Genotype X Environment Interaction Research Articles

Behavior and morphometric characterization of local and introduced cultivars of sweet cherries (Prunus avium), tested in a multi-site trial in Tunisia

Sweet cherry (Prunus avium L.) is a hardy species able to be adapted to various soil and climatic conditions; but its development is hampered by some physical, climatic and physiological constraints. The objective of this work is to study the behavior of 11 sweet cherry cultivars in three experimental sites characterized by different pedo-climatic conditions in the North West of Tunisia (Ain-Draham, Bousalem and Tibar) and to explore the "Genotype -by- environment" interaction to select the most suitable cultivar for the mild wintry climate of North West Tunisia. Six cultivars are of known origins (1 cultivar from Tunisia, 1 cultivar from Germany, 1 cultivar from France and 3 cultivars from Canada) as well as 5 cultivars are of unknown origins. Morphometric measurements were made on the leaves, flowers and fruits. Univariate statistical analyses comparing the obtained means at each experimental site were performed. To study the « Genotype x Environment » interaction (GxE), an inter-site analysis of variance was performed on the common cultivars to both Tibar and Ain-Draham sites. The decomposition of the “GxE” interaction by using Wrike's ecovalence showed that, firstly the French cultivar “Moreau” and secondly the Canadian cultivar “Van”, are the two main cultivars influenced by the environmental conditions for the most studied morphometric characteristics. Multivariate analyses based on cluster analysis and principal component analysis was performed on the mean values ​​of all the measured parameters for the each cultivar-site combinations. Napoleon, Van, Moreau, Stella, Bouargoub, BV9 and BV11 were best adapted cultivars to the climate with mild winter.

Genotype-by-environment interaction in coast redwood outside natural distribution - search for environmental cues

BackgroundEffective matching of genotypes and environments is required for the species to reach optimal productivity and act effectively for carbon sequestration. A common garden experiment across five different environments was undertaken to assess genotype x environment interaction (GxE) of coast redwood in order to understand the performance of genotypes across environments.ResultsThe quantitative genetic analysis discovered no GxE between investigated environments for diameter at breast height (DBH). However, no genetic component was detected at one environment possibly due to stressful conditions. The implementation of universal response function allowed for the identification of important environmental factors affecting species productivity. Additionally, this approach enabled us to predict the performance of species across the New Zealand environmental conditions.ConclusionsIn combination with quantitative genetic analysis which identified genetically superior material, the URF model can directly identify the optimal geographical regions to maximize productivity. However, the finding of ideally uncorrelated climatic variables for species with narrow ecological amplitude is rather challenging, which complicates construction of informative URF model. This, along with a small number of tested environments, tended to overfit a prediction model which resulted in extreme predictions in untested environments.

Interaksi Genotipe x Lingkungan pada Morfologi Malai Galur-galur Padi (Oryza sativa L.) Bermalai Lebat

Breeding rice for heavy panicle is prospective to improve production. However, the information on genotype x environment interaction (GxE) of rice panicle morphology is limited. This study was aimed to evaluate the GxE interaction on panicle morphology of heavy panicle rice (Oryza sativa L.) genotypes. The experiments were conducted in four environmental conditions. The research was conducted from December 2017 to May 2019 at the Department of Agronomy and Horticulture, IPB University, using 24 genotypes (F5-F6 generation) with 6 check varieties. The experimental design was an augmented design (3 replicates of check). Analysis of variance showed that GxE interaction effects were significant on the panicle length, number of axis nodes, primary branches number, secondary branches number, tertiary branches number, number of grains per panicle, and grain density per primary branch. The results showed that the two environments in the rainy season produced higher primary branches number, secondary branches number, tertiary branches number, number of grain per panicle, and grain density per primary branch than the two environments in the dry season. Correlation and path analyses showed that panicle length, number of secondary branches, and grain density per primary branch had a significant and direct positive effect on the number of grains per panicle.
 Keywords: primary branches, panicle length, secondary branches, tertiary branches

Genotype x Environment Interaction and AMMI Analysis of Oil Yield Sesame (<i>Sesamum indicum</i> L.) Genotypes in Northern Ethiopia

