RBras is a scientific society founded in 1955, of a cultural character, non-profit, dedicated to Brazilian researchers who work with the mathematical and statistical aspects of agronomy, biological sciences and related areas. According to its statute, RBras seeks to stimulate the research activities of its members, encouraging and supporting scientific events with the following objectives: (i) to bring together researchers in the area of applied statistics, biometrics and biostatistics; (ii) to promote scientific events to discuss research topics in applied statistics; (iii) to publicize the methods developed in the area of statistics; and (iv) to offer courses on new topics in applied statistics. RBras belongs to The International Biometric Society, made up of several other regions and networks, and involving researchers in the area of Biometrics from all over the world.
{"title":"SPECIAL ISSUE ON BIOSTATISTICS AND BIOMETRY IN THE ERA OF DATA SCIENCE","authors":"P. Rodrigues, L. R. Nakamura, C. Pereira","doi":"10.28951/RBB.V39I1.556","DOIUrl":"https://doi.org/10.28951/RBB.V39I1.556","url":null,"abstract":"RBras is a scientific society founded in 1955, of a cultural character, non-profit, dedicated to Brazilian researchers who work with the mathematical and statistical aspects of agronomy, biological sciences and related areas. According to its statute, RBras seeks to stimulate the research activities of its members, encouraging and supporting scientific events with the following objectives: (i) to bring together researchers in the area of applied statistics, biometrics and biostatistics; (ii) to promote scientific events to discuss research topics in applied statistics; (iii) to publicize the methods developed in the area of statistics; and (iv) to offer courses on new topics in applied statistics. RBras belongs to The International Biometric Society, made up of several other regions and networks, and involving researchers in the area of Biometrics from all over the world.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79026411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Q. Nomelini, J. W. Silva, C. A. Gallo, R. M. F. Neto, José Dos Reis Vieira de Moura Junior, J. E. Ramos
ABSTRACT: Statistical Process Control (SPC) stands out for the use of control charts and for repeatability and reproducibility (R&R) techniques. This work aimed at its applications in the aspects of pre-processing of structural monitoring. The experiment was carried out in a completely randomized design (CRD) with two sources of variation: eight aluminum beams with piezoelectric patches and five types of damage (D1 = baseline, D2 = 0.6g, D3 = 1.1g, D4 = 1.6g, D5 = 2.2g). All measurements were gathered at 30C and with 20 repetitions for each condition case, producing a damage metric. In the R&R study, a low variation of repetition was observed (9.84%), but a high reproducibility (72.39%), representing that the damage metrics were similar for each situation, but a high variation among beams and damages. Based on this evaluation, the control charts helped to verify in which beams and damages these greatest variabilities were found. Concluding, the control charts for mean and individual measures as well as the R&R study were interesting tools for raw data preprocessing step for measurement error detection.
{"title":"STATISTICAL PROCESS CONTROL (SPC) OF DAMAGE METRICS IN THE IMPEDANCE-BASED STRUCTURAL HEALTH MONITORING","authors":"Q. Nomelini, J. W. Silva, C. A. Gallo, R. M. F. Neto, José Dos Reis Vieira de Moura Junior, J. E. Ramos","doi":"10.28951/RBB.V39I1.482","DOIUrl":"https://doi.org/10.28951/RBB.V39I1.482","url":null,"abstract":" ABSTRACT: Statistical Process Control (SPC) stands out for the use of control charts and for repeatability and reproducibility (R&R) techniques. This work aimed at its applications in the aspects of pre-processing of structural monitoring. The experiment was carried out in a completely randomized design (CRD) with two sources of variation: eight aluminum beams with piezoelectric patches and five types of damage (D1 = baseline, D2 = 0.6g, D3 = 1.1g, D4 = 1.6g, D5 = 2.2g). All measurements were gathered at 30C and with 20 repetitions for each condition case, producing a damage metric. In the R&R study, a low variation of repetition was observed (9.84%), but a high reproducibility (72.39%), representing that the damage metrics were similar for each situation, but a high variation among beams and damages. Based on this evaluation, the control charts helped to verify in which beams and damages these greatest variabilities were found. Concluding, the control charts for mean and individual measures as well as the R&R study were interesting tools for raw data preprocessing step for measurement error detection. ","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82168184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The national inventories of greenhouse gas (GHG) emissions, which are periodically prepared by countries that signed the Climate Change Convention, compute emissions from anthropogenic sources among them agricultural activities. The protocols established within the scope of the International Panel on Climate Change (IPCC) make it possible to estimate these emissions. These protocols use standard emission factors that vary according to the characteristics of the monitored activities and only scientific research, published in journals of recognized quality, can establish other local factors. Brazilian researchers carry out experiments to measure GHG emissions from agricultural activities, aiming to calculate specific parameters for the national climatic and management conditions. These field experiments are complex, costly, with a limited number of repetitions and, eventually, high natural variability. Often, these limitations result in the inability of the analysis of variance (ANOVA) to identify differences between treatments. The objective of this work is to present the non-parametric Kolmogorov-Smirnov (KS) test as an alternative to compare the effect of flooded irrigation management on methane (CH4) emission throughout the rice crop cycle. We present a case study in which ANOVA produced non-significant results for the adjustment of the model while the KS identified the emission curves as significantly different. The KS test could be adapted, via the SAS NPAR1WAY routine, to compare events with responses over time, such as methane emissions in flooded rice, resulting in test values and graphs that are easy to understand and interpret.
