scholarly journals Yield Stability and Farmer Preference of Cowpea (Vigna Uncuilata) Lines in semi-arid Eastern Kenya

Afrika Focus ◽  
2019 ◽  
Vol 32 (2) ◽  
Author(s):  
Rose Wangari Kuruma ◽  
Patrick Sheunda ◽  
Charles Muriuki Kahwaga
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Early Maturing ◽  
Superior Genotypes ◽  
High Yielding Varieties ◽  
Main Effects ◽  
Pod Length

Stability in yields of agronomically acceptable cultivars is generally regarded as the ultimate goal in cowpea improvement. Nine advanced cowpea lines and 3 local checks were evaluated for grain yield in eastern Kenya with the aim of identifying stable genotypes and integrating farmer preferences. The study was conducted in 3 locations over 2 years under a randomized complete block design with 3 replications. Stability was estimated using additive main effects and multiplicative interaction (AMMI) and genotype by environment (GGE) models. There was variation among genotypes, locations and their interactions for grain yield. Genotype G5, G9 and G2 were found to be stable and high yielding. Environments Kit16 and Kit15 were considered as the most suitable for selecting superior genotypes for adaptability and stability. Farmers’ criteria for selecting genotypes included early maturing, pod length, disease tolerant and high yielding varieties. Cowpea performance for grain yield was greatly influenced by inherent genotypic factors, environment and their interaction effects. KEY WORDS: COWPEA, ENVIRONMENT, GENOTYPE BY ENVIRONMENT INTERACTION, STABILITY, GRAIN YIELD

scholarly journals Yield Stability and Farmer Preference of Cowpea (Vigna Unguiculata) Lines in Semi-Arid Eastern Kenya

Afrika Focus ◽  
2019 ◽  
Vol 32 (2) ◽  
pp. 65-82
Author(s):  
Rose Wangari Kuruma ◽  
Patrick Sheunda ◽  
Charles Muriuki Kahwaga
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment ◽  
Randomized Complete Block Design ◽  
Early Maturing ◽  
Superior Genotypes ◽  
High Yielding Varieties ◽  
Main Effects ◽  
Pod Length ◽  
Semi Arid

Stability in yields of agronomically acceptable cultivars is generally regarded as the ultimate goal in cowpea improvement. Nine advanced cowpea lines and 3 local checks were evaluated for grain yield in eastern Kenya with the aim of identifying stable genotypes and integrating farmer preferences. The study was conducted in 3 locations over 2 years under a randomized complete block design with 3 replications. Stability was estimated using additive main effects and multiplicative interaction (AMMI) and genotype by environment (GGE) models. There was variation among genotypes, locations and their interactions for grain yield. Genotype G5, G9 and G2 were found to be stable and high yielding. Environments Kit16 and Kit15 were considered as the most suitable for selecting superior genotypes for adaptability and stability. Farmers’ criteria for selecting genotypes included early maturing, pod length, disease tolerant and high yielding varieties. Cowpea performance for grain yield was greatly influenced by inherent genotypic factors, environment and their interaction effects.

scholarly journals Analysis of Genotype by Environment Interaction of Improved Pearl Millet for Grain Yield and Rust Resistance

2017 ◽  
Vol 9 (2) ◽  
pp. 188
Author(s):  
G. Lubadde ◽  
P. Tongoona ◽  
J. Derera ◽  
J. Sibiya
Keyword(s):  
Grain Yield ◽  
Pearl Millet ◽  
Rust Resistance ◽  
Genotype By Environment Interaction ◽  
Climatic Conditions ◽  
Arid Zones ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Superior Genotypes ◽  
Main Effects

Pearl millet is grown by inhabitants of the semi-arid zones. Due to the unpredictable climatic conditions the genotype-by-environment interaction (GEI) makes it hard to select genotypes adapted to such conditions. The study objectives therefore were to analyse the patterns of GEI and to identify superior genotypes for grain yield and rust resistance. Seventy six genotypes were planted in four environments in 4×19 alpha design with two replications. The ANOVA results showed that main effects of environments were significant (p ≤ 0.05) for grain yield and highly significant (p ≤ 0.001) for rust resistance while the main effects of the genotypes and their interactions with environments were also important for grain yield and rust severity at 50% physiological maturity. The GGE biplot analysis revealed that environments associated with more rains received during vegetative phase performed better than those receiving more rains during post-anthesis phase. The winner in the best environment for grain yield was ICMV3771×SDMV96053 while Shibe×CIVT9206 and Shibe×GGB8735 were the best for rust resistance.

