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You searched for: Keyword "genotype-environment interaction" Remove constraint Keyword: "genotype-environment interaction"
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1. Genotype × Environment Interaction Studies of Promising Teppi Coffee (Coffea arabica L.) Genotypes in Southwestern Ethiopia

Author:
Wakuma Merga; Wosene Gebreselassie; Weyessa Garedew
Source:
International journal of agronomy 2021 v.2021 pp. -
ISSN:
1687-8167
Subject:
genotype-environment interaction,   etc   ; Coffea arabica; agronomy; analysis of variance; crops; genotype; hybridization; models; stimulant plants; Ethiopia;     Show all 10 Subjects
Abstract:
... Coffee is the stimulant crop plant that belongs to the genus Coffea, in the family Rubiaceae. The yield variation and pattern of the crop varied within short geographic distance and thus attributed to low productivity and unpredictable production. The objective of this study was to determine the extent of genotype × environment interaction on yields of promising Teppi coffee genotype ...
DOI:
10.1155/2021/5519467

2. Integrating univariate and multivariate statistical models to investigate genotype × environment interaction in durum wheat

Author:
Reza Mohammadi; Behzad Sadeghzadeh; Mohammad Mehdi Poursiahbidi; Malak Masoud Ahmadi
Source:
Annals of applied biology 2021 v.178 no.3 pp. 450-465
ISSN:
0003-4746
Subject:
genotype-environment interaction,   etc   ; durum wheat; genotype; grain yield; rain; relative humidity; temperature; variance;     Show all 8 Subjects
Abstract:
... There has been a significant trend in the use of different statistical tools to analyse genotype × environment (GE) interaction for grain yield in multi‐environment trials. Several statistical models including 16 univariate stability methods and four multivariate models such as the additive main effects and multiplicative interaction (AMMI), GGE biplot (G+GE biplot), and factorial regression and p ...
DOI:
10.1111/aab.12648

3. Genotype × Environment Interaction of Yield and Grain Quality Traits of Maize Hybrids in Greece

Author:
Nikolaos Katsenios; Panagiotis Sparangis; Sofia Chanioti; Marianna Giannoglou; Dimitris Leonidakis; Miltiadis V. Christopoulos; George Katsaros; Aspasia Efthimiadou
Source:
Agronomy 2021 v.11 no.2 pp. -
ISSN:
2073-4395
Subject:
genotype-environment interaction,   etc   ; agronomy; corn; field experimentation; genotype; grain protein; grain quality; protein content; soil texture; Greece;     Show all 10 Subjects
Abstract:
... The interaction of genotype by the environment is very common in multi-environment trials of maize hybrids. This study evaluates the quantity and the quality of grain production and the stability of four maize genotypes in a field experiment that was conducted in five different locations for two years. In order to make a reliable evaluation of the performance of genotypes in the environments, prin ...
DOI:
10.3390/agronomy11020357

4. Effect of Genotype × Environment Interaction on Yield of Maize Hybrids in Greece Using AMMI Analysis

Author:
Nikolaos Katsenios; Panagiotis Sparangis; Dimitriοs Leonidakis; George Katsaros; Ioanna Kakabouki; Dimitrios Vlachakis; Aspasia Efthimiadou
Source:
Agronomy 2021 v.11 no.3 pp. -
ISSN:
2073-4395
Subject:
genotype-environment interaction,   etc   ; agronomy; corn; field experimentation; grain yield; models; pH; rain; temperature; Greece;     Show all 10 Subjects
Abstract:
... An increase in grain yield remains a major target for all involved in maize cultivation. In this study, five maize genotypes were evaluated in a two-year (2017 and 2018) field experiment that was conducted at six locations. Additive main effects and multiplicative interaction (AMMI) analysis was used to detect the narrow adaptations of genotypes in specific mega-environments and the positive inter ...
DOI:
10.3390/agronomy11030479

5. Genotype × environment interaction for resistance to early leaf spot of groundnut mini core collections in the savannas of Nigeria

Author:
Abdulwahab S. Shaibu; Zainab L. Miko; Sanusi G. Mohammed; Hakeem A. Ajeigbe; Alhassan Usman; Mohammed S. Mohammed; Muhammad L. Umar
Source:
Legume research 2021 v.44 no.4 pp. 472-479
ISSN:
0976-0571
Subject:
genotype-environment interaction,   etc   ; Arachis hypogaea; genotype; leaf spot; peanuts; research; statistical models; variance; Nigeria;     Show all 9 Subjects
Abstract:
... The genetic yield potential of groundnut (Arachis hypogaea L.) has been continuously challenged by several diseases including early leaf spot (ELS). In the current study, we evaluated groundnut mini core collections under artificial and natural disease epiphytotics in six environments to identify stable elite sources for ELS resistance and pod yield. Mixed model analysis was done to adequately cap ...
DOI:
10.18805/LR-579