{"title":"APPLICATION OF THE KOLMOGOROV-SMIRNOV TEST TO COMPARE GREENHOUSE GAS EMISSIONS OVER TIME","authors":"A. J. B. Luiz, Magda Aparecida de Lima","doi":"10.28951/RBB.V39I1.498","DOIUrl":"https://doi.org/10.28951/RBB.V39I1.498","url":null,"abstract":"The national inventories of greenhouse gas (GHG) emissions, which are periodically prepared by countries that signed the Climate Change Convention, compute emissions from anthropogenic sources among them agricultural activities. The protocols established within the scope of the International Panel on Climate Change (IPCC) make it possible to estimate these emissions. These protocols use standard emission factors that vary according to the characteristics of the monitored activities and only scientific research, published in journals of recognized quality, can establish other local factors. Brazilian researchers carry out experiments to measure GHG emissions from agricultural activities, aiming to calculate specific parameters for the national climatic and management conditions. These field experiments are complex, costly, with a limited number of repetitions and, eventually, high natural variability. Often, these limitations result in the inability of the analysis of variance (ANOVA) to identify differences between treatments. The objective of this work is to present the non-parametric Kolmogorov-Smirnov (KS) test as an alternative to compare the effect of flooded irrigation management on methane (CH4) emission throughout the rice crop cycle. We present a case study in which ANOVA produced non-significant results for the adjustment of the model while the KS identified the emission curves as significantly different. The KS test could be adapted, via the SAS NPAR1WAY routine, to compare events with responses over time, such as methane emissions in flooded rice, resulting in test values and graphs that are easy to understand and interpret.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73853603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The quantity and complexity of generated data due to advances in genetic sequencing technologies has made statistical analysis an essential tool for their correct study and interpretation. However, there is still no agreement about which methodologies are more appropriate for those data, especially for the selection of genetic features that influence a specific phenotype. Genetic data are usually characterized by having a number of variables which is much greater than the number of observations. These variables exhibit little variability and high correlation. These characteristics hinder the application of traditional methodologies for variable selection. In this work (i.) we present different methodologies for selecting variables Random Forest, LASSO and the traditional Stepwise method; (ii.) we apply them to genetic data to select SNP markers that characterize the presence or absence of a disease and (iii.) we compare their performances. Random Forest and Lasso show similar prediction performance, however none of them correctly select the relevant SNPs.
{"title":"SELECTION OF SNP MARKERS: ANALYZING GAW17 DATA USING DIFFERENT METHODOLOGIES","authors":"Mariana Pavan Ióca, D. Zuanetti","doi":"10.28951/RBB.V39I1.499","DOIUrl":"https://doi.org/10.28951/RBB.V39I1.499","url":null,"abstract":"The quantity and complexity of generated data due to advances in genetic sequencing technologies has made statistical analysis an essential tool for their correct study and interpretation. However, there is still no agreement about which methodologies are more appropriate for those data, especially for the selection of genetic features that influence a specific phenotype. Genetic data are usually characterized by having a number of variables which is much greater than the number of observations. These variables exhibit little variability and high correlation. These characteristics hinder the application of traditional methodologies for variable selection. In this work (i.) we present different methodologies for selecting variables Random Forest, LASSO and the traditional Stepwise method; (ii.) we apply them to genetic data to select SNP markers that characterize the presence or absence of a disease and (iii.) we compare their performances. Random Forest and Lasso show similar prediction performance, however none of them correctly select the relevant SNPs.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75754993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laryssa Ribeiro Calcagnoto, Tiago V. F. Santana, R. R. Pescim
Absenteeism is the practice or custom of an employee to be absent from workplace. Its causes are diverse and may affect the workers income as well as to cause operational disruption, stress the administration and also financial losses for the company. Cluster analysis is a multivariate tool that can be used to determine groups in the sense that each group has its own characteristics in terms of the observed variables. In this sense, that technique can be used as a support to show which characteristics may contribute to absenteeism. We use the Ward hierarchical algorithm to build the clusters and to compare the groups the Kruskal-Wallis nonparametric test is adopted. Finally, a study on the strength of association among the variables is developed using Spearman’s correlation and for the relationship among those variables related to absence and social aspects, we use the principal component analysis. Moreover, the study indicates the possibility to determine three heterogeneous groups in the company and to show characteristics in those groups which are potential factors that cause absenteeism to a greater or lower extent.