The study was conducted to evaluate the nature and magnitude of Genotype x Environment Interaction (GEI) for oil yield of sesame genotypes and to identify stable and promising genotypes for general and specific adaptations across sesame growing areas of northern Ethiopia: Humera, Dansha, Maykadra, Sheraro, Wargiba and Gendawuha. Randomized Complete Block Designs (RCBD) with three replications across all the environments used. Seventeen white seeded sesame genotypes were evaluated in all locations. The combined analysis of variance revealed that highly significance difference (p<0.001) among genotypes, environments and GEI for oil yield. The grand mean oil yield over six environments was 296.6kg/ha and the mean oil yield of genotypes across six environments ranged between 125.48kg/ha in Humera to 531.21kg/ha in Sheraro, respectively. High mean oil yield variation was detected among genotypes ranged between 193.6 kg/ha for G8 and 409.4kg/ha for G1 respectively. The oil yield of genotypes varied to different environments with rank changed, this variation among genotypes indicating that selection should be based on mean oil yield performances of the genotypes to their respective environments. According to stability models, AMMI Stability Value (ASV), Yield Stability Index (YSI) and Environmental Index (EI) land racegumero and HuRC-4 were identified as the most stable and higheroil yield were recommended for wider areas. While, HuRC-2and Acc 227880 were unstable accompanied with high oil yield performance will be recommended for specific environments.

STABILITY OF GRAIN YIELD IN BREAD WHEAT GENOTYPES UNDER DIFFERENT ENVIRONMENTS

Stability is important indicator in light of climate change in the Mediterranean region. Therefore, thirteen bread wheat genotypes were evaluated for grain yield under eight different environments. The environments were the combinations of four irrigation regimes (normal, mild, moderate and severe stress) × two seasons (2016/2017 and 2017/2018). Results indicated that stability analysis of variance revealed highly significant G x E “linear” for grain yield. Phenotypic stability parameters showed that wheat genotypes Gemmeiza12 and Line 3 were highly adapted to improved environments. On the contrary, wheat genotypes Sakha 95, Line 142 and Line 1 were adapted to water stress environments. Furthermore, wheat genotypes which could be grown under a wide range of environments were Misr 1, Misr 2, Sakha 94, Giza 171, Shandweel 1, Line 26 and Line 6 for grain yield. The most desired and stable genotypes were Misr 1, and Gemmeiza 11 for grain yield. The additive main effect and multiplicative interaction (AMMI) analysis of variance showed that 49.56, 28.90 and 1.79% of the total sum of squares were attributable to environmental, genotypic and genotype x environment interaction (GEI) effects for grain yield, respectively. Both models of Eberhart and Russell (1966) and AMMI (Gauch, 1992) are consistent in describing the stability of Misr 1 and Gemmeiza 11 for grain yield. These genotypes could be useful in wheat improvement programs for enhancing stability.

Analysis of yield stability of malt barley genotypes under terminal moisture stressed areas of North Wollo, Ethiopia

Field experiments were conducted at Estayish, Geregera and Kon testing sites of Sirinka Agricultural Research Center (SARC), North Wollo, Ethiopia for two consecutive years (2013 and 2014) during the main season with the objective of evaluating the performance of malt barley genotypes for grain yield and yield stability under diverse environments. Fifteen promising malt barley genotypes, along with the standard check (Miscal 21) were evaluated using Randomized Complete Block Design (RCBD), replicated three times. Genotypes were row-planted on a plot size of 3 m2. N and P2O5, in the form of Urea and Di-Ammonium Phosphate (DAP) fertilizers, were applied at the rate of 23 kg ha-1 and 46 kg ha-1, respectively and all other cultural practices were carried-out uniformly for all treatments as required. Grain yield was recorded from the central four rows (2 m2) and measured with sensitive balance. Data were subjected to analysis of variance (ANOVA) using Genstat software package 16th edition. Duncan Multiple Range Test (DMRT) was used to separate means. Genotype by Genotype-Environment (GGE) biplot model was employed to analyze phenotypic stability of malt barley genotypes for grain yield. ANOVA depicted significant variations (p<0.01) among genotypes (G), years (Y), locations (L) and their two and three way interactions for grain yield. The presence of significant variations among the tested malt barley genotypes for grain yield indicated the possibility of improving productivity of malt barley through selection. However, the existence Genotype x Environment Interaction (GEI) revealed differential response of malt barley genotype across environments, necessitating to develop environmentally less sensitive malt barley genotype. Analysis of GGE revealed that G6 and G11 were close to the ideal genotype and hence recommended for major barley producing areas of North Wollo.

