A study was conducted to determine the genotype by environment interaction (GEI) effects on yield... more A study was conducted to determine the genotype by environment interaction (GEI) effects on yield and its components in sesame grown at three different locations across the Awash valleys in Ethiopia using AMMI and Joint Regression models. Ten released sesame varieties were evaluated in a randomized complete block design with 3 replications for two different seasons (2010/11 & 2011/12). Both models revealed that the mean squares for genotypes, environments and GEI were significant for the characters viz., seed yield, harvest index and number of capsules, indicating the presence of sufficient genetic variation among varieties and possible selection of stable entries. However, the variances due to GEI (linear) for number of capsules was not significant with rather high environmental variances, showing that the variability due to environments was higher than that due to genotypes for this particular trait. Moreover, the squared deviation from regression (S 2 di) was not significant for all characters indicating that the nonlinear sensitivity in the expressions of these traits was not important. Ranking of genotypes based on the different stability indices discriminated genotypes (Adi and Srk) for seed yield and number of capsules; (M-80, Srk and Tat) for harvest index showed high mean yield and low interaction effect which can be considered as stable varieties across environments. Whereas, genotypes (Abs and Tat) for both seed yield and number of capsules; (Adi, Arg and Klf) for harvest index, exhibited high interaction effect and are suitable for specific environments. Overall ranking revealed that genotype Srk is identified as the best variety across all environments and traits; hence it is recommended for diverse environmental conditions of the Awash valleys to exploit its yield potential. Assaita season-II and Werer season-I were the best environments where the highest mean of all traits recorded. Therefore, these environments can be ideal for increased sesame production along the Afar Rift valley of Ethiopia.
A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yie... more A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yield in sesame varieties and to identify stable and promising varieties for general and specific adaptations. The experiment was carried out at three locations across the areas of the Awash Valley in Ethiopia; namely Assaita, Melkassa and Werer over two seasons during the 2011 cropping and 2012 off seasons. Ten improved sesame varieties were planted in a randomized complete block design (RCBD) replicated trice in each location and year. Analysis of variance using AMMI model revealed significant differences (P<0.01) for genotype, environment, GEI and interaction principal component (IPCA1), suggesting differential response of varieties across testing environments and the need for stability analysis. Stability analysis using Biplot graph and AMMI stability value were done to further shed light on the GEI of oil yield. The study revealed that the environment Wr1 (Werer season-I) had relati...
American Journal of Experimental Agriculture, 2015
Aim: The study was carried out to assess the genetic variability and association of traits with r... more Aim: The study was carried out to assess the genetic variability and association of traits with respect to seed yield and its components in (mid - altitude) sesame germplasm of Ethiopia. Study Design: A 9 x 9 Simple Lattice Design (SLD) with two replications was used. Place and Duration of Study: Melkassa Agricultural Research Centre Ethiopia, during the July December, 2011 main cropping seasons. Methodology : The data recorded on 14 quantitative traits were analyzed for phenotypic and genotypic coefficient of variances, heritability and genetic advance, correlation coefficient, path Original Research Article
American Journal of Experimental Agriculture, 2015
Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties ... more Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties and to identify stable and promising varieties for general and specific adaptations across the areas of the Awash valleys in Ethiopia. Study Design: Entries were planted in a randomized complete block design (RCBD) replicated thrice in each location and year. Original Research Article Abate et al.; AJEA, 9(2): 1-12, 2015; Article no.AJEA.18482 2 Place and Duration of Study: The study was conducted at Assaita, Melkassa and Werer representing the Lower, Upper and Middle Awash valleys of Ethiopia respectively, during the 2010/11 main cropping season and 2011/12 off season. Methodology: Morphological data taken from each environment were analyzed for combined analysis of variance, Additive Main Effects and Multiplicative Interaction (AMMI), Biplot analysis, AMMI Stability Value (ASV), and regression analysis. Finally, ranking of genotypes was done based on the overall results of all stability indices. Results: Combined analysis of variance showed highly significant (P<0.01) difference between the varieties, environments and GEI, suggesting differential response of varieties across testing environments and the need for stability analysis. Proportion of variance captured by environments was 1.43%, genotypes 91.5% and GEI 7.1% of the total variation, indicating less effect of environments on oil content as compared to the effect of genotypes. Stability analysis by AMMI and Joint-regression model were used to further shed light on the GEI of oil content. Two IPCA of AMMI were significant (P<0.01) and captured the largest portion of variation of the total GEI, which indicated that the AMMI model was the best for the data set. The Joint regression analysis indicated that the linear regression (bi) did not deviate from unity for all varieties, suggesting that performance of the cultivars could not be predicted in a linear manner. Conclusion: The influence of environment is less prominent in the manifestation of oil content along the areas of Awash valleys. Season two is the best environment for growing the present set of genotypes for oil content. Variety Adi was identified as the most stable variety across environments for oil content. This variety can be recommended for varied environments of the Awash valleys to exploit its yield potential. The rest high yielder varieties, Serkamo, Tate and Argene can be adapted only under favorable environmental conditions.
Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes u... more Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes using ISSR markers and identify highly diverse genotypes for the purposes of broadening the genetic base of sesame landraces grown in Ethiopia. Place and Duration of Study: The study was conducted in Botany research laboratory of Kasetsart University, Thailand, from April to July, 2013. Methodology: Genomic DNA of 128 sesame genotypes were subjected to PCR amplification and electrophoresis using seven ISSR markers and a binary data matrix prepared for each primer by scoring clear bands. The data generated were used to calculate the number of total bands (TB), Original Research Article Abate et al.; BBJ, 8(4): 1-13, 2015; Article no.BBJ.18481 2 polymorphic bands (PB), polymorphism percentage (P %) and polymorphic information content (PIC) for each locus. The number of different (Na) and effective (Ne) alleles, polymorphic loci (%), Shannon’s information index (I) and Nei’s gene diversity (He) for each population were calculated using GenAlEx 6.5 software. The data were also subjected to analysis of molecular variance (AMOVA) and principal coordinate analysis (PCoA) via distance matrix. Fixation index (Fst) was computed to measure genetic differentiation among populations. Genetic associations among individual genotypes were determined based on dissimilarity matrix using Darwin version 5.0 and a Neighbour-Joining hierarchal tree was constructed based on UPGMA. Results: The 7 ISSR primers in 128 sesame genotypes yielded 96 reproducible amplified bands. The number of amplified bands varied from 7 to 19. Out of 96 bands, 89 (92.2%) were polymorphic. Average number of bands and polymorphic bands per primer were 14 and 12.6 respectively. The polymorphic information content (PIC) value ranged between 0.26 and 0.76, showing the high informativeness of the selected primers. The overall gene diversity and Shannon’s information index were 0.37 and 0.54 respectively. Average dissimilarity value among the genotypes was 0.39. Maximum dissimilarity (0.88) was observed between genotypes Amr-NW6 and Amr-NG9 and less dissimilarity (0.014) was recorded between Amr-NW1 and Amr-NG1. SNNP-7 was the most diverse of all genotypes with highest average dissimilarity value of 0.77. AMOVA showed lower genetic divergence between populations (6%) than within population (94%) with average Fst of 0.061 across populations. The high intra-population variation could be because of large number of genotypes included and due to high out-crossing nature of sesame. Clustering and PCoA analyses clustered the genotypes into individual groups where most of the landraces were grouped in separate clusters irrespective of their geographic origins, while the cultivars were grouped in one cluster, suggesting less variability within the released varieties than the landraces. Accessions no. 56, 73, and 105 were out grouped from the rest. Conclusion: There exist considerable variations among sesame genotypes collected from different geographical regions of Ethiopia. Genotypes Amr-NSh-6, Benishangul-6 and SNNP-7 exhibited a good amount of genetic divergence and hence can be used in crossing program for genetic improvement of sesame in Ethiopia.
Aim: The study was undertaken to assess the genetic variability and character association in 81 m... more Aim: The study was undertaken to assess the genetic variability and character association in 81 mid-altitude sesame accessions of Ethiopia based on important agronomic traits. Study Design: A 9 x 9 Simple Lattice Design (SLD) with two replications was used. Place and Duration of Study: Melkassa Agricultural Research Centre Ethiopia, during the July-December, 2011 main cropping seasons. Methodology: The data recorded on 14 quantitative traits were analyzed for phenotypic and genotypic coefficient of variances, heritability and genetic advance, correlation coefficient, path coefficient analysis, principal component analysis and divergence analysis based on Mahalanobis statistics, using SAS 9.2. Statistical software to evaluate the pattern and extent of variation among 81 mid-altitude genotypes. Results: Analysis of variance revealed significant difference among genotypes for all traits studied. Less than 50% heritability was noted in all traits studied. Moderate heritability coupled w...
The Italian Sarcoma Group and the Scandinavian Sarcoma Group designed a joint study to improve th... more The Italian Sarcoma Group and the Scandinavian Sarcoma Group designed a joint study to improve the prognosis for patients with Ewing&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s family tumors and synchronous metastatic disease limited to the lungs, or the pleura, or a single bone. The study was opened in 1999 and closed to the enrollment in 2008. The program consisted of intensive five-drug combination chemotherapy, surgery and/or radiotherapy as local treatment, and consolidation treatment with high-dose busulfan/melphalan plus autologous stem cell rescue and total-lung irradiation. During the study period, 102 consecutive patients were enrolled. The median follow-up was 62 months (range 24-124). The 5-year event-free survival probability was 0.43 [standard deviation (SD) = 0.05] and the 5-year overall survival probability was 0.52 (SD = 0.052). Unfavorable prognostic factors emerging on multivariate analysis were a poor histological/radiological response at the site of the primary tumor [relative risk (RR) = 3.4], and incomplete radiological remission of lung metastases after primary chemotherapy (RR = 2.6). One toxic death and one secondary leukemia were recorded. This intensive approach is feasible and long-term survival is achievable in ∼50% of patients. New treatment approaches are warranted for patients responding poorly to primary chemotherapy.
A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yie... more A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yield in sesame varieties and to identify stable and promising varieties for general and specific adaptations. The experiment was carried out at three locations across the areas of the Awash Valley in Ethiopia; namely Assaita, Melkassa and Werer over two seasons during the 2011 cropping and 2012 off seasons. Ten improved sesame varieties were planted in a randomized complete block design (RCBD) replicated trice in each location and year. Analysis of variance using AMMI model revealed significant differences (P<0.01) for genotype, environment, GEI and interaction principal component (IPCA1), suggesting differential response of varieties across testing environments and the need for stability analysis. Stabil ity analysis using Biplot graph and AMMI stability value were done to further shed light on the GEI of oil yield. The study revealed that the environment Wr1 (Werer season-I) had relatively little interaction effects with above average mean oil yield per environment. Hence, it can be recommended as ideal environment for growing the present set of sesame genotypes for breeding programme. Ranking of genotypes based on the different stability indices identified the varieties Adi and Serkamo to be the most stable genotypes across all environments. Therefore, these varieties can be recommended as promising cultivars for oil yield of sesame across diverse agro-ecologies of the Awash Valley to exploit their yield potential. On the other hand, the two high yielding varieties Abasena and Tate were found to be highly interactive and they are recommended for cultivation under favorable environmental conditions for oil yield. Moreover, the study indicated that high performance of genotypes for oil yield recorded in season two (2012). Hence, the off season generally is suggested as the best environment for oil yield of sesame across the areas of the Awash Valley. In this study, AMMI analysis with two IPCA was the best predictive model to reveal the maximum GEI for oil yield in sesame. Abbreviations: ASV = AMMI Stability Value, GEI = Genotype by Environment Interaction, IPCA = Interaction Principal Component.