6. Genotype-by-environment interaction on canning and cooking quality of advanced large-seeded common bean genotypes

Author:
Samir Hashim Gelete; Firew Mekbib; Berhanu Amsalu Fenta; Mulgeta Teamir
Source:
Heliyon 2021 v.7 no.5 pp. e06936
ISSN:
2405-8440
Subject:
genotype-environment interaction,   etc   ; beans; genotype; Ethiopia;     Show all 4 Subjects
Abstract:
... Developing beans for high canning and cooking quality has been a major concern of plant breeders as the demand of consumers for beans in terms of quality is increasing. This study determined the effect of genotype-by-environment (GEI) on canning and cooking quality of common beans. Twenty three newly developed large-seeded bean genotypes and two standard checks collected from five growing sites of ...
DOI:
10.1016/j.heliyon.2021.e06936

7. The consequence of genotype × environment interaction on high essential oil yield and its composition in clove basil (Ocimum gratissimum L.)

Author:
Ashish Kumar; Raj Kishori Lal
Source:
Acta ecologica Sinica 2021 pp. -
ISSN:
1872-2032
Subject:
genotype-environment interaction,   etc   ; Ocimum gratissimum; antioxidant activity; autumn; basil; cloves; cold; cough; essential oils; eugenol; fever; food industry; fungi; lipid content; phenol; summer; tea; winter; India; Nigeria;     Show all 20 Subjects
Abstract:
... Clove basil (Ocimum gratissimum L.) is an aromatic, perennial herb belonging to the family Lamiaceae. The plant is indigenous to tropical areas especially India and West Africa. In Nigeria, it is found in the Savannah and coastal areas. The whole herbs of the plant contain essential oils and it is cultivated for various purposes. The plant is a rich source of eugenol in its essential oil. It is al ...
DOI:
10.1016/j.chnaes.2021.06.002

8. Delineating photosynthesis, essential oil yield performance, and their component traits under genotype × traits × environments interactions in Ocimum genotypes

Author:
R.K. Lal; Pankhuri Gupta; S. Srivastva; C.S. Chanotiya; A. Mishra; A. Yadav; R. Maurya
Source:
South African journal of botany 2021 v.141 pp. 54-65
ISSN:
0254-6299
Subject:
genotype-environment interaction,   etc   ; Ocimum; essential oils; genotype; oils; photosynthesis; transpiration;     Show all 7 Subjects
Abstract:
... The stability parameters were quantified through a study in the thirteen economic traits in fourteen genotypes of Ocimum. The essential oil yields of the Ocimum in different environments are influenced by economic traits that are affected by genotype × environment interactions. The genotype × environment interaction analysis in Ocimum is scanty for the essential oil yield. This experiment ...
DOI:
10.1016/j.sajb.2021.03.039

9. Diversifying maize genomic selection models

Author:
Brian R. Rice; Alexander E. Lipka
Source:
Molecular breeding 2021 v.41 no.5 pp. 33
ISSN:
1380-3743
Subject:
genotype-environment interaction,   etc   ; corn; encapsulation; inbreeding; marker-assisted selection; phenotype;     Show all 6 Subjects
Abstract:
... Genomic selection (GS) is one of the most powerful tools available for maize breeding. Its use of genome-wide marker data to estimate breeding values translates to increased genetic gains with fewer breeding cycles. In this review, we cover the history of GS and highlight particular milestones during its adaptation to maize breeding. We discuss how GS can be applied to developing superior maize in ...
DOI:
10.1007/s11032-021-01221-4

10. Genotype-by-environment interaction and stability analyses of grain yield in pigeonpea [Cajanus cajan (L.) Millspaugh]

Author:
Esnart Nyirenda Yohane; Hussein Shimelis; Mark Laing; Isack Mathew; Admire Shayanowako
Source:
Acta agriculturæ Scandinavica 2021 v.71 no.3 pp. 145-155
ISSN:
1651-1913
Subject:
genotype-environment interaction,   etc   ; Cajanus cajan; genotype; grain yield; pigeon peas; seasonal variation; Malawi;     Show all 7 Subjects
Abstract:
... pigeonpea genotypes were tested under six environments using a 9 × 9 alpha-lattice design with two replications. Data collected were subjected to additive main effects and multiplicative interaction (AMMI) analysis and genotype plus genotype-by-environment interaction (GGE) biplot analysis. Genotype, environment, and genotype × environment interaction (GEI) accounted for 16.4, 33.5, and 49.6 ...
DOI:
10.1080/09064710.2020.1859608

