Innovation in the prediction of the energy values of poultry feedstuffs

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.