Yield, frying quality, plant vigor, and maturity of potato clones

ABSTRACT The objective of this research was to evaluate advanced potato clones for tuber yield, frying quality, plant vigor, and maturity, grown from minituber seeds, and to assess correlations between these traits. Eight advanced potato clones of Embrapa Potato Breeding Program (F11-09-03, F05-11-03, F54-11-06, F141-11-01, C2718-12-09, C2718-24-09, C2743-09-09, and CL308) and three commercial cultivars (Agata, Asterix and BRSIPR Bel) were evaluated. Experiments were carried out in autumn 2017, in Canoinhas-SC and Pelotas-RS. A randomized complete block design with four replicates was used. We used tuber seeds type IV (minibubers). We evaluated plant vigor, maturity, yield and number of marketable tubers, yield and number of total tubers, average tuber weight, specific gravity, and frying color. Individual and joint variance analyses revealed significant differences (p &lt;0.05) among genotypes for all traits at both locations. The GxE (genotype x environment) interaction was significant for all traits. For the two locations together, clones F05-11-03, C2718-12-09, C2718-24-09 and the control cultivar BRSIPR Bel showed higher marketable tuber yields. The first two clones also showed tubers with high average tuber weight. Clone F54-11-06 showed the later maturity at both locations. Regarding the frying quality characteristics, only clone F141-11-01 showed a pattern comparable to that of the control cultivar Asterix. Also, clones with higher plant vigor had higher tuber yield, but late maturity. Frying quality traits were not correlated between them and among other traits.

AMMI based simultaneous selection for yield and stability of chickpea genotypes in south zone of India

Multi-environmental trials have generally significant genotype main effects and genotype x environment interaction (GEI) effect and, therefore different univariate and multivariate stability methods have been used to study the GEI. Among the multivariate methods, the additive main effects and multiplicative interaction (AMMI) analysis is widely used for GEI investigation. This method has been effective because it captures a large portion of the GEI sum of squares; it clearly separates main and interaction effects and often provides meaningful interpretation of data to support a breeding program such as genotypic stability. Based on the AMMI model, a stability index has been used to rank the genotypes. This index is the weightage of stability and yield component and higher the index value better is the genotypes. The index of 40 promising chickpea genotypes were calculated with two different weight of yield (50% and 75%) and stability component (50% and 25%). These genotypes were evaluated at seven locations viz. Hiriyur, Nandyal, Coimbtore, Dharwad, Lam, Bijapur and Gulbarga representing the south zone of All India Coordinated Research Project on Chickpea program during 2015-16. Ranking of genotypes are done based on two different weight of stability and yield component.

Growth performance and stability of hybrid poplar clones in simultaneous tests on six sites

Growth, stability, and genotype x environment (GxE) interaction were investigated for 69 clones after five years at six sites in Minnesota. Fifty-three clones were Populus deltoides x Populus nigra (DxN) crosses, nine were P. deltoides x P. maximowiczi, ten other crosses. Most clones were previously screened for growth and disease resistance in Minnesota. Five-year diameter (DBH) and basal area (BA) at 1.38 m averaged 93.5 mm and 72.11 cm2, respectively, over the six sites. DBH site means varied from 109.0 to 79.4 mm. The fastest-growing clone BA was 64% and 49% larger than the mean of the two commercial standards and the mean of the population, respectively. Site, clone, and clone x site effects were highly significant in the ANOVA. The variance component for clone was over twice that of clone x site (GxE), indicating a relatively small reduction in genetic gain due to GxE. Clonal rank did not change between sites. GxE interaction was dominated by relative performance differences of clones on the different sites. Twenty-six percent of clones were stable (little change in growth between sites), 74% unstable. Stability coefficients of the unstable clones varied over a 99% range, indicating the population had high and variable phenotypic plasticity. Only 15% of clones were both stable and fast growing. Seven putatively superior clones, all DxN, were selected for future testing under near-commercial conditions. The results, if representative of other inter-specific Populus populations, suggest it will be difficult, and probably impractical, to reduce GxE with standard quantitative genetics methods in hybrid poplar tree improvement programs without sacrificing productivity gains.

