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

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Joseph Adjebeng-Danquah ◽  
Kwabena Acheremu ◽  
Emmanuel Boachie Chamba ◽  
Freda Ansaah Agyapong ◽  
Alhassan Sayibu
Keyword(s):  
Yield Components ◽  
Tuber Yield ◽  
Block Design ◽  
Genotypic Variation ◽  
Sum Of Squares ◽  
Yield Stability ◽  
Northern Ghana ◽  
Environment Interaction ◽  
Genotype Effect ◽  
Gxe Interaction

Studies were conducted to determine tuber yield stability and adaptability of some elite yam (Dioscorea sp.) genotypes in northern Ghana. Ten elite exotic yam genotypes alongside one locally cultivated farmer-preferred variety, Laribako, were grown in five environments between 2010 and 2012. These 11 genotypes were arranged in a randomised complete block design with three replications 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 < 0.05 higher tuber yields than the local check, Laribako. The highest tuber yield (16.03 t ha−1) across environments was obtained from 96/19158 followed by 95/00594 (14.9 t ha−1). According to the additive main effect multiplicative interaction (AMMI) analysis, genotype (G), environment (E), and GxE interaction, respectively, explained 39.71%, 36.03%, and 24.26% of the total sum of squares for tuber yield. For number of tubers per plant, GxE effect explained the greatest percentage (60.46%) of the total sum of squares compared to genotype effect (22.00%) and environment effect (17.54%). The local variety, Laribako, was more stable across all environments though low yielding compared to the exotic genotypes. Three genotypes, 95/19158, 95/19177, and 96/02025, were more stable across environments than the other exotic genotypes. Genotype 95/18544 was the most sensitive and for that matter responded positively in the favorable environments. The study identified genotypes with specific and general adaptation potential across different environments for tuber yield that can be further tested in on-farm trials for possible release.

scholarly journals AMMI Stability Analysis and Estimation of Genetic Parameters for Growth and Yield Components in Cassava in the Forest and Guinea Savannah Ecologies of Ghana

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Joseph Adjebeng-Danquah ◽  
Joseph Manu-Aduening ◽  
Vernon Edward Gracen ◽  
Isaac Kwadwo Asante ◽  
Samuel Kwame Offei
Keyword(s):  
Block Design ◽  
Sum Of Squares ◽  
Yield Stability ◽  
Growth And Yield ◽  
High Yield ◽  
Phenotypic Variance ◽  
Environment Interaction ◽  
Dry Matter Content ◽  
Root Yield ◽  
Ammi Analysis

Twenty cassava genotypes were arranged in a randomised complete block design with three replications and assessed for growth and yield stability using the additive main effect and multiplicative interaction (AMMI) analysis. Highly significant (P<0.001) effects of genotype, environment, and genotype ⁎ environment interaction were observed for all traits studied. The AMMI analysis of variance indicated that genotype accounted for 51% of the total sum of squares for height at first branching followed by environment (33%) and interaction (15%). For fresh root yield, environment effects accounted for 37% of the total sum of squares, whilst genotype and interaction accounted for 32% and 29%, respectively. Genotypic variances for harvest index (HI), plant height, storage root yield, and dry matter content contributed a greater proportion of the phenotypic variance indicating stronger genetic control. This suggests better chance of progress in the genetic improvement of these traits. Genotype MM96/1751 combined high yield with stability according to the yield stability index ranking across environments. On the other hand genotypes UCC 2001/449 and 96/1708 though high yielding were unstable according to AMMI stability value scores. However they can be tested further in more environments to ascertain their specific adaptability for release to farmers for cultivation to boost cassava production and ensure food security.

scholarly journals Genotype by environment interaction and stability analysis for rice genotypes under Boro condition

Genetika ◽  
2014 ◽  
Vol 46 (2) ◽  
pp. 521-528 ◽  
Author(s):  
Lotan Bose ◽  
Nitiprasad Jambhulkar ◽  
Kanailal Pande
Keyword(s):  
Interaction Analysis ◽  
Block Design ◽  
Principal Component ◽  
Stability Index ◽  
Yield Stability ◽  
Environment Interaction ◽  
Multiplicative Interaction ◽  
Genotype Effect ◽  
Rice Genotypes ◽  
Stability Statistics