Genetic diversity among 128 sesame (Sesamum indicum L.) genotypes representing 10 geographically ... more Genetic diversity among 128 sesame (Sesamum indicum L.) genotypes representing 10 geographically distinct populations in Ethiopia was assessed at DNA level using RAPD analysis. Eleven RAPD primers used amplified a total of 149 bands, of which 142 (95. 45%) were polymorphic. Each primer generated 7 to 23 amplified fragments with an average of 13.5 bands per primer. Percent of polymorphic loci (P%), number of different (Na) and effective (Ne) alleles along with Shannon information index (I) and Nei's gene diversity (He) values suggested that the population of Oromia was the most diverse of all populations, while populations from Afar (cultivars) and AM-NSh were found to be the least diverse. Based on average dissimilarity values obtained with RAPD primers, AM-NG-25, SNNP-7 and SNNP-8 were the most distinct of all genotypes, while genotypes ORO-20 and TIGR-5 showed maximum similarity with others. The UPGMA clustering based on the dissimilarity matrix clustered the genotypes into 3 major groups and 11 subgroups, while three genotypes viz., BENSH-6, ORO-14 and SNNP-5 were found out-grouped from the rest and did not join any of the cluster; they are then most divergent genotypes. Generally, both clustering and PCoA patterns revealed that most genotypes located geographically far apart were found to cluster in the same group, while those genotypes from the same origin dispersed. Overall results indicated that RAPD technique revealed a high level of genetic variation among sesame genotypes collected from diverse ecologies of Ethiopia. AMOVA = Analysis of Molecular Variance, NJ = Neighbor Joining, PCoA = Principal Coordinate Analysis, UPGMA= Unweighted Pair-group Method with Arithmetic mean.
Forty nine sesame genotypes collected from low-altitude areas of Ethiopia were evaluated at Werer... more Forty nine sesame genotypes collected from low-altitude areas of Ethiopia were evaluated at Werer Agricultural Research Centre, during the 2011/12 growing season for genetic variability and character association. Morphological data recorded on 14 quantitative traits were analyzed for analysis of variance, phenotypic and genotypic variability, heritability, genetic advance, genetic divergence based on Mahalanobis (D 2) statistics and principal component analysis. Analysis of variance revealed significant difference among the genotypes for each character except for primary branches. Higher genotypic variance was observed for seed yield and number of capsules/plant. Moderate heritability with moderate genetic advance was observed for most of the yield related traits, signifying that these attributes are governed by both additive and non-additive genes action. Based on D 2 values, the genotypes were grouped into seven clusters. The clustering pattern suggested that genotypes of the same origin were distributed into different clusters, indicating the absence of parallelism between clustering and geographic distributions. Maximum inter cluster distance was observed between clusters VI and VII while lowest distance was noticed between cluster I and III. Traits viz., harvest index, seed yield, biomass yield and plant height had highest contribution towards genetic divergence. There is high level of genetic variability in the studied germplasm with regard to seed yield and its component traits. The clustering pattern suggested the absence of relationship between geographic diversity and genetic diversity. Genotypes from distant clusters are suggested to be used as parents for hybridization program to achieve novel recombinants. The use of the selected traits in sesame improvement program would increase yield.
Forty nine sesame genotypes collected from low-altitude areas of Ethiopia were evaluated at Werer... more Forty nine sesame genotypes collected from low-altitude areas of Ethiopia were evaluated at Werer Agricultural Research Centre, during the 2011/12 growing season for genetic variability and character association. Morphological data recorded on 14 quantitative traits were analyzed for analysis of variance, phenotypic and genotypic variability, heritability, genetic advance, correlation and path coefficient analysis. Analysis of variance revealed significant difference among the genotypes for each character except for primary branches, suggesting the existence of considerable genetic variation in the studied germplasm with regard to seed yield and its component traits. There is a high variation in mean performance of genotypes for the studied traits. Am-NG-15 is a high yielding genotype but with lowest oil content, whereas Tigray-13 is a low yielding genotype but with highest oil content. Hence, a crossing program between these genotypes can result in desirable hybrid that can be used for the ongoing sesame improvement program. Moderate heritability with moderate genetic advance was observed for most of the yield related traits, signifying that these attributes are governed by both additive and non-additive genes action. The traits Biomass/plant, harvest index and 1000 seed weight exhibited highly significant positive correlation with seed yield/plant. These characters also had the highest positive direct effect on seed yield/plant. Hence these three traits can be considered as the principal yield components while selecting for yield improvement of lowland sesame genotypes in Ethiopia.
Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties ... more Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties and to identify stable and promising varieties for general and specific adaptations across the areas of the Awash valleys in Ethiopia. Study Design: Entries were planted in a randomized complete block design (RCBD) replicated thrice in each location and year. Original Research Article Abate et al.; AJEA, 9(2): 1-12, 2015; Article no.AJEA.18482 2 Place and Duration of Study: The study was conducted at Assaita, Melkassa and Werer representing the Lower, Upper and Middle Awash valleys of Ethiopia respectively, during the 2010/11 main cropping season and 2011/12 off season. Methodology: Morphological data taken from each environment were analyzed for combined analysis of variance, Additive Main Effects and Multiplicative Interaction (AMMI), Biplot analysis, AMMI Stability Value (ASV), and regression analysis. Finally, ranking of genotypes was done based on the overall results of all stability indices. Results: Combined analysis of variance showed highly significant (P<0.01) difference between the varieties, environments and GEI, suggesting differential response of varieties across testing environments and the need for stability analysis. Proportion of variance captured by environments was 1.43%, genotypes 91.5% and GEI 7.1% of the total variation, indicating less effect of environments on oil content as compared to the effect of genotypes. Stability analysis by AMMI and Joint-regression model were used to further shed light on the GEI of oil content. Two IPCA of AMMI were significant (P<0.01) and captured the largest portion of variation of the total GEI, which indicated that the AMMI model was the best for the data set. The Joint regression analysis indicated that the linear regression (bi) did not deviate from unity for all varieties, suggesting that performance of the cultivars could not be predicted in a linear manner. Conclusion: The influence of environment is less prominent in the manifestation of oil content along the areas of Awash valleys. Season two is the best environment for growing the present set of genotypes for oil content. Variety Adi was identified as the most stable variety across environments for oil content. This variety can be recommended for varied environments of the Awash valleys to exploit its yield potential. The rest high yielder varieties, Serkamo, Tate and Argene can be adapted only under favorable environmental conditions.
