Relative performance of wheat genotypes under individual and combined water deficit and salinity stress

Ascertaining the genetic variability and its relationships among valuable genetic resources is important for crop improvement programme. Here, we assessed the response of eleven wheat (Triticum aestivum L.) genotypes using cluster and principal component analysis (PCA) based on morphophysiological data and yield under nine different environments. Wheat genotype WH 1080 maintained higher photosynthetic efficiency under individual stress of 50% water deficit (drought) and 100 mM NaCl (salt), whereas under interactive stresses KRL 370 and KRL 283 were found to be the best genotypes. The highest value of Na+/K+ ratio in shoots was recorded for WH 1080 (1.167) and lowest in KRL 283 (0.612) under combined stresses. Proline accumulation was maximum in KRL 330 (3.17 mg g-1 FW) and minimum in KRL 283 (2.8 mg g-1 FW). Significantly higher reduction (73.4%) was observed in HD 2009 for grain weight/plant at 100 mM NaCl + 50% WD stress treatment whereas minimum reduction of 39.18% was recorded in KRL 370 in comparison to the control treatment. The PCA showed that the first three components comprising about 91% of the total variation for which the variables were analyzed. AMMI model revealed KRL 210 to be stable genotype as being close to center on biplot. E5 environment (100 mM NaCl) was most stable followed by E9 (50% WD + 100 mM NaCl). HD 2888, C-306, HD 2851 and HD 2009 were having positive interaction with E1 (Control) whereas WH 1080 had positive interaction with water deficit environments i.e. E2 and E3 (25 and 50% WD) while KRL 433 had highest positive interaction with combined water deficit and salt stress environments E6, E7, E8 and E9, followed by KRL 370. Similarly, KRL 283, KRL 330, KRL 210 and Kharchia 65 had high positive interaction with saline environments E4 and E5. Findings of the experiment would be beneficial to wheat breeders, specifically the location-specific promising genotypes could possibly be used to develop/breed MAGIC populations to tag genes/alleles conferring drought and salinity tolerance.

Análises Biplot: conceitos, interpretações e aplicações / Biplot analysis: concepts, interpretations and uses

A seleção e recomendação de genótipos superiores são dificultadas devido à ocorrência da interação genótipo e ambiente. Nesse contexto, as análises biplot têm sido cada vez mais utilizadas na análise de dados agronômicos, com interações de natureza complexa. Entretanto, as particularidades existentes no gráfico biplot dificultam sua interpretação, podendo induzir o pesquisador a erros. Assim, este artigo de revisão discute a aplicabilidade e a interpretação gráfica dos modelos AMMI (Additive Main effects and Multiplicative Interaction) e GGE biplot (genotype main effects + genotype environment interaction) destas análises no gráfico biplot. Também, visa a desmistificar a necessidade de comparação entre ambas as metodologias. Discute-se quanto à escolha da metodologia mais adequada, levando em consideração a informação requerida e os objetivos do pesquisador.

The genotype environment interaction (GE) influences on the selection and recommendation of cultivars. Biplot analysis has been increasingly used in data analysis of complex traits in agriculture. However, the peculiarities of biplot graphic could induce the researcher to errors on interpretation. Thus, this review argues the applicability and graphic interpretation of models AMMI (Additive Main Effects and Multiplicative Interaction) and GGE biplot (genotype main effects + genotype environment interaction). Moreover, also aims to explain that it is not adequate to compare both statistical methods. It is discussed the best methodology considering the information required and the research objectives.

Genotype X Environment Interaction and Yield Performance of 43 Improved Cassava (Manihot esculenta Crantz) Genotypes at Three Agro-climatic Zones in Nigeria.

Aim: To determine the possible effects of environment and genotypic differences on root yield and other related traits. Methodology: 43 improved cassava genotypes were evaluated for root yield, root number, root dry matter, cassava mosaic disease and Cassava bacterial disease. The experiments were conducted using a randomized complete-block design with four replications for two years in three representative agro-ecological zones (Mokwa, Ibadan and Onne) in Nigeria. The data collected were subjected to combined analyses of variance using the GLM procedure of Statistical Analysis System (SAS 9.2) to determine the magnitude of the main effects and interactions. GGEbiplot software (GGEbiplot, 2007) was applied for visual examination of the GEI pattern of the data. Results: Genotype, Location and genotype by environment (GXE) interaction were highly significant for all the traits studied (P< 0.001), indicating genetic variability between genotypes by changing environments. The partitioning of GGE through GGE biplot analysis showed that PC1 and PC2 accounted for 61.3% and 28.8% of GGE sum of squares respectively for root yield, explaining a total of 90.1% variation. Conclusion: Genotypes G4 and G15 were the highest yielding and stable genotypes. G2 and G7 were equally stable but with poor roots yield. G43, which had a mean yield similar to the grand mean, may be regarded as a desirable genotype. Mokwa and Ibadan were found to be the most discriminative and the least representative environments for root yields while Onne environment was found to be the most representative and the least discriminative.

Testes multiambientais na seleção de genótipos de arroz utilizando o modelo de regressão nos sítios ou locais / Multi-environment tests in the selection of rice genotypes using sites regression model

A análise da interação genótipo x ambiente utilizda no melhoramento de plantas tem sofrido mudanças na última década, melhorando a sua eficiência quanto à seleção dos genótipos sob diferentes condições ambientais. O objetivo deste trabalho foi analisar a produtividade e estabilidade de 12 genótipos de arroz em oito ambientes, durante os anos 2005 e 2006, na Colômbia. O delineamento utilizado foi o de blocos ao acaso com quatro repetições. Os parâmetros de estabilidade fenotípica e o agrupamento dos ambientes foram estimados pelo estudo da interação genótipo x ambiente, segundo o método SREG (Regressão nos sítios ou locais) e seu gráfico biplot (GGE). As análises estatísticas indicaram diferenças significativas (com 5 por cento de probabilidade de erro) entre genótipos e entre ambientes e significância (com 5 por cento de probabilidade de erro) da interação genótipo x ambiente, sugerindo uma resposta diferente dos genótipos nos vários ambientes. No método SREG, os dois primeiros componentes principais da interação explicaram 75,29 por cento da interação. Os genótipos 400094, 350361 e a variedade Fedearroz 50 foram considerados os de maior produtividade. Segundo o gráfico biplot GGE, os ambientes La Libertad e Escobal foram os mais favoráveis para o cultivo do arroz.

The analysis of genotype x environment interaction in plant breeding have been enlarged with new methodologies in the last decade, improving its efficiency on the selection of genotypes under different environmental conditions. The objective of this research was to analyze the yield and stability of twelve genotypes of rice, in eight environments, during the years 2005 and 2006 in Colombia. Completely randomized block designs with four replications were used. The phenotypic stability parameters and grouping of environments were estimated by the genotype-environment interaction study according to SREG (Sites Regression) method and its biplot graphic (GGE). The statistical analysis indicated significant differences (with 5 percent probability error) among genotypes and among environments. Also, it pointed out the significance (with 5 percent probability error) of the genotype-environment interaction, indicating different responses of genotypes confronted with different environments. In SREG method, the two first principal components of interactions explained 75.29 percent of the interaction. The genotypes 400094, 350361 and the variety Fedearroz were found as the highest yields. According to the biplot GGE graphic the environments La Libertad and Escobal were the ones with small variations during the years of study.