ABSTRACT: This research evaluated the agronomic performance through mixed models, and determined the genetic divergence between black oat genotypes. The experiment was carried out at Federal University of Santa Maria, Frederico Westphalen/RS. Fourteen black oat genotypes were evaluated, being 11 lines developed by Breeding Program of University, and three commercial cultivars (IAPAR 61, UPFA 21 - Moreninha and, IPR Cabocla). We evaluated quantitative traits associated to plant height, cycle, dry mass yield and seeds yield; and 19 qualitative traits, being these morphological descriptors. The results showed that lines UFSMFW 2-05 and UFSMFW 2-07 stand out with characteristics such as early cycle, higher dry mass and grain yield. Divergence analysis revealed the formation of three distinct groups, indicating the presence of variability. These results suggested the potential for the development of new cultivars of black oat, presenting early cycle and good grain yield.

RESUMO: O objetivo deste trabalho foi avaliar o desempenho agronômico por meio de modelos mistos e determinar a divergência genética entre genótipos de aveia preta. O experimento foi conduzido na Universidade Federal de Santa Maria, campus de Frederico Westphalen/RS. Catorze genótipos de aveia preta foram avaliados, sendo 11 linhagens desenvolvidas pelo Programa de Melhoramento da Universidade e três cultivares comercias (IAPAR 61, UPFA 21 - Moreninha e IPR Cabocla). Foram avaliadas características agronômicas quantitativas relacionadas ao porte, ciclo e produtividade de massa seca e de sementes; e 19 características qualitativas, sendo estes descritores morfológicos. Os resultados mostraram que as linhagens UFSMFW 2-05 e UFSMFW 2-07 se destacam com características como ciclo precoce, elevada produtividade de massa seca e de sementes. A análise de divergência revelou a formação de três grupos distintos, indicando presença de variabilidade. Os resultados demonstram o potencial de desenvolvimento de novas cultivares de aveia preta, apresentando precocidade e boa produtividade de sementes.

ABSTRACT A large set of variables is assessed for progeny selection in a plant-breeding program and other agronomic fields. The meta-analysis of the coefficient of variation (CVe) produces information for researchers and breeders on the experimental quality of trials. This analysis can also be applied in the decision-making process of the experimental plan regarding the experimental design, the number of repetitions, and the treatments and plants/progenies to be measured. In this study, we evaluated the dataset distribution and the descriptive statistics of CVe through the Frequentist and Bayesian approaches, aiming to establish the credibility and confidence intervals. We submitted CVe data of ten wheat (Triticum aestivum L.) traits reported in 1,068 articles published to the Bayesian and Frequentist analyses. Sample data were analyzed via Gamma and normal models. We selected the model with the lowest Akaike Information Criterion (AIC) value, and then we tested three link functions. In the Bayesian analysis, uniform distributions were used as non-informative priors for the Gamma distribution parameters with three ranges of q~U (a,b,). Thus, the prior probability density function was given by: p θ = 1 β - α , θ ∈ α , β . The Bayesian and Frequentist approaches with the Gamma model presented similar results for CVe; however, the range Bayesian credible intervals was narrower than the Frequentist confidence intervals. Gamma distribution fitted the CVe data better than the normal distribution. The credible and confidence intervals of CVe were successfully applied to wheat traits and could be used as experimental accuracy measurements in other experiments.

Abstract The objective of this work was to select black oat genotypes using the MGIDI for simultaneous selection, comparing it with the Smith-Hazel index. The experiment was carried out in Frederico Westphalen/RS and Pato Branco/PR, in a randomized block design, with three replications, with 9 genotypes tested. Days from emergence to flowering and maturation; cutting and plant height; number of tillers; panicle length; tiller, plant, panicle, panicle seed mass, green and dry; and seed yield were obtained. MGIDI selected the genotypes UFSMFW 2-01 and UFSMFW 2-04 for Frederico Westphalen and UFSMFW 2-07 and UFSMFW 2-04 for Pato Branco, which varied compared to the Smith-Hazel index in both environments. MGIDI was efficient in selecting the best black oat genotypes, showing desirable selection gains for most traits.

