Genetic diversity of standard leaf nutrients in Coffea canephora genotypes during phenological phases.

Diagnosing foliar nutritional status is essential for fertilizer recommendations and for the identification of nutrient imbalances. This study aimed to verify genetic diversity and establish mean standards (leaf nutrient contents; LNCs) and relationships among leaf nutrients (LNC relationships; LNCRs) in seven conilon coffee genotypes during both pre-flowering and bean-filling stages. Twenty crops from several cities in the northern region of Espírito Santo State, Brazil, with crop yield either equal to or greater than 100 bags per hectare (during two harvests) were assessed. A total of 140 samples were collected during each evaluation period for quantification of leaf nutrient contents (N, P, K, Ca, Mg, S, Fe, Zn, Cu, Mn, and B). The Ward procedure, a hierarchical genetic clustering method, was used to quantify the genetic diversity among genotypes. To examine differences between the LNCs and LNCRs, F-and Scott-Knott tests were used. LNCs and LNCRs showed significant differences among the conilon coffee genotypes during the evaluation periods. Additionally, the 8V, 10V,and 12V genotypes exhibited the highest values for most of the nutrients, especially for N, P, and Cu. Therefore, the clustering method revealed genetic diversity among genotypes for standard leaf nutrient levels, implying that leaf diagnosis could be specific to each genotype and phenological stage.

Assessment of genetic divergence among coffee genotypes by Ward-MLM procedure in association with mixed models.

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.

Adaptability and stability of conilon coffee in areas of high altitude.

In view of the predicted models of global climate change and differences in prices and production costs, there is increased interest in Coffea canephora cultivation in areas of high altitude. However, this species is sensitive to low temperatures, where genotypes vary regarding adaptation/tolerance mechanisms, demonstrating genotype x environment interaction. The aim of this study was to evaluate the stability and adaptability of C. canephora varieties in high-altitude areas. The experiments were carried out in February 2004, in Bom Jesus do Itabapoana, Rio de Janeiro State, Brazil, at an altitude of 725 m. Four clonal varieties (EMCAPA 8111, EMCAPA 8121, EMCAPA 8131, and EMCAPA 8151) and five harvests (2006 to 2010) were used. The experimental design was randomized blocks with four treatments and six plots, with 12 plants in each plot and spaced 2.5 x 1.2 m. Adaptability and stability parameters were determined using methods based on nonparametric analysis and analysis of variance. The results showed that the EMCAPA 8131 had the best performance according to stability and adaptability parameters and may be promising for high-altitude regions.

Agronomic performance of arabica coffee genotypes in northwest Rio de Janeiro State.

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.

Adaptability and genotypic stability of Coffea arabica genotypes based on REML/BLUP analysis in Rio de Janeiro State, Brazil.

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.