Genotype X environment Interaction and Stability of Oil Content of Sesame (Sesamum indicum L.) Genotypes in Northern Ethiopia

The experiment for oil content analysis was conducted for two growing seasons under rainfed condition (2012-2013) in Humera and Dansha, and in a single year (2013 cropping season) in Sheraro (comprising a total of five environments). The experiment comprised of 13 sesame genotypes, laid out in a randomized complete block design of three replications with the objective of determining the magnitude of Genotype x Environment Interaction (GEI)and oil content. here was highly significant (p0.01) oil content variation based on genotypes, environments and GEI resulting 26%, 42.7 % and 30.9% of the total sum of squares for the oil content variation respectively. The mean of the oil content was 53.9%, with genotypes G4 and G11 with the highest oil content (55.1 %) each, and G8 with the lowest oil content (51.4 %). G4 was the exceptional genotype with the highest oil content (55.1 %) and oil yield (512.9 kg/ha). Based on the Environmental Index (EI) analysis, Environments E4 and E5 were the favourable environments, while E1, E2 and E3 were unfavourable environments for sesame oil production. According to the AMMI1(Additive main effects and multiplicative interaction) bi-plot, Genotypes G4, G13 and G10 with oil the content of 55.1%, 54.7 and 54.2 respectively, were stable genotypes. On the other hand, genotypes G2, G8, G9, G3 and G1 were unstable genotypes in most of the environments. The AMMI 2 bi-plot showed that, genotypes G2, G3 and G9, with long vector length, were specifically adaptable genotypes and genotypes G10, G12, G4 and G7 with shorter vector length were widely adaptable in most of the environments for their oil content. Oil content of sesame varies highly both across years and locations.

English

Fifteen common bean genotypes were tested at four locations with two management regimes of lime treated and lime untreated acidic soils. The experiment was laid out in split plot design with three replications during 2016/17 cropping season. The combined analysis of variance over environments showed significant differences among environments, genotypes, genotype x environment interaction (GEI), management, genotype by management interaction (G x M) and genotype by environment by management interaction (G x E x M) on seed yield. Analysis of variance for seed yield from AMMI model indicated that contribution of the IPCA 1 and IPCA 2 accounted for 53.37 and 25.04%, respectively for lime treated soils and 72.89 and 18.30% respectively for lime untreated soils of the observed variation due to GEI. The result indicated environment contributed much to the observed variations suggesting the need to test common bean genotypes at diverse environments. Two genotypes, ALB 212 (1.65 t/ha) and BFS 39 (1.63 t/ha) had first and second highest yield, identified as responsive to both environments but more to favorable environments suggesting the need for further test to develop as varieties. It could be possible to recommend genotypes ALB 179, ALB 207, ALB 209, BFS 35, BFS 39 and ALB 212 to be tested as National Variety trial for all environments with both management measures as they have wider adaptability. Key words: Additive main effect and multiplicative interaction (AMMI), common bean, genotype x environment interaction (GEI), split plot. &nbsp

Jatropha half-sib family selection with high adaptability and genotypic stability.