ABSTRACT The agronomic traits have complex quantitative inheritance, wheat breeding has a highly cost and time expending to achieve advanced lines, and new cultivars. The objective of this work was to estimate the phenotypic (rp), genotypic (rg) and environmental (re) correlation coefficients and the genetic parameters, as well as to estimate the selection gains between agronomic traits in wheat using multivariate analysis. F6 generation was carried out in a randomized block experimental design, with fifteen wheat genotypes arranged in three replications. The traits measured were days of emergence to flowering, plant height, number of tillers, spike length, number of spikelets, kernel weight and thousand kernel weight. Correlation coefficients, variance components, genetic parameters, selection gain, Euclidiana’s distance, relative contribution of traits and canonical variables were estimated. Selection based on number of tillers, kernel weight and thousand kernel weight may result in expressive selection gains. The number of fertile tillers per plant showed a significant and positive intermediate association with kernel weight and positive correlation with number of spikelets. The cycle showed greater contribution to the genetic divergence among genotypes studied. Distinct groups highlighted the genetic variability among genotypes.

ABSTRACT. Coffee outturn can be defined as the ratio between the harvested coffee and its respective processed grains. This character is greatly influenced by genotypic and environmental effects, and in breeding programs your analysis is costly and time-consuming. In this sense, the use of an outturn index to estimate coffee yield on experimental plots is a desirable measure aiming at reducing resources and time in postharvest evaluations. Thus, the present study aimed to evaluate the accuracy of the use of an outturn index equal to 4.0, in the estimation of Conilon coffee grains production. This index indicates that four kilograms of harvested fruit would be needed to obtain one kilogram of processed grains. Based on the average of 157 genotypes conducted in three trials and four harvests, we evaluated the relationship between harvested fruits and processed grains (FcBe), the observed (OGY), and the estimated grain yield per plant (EGY) based on FcBe equal to 4.0 (an outturn index). Descriptive statistics, adequation test for EGY, and the coincidence of occurrence of genotypes observations relating to the top 20% of all observations of OGY and EGY. In the estimation of grain yield in Conilon, the use of FcBe equal to 4.0 showed high precision in the average of the analyzed trials. However, further studies should be conducted to elucidate the effects of climate variables on the yield of Conilon coffee, especially in atypical crop years. Thus, the use of an outturn index becomes interesting in cases where the number of genotypes to be evaluated is very large and a screening of the promising ones is desirable.

Abstract UFSMFW 2202 is an early black oat cultivar with high dry matter and grain yield potential. When used in rotation systems, the early cycle has the immediate advantage of allowing anticipated sowing of subsequent crop. Initially, the cultivar is recommended for the North and Northwest of Rio Grande do Sul.

Abstract The black oat cultivar UFSMFW 2101, recommended for Northwest of the state of Rio Grande do Sul, is very early and can produce high dry matter and grain yields. In rotation systems, an immediate advantage is the very early cycle, with the possibility of anticipated sowing of the subsequent crop.

ABSTRACT. Strawberry is an economically and socially important crop in several regions worldwide. Thus, studies that provide information on topics in strawberry growth are important and must be constantly updated. The aims of this study were to fit a logistic growth model to describe strawberry fruit production and to estimate the partial derivatives of the fitted model in order to estimate and interpret the critical points, in addition to using multivariate analyses. To do this, data on 16 treatments [combinations of two cultivars (Albion and Camarosa), two origins (national and imported), and four mixed organic substrates (70% crushed sugar cane residue + 30% organic compost, 70% crushed sugar cane residue + 30% commercial substrate, 70% burnt rice husk + 30% organic compost, and 70% burnt rice husk + 30% commercial substrate)] conducted in a randomized complete block design (RCBD) with four replicates were used. A logistic model was fitted to the accumulated fruit production stratified by treatment and replication. Partial derivatives related to the accumulated thermal sum were estimated in order to quantify the critical points of the model. Subsequently, a principal component analysis was performed. The results show that the use of growth models substantially increases the inferences that can be made about crop growth, and the multivariate analysis summarizes this information, simplifying its interpretation. Approaches such as those carried out in this study are still rarely used, but, compared to simpler models, they increase the amount of inferences that can be made and provide greater elucidation of the results.

