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Agronomy
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Current Status and Future Prospects of Genotype X Environment Interaction...
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Current Status and Future Prospects of Genotype X Environment Interaction in Plant Breeding and Crop Adaptation

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: closed (20 October 2022) | Viewed by 6310

Special Issue Editors

Dr. Ioannis Mylonas

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Guest Editor
Institute of Plant Breeding and Genetic Resources, Hellenic Agricultural Organization–"Demeter", 57001 Thessaloniki, Greece
Interests: cereal genetics and breeding; plant genetic resources; diversity; multi-environment field evaluation; tolerance to abiotic stress; GxE interaction; wide and specific agronomic adaptation; responsiveness to inputs; climate change
Special Issues, Collections and Topics in MDPI journals
Dr. Elissavet Ninou

E-Mail Website
Guest Editor
School of Geotechnical Sciences, Department of Agriculture, International Hellenic University, Sindos, 57400 Thessaloniki, Greece
Interests: agronomic use of plant genetic resources; abiotic stress; multienvironment field evaluation; cereals; legumes; medicinal and aromatic crops; crop physiology; cultivation systems; resource use efficiency; agro-biodiversity
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Fokion Papathanasiou

E-Mail Website
Guest Editor
Department of Agriculture, University of Western Macedonia, 50100 Florina, Greece
Interests: sustainable agriculture; landraces; botany; crop physiology; climate change and agriculture; quality characteristics; stress physiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Generally, genotype X environment interaction (GEI) could be considered the differential response of genotypes to different cultivation environments or systems. Thus, a genotype with a superior performance in one environment could be inferior in another. Aside from plant breeding and agriculture inputs, the GEI has contributed significantly to the yield increase (~10–50% in the last 50–80 years) of important staple crops such as maize, wheat, barley, etc. and could continue to contribute to increased productivity in the future. This Special Issue aims to exchange knowledge for the quantification, interpretation, and detailed study of GEI using proper current tools and univariate/multivariate statistical models. This could (a) increase the genetic gain in plant breeding programs that become more international, (b) make the selection of genotypes with wide adaptability less complicated and more effective, (c) help in the recognition of the most relevant testing environments, (d) contribute to the identification of erratic/special environments where genotypes with specific adaptability should be cultivated, and (e) help in the strategy that aims to enable an optimum allocation of resources used in a breeding program or a farming system.

Dr. Ioannis Mylonas
Prof. Dr. Elissavet Ninou
Prof. Dr. Fokion Papathanasiou
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Agronomy is an international peer-reviewed open access monthly 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

  • multi-environment evaluation
  • agronomic adaptability
  • genetic gain
  • wide and specific adaptation
  • climate change

Published Papers (3 papers)

