جستجوی مقالات مرتبط با کلیدواژه « روش AMMI » در نشریات گروه « زراعت »

Quantitative and qualitative traits and stability of marketable tuber yield of 14 promising potato clones, along with three commercial cultivars (Agria, Marfona and Savalan) as checks, were evaluated at the Ardabil Agricultural and Natural Resources Research Station during 2013 and 2014. The experiment was based on a randomized complete block design with four replications. During growing period and after harvest, traits like main stem number per plant, plant height, tuber number and weight per plant, total and marketable tuber yield, dry matter percentage, baking type, hollow heart, tuber inner ring and discoloration of raw tuber flesh after 24 hours were measured. Combined ANONA for quantitative traits showed that there were significant differences among promising clones as to total and marketable tuber yield, tuber number and weight per plant, plant height, tuber mean weight, main stem number per plant and dry matter percentage and their interactions with year in total and marketable tuber yield. The clone 9 (397078-3) with the least amount of marketable tuber yield had significant difference with clones 4 (397045-13), 1 (397031-16), 3 (397031-11), 6 (397009-8) and 12 (397067-6) in 2013 and with clone 4 (397045-13) and Agria cultivar in 2014. The clones 4(397045-13), 1 (397031-16) and 12 (397067-6) had uniform tuber, yellow to dark-yellow skin and light-yellow to yellow flesh color, tuber shape of oval round and round, shallow to mid shallow eyes, no tuber inner ring, hollow heart and tuber inner crack and mid-late maturity. They were selected for home consumption of chips, french-fries and frying. Based on the results of factor analysis, "tuber yield", "number of tuber" and "plant structural and quality "were named as first, second and third quality determining factors respectively. In this experiment, GGE Bi-plot model and AMMI Stability Value (ASV) parameter, were acceptable methods for the selection of marketable tuber yield stability which found to be simultaneously could introduce clones 1 (397031-16), 3 (397031-11), 4 (397045-13) and 12 (397067-6) to be selected as stable clones with high marketable tuber yield.

Estimation of genotype by environment interaction (GE) is one of the main interests for a plant breeder. The statistical analysis، AMMI، is combination of ANOVA and PCA methods that calculate additive and multiplicative interactions. Nine advanced lines obtained from yield trials accompanied with Gachsaran cultivar (check) planted using a randomized complete block design replicated four times and 2 years (2002-2003) in 5 locations of Iran. Combined ANOVA showed that GE interaction was significant (at 1% level test). In this research AMMI methods used for analyzing of GE interaction. Three first IPCA were significant at 1% level test، next to model correction with Cornelious proposed method only IPCA1 was significant at 1% level test and IPCA2 was significant at 5% level test. ASV، SIPC1 and AMGE calculated، these are most important of AMMI parameters. Result showed genotype 9 (ILL 6199) had smallest ASV & SIPC1 (3. 98 and 1. 64 respectively) and highest mean yield (1265 kg. ha-1) was stable genotype in this research. Genotype no. 8 (ILL 6037) ranked as second in this research. Correlation among other stability statistics and AMMI parameter showed that ASV parameter had positive and high correlation with Wricke Ecovalence and Shukla stability variance (r = 0. 911**) and negative and high correlation with coefficient of determination (r = -0. 851**). SIPC1 had high correlation with regression coefficient (r = 0. 818**) and correlated with R2 (r = 0. 628*). AMGE parameter had no correlation with AMMI parameters and other stability statistics also we propose that in use of this parameter for yield stability has more attention.

This research was conducted to investigate genotyp×environment interaction for grain yield of ten wheat cultivars in 8 environments (combinations of two nitrogen fertilizer treatment and four irrigation regimes). Analysis of additive main effects (analysis of variance) and multiplicative interaction effects (principal component analysis) revealed that the effects of genotype, environment and genotype ×environment interaction were highly significant. three first principal components explained 89% of the interaction sum squares. Biplot of the first principal component and mean grain yields for genotypes and environments revealed that high yielding genotypes of Pishtaz and Moghan1 were more stable cultivars. Pattern analysis of two first significant principal components for genotypes and environments and also cluster analysis based on stability statistics of AMMI3 model (SIPC3 and EV3) showed that Pishtaz genotype had general stability. The grain yield of this cultivar was higher than the average of all genotypes, it was implied that this cultivar had general adaptability. Khazar cultivar was ranked as the second stable cultivar with having grain yield of approximately as much as the average of all genotypes; thus it was considered as a genotype with moderate general adaptability. Cultivars of Alvand, Sabalan, Moghan1, Darab and Falat showed very low stability. Sardary and Omid with lower yield were recognized as unstable cultivars. Also, it was found that all environments had contribution in the interaction effects.

Estimation of genotype environment (GE) interaction is very important for plant breeders. The additive main effects and multiplicative interaction (AMMI) model is the combination of the analysis of variance (ANOVA) and principal components analysis (PCA) which calculates both additive and multiplicative effects. To estimate GE interaction by AMMI model, ten corn hybrids including nine hybrids that were the best hybrids in yield trials, and KSC301 were evaluated for two years in seven locations of Iran in a randomized complete block design with four replications. Results showed that the first four IPCAs and the fifth IPCA were significant at 1% and 5% probability levels, respectively. The first IPCA displayed 25.2% of GE interaction sum of squares and the other IPCAs 65.1% of GE interaction sum of squares. Four parameters including SIPC4, AMGE4, ASV and EV4 were calculated for stability determination of corn hybrids. ASV parameter showed positive and highly significant correlation with Wricke ecovalence (r = 0.76) and Huehn's S2 nonparametric statistics (r = 0.67). EV4, SIPC4 and ASV parameters had no correlation with each others. The highest grain yield belonged to hybrids No. 8 and No. 2 with 9705 and 9272 kgha-1 respectively. According to ASV parameter, hybrid No. 8 was determined as a stable hybrid with minimum interaction (260.274) and maximum grain yield (9705 kgha-1) and hybrid No. 3 with minimum interation (1899.58) was determined as unstable hybrid. According to obtained results for stability determination, hybrid No. 8 was selected as the most stable hybrid and ASV parameter was selected as the best stability parameter regarding its accurate results in comparison to the other AMMI parameters

In this study, efficiency of AMMI method and pattern analysis were investigated. Seventeen sugar beet varieties were studied in thirteen locations over three cropping seasons and root yield and sugar content were measured. On the basis of combined analysis of variance, effect of variety and variety environment interactions for both traits were significant. The yield stabitity estimated-using Eberhart and Russell, Wricke’s Ecovalance, Shukla’s stabilty variance, AMMI and pattern analysis methods. In all stability methods used, varieties PP8, BR1 (developed is Ardabil) and IC1 were the most stable genotypes. Efficiency of Eberhart and Russell’s method for estimating of G  E interaction for both traits was lower than IPC1 in AMMI method. The efficiency of IPC1 was greater, by five to six times, than that of Eberhart and Russell’s method for root yield and sugar content, respectively. SIPC3 in AMMI method were accounted about 50 % of G  E interaction sum of squars. Biplot of IPC1 and the mean of traits for varieties and locations or environments had good efficiency for detecting of G E interaction patterns. Ranked correlation coefficients showed that AMMI method often generated more information than the other methods. Furthermore, this method generates new information which cannot be estimated by the other methods. It seems that AMMI and pattern analysis have higher efficiency for stability studies. However, results showed that using only one component of AMMI method is insufficient, and at least two components (e. g. IPC1 and SIPCf) should be considered.