RESUMEN
Mixed linear models have been used for the analysis of the genetic diversity and provided further accurate results in crops such as eucalyptus, castor, and sugarcane. However, to date, research that combined this analysis with Ward-MLM procedure has not been reported. Therefore, the aim of the present study was to identify divergent coffee genotypes by Ward-MLM procedure, in association with the mixed-decision models. The experiment was initiated in February 2007, in the northwestern Rio de Janeiro State. The 25 evaluated genotypes were grown with a spacing of 2.5 x 0.8 m, in a randomized block design, with 5 replications, containing 8 plants each. The following agronomic traits were evaluated: plant height, stem diameter, plagiotropic branch number, and productivity. Four measurements were performed for each character from 2009 to 2012, between May and July. Data were analyzed using REML/BLUP analysis and Ward- MLM procedure. The Ward-MLM procedure in association with mixed linear models demonstrated the genetic variability among the studied coffee genotypes. We identified two groups of most divergent coffee genotypes, which can be combined by crossings and selections in order to obtain genotypes with high productivity and variability.
Asunto(s)
Café/genética , Modelos Genéticos , Productos Agrícolas/genética , Flujo Genético , Variación Genética , Genotipo , Fenotipo , Fitomejoramiento , Carácter Cuantitativo HeredableRESUMEN
Considering the productive potential of arabica coffee in the Rio de Janeiro State and the shortage of breeding programs for this species in the state, this study aimed to evaluate the vegetative and productive characteristics of 25 arabica coffee genotypes to indicate 1 or more varieties for the northwest Rio de Janeiro region. The experiment was in Varre e Sai, RJ, Brazil, and plants were planted in 2007 with a spacing of 2.5 x 0.8 m. Five plots were used, consisting of 8 plants per plot to measure vegetative growth, height, stem diameter, and plagiotropic branch number characteristics and productivity in the biennia 2009/2010 and 2011/2012. The classification by sieve was performed at harvest in 2011. The variables were subjected to analysis of variance and means grouped by the Scott Knott test at 5% probability, and the productivity was subjected to joint analysis of variance. Pearson's correlation coefficients between growth and productivity variables were estimated. The best genotypes were Catucaí Amarelo 2 SL, Catiguá MG 02, Acauã, Palma II, Sabiá 398, IPR 103, IPR 100, Catucaí Amarelo 24/137, and Catucaí Amarelo 20/15.
Asunto(s)
Agricultura , Coffea/genética , Genotipo , Brasil , Coffea/crecimiento & desarrollo , Estudios de Asociación Genética , Fenotipo , Carácter Cuantitativo HeredableRESUMEN
Biannuality in coffee culture causes temporal variability in plant productivity. Consequently, it is essential to evaluate genotypes during various crop years to ensure selection of productive and stable genotypes. We evaluated the effectiveness of simultaneous selection of coffee genotypes along harvests, based on productivity, stability, and adaptability, via mixed models, for indication of varieties suitable for Rio de Janeiro State. We evaluated 25 genotypes during 4 crop seasons (2009-2012), in a randomized block design with 5 replications. The ranking of genotypes was obtained on the basis of the adaptability and temporal stability methods (harmonic average of genetic values, relative performance of genetic values, and harmonic mean of the relative performance of the genetic values), obtained via restricted maximum likelihood/best linear unbiased procedure analysis. The selection accuracy (0.8717), associated with the high magnitude of mean heritability, indicate good reliability and prospects for success in the indication of agronomically superior genotypes. There was little variation in the ordering of genotypes among the environments, indicating low influence of harvests in the performance of the genotypes. Five of the 25 genotypes were superior and could be recommended for planting in the northwestern region of Rio de Janeiro State, due to high predicted productivity and stability. We recommend that these methodologies for evaluation of productivity, stability, and adaptability be included in the selection criteria for recommendation of genotypes for commercial plantings.