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Agriculture
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Genetic Diversity Assessment and Phenotypic Characterization of Crops—2nd Edition
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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: 15 October 2026 | Viewed by 4210

Special Issue Editors

Prof. Dr. Andrijana Rebekić

E-Mail Website
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
Special Issues, Collections and Topics in MDPI journals
Dr. Ankica Kondić-Špika

E-Mail Website
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
Special Issues, Collections and Topics in MDPI journals

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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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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Related Special Issue

Published Papers (4 papers)

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Research

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11 pages, 1434 KB  
Article
Efficiency of Factor Analysis-Based Selection Indices Under Varying Heritability and Trait-Environment Correlations
by Wanessa Alves Lima Paiva, Brenda Vieira de Oliveira, Camila Ferreira Azevedo, Ana Carolina Campana Nascimento, Diego Jarquin and Moyses Nascimento
Agriculture 2026, 16(9), 1001; https://doi.org/10.3390/agriculture16091001 - 2 May 2026
Viewed by 1238
Abstract
The main approach for improving multiple traits simultaneously is the selection index. The most widely used selection indices are those based on factor analysis, which overcome statistical limitations such as multicollinearity and the reliance on arbitrary weights of the classical Smith–Hazel approach and [...] Read more.
The main approach for improving multiple traits simultaneously is the selection index. The most widely used selection indices are those based on factor analysis, which overcome statistical limitations such as multicollinearity and the reliance on arbitrary weights of the classical Smith–Hazel approach and support multi-environment trials. Nevertheless, the efficiency indices are affected by factors such as genotype number, environment and trait correlation, and heritability. In this study, we simulated different scenarios varying the mentioned factors to evaluate the performance of the Factor-Analysis and Ideotype-Design-Based Index (FAI-BLUP), Multi-trait Genotype–Ideotype Distance Index (MGIDI), and Multi-Trait Stability Index (MTSI). All correlations were positive and constant within each scenario, while the ideotype sought genetic gains for traits in opposite directions. Simulations were conducted using AlphaSimR and FieldSimR, and indices were implemented via the metan package. Results showed that index efficiency was higher in scenarios with larger numbers of genotypes, low-to-moderate trait correlations, and moderate-to-high inter-environment correlations. However, strong correlations among traits, particularly when combined with high heritability, compromise selection index efficiency in scenarios with antagonistic trait objectives. Despite that, the MGIDI consistently outperformed the other indices across most scenarios. Therefore, we emphasize accounting for trait genetic architectures, genotype–trait correlations, and target environment correlations. Full article
(This article belongs to the Special Issue Genetic Diversity Assessment and Phenotypic Characterization of Crops—2nd Edition)
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15 pages, 1402 KB  
Article
Mapping Quantitative Trait Loci for Pre-Harvest Sprouting Resistance in Wheat Using Berkut × Worrakatta Recombinant Inbred Lines
by Yunkun Cheng, Yiling Xing, Lei Xie, Wanlong He, Jinjin Ding, Haiyan Zhang, Xiaomei Liu and Hongwei Geng
Agriculture 2026, 16(9), 926; https://doi.org/10.3390/agriculture16090926 - 23 Apr 2026
Viewed by 369
Abstract
Pre-harvest sprouting (PHS) in wheat is a significant global challenge influenced by climate. This study aimed to decipher the genetic underpinnings of PHS and identify resistance genes using 309 recombinant inbred lines (RILs) derived from the “Berkut” × “Worrakatta” cross. Methods: Phenotypic assessment [...] Read more.
Pre-harvest sprouting (PHS) in wheat is a significant global challenge influenced by climate. This study aimed to decipher the genetic underpinnings of PHS and identify resistance genes using 309 recombinant inbred lines (RILs) derived from the “Berkut” × “Worrakatta” cross. Methods: Phenotypic assessment of PHS traits was performed using the whole-spike sprouting method across various environments, complemented by quantitative trait loci (QTL) analysis employing a wheat 50 K SNP chip. Results showed high PHS rates in both parental lines across multiple environments. Progeny exhibited substantial variation in PHS rates, with coefficients of variation ranging from 0.16 to 0.19 and phenotypic variation ranging from 23.92% to 100%, suggesting pronounced transgressive segregation. Nine QTLs associated with PHS were identified on chromosomes 1AL, 1DL, 2AL, 2AS, 2BS, 3DS, 4BL, and 7BL. These loci accounted for 2.67% to 6.39% of the phenotypic variation. Notably, the enhancer alleles at four loci—1DL, 2BS, 4BL, and 7BL—originated from “Worrakatta”, and “Berkut” contributed the enhancer alleles at the remaining five loci. Two QTLs, QPHS.xjau-1AL.1 and QPHS.xjau-1AL.2, were stable across multiple environments. Specifically, QPHS.xjau-1AL.1 was present in three environments and explained 3.86% to 6.39% of the phenotypic variation, while QPHS.xjau-1AL.2 appeared in one environment under average conditions, explaining 2.67% to 4.87% of the variation. Our study also identified eight candidate genes associated with wheat PHS, including those encoding Myb transcription factors that influence flavonoid biosynthesis and grain color, as well as genes involved in stress response and gibberellin biosynthesis, which are crucial for plant growth and development. These genes represent vital targets for enhancing wheat PHS resistance. Full article
(This article belongs to the Special Issue Genetic Diversity Assessment and Phenotypic Characterization of Crops—2nd Edition)
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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
Cited by 1 | Viewed by 1298
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
(This article belongs to the Special Issue Genetic Diversity Assessment and Phenotypic Characterization of Crops—2nd Edition)
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Review

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24 pages, 1795 KB  
Review
Speed Breeding: A Tool for Climate Resilient Agriculture
by Tihomir Čupić, Ivana Plavšin, Branimir Tokić, Marijana Tucak, Katarina Perić and Sonja Petrović
Agriculture 2026, 16(8), 831; https://doi.org/10.3390/agriculture16080831 - 9 Apr 2026
Viewed by 849
Abstract
Climate change is advancing faster than conventional crop cycles, and this temporal lag represents a critical constraint on modern agricultural production. By significantly shortening generation times, speed breeding (SB) transforms breeding from a fixed constraint into a manageable experimental parameter. Today, SB is [...] Read more.
Climate change is advancing faster than conventional crop cycles, and this temporal lag represents a critical constraint on modern agricultural production. By significantly shortening generation times, speed breeding (SB) transforms breeding from a fixed constraint into a manageable experimental parameter. Today, SB is increasingly integrated within climate-smart agriculture, not only for rapid generation turnover but also through emerging stress-informed SB protocols designed to mimic key abiotic constraints. At the same time, no universal approach to SB exists. Protocols must be adapted to the highly heterogeneous species-specificities regarding photoperiodicity and light response. The accelerated loss of genetic diversity due to small populations, together with the limited ability of controlled chambers to simulate complex field conditions, remains a major challenge. This review synthesizes literature from 1995 to 2025 on the technical foundations of SB, its application in major crops, and integration with modern breeding, phenotyping, and AI-driven tools. The available knowledge and evidence indicate that SB is most effective when integrated into breeding pipelines together with multi-district field-testing and stress-aware protocols, rather than used as an isolated technique. SB provides one of the strongest levers available to accelerate crop improvement under rapidly changing climate conditions. Full article
(This article belongs to the Special Issue Genetic Diversity Assessment and Phenotypic Characterization of Crops—2nd Edition)
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