Sisvar is a statistical analysis system, first released in 1996 although its development began in 1994. The first version was done in the programming language Pascal and compiled with Borland Turbo Pascal 3. Sisvar was developed to achieve some specific goals. The first objective was to obtain software that could be used directly on the statistical experimental course of the Department of Exact Science at the Federal University of Lavras. The second objective was to initiate the development of a genuinely Brazilian free software program that met the demands and peculiarities of research conducted in the country. The third goal was to present statistical analysis software for the Brazilian scientific community that would allow research results to be analyzed efficiently and reliably. All of the initial goals were achieved. Sisvar gained acceptance by the scientific community because it provides reliable, accurate, precise, simple and robust results, and allows users a greater degree of interactivity. Index terms:Multiple comparisons, analysis of variance, regression, hypothesis tests. RESUMOO Sisvar é um sistema de análise estatística que foi lançado em 1996, embora o seu desenvolvimento tenha sido iniciado em 1994. A primeira versão foi desenvolvida em linguagem de programação Pascal e compilada com o Borland Turbo Pascal 3. O Sisvar foi desenvolvido em virtude de algumas razões específicas. O primeiro objetivo foi o de obter um software que pudesse ser usado diretamente no curso de estatística experimental do Departamento de Ciências Exatas da Universidade Federal de Lavras. O segundo objetivo foi o de iniciar o desenvolvimento de um software genuinamente brasileiro, gratuito que atendesse às demandas e peculiaridades das pesquisas realizadas no país. O terceiro objetivo foi o de apresentar um software de análise estatística para a comunidade científica brasileira que permitisse que os resultados da pesquisa pudessem ser analisados de forma eficiente e confiável. Todos os objetivos iniciais foram atingidos. O motivo da aceitação Sisvar pela comunidade científica é decorrente do fato de que ele é capaz de permitir uma maior interatividade com o usuário e produzir análises confiáveis, pelo fato de elas serem exatas, precisas, simples e robustas. Termos para indexação:Comparações múltiplas, análises de variância, regressão, testes de hipóteses.

Sisvar is a statistical analysis system with a large usage by the scientific community to produce statistical analyses and to produce scientific results and conclusions. The large use of the statistical procedures of Sisvar by the scientific community is due to it being accurate, precise, simple and robust. With many options of analysis, Sisvar has a not so largely used analysis that is the multiple comparison procedures using bootstrap approaches. This paper aims to review this subject and to show some advantages of using Sisvar to perform such analysis to compare treatments means. Tests like Dunnett, Tukey, Student-Newman-Keuls and Scott-Knott are performed alternatively by bootstrap methods and show greater power and better controls of experimentwise type I error rates under non-normal, asymmetric, platykurtic or leptokurtic distributions.

This paper presents a special capability of Sisvar to deal with fixed effect models with several restriction in the randomization procedure. These restrictions lead to models with fixed treatment effects, but with several random errors. One way do deal with models of this kind is to perform a mixed model analysis, considering only the error effects in the model as random effects and with different covariance structure for the error terms. Another way is to perform a analysis of variance with several error. These kind of analysis, when the data are balanced, can be done by using Sisvar. The software lead a exact $F$ test for the fixed effects and allow the user to applied multiple comparison procedures or regression analysis for the levels of the fixed effect factors, regarding they are single effects, interaction effects or hierarchical effects. Sisvar is an interesting statistical computer system for using in balanced agricultural and industrial data sets.

Key message We compare genomic selection methods that use correlated traits to help predict biomass yield in sorghum, and find that trait-assisted genomic selection performs best.AbstractGenomic selection (GS) is usually performed on a single trait, but correlated traits can also help predict a focal trait through indirect or multi-trait GS. In this study, we use a pre-breeding population of biomass sorghum to compare strategies that use correlated traits to improve prediction of biomass yield, the focal trait. Correlated traits include moisture, plant height measured at monthly intervals between planting and harvest, and the area under the growth progress curve. In addition to single- and multi-trait direct and indirect GS, we test a new strategy called trait-assisted GS, in which correlated traits are used along with marker data in the validation population to predict a focal trait. Single-trait GS for biomass yield had a prediction accuracy of 0.40. Indirect GS performed best using area under the growth progress curve to predict biomass yield, with a prediction accuracy of 0.37, and did not differ from indirect multi-trait GS that also used moisture information. Multi-trait GS and single-trait GS yielded similar results, indicating that correlated traits did not improve prediction of biomass yield in a standard GS scenario. However, trait-assisted GS increased prediction accuracy by up to when using plant height in both the training and validation populations to help predict yield in the validation population. Coincidence between selected genotypes in phenotypic and genomic selection was also highest in trait-assisted GS. Overall, these results suggest that trait-assisted GS can be an efficient strategy when correlated traits are obtained earlier or more inexpensively than a focal trait.Electronic supplementary materialThe online version of this article (10.1007/s00122-017-3033-y) contains supplementary material, which is available to authorized users.