Aim: The study was carried out to assess the genetic variability and association of traits with r... more Aim: The study was carried out to assess the genetic variability and association of traits with respect to seed yield and its components in (mid-altitude) sesame germplasm of Ethiopia. Study Design: A 9 x 9 Simple Lattice Design (SLD) with two replications was used. Place and Duration of Study: Melkassa Agricultural Research Centre Ethiopia, during the July-December, 2011 main cropping seasons. Methodology: The data recorded on 14 quantitative traits were analyzed for phenotypic and genotypic coefficient of variances, heritability and genetic advance, correlation coefficient, path Original Research Article Abate et al.; AJEA, 9(3): 1-14, 2015; Article no.AJEA.18483 2 coefficient analysis, principal component analysis and divergence analysis based on Mahalanobis statistics, using SAS 9.2. Statistical software to evaluate the pattern and extent of variation among 81 mid-altitude genotypes. Results: Analysis of variance revealed significant difference among genotypes for all traits studied. Less than 50% heritability was noted in all traits studied. Moderate heritability coupled with moderate to high genetic advance was recorded for most of yield related traits, indicating that these traits are controlled by both additive and non-additive genes. Characters viz., number of capsules, biomass yield, harvest index and 1000 seed weight showed highly significant positive correlation with seed yield. Maximum positive direct effect on seed yield was exerted by number of capsules, biomass yield, days to maturity and harvest index, showing that these traits can be used for selection to improve the primary trait. Divergence analysis based on Mahalanobis statistics grouped the genotypes into seven different clusters. Genotypes were not grouped in relation to their geographical distribution. Maximum inter cluster distance was observed between cluster V and VII; hence, genotypes from these two clusters are suggested as parents for hybridization program to achieve promising recombinants. Conclusion: The germplasm lines had sufficient level of genetic variability for seed yield and its components. Clustering was not associated with the geographical distribution instead genotypes were mainly grouped due to their morphological differences. Seed yield, biomass/plant, harvest index and number of capsules contributed highest towards genetic divergence. The use of these traits in sesame improvement program would increase yield.
Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes u... more Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes using ISSR markers and identify highly diverse genotypes for the purposes of broadening the genetic base of sesame landraces grown in Ethiopia. Place and Duration of Study: The study was conducted in Botany research laboratory of Kasetsart University, Thailand, from April to July, 2013. Methodology: Genomic DNA of 128 sesame genotypes were subjected to PCR amplification and electrophoresis using seven ISSR markers and a binary data matrix prepared for each primer by scoring clear bands. The data generated were used to calculate the number of total bands (TB), Original Research Article Abate et al.; BBJ, 8(4): 1-13, 2015; Article no.BBJ.18481 2 polymorphic bands (PB), polymorphism percentage (P %) and polymorphic information content (PIC) for each locus. The number of different (Na) and effective (Ne) alleles, polymorphic loci (%), Shannon's information index (I) and Nei's gene diversity (He) for each population were calculated using GenAlEx 6.5 software. The data were also subjected to analysis of molecular variance (AMOVA) and principal coordinate analysis (PCoA) via distance matrix. Fixation index (Fst) was computed to measure genetic differentiation among populations. Genetic associations among individual genotypes were determined based on dissimilarity matrix using Darwin version 5.0 and a Neighbour-Joining hierarchal tree was constructed based on UPGMA. Results: The 7 ISSR primers in 128 sesame genotypes yielded 96 reproducible amplified bands. The number of amplified bands varied from 7 to 19. Out of 96 bands, 89 (92.2%) were polymorphic. Average number of bands and polymorphic bands per primer were 14 and 12.6 respectively. The polymorphic information content (PIC) value ranged between 0.26 and 0.76, showing the high informativeness of the selected primers. The overall gene diversity and Shannon's information index were 0.37 and 0.54 respectively. Average dissimilarity value among the genotypes was 0.39. Maximum dissimilarity (0.88) was observed between genotypes Amr-NW6 and Amr-NG9 and less dissimilarity (0.014) was recorded between Amr-NW1 and Amr-NG1. SNNP-7 was the most diverse of all genotypes with highest average dissimilarity value of 0.77. AMOVA showed lower genetic divergence between populations (6%) than within population (94%) with average Fst of 0.061 across populations. The high intra-population variation could be because of large number of genotypes included and due to high out-crossing nature of sesame. Clustering and PCoA analyses clustered the genotypes into individual groups where most of the landraces were grouped in separate clusters irrespective of their geographic origins, while the cultivars were grouped in one cluster, suggesting less variability within the released varieties than the landraces. Accessions no. 56, 73, and 105 were out grouped from the rest. Conclusion: There exist considerable variations among sesame genotypes collected from different geographical regions of Ethiopia. Genotypes Amr-NSh-6, Benishangul-6 and SNNP-7 exhibited a good amount of genetic divergence and hence can be used in crossing program for genetic improvement of sesame in Ethiopia.