scholarly journals Genotype-by-Environment Interaction and Stability Analysis in Grain Yield of Improved Tef (Eragrostis tef) Varieties Evaluated in Ethiopia

2019 ◽  
pp. 1-13
Author(s):  
Habte Jifar ◽  
Kebebew Assefa ◽  
Kassahun Tesfaye ◽  
Kifle Dagne ◽  
Zerihun Tadele
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Eragrostis Tef ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Testing Environments ◽  
One Year ◽  
Main Effects

Aims: To assess the magnitude of genotype by environment interaction; possible existence of different mega-environments; and discriminating ability and representativeness of the testing environments. Study Design: Randomized complete Block Design with three replications. Place and Duration of Study: The study was conducted at Debre Zeit, Holetta and Alem Tena for two years (2015 and 2016) and at Adet, Axum and Bako for one year (2015). Methodology: Thirty-five improved tef varieties were evaluated at nine environments. The G × E interaction were quantified using additive main effects and multiplicative interaction (AMMI) and the genotype and genotype by environment (GGE) biplot models. Results: Combined analysis of variance revealed highly significant (P = 0.01) variations due to genotype, environment and genotype by environment interaction effects. AMMI analysis revealed 4.3%, 79.7% and 16% variation in grain yield due to genotypes, environments and G x E effects, respectively. G6 gave the highest mean grain yield (3.33 t/ha) over environments whereas G29 gave the lowest mean yield (2.49 t/ha). The GGE biplot grouped the nine testing environments and the 35 genotypes into four mega environments and seven genotypic groups. The four mega environments include: G-I (E1, E4 and E6); G-II (E2, E3, E7 and E8); G-III (E9), and G-IV (E5). E5, E6, E7 and E8 which had the longest vector were the most discriminating of all environments while, E1 and E4 which had the smallest angle with the average environmental axis were the most representative of all environments. Regarding genotypes, G6, G25, G34 and G16 were identified as the best yielding and relatively stable genotypes to increase tef productivity. Conclusion: AMMI and GGE were found to be efficient in grouping the tef growing environments and genotypes.

Evaluation of sugarcane genotypes with respect to sucrose yield across three crop cycles using GGE biplot analysis

2021 ◽  
pp. 1-13
Author(s):  
Aliya Momotaz ◽  
Per H. McCord ◽  
R. Wayne Davidson ◽  
Duli Zhao ◽  
Miguel Baltazar ◽  
...  
Keyword(s):  
Block Design ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Gge Biplot ◽  
Genotype By Environment ◽  
Biplot Analysis ◽  
Genotype Environment Interaction ◽  
Area 5 ◽  
Randomized Complete Block Design ◽  
Main Effects

Summary The experiment was carried out in three crop cycles as plant cane, first ratoon, and second ratoon at five locations on Florida muck soils (histosols) to evaluate the genotypes, test locations, and identify the superior and stable sugarcane genotypes. There were 13 sugarcane genotypes along with three commercial cultivars as checks included in this study. Five locations were considered as environments to analyze genotype-by-environment interaction (GEI) in 13 genotypes in three crop cycles. The sugarcane genotypes were planted in a randomized complete block design with six replications at each location. Performance was measured by the traits of sucrose yield tons per hectare (SY) and commercial recoverable sugar (CRS) in kilograms of sugar per ton of cane. The data were subjected to genotype main effects and genotype × environment interaction (GGE) analyses. The results showed significant effects for genotype (G), locations (E), and G × E (genotype × environment interaction) with respect to both traits. The GGE biplot analysis showed that the sugarcane genotype CP 12-1417 was high yielding and stable in terms of sucrose yield. The most discriminating and non-representative locations were Knight Farm (KN) for both SY and CRS. For sucrose yield only, the most discriminating and non-representative locations were Knight Farm (KN), Duda and Sons, Inc. USSC, Area 5 (A5), and Okeelanta (OK).

scholarly journals Genotype by environment interaction for seeds yield in pea (Pisum sativum L.) using additive main effects and multiplicative interaction model

Euphytica ◽  
2019 ◽  
Vol 215 (11) ◽  
Author(s):  
Jan Bocianowski ◽  
Jerzy Księżak ◽  
Kamila Nowosad
Keyword(s):  
Pisum Sativum ◽  
Block Design ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Ge Interaction ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Randomized Complete Block Design ◽  
Main Effects