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Understanding native communities is a crucial step for the management of biological nitrogen fixation, since they may be either a source of efficient strains or a limiting factor when efficient strains need to be introduced. This work aimed to evaluate the density, diversity and efficiency of Leguminosae nodulating bacterial (LNB) communities and their component strains in soils under various land use systems (LUSs): pristine forest, agriculture, pasture, agroforestry, young secondary forest, and old secondary forest,. The LNB communities were trapped from these soils by using the promiscuous host siratro under controlled conditions. We also studied their relationships with physical and chemical attributes of the soil. Agroforestry and agriculture soil samples induced the highest number of nodules in siratro, while forest soil samples induced the lowest number of nodules. No relationship was found between LNB and Leguminosae species diversity in the LUSs. The soil chemical variables that were most related to differences in nodule number and shoot dry matter weight of plants inoculated with soil suspensions of the LUSs were, respectively: Ca 2+ , Mg 2+ , base saturation, exchangeable bases and Cu 2+ ; and pH, cation exchange capacity, B, Cu 2+ and clay. Although, LNB communities from all LUSs were efficient under controlled and similar conditions, they were found to be composed of strains with variable efficiency: inefficient, efficient, highly efficient and superior efficiency. Efficient strains occurred at the highest frequency in all LUSs. The isolated strains presented similar and new sequences that were phylogenetically related to well known LNB genera in α-and β-Proteobacteria. Unusual genera in these branches, as well as in other branches, which are probably endophytic bacteria, were also isolated from nodules. These data support siratro as a useful trap species to study the LNB biodiversity of diverse ecosystems in tropical soils. The fact that the highest diversity and nodulation were seen in managed systems such as agriculture and agroforestry suggests a high resilience of LNB communities to changes in land use after deforestation in a region where large forest areas are still preserved and can be a source of propagules.

RESUMOConduziu-se este trabalho, com o objetivo de caracterizar a variabilidade genética entre 116 acessos de açaizeiro da coleção de germoplasma da Embrapa Amazônia Oriental por marcadores microssatélites (SSR). As reações foram efetuadas com base em 116 amostras de DNA, utilizando sete primers SSR. Os níveis de polimorfismo e as estimativas das distâncias genéticas de Roger foram determinados pelas frequências alélicas e agrupado pelo método UPGMA. Os sete locos SSR revelaram 42 alelos com média de 6 alelos por loco. O conteúdo de informação de polimorfismo (PIC) variou de 0,60 a 0,86 com média de 0,75 e as heterozigosidades observada (H o ) e esperada (H e ) foram de 0,54 e 0,75, respectivamente. A distância genética média entre todos os acessos foi de 0,61, variando de 0 a 0,96. O método UPGMA formou seis agrupamentos distintos delimitados pela distância genética média (dg m = 0,61). Os acessos de açaizeiro possuem alta diversidade para ser explorada em programas de melhoramento, sendo pelo menos quatro deles altamente divergentes com base nos marcadores SSR. Termos para indexação:Euterpe oleracea, germoplasma, polimorfismo, diversidade genética, SSR. ABSTRACTThe objective of this work was to characterize genetic variability among 116 accessions of assai palm of the Embrapa Eastern Amazon Germplasm Collection, were examined with microsatellite (SSR) markers. The 116 DNA sample were utilized in the reactions with seven SSR loci. The levels of polymorphism and Roger's genetic distance were estimated from allele frequencies and clustered with the UPGMA method. The seven SSR loci revealed 42 alleles, with average of 6 alleles per locus. The polymorphic information content (PIC) varied from 0.60 to 0.86, with average of 0.75 and observed (H o ) and expected (H e ) heterozygosities were 0.54 and 0.75, respectively. The mean genetic distance between all accessions was 0.61, varying from 0.00 to 0.96. The UPGMA dendrogram presented six distinct groupings, delimited by the mean genetic distance (dg m = 0.61). The accessions of assai palm possess high diversity that may be explored in breeding program and germplasm organization, with at least, four highly divergent accessions.

Resumo -Este trabalho teve como objetivo estimar a divergência genética entre acessos de açaizeiro conservados na coleção de germoplasma da Embrapa Amazônia Oriental, em Belém, PA, por meio de descritores morfoagronômicos. A avaliação foi realizada em 87 acessos, com base em 22 caracteres: sete relativos à planta, três à floração, três a frutos e nove à produção de frutos, no período de 1995 a 2001. Foram efetuadas análises univariadas e multivariadas, com estimativas das dissimilaridades obtidas pela distância euclidiana média padronizada, e formação dos agrupamentos obtida pelos métodos UPGMA e Tocher. Os acessos apresentaram alto índice de variação na maioria dos caracteres. As distâncias genéticas entre os pares de acessos variaram de 0,09 a 1,87, com média de 1,39. O método UPGMA dividiu os acessos em cinco grupos, enquanto o de Tocher formou 24 agrupamentos. Os cinco acessos indicados como mais divergentes devem compor programas de intercruzamentos, para obtenção de genótipos superiores.Termos para indexação: Euterpe oleracea, variabilidade, análise multivariada, agrupamento, distância genética. Genetic divergence among accessions of assai palm based on morphoagronomic descriptorsAbstract -The objective of this research was to estimate the genetic divergence among accessions of the assai palm, sampled in the germplasm collection of Embrapa Amazônia Oriental based on morphoagronomic traits, at Belém, PA. The 22 morphoagronomic traits were evaluated in 87 accessions, from 1995 to 2001. Among the 22 traits, seven were relative to the plant, three to the flowering, three to the fruit, and nine to the fruit production. The traits were analyzed using univariate and multivariate analysis. The estimates of the dissimilarities were obtained by the average Euclidian distance with standardized data, and the groupings by UPGMA and Tocher methods. The accessions presented high variation index in the majority of the characters. Genetic distances among accession pair varied from 0.09 to 1.87, with average of 1.39. The method UPGMA divided the accessions into five groups, while the Tocher method formed 24 groupings. The five accessions indicated as more divergent must be used in breeding programs aiming at the obtention of superior genotypes.