{"title":"CLASSIFICATION AND IDENTIFICATION OF THE CAUSES OF ABSENTEEISM IN A PUBLIC TRANSPORT COMPANY USING CLUSTER ANALYSIS AND PRINCIPAL COMPONENTS TECHNIQUES","authors":"Laryssa Ribeiro Calcagnoto, Tiago V. F. Santana, R. R. Pescim","doi":"10.28951/RBB.V39I1.493","DOIUrl":"https://doi.org/10.28951/RBB.V39I1.493","url":null,"abstract":"Absenteeism is the practice or custom of an employee to be absent from workplace. Its causes are diverse and may affect the workers income as well as to cause operational disruption, stress the administration and also financial losses for the company. Cluster analysis is a multivariate tool that can be used to determine groups in the sense that each group has its own characteristics in terms of the observed variables. In this sense, that technique can be used as a support to show which characteristics may contribute to absenteeism. We use the Ward hierarchical algorithm to build the clusters and to compare the groups the Kruskal-Wallis nonparametric test is adopted. Finally, a study on the strength of association among the variables is developed using Spearman’s correlation and for the relationship among those variables related to absence and social aspects, we use the principal component analysis. Moreover, the study indicates the possibility to determine three heterogeneous groups in the company and to show characteristics in those groups which are potential factors that cause absenteeism to a greater or lower extent.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76744566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andson Nunes da Silva, S. Anyosa, Jorgelina Guzmán
In this work, we presented, in a didactic way, the Bayesian binary regression modeling for unbalanced data using new links functions. Under the Bayesian approach and using information criteria, predictive evaluation measures and introducing the analysis of residuals, we show that the models that use power and reverse power link functions are better than traditional models in the presence of unbalanced data, considering two applications. Additionally, codes with the procedures presented using the Stan package are made available in order to facilitate the use of these models. The work also contains a simulation study that shows how the unbalance in the response variable affects the estimation of the parameters of a logistic regression with respect to the bias, mean square error and standard deviation of the estimates, regardless of the sample size. At the same time, considering two applications, we show how binary regression models with the power and reverse power links recently formulated in the literature can be used to adequately estimate the parameters in the type of unbalance considered.
{"title":"Modelagem Bayesiano de regressão binária para dados desbalanceados usando novas ligações","authors":"Andson Nunes da Silva, S. Anyosa, Jorgelina Guzmán","doi":"10.28951/rbb.v38i4.455","DOIUrl":"https://doi.org/10.28951/rbb.v38i4.455","url":null,"abstract":"In this work, we presented, in a didactic way, the Bayesian binary regression modeling for unbalanced data using new links functions. Under the Bayesian approach and using information criteria, predictive evaluation measures and introducing the analysis of residuals, we show that the models that use power and reverse power link functions are better than traditional models in the presence of unbalanced data, considering two applications. Additionally, codes with the procedures presented using the Stan package are made available in order to facilitate the use of these models. The work also contains a simulation study that shows how the unbalance in the response variable affects the estimation of the parameters of a logistic regression with respect to the bias, mean square error and standard deviation of the estimates, regardless of the sample size. At the same time, considering two applications, we show how binary regression models with the power and reverse power links recently formulated in the literature can be used to adequately estimate the parameters in the type of unbalance considered.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78419588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Basto, E. M. Nascimento, B. B. Pereira, J. Ribeiro Filho, R. Perez, Cristiane Alves Vilella Nogueira
Although Model for End-Stage Liver Disease (MELD) score is adopted worldwide for liver transplant allocation, but it has prognostic limitations. The aim of this study was to apply the survival tree analysis to evaluate interaction between variables related to mortality in cirrhotics patients enlisted for liver transplantation, and to develop a new mortality predictive score. Demographic, clinical and laboratory data of cirrhotic patients waiting for liver transplantation during a 12-year period were considered. Charts from 765 patients were reviewed. The interaction between prognostic covariates was obtained using a survival tree analysis. In order to develop the predictive score, Cox regression analysis was performed applying significant data obtained by the survival tree analysis. The prognostic covariates evaluated in the survival tree were MELD score, Child-Pugh score, serum sodium, viral disease etiology, hepatocellular carcinoma diagnosis and generated a coefficient for each. Based on the survival tree analysis, MELD = 15 was the primary root variable (p<0.001). The survival tree provided eight prognostic groups. The higher mortality hazard ratio (HR) risk was observed in the MELD >28 group (HR= 16.7). The new score (Survival Tree Score – STS) was obtained according to the coefficients provided. The STS prognostic performance was superior to MELD score (AUROC 0.713 vs 0.653, p<0.001). STS, could be a useful tool to accurately identify individual mortality risk in advanced liver disease.