11. Genotype by environment interaction for main winter triticale varieties characteristics at two levels of technology using additive main effects and multiplicative interaction model

Author:
Jan Bocianowski; Anna Tratwal; Kamila Nowosad
Source:
Euphytica 2021 v.217 no.2 pp. 26
ISSN:
0014-2336
Subject:
genotype-environment interaction,   etc   ; cultivars; genotype; grain yield; models; plant height; triticale;     Show all 7 Subjects
Abstract:
... The aim of this study was to assess genotype by environment interaction for grain yield, plant height and thousand-grain weight in winter triticale cultivars by the additive main effects and multiplicative interaction (AMMI) model. The study comprised of ten winter triticale varieties i.e.: Algoso, Baltiko, Grenado, Magnat, Moderato, Pawo, Todan, Trimester, Trismart and Witon. Field trials were pe ...
DOI:
10.1007/s10681-020-02756-x

12. Yield stability analysis of orange - Fleshed sweet potato in Indonesia using AMMI and GGE biplot

Author:
Agung Karuniawan; Haris Maulana; Debby Ustari; Sitaresmi Dewayani; Eso Solihin; M. Amir Solihin; Suseno Amien; Mahfud Arifin
Source:
Heliyon 2021 v.7 no.4 pp. e06881
ISSN:
2405-8440
Subject:
genotype-environment interaction,   etc   ; agroecosystems; genotype; sweet potatoes; variance; yield components; Indonesia;     Show all 7 Subjects
Abstract:
... Orange-Fleshed Sweet Potato (OFSP) is an important crop in Indonesia. Yield potential and genotypic adaptability are important factors in varietal development. The purpose of this study was to estimate the stability of yield and to select the best OFSP genotypes across three agroecosystems in West Java, Indonesia. The field trials used were augmented design with 50 F1 Orange-Fleshed Sweet Potato ( ...
DOI:
10.1016/j.heliyon.2021.e06881

13. AMMI and GGE biplot analysis of yield of different elite wheat line under terminal heat stress and irrigated environments

Author:
Bishwas K.C.; Mukti Ram Poudel; Dipendra Regmi
Source:
Heliyon 2021 v.7 no.6 pp. e07206
ISSN:
2405-8440
Subject:
genotype-environment interaction,   etc   ; analysis of variance; genotype; heat stress; irrigation; models; wheat; Nepal;     Show all 8 Subjects
Abstract:
... by understanding the genotype-environment interaction. The objective of this research is to obtain a high yielding line with a stable performance across the environments. In order to do so, we conducted an experiment using eighteen elite wheat lines and two check varieties in alpha-lattice design with two replications in different environments viz. irrigated and terminal heat stress environment from November ...
DOI:
10.1016/j.heliyon.2021.e07206

14. Assessing the potential of improving growth and survival to the eyed stage in selectively bred Arctic charr (Salvelinus alpinus)

Author:
Christos Palaiokostas; Henrik Jeuthe; Dirk‐Jan De Koning
Source:
Journal of animal breeding and genetics 2021 v.138 no.3 pp. 326-337
ISSN:
0931-2668
Subject:
genotype-environment interaction,   etc   ; Salvelinus alpinus; body weight; dimorphism; fish; heritability; prediction; Sweden;     Show all 8 Subjects
Abstract:
... The Arctic charr breeding programme has been a main driving force for developing the aquaculture industry in Sweden. Selection has been performed for almost 40 years using animals from a closed breeding nucleus. The aim of the current study was to evaluate the potential of further improving growth‐related traits taking into account the existence of genotype‐by‐environment interaction. Furthermore, ...
DOI:
10.1111/jbg.12509

15. Impact of the complexity of genotype by environment and dominance modeling on the predictive accuracy of maize hybrids in multi-environment prediction models

Author:
Filipe Couto Alves; Giovanni Galli; Filipe Inácio Matias; Miriam Suzane Vidotti; Júlia Silva Morosini; Roberto Fritsche-Neto
Source:
Euphytica 2021 v.217 no.3 pp. 37
ISSN:
0014-2336
Subject:
genotype-environment interaction,   etc   ; corn; data collection; genomics; grain yield; models; prediction; Brazil;     Show all 8 Subjects
Abstract:
... The prediction accuracy of multi-environment prediction models can be affected by the complexity of the genotype by environment interaction (G×E). Moreover, depending on the trait genetic architecture, accounting for non-additive effects, such as dominance effects, may increase the prediction accuracy of genomic models. Hence, we aimed to verify empirically: (i) the impact of the genotype by envir ...
DOI:
10.1007/s10681-021-02779-y