A study was conducted to determine the genotype by environment interaction (GEI) effects on yield... more A study was conducted to determine the genotype by environment interaction (GEI) effects on yield and its components in sesame grown at three different locations across the Awash valleys in Ethiopia using AMMI and Joint Regression models. Ten released sesame varieties were evaluated in a randomized complete block design with 3 replications for two different seasons (2010/11 & 2011/12). Both models revealed that the mean squares for genotypes, environments and GEI were significant for the characters viz., seed yield, harvest index and number of capsules, indicating the presence of sufficient genetic variation among varieties and possible selection of stable entries. However, the variances due to GEI (linear) for number of capsules was not significant with rather high environmental variances, showing that the variability due to environments was higher than that due to genotypes for this particular trait. Moreover, the squared deviation from regression (S 2 di) was not significant for all characters indicating that the nonlinear sensitivity in the expressions of these traits was not important. Ranking of genotypes based on the different stability indices discriminated genotypes (Adi and Srk) for seed yield and number of capsules; (M-80, Srk and Tat) for harvest index showed high mean yield and low interaction effect which can be considered as stable varieties across environments. Whereas, genotypes (Abs and Tat) for both seed yield and number of capsules; (Adi, Arg and Klf) for harvest index, exhibited high interaction effect and are suitable for specific environments. Overall ranking revealed that genotype Srk is identified as the best variety across all environments and traits; hence it is recommended for diverse environmental conditions of the Awash valleys to exploit its yield potential. Assaita season-II and Werer season-I were the best environments where the highest mean of all traits recorded. Therefore, these environments can be ideal for increased sesame production along the Afar Rift valley of Ethiopia.
A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yie... more A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yield in sesame varieties and to identify stable and promising varieties for general and specific adaptations. The experiment was carried out at three locations across the areas of the Awash Valley in Ethiopia; namely Assaita, Melkassa and Werer over two seasons during the 2011 cropping and 2012 off seasons. Ten improved sesame varieties were planted in a randomized complete block design (RCBD) replicated trice in each location and year. Analysis of variance using AMMI model revealed significant differences (P<0.01) for genotype, environment, GEI and interaction principal component (IPCA1), suggesting differential response of varieties across testing environments and the need for stability analysis. Stability analysis using Biplot graph and AMMI stability value were done to further shed light on the GEI of oil yield. The study revealed that the environment Wr1 (Werer season-I) had relati...
American Journal of Experimental Agriculture, 2015
Aim: The study was carried out to assess the genetic variability and association of traits with r... more Aim: The study was carried out to assess the genetic variability and association of traits with respect to seed yield and its components in (mid - altitude) sesame germplasm of Ethiopia. Study Design: A 9 x 9 Simple Lattice Design (SLD) with two replications was used. Place and Duration of Study: Melkassa Agricultural Research Centre Ethiopia, during the July December, 2011 main cropping seasons. Methodology : The data recorded on 14 quantitative traits were analyzed for phenotypic and genotypic coefficient of variances, heritability and genetic advance, correlation coefficient, path Original Research Article
American Journal of Experimental Agriculture, 2015
Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties ... more Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties and to identify stable and promising varieties for general and specific adaptations across the areas of the Awash valleys in Ethiopia. Study Design: Entries were planted in a randomized complete block design (RCBD) replicated thrice in each location and year. Original Research Article Abate et al.; AJEA, 9(2): 1-12, 2015; Article no.AJEA.18482 2 Place and Duration of Study: The study was conducted at Assaita, Melkassa and Werer representing the Lower, Upper and Middle Awash valleys of Ethiopia respectively, during the 2010/11 main cropping season and 2011/12 off season. Methodology: Morphological data taken from each environment were analyzed for combined analysis of variance, Additive Main Effects and Multiplicative Interaction (AMMI), Biplot analysis, AMMI Stability Value (ASV), and regression analysis. Finally, ranking of genotypes was done based on the overall results of all stability indices. Results: Combined analysis of variance showed highly significant (P<0.01) difference between the varieties, environments and GEI, suggesting differential response of varieties across testing environments and the need for stability analysis. Proportion of variance captured by environments was 1.43%, genotypes 91.5% and GEI 7.1% of the total variation, indicating less effect of environments on oil content as compared to the effect of genotypes. Stability analysis by AMMI and Joint-regression model were used to further shed light on the GEI of oil content. Two IPCA of AMMI were significant (P<0.01) and captured the largest portion of variation of the total GEI, which indicated that the AMMI model was the best for the data set. The Joint regression analysis indicated that the linear regression (bi) did not deviate from unity for all varieties, suggesting that performance of the cultivars could not be predicted in a linear manner. Conclusion: The influence of environment is less prominent in the manifestation of oil content along the areas of Awash valleys. Season two is the best environment for growing the present set of genotypes for oil content. Variety Adi was identified as the most stable variety across environments for oil content. This variety can be recommended for varied environments of the Awash valleys to exploit its yield potential. The rest high yielder varieties, Serkamo, Tate and Argene can be adapted only under favorable environmental conditions.
Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes u... more Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes using ISSR markers and identify highly diverse genotypes for the purposes of broadening the genetic base of sesame landraces grown in Ethiopia. Place and Duration of Study: The study was conducted in Botany research laboratory of Kasetsart University, Thailand, from April to July, 2013. Methodology: Genomic DNA of 128 sesame genotypes were subjected to PCR amplification and electrophoresis using seven ISSR markers and a binary data matrix prepared for each primer by scoring clear bands. The data generated were used to calculate the number of total bands (TB), Original Research Article Abate et al.; BBJ, 8(4): 1-13, 2015; Article no.BBJ.18481 2 polymorphic bands (PB), polymorphism percentage (P %) and polymorphic information content (PIC) for each locus. The number of different (Na) and effective (Ne) alleles, polymorphic loci (%), Shannon’s information index (I) and Nei’s gene diversity (He) for each population were calculated using GenAlEx 6.5 software. The data were also subjected to analysis of molecular variance (AMOVA) and principal coordinate analysis (PCoA) via distance matrix. Fixation index (Fst) was computed to measure genetic differentiation among populations. Genetic associations among individual genotypes were determined based on dissimilarity matrix using Darwin version 5.0 and a Neighbour-Joining hierarchal tree was constructed based on UPGMA. Results: The 7 ISSR primers in 128 sesame genotypes yielded 96 reproducible amplified bands. The number of amplified bands varied from 7 to 19. Out of 96 bands, 89 (92.2%) were polymorphic. Average number of bands and polymorphic bands per primer were 14 and 12.6 respectively. The polymorphic information content (PIC) value ranged between 0.26 and 0.76, showing the high informativeness of the selected primers. The overall gene diversity and Shannon’s information index were 0.37 and 0.54 respectively. Average dissimilarity value among the genotypes was 0.39. Maximum dissimilarity (0.88) was observed between genotypes Amr-NW6 and Amr-NG9 and less dissimilarity (0.014) was recorded between Amr-NW1 and Amr-NG1. SNNP-7 was the most diverse of all genotypes with highest average dissimilarity value of 0.77. AMOVA showed lower genetic divergence between populations (6%) than within population (94%) with average Fst of 0.061 across populations. The high intra-population variation could be because of large number of genotypes included and due to high out-crossing nature of sesame. Clustering and PCoA analyses clustered the genotypes into individual groups where most of the landraces were grouped in separate clusters irrespective of their geographic origins, while the cultivars were grouped in one cluster, suggesting less variability within the released varieties than the landraces. Accessions no. 56, 73, and 105 were out grouped from the rest. Conclusion: There exist considerable variations among sesame genotypes collected from different geographical regions of Ethiopia. Genotypes Amr-NSh-6, Benishangul-6 and SNNP-7 exhibited a good amount of genetic divergence and hence can be used in crossing program for genetic improvement of sesame in Ethiopia.
Aim: The study was undertaken to assess the genetic variability and character association in 81 m... more Aim: The study was undertaken to assess the genetic variability and character association in 81 mid-altitude sesame accessions of Ethiopia based on important agronomic traits. Study Design: A 9 x 9 Simple Lattice Design (SLD) with two replications was used. Place and Duration of Study: Melkassa Agricultural Research Centre Ethiopia, during the July-December, 2011 main cropping seasons. Methodology: The data recorded on 14 quantitative traits were analyzed for phenotypic and genotypic coefficient of variances, heritability and genetic advance, correlation coefficient, path coefficient analysis, principal component analysis and divergence analysis based on Mahalanobis statistics, using SAS 9.2. Statistical software to evaluate the pattern and extent of variation among 81 mid-altitude genotypes. Results: Analysis of variance revealed significant difference among genotypes for all traits studied. Less than 50% heritability was noted in all traits studied. Moderate heritability coupled w...
The Italian Sarcoma Group and the Scandinavian Sarcoma Group designed a joint study to improve th... more The Italian Sarcoma Group and the Scandinavian Sarcoma Group designed a joint study to improve the prognosis for patients with Ewing&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#39;s family tumors and synchronous metastatic disease limited to the lungs, or the pleura, or a single bone. The study was opened in 1999 and closed to the enrollment in 2008. The program consisted of intensive five-drug combination chemotherapy, surgery and/or radiotherapy as local treatment, and consolidation treatment with high-dose busulfan/melphalan plus autologous stem cell rescue and total-lung irradiation. During the study period, 102 consecutive patients were enrolled. The median follow-up was 62 months (range 24-124). The 5-year event-free survival probability was 0.43 [standard deviation (SD) = 0.05] and the 5-year overall survival probability was 0.52 (SD = 0.052). Unfavorable prognostic factors emerging on multivariate analysis were a poor histological/radiological response at the site of the primary tumor [relative risk (RR) = 3.4], and incomplete radiological remission of lung metastases after primary chemotherapy (RR = 2.6). One toxic death and one secondary leukemia were recorded. This intensive approach is feasible and long-term survival is achievable in ∼50% of patients. New treatment approaches are warranted for patients responding poorly to primary chemotherapy.
A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yie... more A study was conducted to estimate the nature and magnitude of G x E Interaction (GEI) for oil yield in sesame varieties and to identify stable and promising varieties for general and specific adaptations. The experiment was carried out at three locations across the areas of the Awash Valley in Ethiopia; namely Assaita, Melkassa and Werer over two seasons during the 2011 cropping and 2012 off seasons. Ten improved sesame varieties were planted in a randomized complete block design (RCBD) replicated trice in each location and year. Analysis of variance using AMMI model revealed significant differences (P<0.01) for genotype, environment, GEI and interaction principal component (IPCA1), suggesting differential response of varieties across testing environments and the need for stability analysis. Stabil ity analysis using Biplot graph and AMMI stability value were done to further shed light on the GEI of oil yield. The study revealed that the environment Wr1 (Werer season-I) had relatively little interaction effects with above average mean oil yield per environment. Hence, it can be recommended as ideal environment for growing the present set of sesame genotypes for breeding programme. Ranking of genotypes based on the different stability indices identified the varieties Adi and Serkamo to be the most stable genotypes across all environments. Therefore, these varieties can be recommended as promising cultivars for oil yield of sesame across diverse agro-ecologies of the Awash Valley to exploit their yield potential. On the other hand, the two high yielding varieties Abasena and Tate were found to be highly interactive and they are recommended for cultivation under favorable environmental conditions for oil yield. Moreover, the study indicated that high performance of genotypes for oil yield recorded in season two (2012). Hence, the off season generally is suggested as the best environment for oil yield of sesame across the areas of the Awash Valley. In this study, AMMI analysis with two IPCA was the best predictive model to reveal the maximum GEI for oil yield in sesame. Abbreviations: ASV = AMMI Stability Value, GEI = Genotype by Environment Interaction, IPCA = Interaction Principal Component.