Genotype (G)?Environment (E) interaction of nine rice genotypes possessing cold tolerance at seedling stage tested over four environments was analyzed to identify stable high yielding genotypes suitable for boro environments. The genotypes were grown in a randomized complete block design with three replications. The genotype ? environment (G?E) interaction was studied using different stability statistics viz. Additive Main effects and Multiplicative Interaction (AMMI), AMMI stability value (ASV), rank-sum (RS) and yield stability index (YSI). Combined analysis of variance shows that genotype, environment and G?E interaction are highly significant. This indicates possibility of selection of stable genotypes across the environments. The results of AMMI (additive main effect and multiplicative interaction) analysis indicated that the first two principal components (PC1-PC2) were highly significant (P<0.05). The partitioning of TSS (total sum of squares) exhibited that the genotype effect was a predominant source of variation followed by G?E interaction and environment. The genotype effect was nine times higher than that of the G?E interaction, suggesting the possible existence of different environment groups. The first two interaction principal component axes (IPCA) cumulatively explained 92 % of the total interaction effects. The study revealed that genotypes GEN6 and GEN4 were found to be stable based on all stability statistics. Grain yield (GY) is positively and significantly correlated with rank-sum (RS) and yield stability index (YSI). The above mentioned stability statistics could be useful for identification of stable high yielding genotypes and facilitates visual comparisons of high yielding genotype across the multi-environments.

scholarly journals GENOTYPE BY ENVIRONMENT INTERACTION AND YIELD STABILITY OF SOYBEAN GENOTYPES

2018 ◽  
Vol 19 (1) ◽  
pp. 25
Author(s):  
Ayda Krisnawati ◽  
M. Muchlish Adie
Keyword(s):  
Yield Components ◽  
Block Design ◽  
Sum Of Squares ◽  
Yield Potential ◽  
High Yield ◽  
Environment Interaction ◽  
Yield Data ◽  
Branch Number ◽  
Soybean Production ◽  
Soybean Genotypes

<p class="abstrakinggris">Soybean breeding program in Indonesia has been actively involved in improving the genetic yield potential to meet the needs of farmers in different parts of the country. The study aimed to determine the presence of soybean production mega-environments and to evaluate the yield performance and stability of 12 soybean genotypes. Soybean yield performances were evaluated in eight production centers in Indonesia during 2013 growing season. The experiment in each location was arranged in a randomized complete block design with four replications. Parameters observed included grain yield and yield components. The yield data were analyzed using GGE biplot and the yield components data were analyzed using analysis of variance. The results showed that the yield performances of soybean genotypes were highly influenced by genotype-environment interaction (GEI) effects. The yield components were significantly affected by GEI except per plant branch number. The partitioning of the G + GE sum of squares showed that PC1 and PC2 were significant components which accounted for 57.41% and 18.55% of G + GE sum of squares, respectively. Based on the GGE visual assessment, agro-ecology for soybean production in Indonesia was divided into at least three mega-environments. Genotypes 8 and 2 were the best yielding genotypes in the most discriminating environment, but adapted to specific environment, thus highly recommended for that specific location. Genotypes 9 and 10 were stable and had relatively high yield performances across environments. Those genotypes would be recommended to be proposed as new soybean varieties.</p>

scholarly journals AMMI and GGE Biplot Analysis of Linseed (Linum usitatissimum L) Genotypes in Central and South-Eastern Highlands of Ethiopia

2018 ◽  
Vol 6 (3) ◽  
pp. 117-127
Author(s):  
Adane C. Chobe ◽  
Abebe D. Ararsa
Keyword(s):  
Degrees Of Freedom ◽  
Block Design ◽  
Pooled Analysis ◽  
Sum Of Squares ◽  
Yield Stability ◽  
Superior Performance ◽  
Environment Interaction ◽  
Linum Usitatissimum L ◽  
Genotype Environment Interaction ◽  
Cropping Season