Abstract The objective of this study was to evaluate the genotype by environment interaction using the additive main effects and multiplicative interaction model for seeds yield of pea cultivars grown in Poland. Twelve pea (Pisum sativum L.) cultivars: Bohun, Boruta, Cysterski, Ezop, Kavalir, Lasso, Medal, Santana, Tarchalska, Terno, Wenus and Zekon were evaluated in 20 environments (ten locations in 2 years). The experiment was laid out as randomized complete block design with three replicates. Seeds yield ranged from 26.10 dt ha−1 (for Wenus in Radostowo 2011) to 79.73 dt ha−1 (for Lasso in Słupia 2010), with an average of 50.70 dt ha−1. AMMI analyses revealed significant genotype and environmental effects as well as genotype-by-environment interaction with respect to seeds yield. In the analysis of variance, 89.19% of the total seeds yield variation was explained by environment, 1.65% by differences between genotypes, and 8.33% by GE interaction. The cultivar Terno is the highest stability. The cultivar Tarchalska is recommended for further inclusion in the breeding program because its stability and the highest averages of seeds yield.

scholarly journals Genotype by Environment Interaction for Grain Yield of Barley Mutant Lines

2019 ◽  
Vol 65 (2) ◽  
pp. 51-58
Author(s):  
Boryana Dyulgerova ◽  
Nikolay Dyulgerov
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Winter Barley ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Growing Seasons ◽  
Stable Mutant ◽  
Check Variety ◽  
Mutant Lines

Abstract The aim of this study was to examine the genotype by environment interaction for grain yield and to identify high-yielding and stable mutant lines of 6-rowed winter barley under different growing seasons. The study was carried out during 7 growing seasons from 2010 – 2011 to 2016 – 2017 in the experimental field of the Institute of Agriculture – Karnobat, Southeastern Bulgaria. Fourteen advanced mutant lines and the check variety Vesletc were studied using a complete block design with 4 replications. The AMMI analysis of variance indicated that 20.54% of the variation for grain yield was explained by the effect of genotype and 37.34% and 42.12% were attributable to the environmental effects and genotype by environment interaction. The magnitude of the genotype by environment interaction was two times larger than that of genotypes, indicating that there was a substantial difference in genotype response across environments. The AMMI and GGE biplot analyses identified G9 as the highest yielding and stable genotype. This mutant line can be recommended for further evaluation for variety release. The mutant lines G6, G13 and G15 were suggested for inclusion in the breeding program of winter barley due to its high grain yield and intermediate stability.

scholarly journals Recurrent selection in inbred popcorn families

2004 ◽  
Vol 61 (6) ◽  
pp. 609-614 ◽  
Author(s):  
Máskio Daros ◽  
Antônio Teixeira do Amaral Jr. ◽  
Messias Gonzaga Pereira ◽  
Fabrício Santana Santos ◽  
Ana Paula Cândido Gabriel ◽  
...  
Keyword(s):  
Genetic Variability ◽  
Recurrent Selection ◽  
Agronomic Traits ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Small Scale ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Randomized Complete Block Design ◽  
Superior Genotypes

Although much appreciated in Brazil, commercial popcorn is currently cropped on a fairly small scale. A number of problems need to be solved to increase production, notably the obtaintion of seeds with good agronomic traits and good culinary characteristics. With the objective of developing superior genotypes in popcorn, a second cycle of intrapopulation recurrent selection based on inbred S1 families was carried out. From the first cycle of selection over the UNB-2U population, 222 S1 families were obtained, which were then divided into six sets and evaluated in a randomized complete block design with two replications within the sets. Experiments were carried out in two Brazilian localities. The analysis of variance revealed environmental effects for all evaluated traits, except popping and stand, showing that, for most traits, these environments affected genotype behavior in different ways. In addition, the set as source of variation was significant for most of the evaluated traits, indicating that dividing the families into sets was an efficient strategy. Genotype-by-environment interaction was detected for most traits, except popping expansion and stand. Differences among genotypes were also detected (1% F-test), making viable the proposition of using the genetic variability in the popcorn population as a basis for future recurrent selection cycles. Superior families were selected using the Smith and Hazel classic index, with predicted genetic gains of 17.8% for popping expansion and 26.95% for yield.

scholarly journals Genotype-by-environment interaction and yield stability analysis in sorghum (Sorghum bicolor (L.) Moench) genotypes in North Shewa, Ethiopia

2017 ◽  
Vol 9 (1) ◽  
pp. 82-94 ◽  
Author(s):  
Sintayehu Admas ◽  
Kassahun Tesfaye
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Yield Data ◽  
Genotype By Environment ◽  
The North ◽  
Sorghum Variety ◽  
Cropping Seasons ◽  
The Given