16. Genetic diversity and selection of bean landraces and cultivars based on technological and nutritional traits

Author:
Nerinéia Dalfollo Ribeiro; Guilherme Godoy dos Santos; Sandra Maria Maziero; Greice Godoy dos Santos
Source:
Journal of food composition and analysis 2021 v.96 pp. 103721
ISSN:
0889-1575
Subject:
genotype-environment interaction,   etc   ; bananas; beans; color; cultivars; food composition; genetic variation; human nutrition; landraces; magnesium;     Show all 10 Subjects
Abstract:
... in which 49 common bean cultivars were evaluated. A significant genotype × environment interaction effect was observed for all traits. Mass of 100 grains was positively correlated with grain length (r = 0.78) and cooking time (r = 0.59) and negatively correlated with magnesium concentration (r = −0.63). The L* (grain lightness) and a* (color variation from green to red) values were more important ...
DOI:
10.1016/j.jfca.2020.103721

17. Regarding the F‐word: The effects of data filtering on inferred genotype‐environment associations

Author:
Collin W. Ahrens; Rebecca Jordan; Jason Bragg; Peter A. Harrison; Tara Hopley; Helen Bothwell; Kevin Murray; Dorothy A. Steane; John W. Whale; Margaret Byrne; Rose Andrew; Paul D. Rymer
Source:
Molecular ecology resources 2021 v.21 no.5 pp. 1460-1474
ISSN:
1755-098X
Subject:
genotype-environment interaction,   etc   ; data collection; ecology; gene frequency; genomics; landscapes; sample size; trees;     Show all 8 Subjects
Abstract:
... Genotype‐environment association (GEA) methods have become part of the standard landscape genomics toolkit, yet, we know little about how to best filter genotype‐by‐sequencing data to provide robust inferences for environmental adaptation. In many cases, default filtering thresholds for minor allele frequency and missing data are applied regardless of sample size, having unknown impacts on the res ...
DOI:
10.1111/1755-0998.13351

18. Spatial areas of genotype probability: Predicting the spatial distribution of adaptive genetic variants under future climatic conditions

Author:
Estelle Rochat; Oliver Selmoni; Stéphane Joost
Source:
Diversity & distributions 2021 v.27 no.6 pp. 1076-1090
ISSN:
1366-9516
Subject:
genotype-environment interaction,   etc   ; climate change; genome; genotype; goats; landscapes; mathematical models; prediction; probability;     Show all 9 Subjects
Abstract:
... In a context of rapid global change, one of the key components for the survival of species is their genetic evolutionary potential for adaptation. Many methods have been developed to identify genetic variants underpinning adaptation to climate, but few tools were made available to integrate this knowledge into conservation management. We present here the SPatial Areas of Genotype probability (SPAG ...
DOI:
10.1111/ddi.13256

19. Yield stability of contrasting orchardgrass (Dactylis glomerata L.) genotypes over the years and water regimes

Author:
Fatemeh Saeidnia; Mohammad Mahdi Majidi; Aghafakhr Mirlohi; Mohammad Reza Dehghani; Behnam Hosseini
Source:
Euphytica 2021 v.217 no.7 pp. 136
ISSN:
0014-2336
Subject:
genotype-environment interaction,   etc   ; Dactylis glomerata; climate change; drought tolerance; forage; forage yield; genes; genetic variation;     Show all 8 Subjects
Abstract:
... Stability of combining ability and the nature and extent of genetic and genotype × environment interaction is poorly understood in orchardgrass especially under climate change conditions. This study was conducted to evaluate the adaptability and yield stability of orchardgrass families in order to facilitate comparison among HS families and environments and identify suitable families for future ...
DOI:
10.1007/s10681-021-02871-3

20. Assessment of Tuber Yield Stability and Adaptability of Some Elite Yam Genotypes in the Guinea Savannah Ecology of Northern Ghana

Author:
Joseph Adjebeng-Danquah; Kwabena Acheremu; Emmanuel Boachie Chamba; Freda Ansaah Agyapong; Alhassan Sayibu
Source:
International journal of agronomy 2021 v.2021 pp. -
ISSN:
1687-8167
Subject:
genotype-environment interaction,   etc   ; Dioscorea; agronomy; analysis of variance; ecology; genetic variation; genotype; yams; Ghana; Guinea;     Show all 10 Subjects
Abstract:
... and assessed for tuber yield and yield components. Analysis of variance indicated significant p<0.05 genotypic variation for tuber yield and the yield components studied. Genotype × environment interaction effect was significant p<0.05 for tuber yield and mean tuber weight but not significant p>0.05 for number of tubers per mound. Apart from genotype 95/18922, all the exotic genotypes had significantly p ...
DOI:
10.1155/2021/6615636