Twelve linseed genotypes were evaluated in 13 environments during the main cropping season in central highlands of Ethiopia. The objective of the study was to determine the magnitude and pattern of G × E interaction and yield stability in linseed genotypes. The study was conducted using randomized complete block design with 3 replications. Genotype × environment interaction and yield stability were estimated using the additive main effects and multiplicative interaction and site regression genotype plus genotype × environment interaction biplot. Pooled analysis of variance for seed yield showed significant (p ≤ 0.001) differences among the genotypes, environments and G × E interaction effects. This indicated that the genotypes differentially responded to the changes in the test environments or the test environments differentially discriminated the genotypes or both. Environment effect was responsible for the greatest part of the variation, followed by G × E interaction and genotype effects, indicating spatial and temporal replications of linseed yield trials. The first three multiplicative component terms of AMMI were found to be significant. The first two multiplicative component terms sum of squares, with their cumulative degrees of freedom of 44, explained 62.9% of the interaction sum of squares. No single variety showed superior performance in all environments but CI-1525 demonstrated top ranking at six of the thirteen environments. The application of AMMI and GGE biplots facilitated the visual comparison and identification of superior genotypes, thereby supporting decisions on variety selection and recommendation in different environments

scholarly journals HASIL DAN STABILITAS HASIL DUA PULUH GENOTIPE JARAK PAGAR (Jatropha curcas L.) SELAMA SEMBILAN BELAS BULAN BERPRODUKSI

2020 ◽  
Vol 16 (3) ◽  
pp. 126
Author(s):  
EDI WARDIANA ◽  
DIBYO PRANOWO
Keyword(s):  
Jatropha Curcas ◽  
Block Design ◽  
Yield Stability ◽  
Environment Interaction ◽  
Physic Nut ◽  
Climate Type ◽  
Jatropha Curcas L ◽  
Experimental Station ◽  
Gxe Interaction ◽  
Randomized Complete Block Design

<p>ABSTRAK</p><p>Pengujian interaksi genotipe dengan lingkungan (GxE) serta analisisstabilitas hasil suatu genotipe merupakan hal yang penting dalam programpemuliaan tanaman. Penelitian dengan tujuan untuk menganalisis hasil danstabilitas hasil 20 genotipe tanaman jarak pagar telah dilakukan di KebunPercobaan Pakuwon, Sukabumi, Jawa Barat, pada ketinggian tempat 450m dpl dengan jenis tanah Latosol dan tipe iklim B mulai bulan Mei 2008sampai Desember 2009. Rancangan yang digunakan adalah acak kelom-pok lengkap dengan 20 perlakuan genotipe tanaman dan tiga ulangan.Peubah yang dianalisis adalah jumlah buah panen selama 19 bulanberproduksi. Analisis ragam dilakukan secara gabungan antara 20 genotipedengan 19 lingkungan (umur tanaman) dan analisis stabilitas hasilmengikuti metode Eberhart dan Russel (1966). Hasil penelitian menunjuk-kan bahwa berdasarkan pada hasil jumlah buah panen selama 19 bulanberproduksi terdapat enam genotipe jarak pagar yang dapat diklasifikasi-kan ke dalam genotipe yang berdaya hasil tinggi dan stabil, yaitu PT7,PT13, PT14, PT15, PT33, dan 3189. Sedangkan MT7 dan HS49diklasifikasikan ke dalam genotipe berdaya hasil tinggi tetapi tidak stabil.</p><p>Kata kunci : Jatropha curcas L., interaksi GxE, hasil, stabilitas hasil</p><p>ABSTRACT</p><p>Yield and yield stability of twenty genotypes of physic nut(Jatropha curcas L.) during nineteen months ofproduction</p><p>Genotype and environment interaction (GxE) and yield stabilityanalysis of the genotypes is more important in plant breeding program.This experiment was carried out from May 2008 until December 2009 atPakuwon Experimental Station, Sukabumi, West Java with altitude about450 m above sea level, Latosol soil type and B climate type. The objectiveof this experiment was to analyze the yield and yield stability of 20genotypes of physic nut. Randomized complete block design with 20treatments of physic nut genotype and three replications was used in thisstudy, and the variabel observed was number of fruit harvested per month.Data were analyzed by combined analysis of variance and stabilityanalysis using Eberhart and Russel (1966) methods. Result showed thatbased on number of fruit harvested during 19 months production the PT7,PT13, PT14, PT15, PT33 and 3189 were classified as high yielding andstable genotypes. While, MT7 and HS49 were classified as high yieldingand unstable genotypes.</p><p>Key words : Jatropha curcas L., GxE interaction, yield, yield stability.</p>

scholarly journals Assessing yield stability in African yam bean (Sphenostylis stenocarpa) performance using year effect

