Yield Stability Analysis Research Articles

Stability Analysis for Grain Yield and Micronutrients in Bread Wheat Genotypes

Stability Analysis for Grain Yield and Micronutrients in Bread Wheat Genotypes

Stability analysis of yield and its component traits in coriander germplasm

Stability analysis were done in 42 coriander genotypes including three check varieties during rabi 2010–11 and 2014–15 at TNAU, Coimbatore with per se performance. The analysis of pooled data indicated highly significant differences among the genotypes and environments for all the traits. The variance due to genotype and environments were highly significant for all the traits. Highly significant pooled deviation for umbels per plant and seed yield per hectare and highly significant G × E (linear) interaction for pods per plant and seed yield per plant indicated the preponderance of non-linear components of G × E interaction. The genotype CS 245 had shown consistent performance and stability in wider environments for seed yield per plant, whereas CS 14 has shown consistent performance in poor environment for seed yield per plant.

Stability analysis for grain yield in rice in demonstrations conducted during rabi season in India

Rice (Oryza sativa L.) is the staple food for more than 50 per cent world's population and 85 per cent Indian population. The rice production areas in the country are very diverse; hence, evaluation of genotype for its stable performance across the environment is very important. The study was undertaken to identify the stable rice variety in demonstration trials conducted on eleven varieties tested in five environments in rabi season. Among many available statistical techniques, the additive main effect and multiplicative interaction (AMMI) has been extensively used for GE interaction and stability analysis. First two PCA's are significant at 1 per cent and explained 89 per cent of the total variation with 24 degrees of freedom. The biplot obtained from AMMI analysis displayed PCA scores plotted against each other provides visual inspection. AMMI Stability Index (ASI) has been used to get quantitative value for stability analysis which helps in interpretation of the results. But, stable genotype may not always be high yielder which is the major requirement of farmers; therefore a new index namely ‘Rank Based Stability Index (RBSI)’ is proposed which identifies the stable genotype with high yield. The result showed that G1 and G2 were the most stable varieties with high grain yield, whereas G7 and G11 were found to be least stable. All eleven varieties were grouped into four clusters. First cluster consists of two varieties G1 and G2; second cluster contains four varieties G6, G10, G5 and G9; third cluster includes two varieties G4 and G11; and fourth cluster comprised of three varieties G8, G3 and G7.

Stability and path co-efficient analysis for yield and its components in pigeonpea [Cajanus cajan (L.) Millsp.

Stability and path co-efficient analysis for yield and its components in pigeonpea [<i>Cajanus cajan</i> (L.) Millsp.

Stability analysis for physiological traits, grain yield and its attributing parameters in oats (Avena sativa L.) in the Kashmir valley

Eleven genotypes of oats were planted at six diverse environments to assess genotype environment interaction and determine stable oat (Avena sativa L.) cultivar in Kashmir division for grain yield using randomized block design during 2014 to 2015. There was considerable variation in grain yield and physiological traits within and across environments. Stability analysis for grain yield was conducted to check the response to Genotype x Environment interactions. The mean squares due to G x E (linear) were significant depicting genetic differences among genotypes for linear response to varying environments. Mean squares due to pooled deviations were highly significant, reflecting considerable differences among genotypes for non-linear response. Out of eleven genotypes, only three oats lines i.e., SKO-98, SKO-166 and Sabzaar, showed non-significant deviation from regression and their regression coefficient values were close to unity and desirable for grain yield across the environments. The cultivar, “SKO-98” with respective regression coefficient value of 1.018, the smallest deviations from regressions (S2di) value (0.025) and the above average grain yield could be considered the most widely adapted cultivar.

