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O objetivo desse estudo foi avaliar 27 cenários simulados com dados reais e auxílio de planilhas integradas do Microsoft Excel®, para sistemas a pasto de recria-engorda de bovinos. Os cenários formaram-se a partir de três níveis de intensificação (módulos de manejo): baixo (campo nativo ? CN), intermediário (CN + pastagem de inverno ? PI) e alto (CN + PI + pastagem de verão ? PV); três categorias animais: bezerro, novilho e vaca; e três arranjos comerciais conforme preços de compra/venda: alto/baixo (desfavorável), médio/médio (médio) e baixo/alto (favorável). Com preços desfavoráveis apenas o bezerro respondeu positivamente à intensificação do módulo de manejo, enquanto novilho e vaca perderam margem do módulo intermediário para o alto. A vaca apresentou margens negativas em todos os módulos de manejo. O novilho apresentou a melhor margem/área nos módulos baixo e intermediário, e o bezerro em módulo alto. Em conjuntura de preços médios, apesar de resultados agora positivos, a vaca mantém decréscimo de margem no módulo alto. O novilho apresenta ganhos crescentes à intensificação, demonstrando melhor desempenho que o bezerro em todos os módulos de manejo. Em preços favoráveis, todas as categorias apresentam aumento de margem/área à intensificação. Em módulo intermediário, a vaca apresentou a melhor margem/área entre as categorias, ao passo que em baixo e alto o novilho respondeu com a melhor margem/área. Ao avaliar a margem/cabeça/ano, em qualquer conjuntura comercial e categoria animal, o módulo alto perde competitividade em relação ao módulo intermediário. Entretanto, quando avaliada a margem/área, apenas em 3 dos 27 cenários ocorreu decréscimo da margem. Made available in DSpace on 2021-12-08T15:00:54Z (GMT). No. of bitstreams: 1 13908-Article-245693-1-10-20210914.pdf: 245096 bytes, checksum: fbfe4461719b00c075a152e25ddc96b8 (MD5) Previous issue date: 2021

O objetivo deste estudo foi realizar uma análise comparativa quando ao lucro por hectare e o risco de distintos cenários de investimentos para produção agropecuária, na região da Campanha Gaúcha, através da elaboração de um modelo de simulação probabilístico de âmbito bioeconômico e análise de risco. Made available in DSpace on 2020-12-01T09:03:38Z (GMT). No. of bitstreams: 1 Lampert-et-al.pdf: 596482 bytes, checksum: a5dcf030fc8613fc0fdb042c5ad9f159 (MD5) Previous issue date: 2020

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

The internal competitiveness of the beef cattle production systems in the Southern Region of Brazil was studied. Thirty-six beef cattle farmers of the state of Rio Grande do Sul were interviewed during the first quarter of 2010. The main indicators that affect the farm gate sector competitiveness were defined: technology, management, market relations, and institutional environment. Then, those indicators were developed into 10, 10, 4 and 7 factors respectively. They were assigned individual weights in order to calculate their competitiveness indices (CI) with specific equations. The competitiveness indices for the 4 indicators and the 31 factors were also calculated, and they ranged from unfavorable to very favorable. The Item Response Theory was employed to statistically treat the data. Data analysis also employed the Correspondence Analysis Technique (ANACOR) available in the SPSS software in its 18.0 version. The average CI of the production systems 7.27, which is considered a favorable one. The main critical competitiveness factors include the producers' organization, price formation, strategic planning and availability of technological innovations. Researches like the current one are of fundamental importance to develop strategies to be carried out by both the public and the private sectors aiming to enhance competitiveness of the beef production chain.

Movement of livestock production within a country or region has implications for genetics, adaptation, well-being, nutrition, and production logistics, particularly in continental-sized countries, such as Brazil. Cattle production in Brazil from 1977 to 2011 was spatialized, and the annual midpoint of production was calculated. Changes in the relative production and acceleration of production were calculated and spatialized using ARCGIS1. Cluster and canonical discriminant analyses were performed to further highlight differences between regions in terms of cattle production. The mean production point has moved from the Center of Minas Gerais State (in the southeast region) to the North of Goiás State (in the Midwest region). This reflects changes in environmental factors, such as pasture type, temperature and humidity. Acceleration in production in the northern region of Brazil has remained strong over the years. More recently, “traditional” cattle-rearing regions, such as the south and southeast, showed a reduction in growth rates as well as a reduction in herd size or internal migration over the period studied. These maps showed that this movement tends to be gradual, with few regions showing high acceleration or deceleration rates.