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Traditional livestock productivity is hard to estimate, since it depends on a gamut of animal production indicators that are difficult to measure for many farms. Thus, we propose an analytical method for estimating productivity and understanding the importance of animal production indicators under different full-cycle cattle production systems in Brazil. To evaluate the impact of these indicators, equations were derived from a comutational model of herd evolution for estimating the output parameters of the system as follows: productivity per hectare (PH) and offtake rate (COR), as a function of the indicators; calving rate (CR), mating age (AM), age of slaughter (AS) and stocking rate (SR). For this analysis, twenty-seven scenarios (simulation data) of low to high productivity were used, resulting from the combination of the following factors and levels: 1) calving rate of 50, 65 and 80 %; 2) mating age of heifers of one, two and three, years of age; and 3) age at slaughter of one, two and three year old steers. The scenario with the highest impact for each parameter and the indicator of highest impact for each scenario were identified for the production conditions in the region. Under most scenarios, a reduction in mating age had a greater impact on the productivity indexes compared to a reduction in slaughter age. Appropriate management of available technologies enables farmers to compare the marginal impacts of specific indicators on full-cycle production systems for beef cattle. Keywords: adoption of technology, animal production, management, stocking rate Made available in DSpace on 2019-12-17T18:08:19Z (GMT). No. of bitstreams: 1 v77n4a05SA20180263.pdf: 544104 bytes, checksum: f1a0f0cd33a1cb950ec0f788260b70ae (MD5) Previous issue date: 2020

Business Intelligence with Data Warehouse technologies are known in the literature as solutions that allow access to business data dynamically and analytical operations on them. Scientific literature lacks works that investigate the current use of these technologies in the agrarian sector, at the international level in the last 10 years. This work presents a bibliometric analysis, which was done through the ProKnow-C methodology, of the application of Business Intelligence and Data Warehouse technologies in the agrarian sector. The objective is to investigate the dissemination of such technologies in this sector in national and international scale. The main findings were the following: number of papers in last years are increasing. Majority of papers were found in the journal named Computers and Eletronics in Agriculture, with a great number of colaborations between authors of France. Few colaborations between authors from different countries were found. Sandro Bimonte was the most cited author. France and India highlight in researches approaching Data Warehouse and Business Intelligence usage in agrarian sciences. The majority of references from Bibliographic Portfolio were from 2001-2010. 66% of papers use some open source technology. Star schema is the most used modelling technique and the use of Unified Modeling Language by authors of France in agricultural Data Warehouse modelling is encouraged. The main limitations were the impossibility of free access in some databases, absence of research on proprietary solutions of technology market in the rural sector and few number of keyword searches. Made available in DSpace on 2019-01-12T23:36:17Z (GMT). No. of bitstreams: 1 Brumetal.pdf: 3940321 bytes, checksum: b55f3c0b37bd76abd3bb581d3e3daf0c (MD5) Previous issue date: 2019-01-11