2020 ◽  
Vol 5 (1) ◽  
pp. 202-212
Author(s):  
Charity Aremu ◽  
Sunday A. Ige ◽  
Dolapo Ibirinde ◽  
Ibrahim Raji ◽  
Stephen Abolusoro ◽  
...  
Keyword(s):  
Seed Yield ◽  
Crop Production ◽  
Tuber Yield ◽  
Block Design ◽  
Field Trials ◽  
Yield Stability ◽  
Environment Interaction ◽  
African Yam Bean ◽  
Year Effect ◽  
Sphenostylis Stenocarpa

AbstractMaintaining yield stability in the African yam bean (AYB) (Sphenostylis stenocarpa) under year-to-year variability is crucial to its sustained productivity. Exploring yield stability in crops is vital in identifying how stable and consistent the yield of such crops is. Cultivation of AYB, an underutilized traditional legume in a specific environment, will further popularize the crop and enhance the acceptance as a cheap protein source thereby reducing hunger and malnutrition especially in regions where climate change has negatively affected legume crop production. Field trials were carried out to study the performance of 23 AYB genotypes in four-year environments. Two seeds of each genotype were sown in a single 5 m row plot spaced at 1 m between and within rows; the trial was conducted during the cropping season of 2011, 2012, 2013, and 2014 and was laid out in a randomized complete block design (RCBD) with three replications. At harvesting, five plants from each row were separately harvested; seeds of all the sampled plants in each plot were bulked and weighed, and the seed yield per plant was then determined. A combined analysis of variance (ANOVA) was performed to test for the significance of genotypes, year, and genotype by year interaction. Before combined ANOVA, a test for homogeneity of residual variances was performed using Bartlet’s test; stability of the genotypes over the years was ascertained numerically and graphically using additive main effects and multiplicative interaction and Genotype X Genotype X Environment interaction (GGE) biplot analyses. Rainfall distribution between 680 and 1,700 mm with an average temperature of 28.50°C under sandy-clay soil type supported high and stable seed yield production in AYB. This environment was found adequate during the 2014 (E1) growing season. Genotypes TSs118, TSs12, TSs109, TSs148, TSs5, TSs61, and TSs69 produced an above-average mean yield across the years and were found to be productive and stable in all the year environments. TSs82 and TSs6 with above-average mean seed and tuber yield can be considered for cultivation where seed and tuber dual-purpose production is to be maximized, while TSs111, TSs49, and TSs96 with high tuber yield ranking above average total tuber yield can be further enhanced for tuber production.

scholarly journals Genotype X Environment Interaction of Food Barley

2015 ◽  
Vol 21 ◽  
pp. 41-48
Author(s):  
Gebremedhin Welu
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Genotype Effect ◽  
Environment Effects ◽  
Randomized Complete Block Design ◽  
Barley Genotypes

The objective of this experiment was to estimate the magnitude of genotype X environment interaction on grain yield and yield related traits. Twelve varieties of food barley were included in the study planted in randomized complete block design with three replications. The ANOVA of combined and individual location revealed significant differences among the food barley genotypes for grain yield and other traits. The results of ANOVA for grain yield showed highly significant (p≤0.01) differences among genotypes evaluated for grain yield at Maychew and significant (p≤0.05) differences in Korem, Alage and Mugulat. The ANOVA over locations showed a highly significant (p≤0.01) variation for the genotype effect, environment effects, genotype X environment interaction (GEI) effect and significant (p≤0.05) variation for GEI effect of yield and for most of the yield related traits of food barley genotypes. Haftysene, Yidogit, Estayish and Basso were the genotypes with relatively high mean grain yield across all locations and they are highly performing genotypes to the area. Among locations, the highest mean grain yield was recorded at Korem and it was a suited environment to all the genotypes whereas Mugulat is unfavoured one. ECOPRINT 21: 41-48, 2014DOI: http://dx.doi.org/10.3126/eco.v21i0.11903

scholarly journals Genotype x Environment Interaction and Yield-Stability Analyses of Rice Grown in Tropical Inland Swamp

2011 ◽  
Vol 39 (1) ◽  
pp. 220 ◽  
Author(s):  
Adesola L. NASSIR ◽  
Omolayo J. ARIYO
Keyword(s):  
Total Variation ◽  
Yield Stability ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Rice Varieties ◽  
Environmental Indices ◽  
Genotype X Environment ◽  
Additional Information ◽  
Gxe Interaction ◽  
The Stability