RESUMO Modelos mistos e análises multivariadas são ferramentas poderosas para selecionar genótipos superiores em programas de melhoramento de plantas. O método BLUP (best linear unbiased prediction) tem sido usado para predizer valores genéticos, eliminando efeitos ambientais. Além disso, o método FAI-BLUP (ideotype-design index) é importante para o melhoramento genético de plantas, devido à seleção de múltiplas características. Objetivou-se determinar o potencial genético de gerações avançadas de trigo, utilizando-se REML/BLUP em combinação com técnicas multivariadas, para a seleção de genótipos superiores. O experimento foi constituído de onze genótipos de trigo (Triticum aestivum L.). O delineamento experimental foi o de blocos casualizados, com três repetições. Foram avaliadas as variáveis altura da planta, altura de inserção da espiga, número de afilhos, número de espiguetas, largura do grão, peso hectolitro e peso de grãos por planta. Os parâmetros genéticos foram estimados utilizando-se a metodologia REML/BLUP, e o índice FAI-BLUP foi calculado por meio dos valores genéticos preditos. Os genótipos UFSMFW 1-02, UFSMFW 1-05 e UFSMFW 1-04 apresentam potencial de incremento para produtividade de grãos. Os ganhos de seleção para número de afilhos (14,63 %) e massa de grãos por planta (22,35 %) são potencias para a seleção de genótipos superiores.

ABSTRACT Mixed models and multivariate analysis are powerful tools for selecting superior genotypes in plant breeding programs. The BLUP (best linear unbiased prediction) method has been used to predict genetic values without environmental effects. Furthermore, the FAI-BLUP (ideotype-design index) procedure is especially valuable for plant breeding because of multiple-trait selection. This study aimed to determine the genetic potential of advanced wheat generations using REML/BLUP in combination with multivariate techniques for the selection of superior genotypes. The experiment consisted of eleven wheat (Triticum aestivum L.) genotypes. The experimental design was randomized blocks, with three replications. Plant height, spike insertion height, number of tillers, number of spikelets, kernel width, hectoliter weight and kernel weight per plant were determined. The genetic parameters were estimated using the REML/BLUP methodology, and the FAI-BLUP index was calculated using predicted genetic values. The genotypes UFSMFW 1-02, UFSMFW 1-05 and UFSMFW 1-04 show potential to increase the grain yield. The selection gains for number of tillers (14.63 %) and kernel weight per plant (22.35 %) indicate the potential to select superior genotypes.

RESUMO: O objetivo deste estudo foi caracterizar a produção de pimenta biquinho através da interpretação dos parâmetros do modelo Logístico e seus pontos críticos obtidos pelas derivadas parciais da função, bem como indicar qual a melhor cultivar e a melhor época de cultivo para locais de clima subtropical. Conduziu-se um experimento em esquema fatorial 2x3 sendo duas cultivares de pimenta biquinho (BRS Moema e Airetama biquinho), em três épocas de cultivo (E1: outubro de 2015, E2: 01 de novembro 2015 e E3: janeiro de 2016). Ajustou-se o modelo logístico para massa de frutos em função da soma térmica acumulada, e calculou-se os pontos críticos através das derivadas parciais do modelo com a finalidade de caracterizar o desempenho produtivo da cultura através da interpretação biológica destes parâmetros. Temperaturas próximas a 0 ºC durante o experimento foram letais às plantas, e por isso, para a época 3, ajustou-se um modelo de regressão linear. A interpretação dos parâmetros do modelo Logístico e seus pontos críticos permitiram que a produção das cultivares nas épocas 1 e 2 fossem caracterizadas, sendo que a cultivar mais produtiva é Airetama biquinho em todas as épocas de transplante. Essa cultivar também apresenta maior concentração de produção no período. Quanto a precocidade produtiva as duas cultivares não diferiram significativamente. Sobre a época 3, não foi possível interpretar da mesma forma, pois o ajuste do modelo linear não permite as mesmas interpretações realizadas para o modelo não linear, reafirmando a sua aplicabilidade em cultura olerícolas de múltiplas colheitas.

