Economic values for index improvement of dual-purpose Simmental cattle
Introduction
Greater economic efficiency comes about from genetic improvement, which is most effective when selection is based on net genetic merit of selection candidates accounting for merit in all the economically relevant traits. Selection indexes are considered the most efficient methodology to estimate net merit due to its incorporation of economic values (EVs) for the breeding goal (Smith, 1937; Hazel, 1943). Those EVs can be defined through profit functions, partial budgets or bio-economic models and their use in cattle has been widely reported (Wolfová et al., 2005; Pravia et al., 2014; Costa et al., 2017; Fernandes et al., 2018).
Breeding goals should account for inputs, such as feed, husbandry and marketing costs, as well as for outputs, such as income from sale of products and surplus animals (Kahi and Nitter, 2004; Aby et al., 2012; Campos et al., 2013). Quantifying level of outputs is usually straightforward, but inputs are more difficult to quantify, especially if there is heterogeneity in production practices and lack of economic and productive records. Bio-economic models are a good tool for deriving EVs by taking account of the biological, economic and management variables for a specific situation (Jones et al., 2004; Wolfová et al., 2005; Ali et al., 2018). Those variables are important because they influence the relative importance of different traits that affect the profitability of commercial farms (Byrne et al., 2010).
The EVs of the selection criteria can directly affect response to selection (Hazel and Lush, 1942; Ali et al., 2019). For example, Spelman and Garrick (1997) showed that varying the EV for live weight affected the responses to selection for milk fat and protein in a selection index. In Colombia, selection indexes have been constructed weighting each trait according to its phenotypic variance or using empirical EVs (Vergara and Iriarte, 2002; Montes et al., 2008; Betancur-Zambrano et al., 2012; Agudelo-Gómez et al., 2016). Combined with selection, that approach leads to genetic changes, but may not result in genetic improvement because phenotypic variance is not the same as EV and profitability for commercial breeders could be lower than expected.
Traits to include in a selection index should be identified by their influence on animal profitability (López-Paredes et al., 2017). Golden et al. (2000) proposed deriving economic contributions only for economically relevant traits (ERT), which they defined as traits that directly affect profitability by being associated with a specific cost of production or an income stream. The weight at any age, the age at first calving, the milk yield and the calving intervals can be ERTs as they have direct effect on costs and income (Albera et al., 2004; Kluyts et al., 2007a; Byrne et al., 2016; Ochsner et al., 2017).
In Colombia, farmers benefit from income arising from the sale of milk as well as from the sale of animals for beef. In such dual-purpose systems, selection indexes should simultaneously account for the values of the genetic changes in milk, beef and reproductive traits. The aim of this study was to derive EVs through a deterministic bio-economic model in order to construct an economic selection index (ESI) for dual-purpose Simmental cattle in Colombia. The ESI considered the weight in kilograms at eight months of age (W8M), age at first calving in days (AFC), first lactation (305-days) milk yield in liters (MY), and first calving interval in days (FCI).
Section snippets
Base production system
A production system was defined as a dual-purpose enterprise comprising an average size Colombian Simmental farm of 42 milking cows. For specification of the base production system, biological input parameters (Table 1) were taken from results obtained by Amaya et al., 2019, Amaya et al., 2020 and the Colombian Simmental Breeders Association (Asosimmental). The economic information (veterinary prices, supplementary feed, pasture maintenance, beef and milk prices) was obtained from 20 farms
Results
In the base system, milking cows constituted 53.2% of the animals in the herd at any one time, replacement heifers constituted 10.1% and animals for sale (surplus bulls and heifers) formed the remaining 36.7%. The highest cost was related to feed, representing 83.3% of the total costs included in the analysis. The highest income resulted from milk production, contributing 86.1% of total income. Regarding beef production, surplus bulls-heifers and culled cows accounted for 13.1 and 0.8% of total
Economic values
Comparison of EVs is difficult between studies because biological parameters and economic information are often different according to production systems and economic circumstances. Some authors consider that comparisons through the REI can be still made (Aby et al., 2012; Pravia et al., 2014; Krupová et al., 2016; Costa et al., 2017; Fernandes et al., 2018). However, such comparisons could also be complicated because REI variation can be high depending on the number and type of traits. In this
Conclusions
The losses from ignoring reproductive traits in the selection criteria can be considerable and the phenotypic improvement of W8M could not be the best strategy to increase economic contributions for W8M and for FCI in dual-purpose Simmental cattle in Colombia. Simmental national genetic evaluation in Colombia includes W8M, AFC, MY and FCI due to the available phenotypic data. However, other traits such as milk fat and protein can be more economically important according to the current Colombian
CRediT authorship contribution statement
Alejandro Amaya: Conceptualization, Formal analysis, Software, Data curation, Methodology, Investigation, Writing - original draft. Dorian Garrick: Methodology, Formal analysis, Software, Supervision, Writing - original draft, Writing - review & editing. Rodrigo Martínez: Writing - review & editing, Data curation, Investigation, Project administration, Funding acquisition. Mario Cerón-Muñoz: Writing - review & editing, Data curation, Investigation, Project administration, Funding acquisition.
Declaration Competing Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors thank ASOSIMMENTAL, AGROSAVIA, Massey University, Universidad de Antioquia and GAMMA research group. Additionally, the first author thanks Universidad de Ciencias Aplicadas y Ambientales U.D.C.A and Colciencias (Scholarship No 727 of 2015) for financing his studies in the doctoral program in Animal Science of Universidad de Antioquia.
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