Abstract A multi-environment sorghum variety trial comprised of nine genotypes along with one standard check, “yeju”, was carried out in the main cropping seasons of the period of 2006–2008. The objective of this research was to identify a stable and better-yielding sorghum variety under the conditions of the sorghum-growing area of North Shewa, Ethiopia. The experiment was arranged in randomized complete block design replicated three times within an experiment. AMMI analysis based on grain yield data revealed that genotypes ICSV 1112BF, 82 LPYT-2 # 5x81ESIP 46, and PGRC/E #222880 were superior to the standard check both in grain yield and stability, and hence these genotypes have been verified, and the genotype PGRC/E #222880 has been registered by the national variety-releasing technical and standing committee by the given name “Chare” for commercial production for the North Shewa sorghum-growing areas.

scholarly journals Genotype by environment interaction of “carioca” seeded common bean advanced lines in northeastern Brazil

2016 ◽  
Vol 37 (4) ◽  
pp. 1745
Author(s):  
Helton Santos Pereira ◽  
Renata Cristina Alvares ◽  
Leonardo Cunha Melo ◽  
Antônio Félix da Costa ◽  
Hélio Wilson Lemos de Carvalho ◽  
...  
Keyword(s):  
Grain Yield ◽  
Common Bean ◽  
Block Design ◽  
Genotype By Environment Interaction ◽  
Northeastern Brazil ◽  
Joint Analysis ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Randomized Block Design ◽  
Environmental Stratification

The objectives of the present work were to identify common bean lines with high grain yield, adaptability and stability; stratify the environment; and detect the most important factors for the genotype by environment (G×E) interaction in northeastern Brazil. Nineteen experiments were conducted in a randomized block design with three replications during the rainy growing season at 11 locations in the States of Pernambuco, Alagoas, Sergipe, and Bahia in 2009 and 2010. In each experiment, 16 “carioca” seeded lines were evaluated, and the grain yield, assessed. Data were subjected to analyses of variance and adaptability and stability by the methodologies of Annicchiarico and Additive Main Effects and Multiplicative Interactions (AMMI), analysis of the factors for environmental stratification and joint analysis with decomposition of the G×E interaction in genotype by year and genotype by location. According to the AMMI method, BRS Estilo and CNFC 11951 were selected as stable high-yielding lines. CNFC 11954, IPR Juriti, CNFC 11948 and BRS Estilo were identified as stable high-yielding lines based on the methodology of Annicchiarico. BRS Estilo was identified as stable according to both methodologies and was therefore considered suitable for growth in the Northeast region for use as a parent line in regional breeding programs. The locations in this region used to test the common bean lines were informative, except Carira, which could be eliminated from the assay network. Interaction among genotypes, locations and years were observed, suggesting that assessments shoud be conducted at the largest number of locations and years, in this order of importance.

scholarly journals Genotype-by-environment interaction for seed glucosinolate content in winter oilseed rape (Brassica napus L.) using an additive main effects and multiplicative interaction model

2018 ◽  
Vol 55 (1) ◽  
pp. 85-96 ◽  
Author(s):  
Jan Bocianowski ◽  
Kamila Nowosad ◽  
Alina Liersch ◽  
Wiesława Popławska ◽  
Agnieszka Łącka
Keyword(s):  
Block Design ◽  
Interaction Model ◽  
Genotype By Environment Interaction ◽  
Glucosinolate Content ◽  
Environment Interaction ◽  
Brassica Napus L ◽  
Multiplicative Interaction ◽  
Genotype By Environment ◽  
Winter Rapeseed ◽  
Main Effects

Summary The objective of this study was to assess genotype-by-environment interaction for seed glucosinolate content in winter rapeseed cultivars grown in western Poland using the additive main effects and multiplicative interaction model. The study concerned 25 winter rapeseed genotypes (15 F1 CMS ogura hybrids, parental lines and two European cultivars: open pollinated Californium and F1 hybrid Hercules), evaluated at five locations in a randomized complete block design with four replicates. The seed glucosinolate content of the tested genotypes ranged from 5.53 to 16.80 μmol∙g-1 of seeds, with an average of 10.26 μmol∙g-1. In the AMMI analyses, 48.67% of the seed glucosinolate content variation was explained by environment, 13.07% by differences between genotypes, and 17.56% by genotype-by-environment interaction. The hybrid PN66×PN07 is recommended for further inclusion in the breeding program due to its low average seed glucosinolate content; the restorer line PN18, CMS ogura line PN66 and hybrids PN66×PN18 and PN66×PN21 are recommended because of their stability and low seed glucosinolate content.

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