ABSTRACT: The objective of this study was to characterize the production of biquinho pepper through the interpretation of parameter estimates from the logistic model and its critical points obtained by the partial derivatives of the function, and to indicate the best cultivar and growing season for subtropical climate sites. For this, a 2x3 factorial experiment was conducted with two cultivars of biquinho pepper (BRS Moema and Airetama biquinho) in three growing seasons (E1: October 2015, E2: November 2015, E3: January 2016). The logistic non-linear model for fruit mass was specified as a function of the accumulated thermal sum, and the critical points were calculated through the partial derivatives of the model, in order to characterize the productive performance of the crop by the biological interpretation of the estimates of the three set parameters. In E3, temperatures close to 0 ºC during the experiment were lethal to the plants, and a linear regression model was used in this case. The production of the cultivars in E1 and E2 were well characterized by the estimated logistic models, and the most productive cultivar was Airetama biquinho in all evaluated seasons. This cultivar also presented higher concentration of production. The two cultivars did not differ significantly with regards to productive precocity. For E3, it was not possible to interpret the parameters in the same way as for E1 and E2, since the use of the linear model did not allow the same interpretations performed for the nonlinear model, reaffirming its applicability horticultural crops of multiple harvests.

ABSTRACT. The objective of this study was to estimate the coefficient of repeatability and the number of measurements required for production and quality variables in a strawberry crop. An experiment was conducted with two strawberry cultivars from two origins grown in four substrate mixtures, totaling 16 treatments, evaluated in a randomized block design with four replications. Mass (MF) and number (NF) of fruits per plant were evaluated as measures of production, and total soluble solids (SST), titratable acidity (AT) and firmness (FIR) of fruits during the crop cycle were evaluated as measures of quality. Subsequently, the repeatability coefficient was estimated by the following methods: analysis of variance (ANOVA), principal component analysis using a correlation matrix (PCcor), principal component analysis using a variance-covariance matrix (PCcov) and structural analysis (SA). The number of measurements was adjusted for each studied variable based on determination coefficients of 0.80, 0.85, 0.90, and 0.95. The repeatability coefficients ranged from low to medium. The ANOVA method gave the lowest r values, while the PCcov method presented the highest values of r. When using the PCcov method, 3.6, 2.9, 6.2, 3.2, and 3.8 measurements were needed to reach 80% confidence for the variables MF, NF, SST, AT, and FIR, respectively, and this increased to 7.3, 14.0, 29.6, 15.4, and 18.1 for 95% confidence in the results for MF, NF, SST, AT, and FIR, respectively.

Abstract In plant breeding, the dialelic models univariate have aided the selection of parents for hybridization. Multivariate analyses allow combining and associating the multiple pieces of information of the genetic relationships between traits. Therefore, multivariate analyses might refine the discrimination and selection of the parents with greater potential to meet the goals of a plant breeding program. Here, we propose a method of multivariate analysis used for stablishing mega-traits (MTs) in diallel trials. The proposed model is applied in the evaluation of a multi-environment complete diallel trial with 90 F1’s of simple maize hybrids. From a set of 14 traits, we demonstrated how establishing and interpreting MTs with agronomic implication. The diallel analyzes based on mega-traits present an important evolution in statistical procedures since the selection is based on several traits. We believe that the proposed method fills an important gap of plant breeding. In our example, three MTs were established. The first, formed by plant stature-related traits, the second by tassel size-related traits, and the third by grain yield-related traits. Individual and joint diallel analysis using the established MTs allowed identifying the best hybrid combinations for achieving F1’s with lower plant stature, tassel size, and higher grain yield.