虽然终末期肝病模型(Model for End-Stage Liver Disease, MELD)评分在全球范围内被用于肝移植分配，但其存在预后局限性。本研究的目的是应用生存树分析来评估肝硬化患者肝移植死亡率相关变量之间的相互作用，并开发一种新的死亡率预测评分。我们考虑了12年间等待肝移植的肝硬化患者的人口学、临床和实验室数据。回顾了765例患者的图表。预后协变量之间的相互作用通过生存树分析得到。为了建立预测评分，应用生存树分析获得的显著性数据进行Cox回归分析。生存树中评估的预后协变量为MELD评分、Child-Pugh评分、血清钠、病毒性疾病病因学、肝细胞癌诊断，并为每个协变量生成系数。根据生存树分析，MELD = 15是主要的根变量(p28组(HR= 16.7))。根据提供的系数得到新的评分(生存树评分- STS)。STS预后优于MELD评分(AUROC 0.713 vs 0.653, p<0.001)。STS可能是准确识别晚期肝病患者个体死亡风险的有用工具。
{"title":"SURVIVAL TREE SCORE: A NOVEL APPROACH TO PREDICT MORTALITY IN CIRRHOTIC PATIENTS","authors":"S. Basto, E. M. Nascimento, B. B. Pereira, J. Ribeiro Filho, R. Perez, Cristiane Alves Vilella Nogueira","doi":"10.28951/rbb.v38i4.464","DOIUrl":"https://doi.org/10.28951/rbb.v38i4.464","url":null,"abstract":"Although Model for End-Stage Liver Disease (MELD) score is adopted worldwide for liver transplant allocation, but it has prognostic limitations. The aim of this study was to apply the survival tree analysis to evaluate interaction between variables related to mortality in cirrhotics patients enlisted for liver transplantation, and to develop a new mortality predictive score. Demographic, clinical and laboratory data of cirrhotic patients waiting for liver transplantation during a 12-year period were considered. Charts from 765 patients were reviewed. The interaction between prognostic covariates was obtained using a survival tree analysis. In order to develop the predictive score, Cox regression analysis was performed applying significant data obtained by the survival tree analysis. The prognostic covariates evaluated in the survival tree were MELD score, Child-Pugh score, serum sodium, viral disease etiology, hepatocellular carcinoma diagnosis and generated a coefficient for each. Based on the survival tree analysis, MELD = 15 was the primary root variable (p<0.001). The survival tree provided eight prognostic groups. The higher mortality hazard ratio (HR) risk was observed in the MELD >28 group (HR= 16.7). The new score (Survival Tree Score – STS) was obtained according to the coefficients provided. The STS prognostic performance was superior to MELD score (AUROC 0.713 vs 0.653, p<0.001). STS, could be a useful tool to accurately identify individual mortality risk in advanced liver disease.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86505272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Josiane Rodrigues, Francisco Humberto Henrique, S. S. Piedade, J. P. Laca-Buendía
Com o objetivo de caracterizar cinco cultivares e um novo genótipo de algodoeiro (Gossypium hirsutum L. r. latifolium Hutch) com respeito a variáveis morfológicas e agronômicas no município de Uberaba (MG), a técnica multivariada da análise de componentes principais foi aplicada. Para a realização do experimento utilizou-se o delineamento casualizado em blocos com seis tratamentos e quatro repetições, em que foram avaliadas as variedades Delta Opal (Delta and Pine), Delta Penta (Delta and Pine), BRS Cedro (EMBRAPA), IAC-25 (IAC), EPAMIG Precoce I e a progênie IAC-06/191 (IAC). As variáveis avaliadas foram: altura do primeiro ramo produtivo, altura da planta, diâmetro do caule na colheita, estande final, peso total de sementes, peso de 100 sementes, peso de um capulho, porcentagem de fibra, índice de fibra e produtividade. A análise de componentes principais possibilitou a visualização conjunta das variáveis avaliadas, sendo aquelas relacionadas à colheita mecânica e à produtividade as maiores responsáveis pela dispersão total dos dados. A linhagem BRS-Cedro demonstrou alta produtividade e aspectos positivos para a colheita mecânica, o que a coloca em destaque em relação a cada uma das outras linhagens. Já a progênie IAC-06/191 mostrou que favorecerá o bom desempenho das colhedoras, embora não tenha apresentado alta produtividade.
