Randomized block design in agricultural Science research: An integrative literature review

• Autor(a) principal: Moraes, Wendel dos Santos
• Data de Publicação: 2021
• Outros Autores: Barros, Octávio Henrique Bernardes, Freitas, Hellen Cristina de, Carneiro, Ana Clara, Oliveira, Gabriella Rayssa Antunes da Silva, Luciano, Daniela de Oliveira, Portella, Augustus Caeser Franke
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/17616
• topic: Factors; Analyze; Experimental units.; Factores; Analizar; Unidades experimentales.; Fatores; Análise; Unidades experimentais.

In the development process of research in agricultural sciences, there are different factors that influence crop management. The randomized block design (DBC) is a technique used to analyze experiments with a set of non-analogous factors in a given location and their impact on the experiment. Treatments are randomized over the experimental units within each block, so this method is used to check for interference between treatments and between blocks. Thus, the present work aimed to carry out an integrative literature review on the applications of the DBC in research in the field of agricultural sciences. The methodology applied was an integrative literature review. The choice of articles to compose the sample was made through journals published from 2010 to 2020, from the Scielo, Google Scholar, and Science Direct databases. And later, the findings were separated into branches of the agricultural sciences area according to the CAPES classification. 41 studies that met the established inclusion criteria were obtained. Of the works acquired, 22 (53.6%) from the Scielo database, 19 (46.3%) from Google Scholar, and 1 (2.4%) from Science Direct. 23 (56.0%) fall into the area of ​​Agronomy, and 18 (43.9%) fall into the area of ​​Forest Resources and Forest Engineering. The results of this study show that the DBC has contributed to the advancement of different fields in the areas of Agrarian Sciences, enabling a better tabulation of acquired data, and facilitating the analysis of experimental units.