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ABSTRACT: The aim of this study was to use quantile regression (QR) to characterize the effect of the adaptability parameter throughout the distribution of the productivity variable on black bean cultivars launched by different national research institutes (research centers) over the last 50 years. For this purpose, 40 cultivars developed by Brazilian genetic improvement programs between 1959 and 2013 were used. Initially, QR models were adjusted considering three quantiles (τ = 0.2, 0.5 and 0.8). Subsequently, with the confidence intervals, quantile models τ = 0.2 and 0.8 (QR0.2 and QR0.8) showed differences regarding the parameter of adaptability and average productivity. Finally, by grouping the cultivars into one of the two groups defined from QR0.2 and QR0.8, it was reported that the younger cultivars were associated to the quantile τ = 0.8, i.e., those with higher yields and more responsive conditions indicating that genetic improvement over the last 50 years resulted in an increase in both the productivity and the adaptability of cultivars.
RESUMO: Neste estudo objetivou-se utilizar a regressão quantílica (RQ) para caracterizar o efeito do parâmetro de adaptabilidade ao longo de toda a distribuição da variável produtividade em cultivares de feijão preto lançadas por diferentes instituições nacionais de pesquisa nos últimos 50 anos. Para tanto utilizou-se 40 cultivares desenvolvidas pelos programas brasileiros de melhoramento genético entre os anos de 1959 a 2013. Inicialmente foram ajustados modelos de RQ considerando três quantis (τ=0,2, 0,5, 0,8). Posteriormente, com os intervalos de confiança verificou-se que os modelos quantílicos τ=0,2 e 0,8 (RQ0,2 e RQ0,8) apresentaram diferenças quanto ao parâmetro de adaptabilidade e produtividade média. Finalmente, por meio do agrupamento das cultivares em um dos dois grupos definidos a partir de RQ0,2 e RQ0,8, constatou-se que as cultivares mais novas foram associadas ao quantil τ = 0,8, ou seja, aquelas com maiores produtividades e mais responsivas as condições ambientais indicando que o melhoramento ao longo dos últimos 50 anos possibilitou o incremento tanto na produtividade quanto na adaptabilidade das cultivares.
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This study was carried out to identify the yield stability and adaptability of the grain maize genotypes (parental inbred lines, F1-hybrids and check varieties), using Additive Main Effects and Multiplicative Interaction (AMMI). A field experiment was executed during the winter and summer seasons of 2009 and 2010 at two locations, Shambat and Elrawakeeb, Sudan. A split-plot design with three replications was used to layout the experiment. The inbred lines and their F1-hybrids were evaluated in the field under normal irrigation and water-stress conditions. The results showed that, highly significant differences were detected among genotypes, environments and for G×E interaction, indicated differential performance of genotypes over environments. Considering mean grain yield, and the Linear Regression parameters bi and S2d values jointly, the F1-hybrids 160×2, 160×3 and 6×3 gave above average mean of grain yield/ha and were most stable for grain yield/ha. AMMI analysis differentiated the genotypes (parental inbred lines and F1-hybrids), based on their grain yield, into different adaptation pattern and stability. Based on AMMI analysis, the F1- hybrids 66y×6 and 6×3 were highly stable with considerable high yield and adapted to favorable environments. However, the F1- hybrids 160×66y and 160×3 exhibited the highest mean grain yield/ha (4.1 tons and 3.5 tons, respectively), with slightly low interaction scores, hence they are regarded as superior hybrids.
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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.