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Research

22 pages, 3234 KiB  
Article
Multiple Stresses of Wheat in the Detection of Traits and Genotypes of High-Performance and Stability for a Complex Interplay of Environment and Genotypes
by Ibrahim Al-Ashkar, Mohammed Sallam, Nasser Al-Suhaibani, Abdullah Ibrahim, Abdullah Alsadon and Abdullah Al-Doss
Agronomy 2022, 12(10), 2252; https://doi.org/10.3390/agronomy12102252 - 21 Sep 2022
Cited by 5 | Viewed by 1565
Abstract
The effect of traits and the interaction of genotype × environment (GE) is one of the major challenges in detecting traits and genotypes with outstanding performance and stability through various stresses and years. The objective of this study was to identify the genetic [...] Read more.
The effect of traits and the interaction of genotype × environment (GE) is one of the major challenges in detecting traits and genotypes with outstanding performance and stability through various stresses and years. The objective of this study was to identify the genetic influence traits of wheat, and genotypes with outstanding performance and stability under different environmental stress. The trials were carried out in two consecutive seasons with three treatments (optimal irrigation, limited irrigation, and heat stress), totaling six test environments at two different locations. After observing the importance of GE interaction, and the statistical significance for all studied traits, multivariate analysis was applied using stepwise regression (SR) for detecting influenced traits, and AMMI, AMMI’s stability values (ASV), yield stability index (YSI), superiority and GGE biplot methods to identify the genotype’s phenotypic stability. SR analysis showed that nine out of 22 traits have contributed significantly to grain yield (GY), which varied according to the environment. Equations of the models (GY) regression coefficient values reflected the importance seven of them have on a significant positive correlation on GY. The study confirmed the importance of AMMI and GGE biplots in decoding the GEI based on GY data. AMMI1 biplots showed that the three environments E1, E4, and E6 were the stronger interacting environments than E2, E3, and E5, in which the interaction was weak. YSI, superiority analysis, and superiority multi-trait analysis scores were largely compatible. YSI scores described the six genotypes viz, G5 (DHL26), G12 (DHL29), G10 (DHL01), G18 (Sakha-93), G2 (DHL02) and, G6 (Gemmeiza-9), these were marked by high stability and productivity. The GGE biplot analysis showed genotypes (G15 (Misr1) and G4 (DHL07)) recorded the highest grain yield in E3 and E4, whereas genotype G18 (Sakha-93) was in E6. It also showed G19 (Pavone-76) was the best genotype due to being situated in the center of the concentric circles and due to its high-yield. The methods considered were compatible with the detection of promising wheat genotypes with high mean performance and outstanding phenotypic stability across various stresses and years. Full article
(This article belongs to the Special Issue Current Status and Future Prospects of Genotype X Environment Interaction in Plant Breeding and Crop Adaptation)
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17 pages, 4387 KiB  
Article
Investigating Stability Parameters for Agronomic and Quality Traits of Durum Wheat Grown under Mediterranean Conditions
by Angelos C. Kyratzis, Andreas Pallides and Andreas Katsiotis
Agronomy 2022, 12(8), 1774; https://doi.org/10.3390/agronomy12081774 - 28 Jul 2022
Cited by 10 | Viewed by 1651
Abstract
Durum wheat in the Mediterranean grows under rainfed conditions, where unpredictable climatic conditions result in substantial variation in grain yield and quality. Climate change intensifies Genotype × Environment interactions and urges breeders to escalate their efforts to breed cultivars combining high performance and [...] Read more.
Durum wheat in the Mediterranean grows under rainfed conditions, where unpredictable climatic conditions result in substantial variation in grain yield and quality. Climate change intensifies Genotype × Environment interactions and urges breeders to escalate their efforts to breed cultivars combining high performance and stability. The current study aimed to appraise the relations between twelve stability parameters derived by different statistical models for yield, yield-related and quality traits of durum wheat grown under Mediterranean conditions. Stability parameters were estimated in two experiments of twenty and sixteen cultivars, respectively. The parameters were categorized into three groups. Group A included Additive Main Effect and Multiplicative Interaction (AMMI)-derived parameters (ASV and AWAI), Wrickle’s ecovalence (Wi), Shukla’s stability variance (σ2), and the nonparametric parameters Si(1) and Si(2). Group B included regression parameters (bi, Bi_A), Coefficient of Variance (CV), and Superiority measure (Pi). Group C encompassed deviation from regression parameters (s2di-DJi) when the heterogeneity of the slope was significant. Correlations between stability parameters for different traits and the between stability parameters and the traits per se were modest. Stability parameters of Group B had higher repeatability for grain yield. The results of the present study contribute to the adjustment of durum wheat breeding strategies. Full article
(This article belongs to the Special Issue Current Status and Future Prospects of Genotype X Environment Interaction in Plant Breeding and Crop Adaptation)
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10 pages, 4117 KiB  
Article
Stability on Maize Hybrids Based on GGE Biplot Graphical Technique
by Seyed Habib Shojaei, Khodadad Mostafavi, Mohammad Reza Bihamta, Ali Omrani, Seyed Mohammad Nasir Mousavi, Árpád Illés, Csaba Bojtor and Janos Nagy
Agronomy 2022, 12(2), 394; https://doi.org/10.3390/agronomy12020394 - 4 Feb 2022
Cited by 13 | Viewed by 2286
Abstract
In this study, 12 maize hybrids were planted and evaluated to determine the effect of genotype and genotype-environment interaction (GEI) base GGE (genotype plus genotype-by-environment) using a Graphical biplot technique in four research stations (Arak, Birjand, Shiraz and Karaj) within two years using [...] Read more.
In this study, 12 maize hybrids were planted and evaluated to determine the effect of genotype and genotype-environment interaction (GEI) base GGE (genotype plus genotype-by-environment) using a Graphical biplot technique in four research stations (Arak, Birjand, Shiraz and Karaj) within two years using a Randomized Complete Blocks Design (RCBD). The combined analysis of variance showed that the effects of the environment, genotype and genotype-environment interaction (GEI) were significant in the one percent probability level. GGE biplot results indicated that the first and second principal components (PC1 and PC2) explained more than 83% of the grain performance variation. Simultaneous study of grain performance and hybrid stability using the biplot of average environment coordinates showed that the KSC705 genotype had the highest yield and stability. Polygon view divided the studied areas into two mega-environments (MEs) and identified the best genotypes in each mega-environment (ME). In the first mega-environment (ME1), the Karaj and Shiraz with KSC706 and KSC400 genotypes were detected, and were the best; and in the second mega-environment (ME2), Arak and Birjand with KSC704 and KSC707 genotypes performed better. The biplot graph for the correlation between the genotypes categorized the studied hybrids into four groups positively related to each other based on the angles between vectors. The KSC704 and KSC707 genotypes were desirable in the yield in Shiraz and Karaj and KSC706 were in Arak and Birjand. Additionally, Arak-Birjand, Karaj-Shiraz showed a positive and significant correlation. Birjand and Karaj had most genotype interaction with each other. Full article
(This article belongs to the Special Issue Current Status and Future Prospects of Genotype X Environment Interaction in Plant Breeding and Crop Adaptation)
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