Twelve rice varieties were cultivated in inland hydromorphic lowland over a four year-season period in tropical rainforest ecology to study the genotype x environment (GxE) interaction and yield stability and to determine the agronomic and environmental factors responsible for the interaction. Data on yield and agronomic characters and environmental variables were analyzed using the Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype x Environment Interaction, GGE and the yield stability using the modified rank-sum statistic (YSi). AMMI analysis revealed environmental differences as accounting for 47.6% of the total variation. The genotype and GxE interaction accounted for 28.5% and 24% respectively. The first and second interaction axes captured 57% and 30% of the total variation due to GXE interaction. The analysis identified ‘TOX 3107’ as having a combination of stable and average yield. The GGE captured 85.8%of the total GxE. ‘TOX 3226-53-2-2-2’ and ‘ITA 230’ were high yielding but adjudged unstable by AMMI. These two varieties along with ‘WITA 1’ and ‘TOX 3180-32-2-1-3-5’ were identified with good inland swamp environment, which is essentially moisture based. The two varieties (‘TOX 3226-53-2-2-2’ and ‘ITA 230’), which were equally considered unstable in yield by the stability variance, ?2i, were selected by YSi in addition to ‘TOX 3107’, ‘WITA 1’, ‘IR 8’ and ‘M 55’. The statistic may positively complement AMMI and GGE in selecting varieties suited to specific locations with peculiar fluctuations in environmental indices. Correlation of PC scores with environmental and agronomic variables identified total rainfall up to the reproductive stage, variation in tillering ability and plant height as the most important factors underlying the GxE interaction. Additional information from the models can be positively utilized in varietal development for different ecologies.

Yield performance stability of adapted and improved cowpea in the Equatoria region of South Sudan

2019 ◽  
Author(s):  
Tony Ngalamu ◽  
Silvestro Meseka ◽  
James Odra Galla ◽  
Nixon James Tongun ◽  
Newton W. Ochanda ◽  
...  
Keyword(s):  
Block Design ◽  
South Sudan ◽  
Yield Stability ◽  
Environment Interaction ◽  
Analysis Method ◽  
Genotype X Environment ◽  
Production Constraints ◽  
Stability Performance ◽  
Randomized Complete Block Design ◽  
Main Production

Cowpea is an important food crop with high nutritional and socio-economical values in South Sudan. However, the lack of improved varieties is one of the main production constraints. This study was undertaken to assess the yield stability performance of improved cowpea genotypes across six environments in South Sudan in 2014 and 2015. Nine genotypes were evaluated in a randomized complete block design with three replications. Genotype and genotype x environment biplot analysis method was used to determine yield stability. Highly significant (p less than 0.001) genotype x environment interaction effect was detected for seed yield. IT90K-277-2 had the highest while ACC004 had the lowest grain yield. Palotaka was as highly discriminating and repeatable environment compare to the other testing sites. IT07K-211-1-8 and Mading Bor II were the most responsive genotypes, while IT90K-277-2 was the most stable high yielding genotype across the test environments and can be grown by farmers across the region.

scholarly journals Interaksi Genotipe x Lingkungan Hasil dan Komponen Hasil 14 Genotipe Tomat di Empat Lingkungan Dataran Rendah

2015 ◽  
Vol 43 (1) ◽  
pp. 59
Author(s):  
Suprayanti Martia Dewi ◽  
Sobir , ◽  
Muhamad Syukur
Keyword(s):  
Stability Analysis ◽  
Block Design ◽  
Fruit Weight ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Gxe Interaction ◽  
Superior Genotype ◽  
Ammi Model ◽  
The Stability

Genotype x environment interaction (GxE) information is needed by plant breeders to assist the identification of superior genotype. Stability analysis can be done if there is a GxE interaction, to show the stability of a genotype when planted in different environments. This study aimed to estimate the effects of genotype x environment interaction on yield and yield components of fruit weight per plant as well as to look at the stability of 14 tomato genotypes at four lowland locations. The study was conducted at four locations, namely Purwakarta, Lombok, Tajur and Leuwikopo. Experiments at each location was arranged in a randomized complete block design with three replications. Stability analysis was performed using the AMMI model. Fruit weight, fruit diameter, number of fruits per plant and total fruit weight per plant characters showed highly significant genotype x environment interactions. Variability due to the effect of GxE interaction based on a AMMI2 contributed by 88.50%. IPBT3, IPBT33, IPBT34, IPBT60 and Intan were stable genotypes under AMMI model.<br />Keywords: AMMI, multilocation trials

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