Stability Analysis of Fresh Root Yield of Sweetpotato in Southern Ethiopia using GGE Bi-Plot

The yield performance of sweetpotato is highly influenced by the effect of genotype by environment interaction (G x E) and stability analysis is required before variety release. The objectives of the study were to estimate the magnitude of G x E interactions, to select high yielding and stable elite sweetpotato clones, and to identify the most discriminating and representative test environments in Ethiopia. The study was conducted across six diverse environments in southern Ethiopia in 2014. The locations were Halaba, Kokate, Areka, Arbaminch, Hawassa and Dilla. Twenty five clones (24 elite clones and one check variety) were used for the study and were arranged in a 5 x 5 simple lattice design for field experimentation. Genotype plus Genotype by Environment Interaction (GGE Bi-plot) method was used to study the stability of the clones for fresh root yield. Significant environment, genotype and G x E interaction variances (p < 0.01) were observed for fresh root yield. The magnitude of environment and G x E interaction effect was higher than that of the genotype effect. Three clones, G1 (Ukrewe x Ejumula-10), G6 (Resisto x Ejumula-7) and G20 (Ejumula x PIPI-10) were identified as stable and relatively high yielding genotypes. The mean root yields of the three clones were 25.1, 26.9 and 25.5 t ha-1, respectively for G1, G6 and G20. Accordingly, the above three elite clones were selected for ultimate evaluation and recommendations. Among the test locations, the highest and stable mean fresh root yield of 37.1 t ha-1 was recorded at Arbaminch. Therefore, Arbaminch was identified as the best environment for sweetpotato production in southern Ethiopia. The study revealed the possibility of breeding sweetpotato varieties for high yielding and stable clones that have wide adaptation in southern and similar agro-ecologies in Ethiopia.

Stability analysis for nut yield and component traits in cashew

Thirteen cashew genotypes developed at different Cashew Research Stations of India, i.e. NRCC Sel.-1, NRCC Sel.-2, M 44/3, M 15/4, BPP 3/33, BPP 10/19, BPP 30/1, BPP 3/28, H- 303, H-320, H-255, H-367 and H-68 were planted at 7.5 m apart during 1994 at Cashew Research Station, AICRP on Cashew, Orissa University of Agriculture and Technology, Odisha. Observations on various parameters like plant height (m), trunk girth (cm), canopy spread (m), flowering laterals per meter square, average nuts panicle−1, nut weight (g), apple weight (g), shelling percentage and nut yield plant−1 (kg) were recorded on four plants of each varieties for 14 years. Stability parameters for different characters were computed using the regression approach. There were considerable variations in yield and its contributing traits within genotypes, years and genotype × year interactions. Estimates of stability parameters revealed that no single genotype was stable for all the traits under study. The stability parameters for nut yield indicated that genotype H-320 was the most stable genotype among the group as it showed high yield per se performance, thus can be recommended for commercial cultivation along with regression coefficient around unity but the deviation from regression line was significantly different from zero. Whereas, BPP-3/28 and BPP-3/33 exhibited high shelling percentage with high mean performance for all vegetative growth characters, though low mean performance for nut yield, which can be utilized as parent in crop improvement programme with special reference to increase shelling percentage.

AMMI Model for Yield Stability Analysis of Linseed Genotypes for the Highlands of Bale, Ethiopia

In order to determine stable linseed genotypes with high grain yield, field experiments were conducted with 14 genotypes for two years (2014-2015) at three locations in the highlands of Bale zone, Ethiopia. The genotypes were laid out in randomized complete design with four replications in each environment. The objective of this study was to identify and recommend high yielder, stable genotypes for testing sites and similar agro-ecologies using the stability parameters. The combined analysis of variance showed highly significant differences for the genotypes, environment, and genotype by environment interaction indicating the possible existence of stable genotypes among the tested once. The results of AMMI (additive main effect and multiplicative interaction) analysis indicated that the first two AMMI (AMMI1-AMMI2) were highly significant (P<0.01). The partitioning of the total sum of square exhibited that the effect of environment was a predominant source of variation followed by genotypes and GE interaction effect. Based on the stability parameters regression coefficient, deviation from regression and mean grain yield out of the tested G6, G9, G11, and G8 were found to be stable. However, the AMMI Stability Value (ASV) discriminated genotypes G12, G4, G6, G13, and G9 as stable genotypes respectively. Based on the Genotypes Selection Index (GSI) the most stable genotypes with high grain yield were G6 and G9. Therefore these two genotypes were identified as candidate genotypes to be verified for possible release.