摘要采用多元主成分分析技术，对乌贝巴市5个棉花品种和1个新基因型(Gossypium hirsutum L. r. latifolium Hutch)的形态和农艺变量进行了研究。试验采用随机区组设计，6个处理4个重复，对品种Delta Opal (Delta and Pine)、Delta Penta (Delta and Pine)、BRS Cedro (EMBRAPA)、IAC-25 (IAC)、EPAMIG Precoce I和后代IAC-06/191 (IAC)进行了评价。评价的变量为:第一个生产分枝高、株高、收获时茎粗、终穗、种子总重、100粒种子重、一粒芽重、纤维百分比、纤维指数和生产力。主成分分析允许对评估的变量进行联合可视化，与机械收获和生产率相关的变量是数据总体分散的主要原因。BRS-Cedro菌株表现出高生产率和机械收获的积极方面，这使它在其他菌株中脱颖而出。IAC-06/191后代表明，虽然产量不高，但有利于收割机的良好性能。
{"title":"ANÁLISE DE COMPONENTES PRINCIPAIS PARA O COMPORTAMENTO MORFOLÓGICO E AGRONÔMICO DE GENÓTIPOS DE ALGODOEIRO NO MUNICÍPIO DE UBERABA – MG","authors":"Josiane Rodrigues, Francisco Humberto Henrique, S. S. Piedade, J. P. Laca-Buendía","doi":"10.28951/rbb.v38i4.458","DOIUrl":"https://doi.org/10.28951/rbb.v38i4.458","url":null,"abstract":"Com o objetivo de caracterizar cinco cultivares e um novo genótipo de algodoeiro (Gossypium hirsutum L. r. latifolium Hutch) com respeito a variáveis morfológicas e agronômicas no município de Uberaba (MG), a técnica multivariada da análise de componentes principais foi aplicada. Para a realização do experimento utilizou-se o delineamento casualizado em blocos com seis tratamentos e quatro repetições, em que foram avaliadas as variedades Delta Opal (Delta and Pine), Delta Penta (Delta and Pine), BRS Cedro (EMBRAPA), IAC-25 (IAC), EPAMIG Precoce I e a progênie IAC-06/191 (IAC). As variáveis avaliadas foram: altura do primeiro ramo produtivo, altura da planta, diâmetro do caule na colheita, estande final, peso total de sementes, peso de 100 sementes, peso de um capulho, porcentagem de fibra, índice de fibra e produtividade. A análise de componentes principais possibilitou a visualização conjunta das variáveis avaliadas, sendo aquelas relacionadas à colheita mecânica e à produtividade as maiores responsáveis pela dispersão total dos dados. A linhagem BRS-Cedro demonstrou alta produtividade e aspectos positivos para a colheita mecânica, o que a coloca em destaque em relação a cada uma das outras linhagens. Já a progênie IAC-06/191 mostrou que favorecerá o bom desempenho das colhedoras, embora não tenha apresentado alta produtividade.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89722758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Genotype x environment interaction is a key issue in plant breeding and new cultivars development. The modelling of such interactions has huge importance to decisions in plant breeding and breeding program optimization. In this context AMMI, W-AMMI and GGE models claims to address such interactions. The present paper aims to check the behaviour of such models in face of data with well behaved parametric properties. The results shows that the three models are efficient to model GxE interactions.