Jatropha (Jatropha curcas) has become one of the most important species for producing biofuels. Currently, Genotype x Environment (GxE) interaction is the biggest challenge that breeders should solve to increase the section accuracy in the plant breeding. Therefore, the objectives in this study were to estimate the parameters in the 180 half-sib families in Jatropha evaluated for five production years, to verify the significance of the GxE interaction variance, to evaluate the adaptability and stability for each family based on three prediction methods, to select superior half-sib families based on the adaptability and stability analyses, and to predict the accuracy for the sixth production year. Jatropha half-sib families were classified and selected using the follow adaptability and stability methods: linear regression, bi-segmented linear regression and mixed models concepts called harmonic mean of the relative performance of genetic values (HMRPGV). The prediction accuracy was estimated by the Pearson correlation between the predicted genetic values by adaptability and stability methods and the phenotypic value in the sixth production year. In result, most half-sib families were classified as general adaptability and general stability for the evaluated traits. The selection gain obtained via HMRPGV was higher than other methods. The prediction accuracy for the sixth production year was 0.45. Therefore, HMRPGV is efficient to maximize the genetic gain, and it can be a useful strategy to select genotype with high adaptability and stability in Jatropha breeding as well as other species that should be evaluated for many years to take a suitable selection accuracy.

A weighted AMMI algorithm for nonreplicated data

Abstract: The objective of this work was to propose a weighting scheme for the additive main effects and multiplicative interactions (AMMI) model, as well as to assess the usefulness of this W-AMMI model in the study of genotype x environment interaction (GxE) and quantitative trait locus x environment interaction (QxE) for nonreplicated data. Data from the 'Harrington' x TR306 barley (Hordeum vulgare) mapping population, with 141 genotypes evaluated in 25 environments, were used to compare the results from the AMMI model with those of two proposed versions of the W-AMMI model: equal weights per row and equal weights per column. The proposed W-AMMI columns algorithm is viable to analyze data with heterogeneous variance, when there are no replicates available. The use of the AMMI and W-AMMI models, in the indicated cases, improves QTL detection, besides providing a sound interpretation of GxE and a better understanding of QxE, which allows obtaining valuable information on increasing productivities in different environments.

English

The genotype x environment interaction (GEI) has an influence on the selection and recommendation of genotypes. To this end, G x E interaction and grain yield stability study was conducted for 17 advanced Ethiopian mustard across three districts (Sinana, Adaba and Agarfa) in the highlands of Bale zone during 2014 and 2015 main cropping season. Randomized complete block design with four replications was used. The combined analysis for the mean grain yield was highly significant (p≤0.01) for genotypes, environment and genotype x environment interaction. The mean seed yield of the locations was ranged from 0.9427 t ha-1 for Agarfa to 2.645 t ha-1 for Sinana in 2014. The Additive Main effects and Multiplicative Interaction (AMMI) analysis indicated that 76.7% of the GE sum squares was justified by the first two AMMI (AMMI1 and AMMI 2) components. The regression coefficient (bi) of genotypes ranged from 0.629 to 1.345. Genotypes G7 was the most stable with optimum grain yield (2.21 t ha-1), bi- value nearer to unity (bi = 1.03) and minimum value of deviation from regression (0.12). Based on the AMMI Stability Value (ASV), G12, G10, G17, G5, G3, G2, G7, and G8 showed the lowest ASV indicating as they are most stable. However the most stable genotypes would not necessarily give the highest yield. Therefore, based on mean grain yield and the result of stability parameters such as ASV, bi and Genotypes Selection Index (GSI), genotype G7 was found the best candidate variety and recommended for possible release for the test environments and similar agro-ecologies. Key words: Additive Main effects and Multiplicative Interaction (AMMI), AMMI stability value (ASV), biplot, genotypes selection index (GSI), mustard, stability.

Evaluation of Genotype x Environment Interaction and Stability of Grain Yield and Related Yield Components in Pearl Millet (Pennisetum glaucum (L.) R.Br.)