Evaluation of Performance and Yield Stability Analysis Based on AMMI and GGE Models in Introduced Upland Rice Genotypes Tested Across Northwest Ethiopia

Evaluation of Performance and Yield Stability Analysis Based on AMMI and GGE Models in Introduced Upland Rice Genotypes Tested Across Northwest Ethiopia

Physiological characterization and grain yield stability analysis of RILs under different moisture stress conditions in wheat (Triticum aestivum L.)

Drought stress is the major environmental constraint contributing to grain yield instability of wheat. In the present study, the recombinant inbred line population derived from DBW43/HI1500 cross was characterized for various morpho-physiological traits as well as grain yield stability analysis under moisture stress. The population was evaluated for grain yield under three different moisture stress environments viz., restricted irrigation, rainfed and late sown rainfed during the cropping season of year 2013–2014. Based on principal component analysis, the first five components explained over 60.40% of genetic variation. Grain yield per plot showed significant correlation with biomass and physiological traits viz., NDVI3, NDVI4, NDVI5, CT1, CT2 and CT3. The combined analysis of variance on grain yield data showed that mean squares of environments, genotypes and GEI were highly significant (p < 0.01). To determine effects of GEI on grain yield, data were subjected to AMMI and GGE biplot analysis, which identified G4, G69, G28, G67, G55 and G112 as the most stable and high yielding genotypes. Hence, the physiological traits NDVI and CT can be effectively used to screen out the line for drought tolerance. In addition, the stable wheat genotypes identified could be used in future wheat breeding programme.

Simulation of genotype-by-environment interactions on irrigated soybean yields in the U.S. Midsouth

Dynamic crop models that incorporate the effect of environmental variables can potentially explain yield differences associated with location, year, planting date, and cultivars with different growing cycles. Soybean (Glycine max (L.) Mer.) cultivar coefficients for the DSSAT-CROPGRO model were calibrated from two growing seasons (2012−2013) comprising 58 irrigated environments (site×year×planting date combinations) for cultivars within maturity groups (MGs) 3 to 6 using end of season data (yield, seed weight, and seed oil and protein concentration) and previously calibrated phenology coefficients. Model accuracy after calibration of cultivar coefficients by MG (cultivars averaged within a MG) was similar compared to cultivar-specific coefficients. During the subsequent growing season in 2014 (33 environments), the model efficiency (ME) for predicting yield was 0.40, with a root mean square error (RMSE) of 571kgha−1. The model was less efficient predicting seed number and seed weight (ME=0.06 and −0.06, respectively) than yield. The model was able to simulate differences in seed oil concentration across environments and MGs (ME=0.52), but not protein concentration (ME=−0.25). The analysis of yield stability had similar slopes for the observed and predicted yield regressions against an observed environmental index (EI) that were only dependent on the MG. Simulated yields were significantly different from the observed when EI>0, but yield differences in the highest yielding environments were still relatively small (245 to 608kgha−1). The results indicate an overall robust model performance in capturing G×E responses with coefficients calibrated by MG.

Stability Analysis of Yield and Grain Quality Traits for the Nixtamalization Process of Maize Genotypes Cultivated in the Central High Valleys of Mexico

In the central high valleys of Mexico, no maize hybrid or variety has shown enough stability to satisfy farmers or the processing industry, in terms of either grain yield or quality parameters for tortilla‐making. The objective of this work was to evaluate the stability of grain yield and grain physical characteristics, as well as of variables of the nixtamalization process and the tortilla quality of 11 maize genotypes cultivated in six locations of the central high valleys of Mexico. Stability was assessed based on the sites regression model (SREG). All variables were affected by the genotype by environment interaction, but only grain yield, hundred‐grain weight, flotation index, test weight, nixtamal moisture, retained pericarp, and tortilla yield were well explained by the SREG model. Among genotypes, ‘H‐76’ was outstanding in this study for its stability in grain yield and size, white grains (grain luminosity = 67.6), and reduced dry matter loss (4.3%) during nixtamalization, more retained pericarp in its nixtamal (42.1%), and good tortilla yield (1.41 kg kg−1 of maize). The best quality traits for nixtamalization process were obtained in 2012 in Huamantla and the worst in Benito Juarez, results that were influenced by good and poor agroclimatic conditions, respectively. The SREG model is a good tool for assessing the stability of grain traits for the nixtamalization process and tortilla quality and enabled identification of the best genotype for recommendation in a large region.