Genetic diversity among 128 sesame (Sesamum indicum L.) genotypes representing 10 geographically ... more Genetic diversity among 128 sesame (Sesamum indicum L.) genotypes representing 10 geographically distinct populations in Ethiopia was assessed at DNA level using RAPD analysis. Eleven RAPD primers used amplified a total of 149 bands, of which 142 (95. 45%) were polymorphic. Each primer generated 7 to 23 amplified fragments with an average of 13.5 bands per primer. Percent of polymorphic loci (P%), number of different (Na) and effective (Ne) alleles along with Shannon information index (I) and Nei's gene diversity (He) values suggested that the population of Oromia was the most diverse of all populations, while populations from Afar (cultivars) and AM-NSh were found to be the least diverse. Based on average dissimilarity values obtained with RAPD primers, AM-NG-25, SNNP-7 and SNNP-8 were the most distinct of all genotypes, while genotypes ORO-20 and TIGR-5 showed maximum similarity with others. The UPGMA clustering based on the dissimilarity matrix clustered the genotypes into 3 major groups and 11 subgroups, while three genotypes viz., BENSH-6, ORO-14 and SNNP-5 were found out-grouped from the rest and did not join any of the cluster; they are then most divergent genotypes. Generally, both clustering and PCoA patterns revealed that most genotypes located geographically far apart were found to cluster in the same group, while those genotypes from the same origin dispersed. Overall results indicated that RAPD technique revealed a high level of genetic variation among sesame genotypes collected from diverse ecologies of Ethiopia. AMOVA = Analysis of Molecular Variance, NJ = Neighbor Joining, PCoA = Principal Coordinate Analysis, UPGMA= Unweighted Pair-group Method with Arithmetic mean.
Forty nine sesame genotypes collected from low-altitude areas of Ethiopia were evaluated at Werer... more Forty nine sesame genotypes collected from low-altitude areas of Ethiopia were evaluated at Werer Agricultural Research Centre, during the 2011/12 growing season for genetic variability and character association. Morphological data recorded on 14 quantitative traits were analyzed for analysis of variance, phenotypic and genotypic variability, heritability, genetic advance, genetic divergence based on Mahalanobis (D 2) statistics and principal component analysis. Analysis of variance revealed significant difference among the genotypes for each character except for primary branches. Higher genotypic variance was observed for seed yield and number of capsules/plant. Moderate heritability with moderate genetic advance was observed for most of the yield related traits, signifying that these attributes are governed by both additive and non-additive genes action. Based on D 2 values, the genotypes were grouped into seven clusters. The clustering pattern suggested that genotypes of the same origin were distributed into different clusters, indicating the absence of parallelism between clustering and geographic distributions. Maximum inter cluster distance was observed between clusters VI and VII while lowest distance was noticed between cluster I and III. Traits viz., harvest index, seed yield, biomass yield and plant height had highest contribution towards genetic divergence. There is high level of genetic variability in the studied germplasm with regard to seed yield and its component traits. The clustering pattern suggested the absence of relationship between geographic diversity and genetic diversity. Genotypes from distant clusters are suggested to be used as parents for hybridization program to achieve novel recombinants. The use of the selected traits in sesame improvement program would increase yield.
Forty nine sesame genotypes collected from low-altitude areas of Ethiopia were evaluated at Werer... more Forty nine sesame genotypes collected from low-altitude areas of Ethiopia were evaluated at Werer Agricultural Research Centre, during the 2011/12 growing season for genetic variability and character association. Morphological data recorded on 14 quantitative traits were analyzed for analysis of variance, phenotypic and genotypic variability, heritability, genetic advance, correlation and path coefficient analysis. Analysis of variance revealed significant difference among the genotypes for each character except for primary branches, suggesting the existence of considerable genetic variation in the studied germplasm with regard to seed yield and its component traits. There is a high variation in mean performance of genotypes for the studied traits. Am-NG-15 is a high yielding genotype but with lowest oil content, whereas Tigray-13 is a low yielding genotype but with highest oil content. Hence, a crossing program between these genotypes can result in desirable hybrid that can be used for the ongoing sesame improvement program. Moderate heritability with moderate genetic advance was observed for most of the yield related traits, signifying that these attributes are governed by both additive and non-additive genes action. The traits Biomass/plant, harvest index and 1000 seed weight exhibited highly significant positive correlation with seed yield/plant. These characters also had the highest positive direct effect on seed yield/plant. Hence these three traits can be considered as the principal yield components while selecting for yield improvement of lowland sesame genotypes in Ethiopia.
Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties ... more Aim: To estimate the nature and magnitude of GEI interaction for oil content in sesame varieties and to identify stable and promising varieties for general and specific adaptations across the areas of the Awash valleys in Ethiopia. Study Design: Entries were planted in a randomized complete block design (RCBD) replicated thrice in each location and year. Original Research Article Abate et al.; AJEA, 9(2): 1-12, 2015; Article no.AJEA.18482 2 Place and Duration of Study: The study was conducted at Assaita, Melkassa and Werer representing the Lower, Upper and Middle Awash valleys of Ethiopia respectively, during the 2010/11 main cropping season and 2011/12 off season. Methodology: Morphological data taken from each environment were analyzed for combined analysis of variance, Additive Main Effects and Multiplicative Interaction (AMMI), Biplot analysis, AMMI Stability Value (ASV), and regression analysis. Finally, ranking of genotypes was done based on the overall results of all stability indices. Results: Combined analysis of variance showed highly significant (P<0.01) difference between the varieties, environments and GEI, suggesting differential response of varieties across testing environments and the need for stability analysis. Proportion of variance captured by environments was 1.43%, genotypes 91.5% and GEI 7.1% of the total variation, indicating less effect of environments on oil content as compared to the effect of genotypes. Stability analysis by AMMI and Joint-regression model were used to further shed light on the GEI of oil content. Two IPCA of AMMI were significant (P<0.01) and captured the largest portion of variation of the total GEI, which indicated that the AMMI model was the best for the data set. The Joint regression analysis indicated that the linear regression (bi) did not deviate from unity for all varieties, suggesting that performance of the cultivars could not be predicted in a linear manner. Conclusion: The influence of environment is less prominent in the manifestation of oil content along the areas of Awash valleys. Season two is the best environment for growing the present set of genotypes for oil content. Variety Adi was identified as the most stable variety across environments for oil content. This variety can be recommended for varied environments of the Awash valleys to exploit its yield potential. The rest high yielder varieties, Serkamo, Tate and Argene can be adapted only under favorable environmental conditions.