Thirty six pearl millet genotypes were evaluated in randomized complete block design with two replications during 2011/2012 at two locations to study the magnitude of genotype by environment interaction for yield and yield related traits and identify the most stable high yielding genotypes. ANOVA of data at individual locations revealed significant differences among genotypes at Marigat and Koibatek for all yield components. Combined mean analysis of variance showed that the Genotype and location main effects and the genotype by environment interaction were highly significant (P≤0.01) for grain yield and other traits, indicating differential response of genotypes across testing locations and the need for stability analysis. Marigat was the most suitable environment and gave highest mean grain yield of 3620 kg/ha. The lowest yield 870 Kg/ha was recorded at Koibatek. Genotypes EUP 32, EUP 35, EUP 19 and EUP 10 produced high mean yield of 3530, 3080, 2690 and 2590 kg/ha respectively. The lowest grain 1290 kg/ha was obtained from genotype EUP 4.Based on the parameters of stability, three stable (widely adapted) and high yielding genotypes (EUP 34, EUP 18, and EUP 9) were identified. They also out-yield the standard open pollinated variety (OPV) check, Kat PM2. Genotypes EUP 32 was the highest yielding across all sites followed by EUP 35 and could be recommended for further multi-location evaluation in warmer environment and possible release for commercial production. The findings of this study showed that pearl millet hybrids have high potential for commercial production in Kenya than the OPVs. The ANOVA results showed that the effects of environments, genotypes and genotype x environment interaction (GE) were important in trait expression and performance of genotypes. In addition, it was observed that amount of rainfall received at both vegetative and post-anthesis phases and temperature had an effect on grain yield. The GGE biplot analysis characterised the environments in terms of stability and productivity, where Marigat was the best for grain yield; implying that environment-specific selection should be adopted. Genotypes EUP 34, EUP 18, and EUP 9 were the best performing since they out yielded the standard OPV check. These stable high yielding genotypes can be evaluated further in varied agro-ecologies and recommended for release as commercial hybrid varieties in ASALs of Kenya.

Identification of stable lentil (Lens culinaris Medik) genotypes through GGE biplotand AMMI analysis for North Hill Zone of India

In the present investigation with 24 lentil genotypes, first two Principal components revealed more than 90 per cent of the variability for the yield which indicates that G and GE together accounted for more than 10 per cent of total variability. Based on the present analysis of using GGE biplot models, considering simultaneous mean yield and stability, the genotypes G4, G12, G6, G13 and G2 were relatively stable in all the environments.The environment E1(Berthin) was discriminative (informative). This environment contributed most to the variability in grain yield. Hence, GGE biplot method is suitable to discriminate the genotypes based on their stable and instability nature across the environments.The AMMI analysis revealed that G13, G14, G12, G2, G23, G16 and G9 had wide adaptation and not be affected by the Genotype x environment interaction (GxE); hence mayyieldedgood across the environments. E2 and E3 could be considered as good selection sites for identifying broad based and most adaptable lentil genotypes. This study has clearly and by far aided in identification of stable and superior genotypes in graphical representation.

Genotype x environment interaction and genotype evaluation for yield, yield components and qualities in sugarcane (Saccharum Spp.), Ethiopia

The presence of genotype x environment interaction (GEI) and the limited knowledge on the relationships among production environments complicate selection of superior varieties in sugarcane. For this reason, studying about the nature of GEI, genotype evaluation and classification of the production environments in to distinct mega environments is very important in sugarcane breeding program. The study was conducted to investigate the nature of genotype x environment interaction, classify environments in to mega environments and evaluate genotypes based on yield performance and stability. Forty-three genotypes along with six standard varieties were evaluated across location and over crop years using simple lattice design. Data of cane yield, cane yield components and yield qualities were subjected to analysis of variance (ANOVA). Results from ANOVA declared the importance of GEI under Ethiopian agro climatic conditions. When the data was analyzed using the GE model, the f-values were inflated and the genetic variation was under estimated. Thus, for multi-environment trials conducted across locations and over seasons, data analysis based on the GLC model would be appropriate. The genotype + genotype x environment interaction (GGE) bi-plots divided the target environment in to distinct mega environments where a repeatable genotype x location interaction was observed for recoverable sucrose% and sugar yields. Moreover, GGE bi-plots identified introduced genotypes that have better broad and specific adaptations than the commercial varieties and can be commercially exploited according to their respective regional niche. Moreover, we recommend a breeding strategy for specific adaptation in future sugarcane breeding programs in Ethiopia.