{"title":"COMPARISON BETWEEN AMMI, W-AMMI AND GGE METHODOLOGY IN THE CONTEXT OF SIMULATED DATA","authors":"Danilo A. Sarti, C. Dias","doi":"10.28951/RBB.V38I3.433","DOIUrl":"https://doi.org/10.28951/RBB.V38I3.433","url":null,"abstract":"Genotype x environment interaction is a key issue in plant breeding and new cultivars development. The modelling of such interactions has huge importance to decisions in plant breeding and breeding program optimization. In this context AMMI, W-AMMI and GGE models claims to address such interactions. The present paper aims to check the behaviour of such models in face of data with well behaved parametric properties. The results shows that the three models are efficient to model GxE interactions.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84679134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. C. Alvarenga, R. R. Lima, Júlio Sílvio de Sousa Bueno Filho, P. B. Rodrigues, R. R. Alvarenga, F. C. Q. Mariano
The Thomson Reuters Web of Science is a database that enables to identify patterns and trends in scientific publications, thereby enabling a broad understanding of the publications in the area of interest. An area that has been arising attention to the statistical community is the Bayesian networks, mainly due to the flexibility of modeling the data, both discrete and continuous, in terms of regression and high accuracy in the obtained results, that is, they are probabilistically promising models. The objective of this study was to identify and describe the main categories of the Web of Science that contemplate studies on Bayesian networks, check the publications over the years, identify the types of documents published, as well as the main funding agencies, the main authors, countries and languages. For the accomplishment of this study, the data of the Thomson Reuters Web of Science database were collected from 1945 to 2018. By means of search it is possible to answer several questions of interest, among them, if there are publications of Bayesian networks mainly in the animal sciences, more specifically in the formulation of diets for broilers. The results confirm that this area of knowledge is still very recent. The first publications took place in 1990 and the main publications are concentrated in computer science and no study was found in the prediction of the metabolizable energy of broilers using this methodology.
汤森路透科学网是一个数据库，可以识别科学出版物的模式和趋势，从而可以广泛了解感兴趣领域的出版物。一个引起统计界关注的领域是贝叶斯网络，主要是由于对数据建模的灵活性，无论是离散的还是连续的，在回归方面和获得的结果的高精度方面，也就是说，它们是概率上有希望的模型。本研究的目的是确定和描述考虑贝叶斯网络研究的科学网络的主要类别，检查多年来的出版物，确定发表的文件类型，以及主要资助机构，主要作者，国家和语言。为了完成本研究，我们收集了1945年至2018年汤森路透Web of Science数据库的数据。通过搜索，有可能回答几个感兴趣的问题，其中，如果有贝叶斯网络的出版物主要是在动物科学，更具体地说，在肉鸡的日粮配方。研究结果证实，这一领域的知识仍然是最近才出现的。第一批出版物于1990年发表，主要出版物集中在计算机科学领域，未发现使用该方法预测肉鸡代谢能的研究。
{"title":"Innovation in the prediction of the energy values of poultry feedstuffs","authors":"T. C. Alvarenga, R. R. Lima, Júlio Sílvio de Sousa Bueno Filho, P. B. Rodrigues, R. R. Alvarenga, F. C. Q. Mariano","doi":"10.28951/RBB.V38I3.429","DOIUrl":"https://doi.org/10.28951/RBB.V38I3.429","url":null,"abstract":"The Thomson Reuters Web of Science is a database that enables to identify patterns and trends in scientific publications, thereby enabling a broad understanding of the publications in the area of interest. An area that has been arising attention to the statistical community is the Bayesian networks, mainly due to the flexibility of modeling the data, both discrete and continuous, in terms of regression and high accuracy in the obtained results, that is, they are probabilistically promising models. The objective of this study was to identify and describe the main categories of the Web of Science that contemplate studies on Bayesian networks, check the publications over the years, identify the types of documents published, as well as the main funding agencies, the main authors, countries and languages. For the accomplishment of this study, the data of the Thomson Reuters Web of Science database were collected from 1945 to 2018. By means of search it is possible to answer several questions of interest, among them, if there are publications of Bayesian networks mainly in the animal sciences, more specifically in the formulation of diets for broilers. The results confirm that this area of knowledge is still very recent. The first publications took place in 1990 and the main publications are concentrated in computer science and no study was found in the prediction of the metabolizable energy of broilers using this methodology.","PeriodicalId":36293,"journal":{"name":"Revista Brasileira de Biometria","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82144682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：