Competitiveness levels in cattle herd farms

Marques, Pedro Rocha; Barcellos, Júlio Otávio Jardim; Dill, Matheus Dhein; Dias, Eduardo; Azevedo, Eduardo Vaz Torres; Lampert, V. do N.; McManus, Concepta

doi:10.1590/0103-8478cr20140401

Cited by 8 publications

(6 citation statements)

References 11 publications

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“…Weaning rates lower than 70% indicate that the farm has management problems that affect the profitability of the business (Canellas et al, 2010;. It has been shown that beef cattle farmers in RS with low performance are less effective in reproductive management, zootechnic control, and economic management practices (Marques et al, 2015;Dill et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

Factors affecting adoption of economic management practices in beef cattle production in Rio Grande do Sul state, Brazil

Dill

Emvalomatis

Saatkamp

et al. 2015

Journal of Rural Studies

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Section: Resultsmentioning

confidence: 99%

Factors affecting adoption of economic management practices in beef cattle production in Rio Grande do Sul state, Brazil

Dill

Emvalomatis

Saatkamp

et al. 2015

Journal of Rural Studies

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“…Perhaps the lack of knowledge about the integral response of biological and economic systems is limiting the adoption of technologies. In this case, it is fundamental to understand the principles that govern the functioning of the system productivity resulting from changes in animal production indicators (Marques et al, 2015). An example of this customization of impacts and costs can be verified by analyzing the advantages and disadvantages of mating heifers at earlier ages.…”

Section: Discussionmentioning

confidence: 99%

Modelling beef cattle production systems from the Pampas in Brazil to assess intensification options

Lampert

Canozzi

McManus

et al. 2020

Sci. agric. (Piracicaba, Braz.)

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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.

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“…Numerous studies have emerged in recent years on various aspects of the competitiveness of farms of different (mostly small) sizes (Alam et al, 2020;Berti and Mulligan, 2016;Latruffe, 2010Latruffe, , 2013Lundy, et al, 2010;Mmari, 2015;Ngenoh et al, 2019;Orłowska, 2019), in selected countries (Alam et al, 2020;Benson, 2007;Jansik and Irz, 2015;Hadley, 2006;Popovic, Knezevic and Tosin, 2009 ;Kleinhanss, 2020;Krisciukaitiene, Melnikiene, and Galnaityte, 2020;Nivievskyi, et al, 2011;Nowak, 2016;Mykhailova et al, 2018;Orłowska, 2019;Ziętara and Adamski, 2018), subsectors (Alam et al , 2020;Benson, 2007;FAO, 2010;Jansik and Irz, 2015;Kleinhanss, 2020;Marques et al, 2011;Marques, 2015;Nivievskyi, et al, 2011;Ngenoh et al, 2019;Oktariani, Daryanto, and Fahmi, 2016;Ziętara and Adamski, 2018), farming systems, such as organic, vertically integrated, greenhouse, etc. (Marques, 2015;Orłowska, 2019), regions (Marques et al, 2011;Nowak, 2016) and chain producers (Lundy, et al, 2010;Ngenoh et al, 2019), comparative studies in different EU countries (FAO, 2010;Jansik and Irz, 2015;…”

Section: Introductionmentioning

confidence: 99%

Assessment of the competitiveness of agricultural holdings in Bulgaria

Bachev

Koteva

2021

SSRN Journal

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The problem of determining the competitiveness of various economic organizations is among the most topical academic and practical issues from the emergence of economics science to the present day. It is particularly important for the agricultural sector, which is characterized by many participants, high specialization and exchange, strong competition at local, national and international level, highly integrated food and supply chains, market segmentation, unequal public support, strong state regulation, processing and trade and professional organizations, strong consumer pressure for quality, eco-behavior, etc., presence of underdeveloped and non-competitive "markets", etc. Nevertheless, despite its importance and continouing debates, there is still no consensus on what is the competitiveness of farms, how to measure the competitiveness of different organizations in agriculture, what is the absolute and comparative competitiveness of different types of farms, which are the critical factors for increasing the competitiveness at the current stage of development, etc. This paper tries to fill the existing gap by applying a holistic approach and assessing the competitiveness of Bulgarian farms as a whole and with different specializations. The multi-criteria assessment found that the level of competitiveness of farms in the country is at a good level, with low adaptive potential and economic efficiency to the greatest extent contributing to lower competitiveness. More than a third of all agricultural holdings have a low level of competitiveness. The most competitive are the farms specialised in the beekeeping, followed by field crops, mixed animal husbandry and mixed crops production, and the lowest for farms in grazing livestock. Most significant factors for increasing the competitiveness of Bulgarian farms are market conditions (supply and demand, prices, competition), direct government subsidies, access to knowledge, advice and counseling, participation in government support programs, available information , financial opportunities, and opportunities for benefits in the near future. Proposed approach should be improved and applied more widely and periodically, increasing accuracy and representativeness. The latter requires close cooperation with producer organizations, advisory service and other stakeholders, and improvement of the agricultural information collection system in the country.

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Competitiveness levels in cattle herd farms

Cited by 8 publications

References 11 publications

Factors affecting adoption of economic management practices in beef cattle production in Rio Grande do Sul state, Brazil

Factors affecting adoption of economic management practices in beef cattle production in Rio Grande do Sul state, Brazil

Modelling beef cattle production systems from the Pampas in Brazil to assess intensification options

Assessment of the competitiveness of agricultural holdings in Bulgaria

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