A soja é a principal cultura de verão do Brasil, atualmente a implantação de segunda safra vem sendo crescente. Neste sentido, o conhecimento da contribuição dos caracteres ao rendimento de grãos nestas condições é necessário. O delineamento experimental utilizado foi blocos casualizados, em esquema fatorial 2 x 8, sendo dois locais de cultivo (Salvador das Missões - RS e Tenente Portela - RS) e oito genótipos de soja com hábito de crescimento indeterminado (BMX Elite, NS 5959, NS 5909, BMX Alvo, BMX Potência, BMX Tornado, BMX Turbo, BMX Garra). Os dados foram submetidos a análise de variância pelo teste F (p<0,05), posteriormente, a análise de trilha foi realizada a partir da matriz de correlações, considerando massa total de grãos como variável dependente, e os demais caracteres agronômicos como explicativos. Os componentes de rendimento, o número de legumes com três grãos, o peso de mil grãos dos legumes com três grãos apresentou tendências lineares mais fortes e positivas com o rendimento dos grãos. Os genótipos NS5959, BMX Potência e BMX Turbo obtiveram a maior massa total de grãos, com a maior contribuição do peso de mil grãos dos legumes com dois e três grãos.

The soybean is the main summer crop in Brazil, currently the cultivation of the second crop has been growing. In this sense, the acknowledgement of traits contribution to grain yield in front of these conditions is necessary. The experimental design was in a randomized block, in 2 x 8 factorial scheme, two locals (Salvador das Missões - RS and Tenente Portela - RS) and eight soybean genotypes with indeterminate habit (BMX Elite, NS 5959, NS 5909, BMX Alvo, BMX Potência, BMX Tornado, BMX Turbo, BMX Garra). Data were submited to analysis of variance by the F test (p <0.05), and after the path analysis was performed from the correlation matrix, considering total grain mass as the dependent variable, and the other agronomic traits as explanatory variables. The grain yield components, number of pods with three grains, thousand grain weight of pods with three grains showed stronger and more positive linear trends with grain yield. The genotypes NS5959, BMX Potência and BMX Turbo obtained the highest total grain mass, and that had more contribution of the thousand grain weight of pods with two and three grains.

ABSTRACT This work aimed to estimate the variance components and genetic parameters, the selection gain, and the cause and effect relationships among traits in order to identify important traits for direct and indirect selection of wheat (Triticum aestivum L.) lines. Three strategies were used to obtain selection gains: direct and indirect selection, an index based on “ranks,” and the Smith and Hazel index. In the 2017 crop season in Brazil, 420 wheat lines from the F5 generation were conducted in families with intercalary controls. High heritability of spike weight, number of kernels, and total kernel weight resulted in the best direct selection gains. The selection of plants with a high number of tillers resulted in grain yield improvement. The use of selection indexes is important in advanced wheat lines; they promote genetic gains distributed among agronomic traits.

ABSTRACT The cultivation of second-harvest with soybean crop after first-harvest with maize crop has become an alternative to aggregate income to farmers in the South region of Brazil. However, there is little information about this cropping system in this region. The aims of this study were to: (i) evaluate the agronomic performance of soybean (Glycine max L.) cultivars growing in second-harvest during the summer; and (ii) evaluate the genetic divergence of the cultivars based on qualitative and quantitative traits. To do this, 18 soybean cultivars were evaluated in three field trials, sown during January in the northwestern region of Rio Grande do Sul state, Brazil. In each experiment, a randomized block design with four replicates was used. Five quantitative traits (representing the agronomic performance of the cultivars) and 12 qualitative traits (morphological descriptors) were assessed aiming at studying the genetic divergence. Variance components and genetic parameters were estimated using mixed models and BLUPs for genotypes were estimated for each quantitative trait. The cultivars FPS Iguaçu RR and BMX Turbo RR have good agronomic performance and are, based on quantitative and qualitative traits, genetically distant. These cultivars have shown agronomic features that allow their cultivation in the second-harvest in the northwestern of Rio Grande do Sul in addition to be potential genitors for future soybean breeding programs.