Progress Made in Developing New High Yielding Potato Varieties for the Kenyan Highlands at KALRO-Tigoni

Breeding has been going on at Kenya Agricultural and Livestock Research Institute (KALRO), Tigoni in Kenya to develop high yielding potato varieties that have good processing qualities. The objective was to develop high yielding potato varieties that are adapted to the Kenyan climatic and environmental conditions and that are suitable for processing. After initial crossing, the resultant families were evaluated for yield as well as crisping and chipping quality for three consecutive generations at KALRO-Tigoni; this resulted in selection of 112 candidate clones. The 112 selected clones (52 potentially for crisping) were then evaluated under Advanced Yield Trials (AYT) during the 2015 short rains season and 2016 long rains season at three sites (Tigoni, Molo and Meru). Yield data was analysed using the lattice procedure of Statistical Analysis Systems (SAS 9.1) statistical package. Genotype x Environment Interaction (GEI) as well as stability and adaptability of potato clones across sites was analysed using additive main effects and multiplicative interaction (AMMI) and genotype main effect and Genotype x Environment Interaction (GGE) biplot analysis. In the AYT, significant Genotype x Environment Interactions (GEI) were observed. Clone G6 (2E87) was closest to the ideal genotype; it was the highest yielding and most stable while environment 2 (long rains season 2016 at KALRO-Tigoni) was the closest to ideal environment and therefore the most desirable of the six environments. From AYT, 18 clones were selected, 11 of them good for crisping. These clones were recommended for the National Performance Trials (NPT) before release of new varieties.

Adaptability Evaluation of Common Bean (Phaseolus vulgaris L.) Genotypes at Western Ethiopia

Fifteen common bean genotypes were tested at four environments with two management regimes of lime treated and lime untreated on acidic soils. The experiment was laid out in split plot design with three replications during 2016/17 cropping season. The combined analysis of variance over environments showed significant differences among Environments, Genotypes, Genotype x Environment interaction (GEI), Management, Genotype by Management interaction (G x M) and Genotype by Environment by Management interaction (G x E x M) on seed yield. Analysis of variance for seed yield from AMMI model indicated that contribution of the IPCA 1 and IPCA 2 accounted for 53.37% and 25.04% respectively for lime treated soils while 72.89% and 18.30% respectively for lime untreated soils of the observed variation due to GEI. The result indicated environment was contributed much to the observed variations suggested the need to test common bean genotypes at diverse environments. Two genotypes, ALB 212 (1.65 t/ha) and BFS 39 (1.63 t/ha) had first and second highest yield, identified as responsive to both environments but more to favorable environments suggested the need to further test to develop as varieties. It could be possible to recommend genotypes ALB 179, ALB 207, ALB 209, BFS 35, BFS 39 and ALB 212 to be tested as National Variety trial for all environments with both management measures as they have wider adaptability.

AMMI analysis of grain yield in rice genotypes across environments

The identification of the highest yielding cultivar for a specificenvironment on the basis of both genotype (G) and genotype xenvironment (GE) interaction would be useful to breeders andproducers since yield estimates based only on G and environment(E) effects are insufficient. The objective of this study wasto demonstrate the usefulness of additive main effects and multiplicativeinteractions (AMMI) model analysis. Replicated grain yielddata of rice (Oryza sativa L.) genotypes at three locations in Coimbatore (E1), Bhavanisagar (E2) and Aliyar Nagar (E3) were obtained andused for this purpose. Through AMMI model analysis, the magnitudeand significance of the effects of GE interaction and its interactionprincipal components relative to the effects of G and E wereestimated. Among the three, E3 environment was far away from the origin. The environments E2 and E3 condition were exhibiting high interaction effect, whereas the environment E1 had moderate interaction effect with the other two environments. The parent TP 1021 R and the hybrids viz., IR 80559 A X RR 286 R, APMS 6 A X IR 62037 R, IR 75601 A X IR 72865 R, IR 75601 A X RR 347 R, IR 75596 A X MDU 5 R, IR 75596 A X ASD 06-8 R, CRMS 32 A X IR 62037 R, CRMS 32 A X TP 1021 R and IR 75608 A X ASD 06-8 R showed IPCA 1 score close to zero with high main effects indicating that these varieties were less influenced by environments. Hence, the above said hybrids were stable and had general adaptability for all the environments. Since, the environments E3 had positive IPCA 1 score and high mean, it had positive interaction with these genotypes and this environment was considered as the stable environment for these hybrids.