Aim: The study was carried out to assess the genetic variability and association of traits with r... more Aim: The study was carried out to assess the genetic variability and association of traits with respect to seed yield and its components in (mid-altitude) sesame germplasm of Ethiopia. Study Design: A 9 x 9 Simple Lattice Design (SLD) with two replications was used. Place and Duration of Study: Melkassa Agricultural Research Centre Ethiopia, during the July-December, 2011 main cropping seasons. Methodology: The data recorded on 14 quantitative traits were analyzed for phenotypic and genotypic coefficient of variances, heritability and genetic advance, correlation coefficient, path Original Research Article Abate et al.; AJEA, 9(3): 1-14, 2015; Article no.AJEA.18483 2 coefficient analysis, principal component analysis and divergence analysis based on Mahalanobis statistics, using SAS 9.2. Statistical software to evaluate the pattern and extent of variation among 81 mid-altitude genotypes. Results: Analysis of variance revealed significant difference among genotypes for all traits studied. Less than 50% heritability was noted in all traits studied. Moderate heritability coupled with moderate to high genetic advance was recorded for most of yield related traits, indicating that these traits are controlled by both additive and non-additive genes. Characters viz., number of capsules, biomass yield, harvest index and 1000 seed weight showed highly significant positive correlation with seed yield. Maximum positive direct effect on seed yield was exerted by number of capsules, biomass yield, days to maturity and harvest index, showing that these traits can be used for selection to improve the primary trait. Divergence analysis based on Mahalanobis statistics grouped the genotypes into seven different clusters. Genotypes were not grouped in relation to their geographical distribution. Maximum inter cluster distance was observed between cluster V and VII; hence, genotypes from these two clusters are suggested as parents for hybridization program to achieve promising recombinants. Conclusion: The germplasm lines had sufficient level of genetic variability for seed yield and its components. Clustering was not associated with the geographical distribution instead genotypes were mainly grouped due to their morphological differences. Seed yield, biomass/plant, harvest index and number of capsules contributed highest towards genetic divergence. The use of these traits in sesame improvement program would increase yield.
Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes u... more Aim: This study aimed to uncover the diversity and population structure of 128 sesame genotypes using ISSR markers and identify highly diverse genotypes for the purposes of broadening the genetic base of sesame landraces grown in Ethiopia. Place and Duration of Study: The study was conducted in Botany research laboratory of Kasetsart University, Thailand, from April to July, 2013. Methodology: Genomic DNA of 128 sesame genotypes were subjected to PCR amplification and electrophoresis using seven ISSR markers and a binary data matrix prepared for each primer by scoring clear bands. The data generated were used to calculate the number of total bands (TB), Original Research Article Abate et al.; BBJ, 8(4): 1-13, 2015; Article no.BBJ.18481 2 polymorphic bands (PB), polymorphism percentage (P %) and polymorphic information content (PIC) for each locus. The number of different (Na) and effective (Ne) alleles, polymorphic loci (%), Shannon's information index (I) and Nei's gene diversity (He) for each population were calculated using GenAlEx 6.5 software. The data were also subjected to analysis of molecular variance (AMOVA) and principal coordinate analysis (PCoA) via distance matrix. Fixation index (Fst) was computed to measure genetic differentiation among populations. Genetic associations among individual genotypes were determined based on dissimilarity matrix using Darwin version 5.0 and a Neighbour-Joining hierarchal tree was constructed based on UPGMA. Results: The 7 ISSR primers in 128 sesame genotypes yielded 96 reproducible amplified bands. The number of amplified bands varied from 7 to 19. Out of 96 bands, 89 (92.2%) were polymorphic. Average number of bands and polymorphic bands per primer were 14 and 12.6 respectively. The polymorphic information content (PIC) value ranged between 0.26 and 0.76, showing the high informativeness of the selected primers. The overall gene diversity and Shannon's information index were 0.37 and 0.54 respectively. Average dissimilarity value among the genotypes was 0.39. Maximum dissimilarity (0.88) was observed between genotypes Amr-NW6 and Amr-NG9 and less dissimilarity (0.014) was recorded between Amr-NW1 and Amr-NG1. SNNP-7 was the most diverse of all genotypes with highest average dissimilarity value of 0.77. AMOVA showed lower genetic divergence between populations (6%) than within population (94%) with average Fst of 0.061 across populations. The high intra-population variation could be because of large number of genotypes included and due to high out-crossing nature of sesame. Clustering and PCoA analyses clustered the genotypes into individual groups where most of the landraces were grouped in separate clusters irrespective of their geographic origins, while the cultivars were grouped in one cluster, suggesting less variability within the released varieties than the landraces. Accessions no. 56, 73, and 105 were out grouped from the rest. Conclusion: There exist considerable variations among sesame genotypes collected from different geographical regions of Ethiopia. Genotypes Amr-NSh-6, Benishangul-6 and SNNP-7 exhibited a good amount of genetic divergence and hence can be used in crossing program for genetic improvement of sesame in Ethiopia.
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