Genotype x environment interaction and stability analysis for yield and yield components in ten flax genotypes.

Genotype x environment interaction and stability analysis for yield and yield components in ten flax genotypes.

Stabilitas Hasil Jagung Varietas Hibrida Harapan Umur Genjah

Maize yield represents the interaction between genotype and environment. An excellent genotype should have high mean yield and small variation across common locations.This information could be obtained through yield performance test and stability analysis of yield data obtained from multilocation trials. This research was aimed to find out yield stability of eight early maturing maize promising lines at five sites using the AMMI method. There were total 12 genotypes of maize hybrids used in this research, consisted of eight hybrids (CH-1, CH-2, CH-3, CH-4, CH-5, CH-6, CH-7, and CH-8) and four check varieties (Gumarang, Bima 3, AS-1, and Bisi 2). This research was conducted at five locations ie. Gowa (South Sulawesi), Donggala (Central Sulawesi), Manado (North Sulawesi), Probolinggo (East Java) and Lombok Barat (West Nusa Tenggara) from April to September 2013. The treatments were arranged in a randomized complete block design (RCBD) with 3 replications. Variable measured was grain yield at all trial locations. Analysis of variance was performed for each site data to determine the performance of each genotype at each location. Results showed that genotype CH-2, CH-4 and CH-6 were considered as stable genotypes. Genotype CH-2 and CH-4 have a potensial to be released as new early maturing variety, due to its high yield of 8.71 and 7.52 t/ha averaged over 5 locations. Genotype CH-6 yielded below the mean yield of all genotypes, while genotype CH-8 was adaptive to a specific location, such as in Donggala, with yield of 8.38 t/ha.

Genotype × Environment Interaction and Yield Stability Analysis in Hybrid Rice (Oryza sativa L.) By AMMI Biplot

CORRECTION: Due to a number of formatting and layout issues, the PDF of this paper was replaced on 10th October 2016. The page numbers of this article have changed from 79-86 to 83-90.Assessing the adaptability and stability of promising rice genotypes is one of the important steps for accurate evaluation. This study determined the genotype × environment interaction (GEI) and stability performance of 12 promising rice genotypes in four environments during 2009 Aman season. The experiment used randomized complete block design with three replications. Yield stability and adaptability of yield performance were analyzed by combined analysis and additive main effects and multiplicative interaction (AMMI) model. The environment, genotype main effects, and the GEI were all highly significant (P&lt;0.001). The study indicated that the tested genotypes, such as BRRHA G1 (5.47 tha-1), G2 (5.68 tha-1), G3 (6.29 tha-1) and G4 (5.27 tha-1) had higher average yields, which indicated these genotypes adapted to favourable environments (E1 and E3). Whereas the environment, E3 could be regarded as a more stable site for high yielding hybrid rice improvement than the other locations. Based on AMMI biplot analysis, genotypes BRRI1A/BRRI827R (G1), IR58025A/BRRI10R (G2), BRRI 10A/BRRI 10R (G3) and BRRI hybrid dhan1 (G4) have higher average mean yields with high main (additive) effects and positive IPCA1 score, among them BRRI 10A/BRRI10R (G3) being the overall best. Locations E1 and E3 could be regarded as a good selection site for rice hybrid improvement due to stable yields.Bangladesh Rice j. 2015, 19(2): 83-90

GGE biplot analysis of yield stability and test location representativeness in proso millet (Panicum miliaceum L.) genotypes

