stage (S2). Phi2, SPAD and FvP/FmP exhibited the highest heritability, suggesting their potential as stable selection targets. Correlation analyses showed that while FvP/FmP and SPAD were modestly associated with yield at S1, stronger positive relationships with Phi2, PAR and FvP/FmP emerged during S2, underscoring the importance of sustained photosynthetic efficiency during pod formation. Principal component analysis identified photosynthetic efficiency and leaf structural traits as key axes of physiological variation. UAV-derived indices such as NDRE, MTCI, SARE, MExG and CIRE were significantly correlated with CF-based traits and yield, highlighting their utility as high-throughput proxies for canopy performance. These findings demonstrate the potential of integrating CF and UAV phenotyping to enhance physiological selection and yield improvement in soybean breeding. Full article
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