The experiments were conducted for three consecutive years across 14 locations using 9 non-waxy proso millet genotypes and 16 locations using 7 waxy proso millet genotypes in China. The objectives of this study were to analyze yield stability and adaptability of proso millets and to evaluate the discrimination and representativeness of locations by analysis of variance (ANOVA) and genotype and genotype by environment interaction (GGE) biplot methods. Grain yields of proso millet genotypes were significantly influenced by environment (E), genotype (G) and their interaction (G×E) (P<0.1%). G×E interaction effect was six times higher than G effect in non-waxy group and seven times in waxy group. N04-339 in non-waxy and Neimi 6 (NM6) in waxy showed higher grain yields and stability compared with other genotypes. Also, Neimi 9 (NM9, a non-waxy cultivar) and 90322-2-33 (a waxy cultivar) showed higher adaptability in 7 and in 11 locations, respectively. For non-waxy, Dalat, Inner Mongolia (E2) and Wuzhai, Shanxi (E5) were the best sites among all the locations for maximizing the variance among candidate cultivars, and Yanchi, Ningxia (E10) had the best representativeness. Wuzhai, Shanxi (e9) and Yanchi, Ningxia (e14) were the best representative locations, and Baicheng, Jilin (e2) was better discriminating location than others for waxy genotypes. Based on our results, E10 and e14 have enhanced efficiency and accuracy for non-waxy genotypes and waxy genotypes selection, respectively in national regional test of proso millet varieties.

Grain Yield Stability Analysis of Barley Doubled Haploid Lines in Algerian Semi-arid Zones

Grain Yield Stability Analysis of Barley Doubled Haploid Lines in Algerian Semi-arid Zones

Yield Stability Analysis of Eight Bread Wheat (Triticum aestivum L.) Cultivars in Kerman Province Condition

Yield Stability Analysis of Eight Bread Wheat (Triticum aestivum L.) Cultivars in Kerman Province Condition

Stability analysis for yield and its attributing traits in advanced breeding lines of rabi sorghum (Sorghum bicolor (L.) Moench)

An experiment was carried out involving twenty three advanced breeding lines along with two checks M 35-1 and Muguthi during rabi season 2012-13 at four locations. Observations were recorded on 10 different characters viz., plant height (cm), stem diameter (cm), ear head length (cm), ear head diameter (cm), days to 50 per cent flowering, days to maturity, 100 seed weight (g), fodder yield per plot (kg), seed yield per plot (kg), and lodging percentage. The pooled analysis of variance revealed that mean sum of squares due to genotypes was significant for ear head diameter, days to 50 per cent flowering, days to maturity and fodder yield, indicating presence of considerable amount of variability in the genotypes. The mean sum of square due to environment + (genotypes x environment) was significant for plant height, ear head length (cm), ear head diameter (cm), days to 50 per cent flowering, fodder yield per plot (kg), seed yield per plot (kg), and lodging percentage characters except stem diameter, days to maturity and 100 seed yield. On the basis of stability parameters a four genotypes viz., GS-6 (2364 kg/ha), GS-16 (2454 kg/ha), GS-22(2775 kg/ha) and GS-23(2978 kg/ha) were found most stable over Gulbarga, Raichur, Bellary and Malnoor environments of Hyderabad Karnataka region.

Genotype x environmental interaction and stability analysis for grain quality and yield in oats (Avena sativa L.)

Ten genotypes of oats were planted at three diverse environments to assess genotype environment interaction and determine stable oat ( Avena sativa L.) cultivar in Kashmir division for grain quality and grain yield using randomized block design during 2011 to 2012. Stability analysis for grain quality and yield was carried out to check the response to Genotype x Environment interactions. The mean squares due to G x E (linear) were significant reveals genetic differences among genotypes for linear response to varying environments, while mean squares due to pooled deviations were highly significant, reflecting considerable differences among the genotypes for non-linear response. Out of ten genotypes, only three oats lines i.e., SABZAAR, SKO-208 and SKO-209 had non-significant deviation from regression and their regression coefficient values were close to unity classified as stable varieties for grain quality and grain yield.. The cultivar, “SKO-208” with regression coefficient value of 1.009, the smallest deviations from regressions (S 2 di) value and the highest grain yield could be considered the most widely adapted cultivar. The other test cultivars were sensitive to production-limiting factors, their wider adaptability, stability and general performance to the fluctuating growing conditions within and across environments.