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Currently, the investment in genetic improvement and the price of future sires are questioned, particularly in countries or breeding conditions that are not the most appropriate for maximum profit in this activity. Actually, it is that not enough work has been done with the economic concepts in genetic improvement, which are evaluated with a view to selection, particularly with the individual economic merit (IEM) of the animals.
Charfeddine (2001) pointed out that, unlike financial analyses, economic studies in breeding programs try to model the benefit obtained on a farm at the scale of an animal and not globally, and based on the characters that form the goal of the program. It seeks to assess the economic importance of each character or group of them, and not the economic situation of the enterprises. These elements are combined in an evaluation, known as individual economic merit. In accordance with the previous, this evaluation models the benefit obtained at the scale of an animal, which is expressed in its breeding values, and not of the joint exploitation, depending on the objective of the genetic improvement program.
According to Yánez (2018), models that allow evaluating the effect of the genetic improvement of the characteristics on the benefit function must be designed, in order to identify them and direct the selection pressure towards them. Seno et al. (2012) showed the economic importance of carrying out genetic improvement study on buffaloes under different improvement strategies and indicated their genetic and economic consequences. In Cuba there are not studies on this topic. However, in an article by Cino (2019), the impact of economic losses due to delay in the main individual economic indicators is studied, at the incorporation age and first calving, through the use of cost sheets in cattle.
Although there is a buffalo genetic improvement program in Cuba (Mitat et al. 2010), the current price of a future sire is not in accordance with its breeding value (BV). These animals are not sold at prices according with their net merit, which depends on various elements. The potential genetic quality is, possibly, the most important, and is determined by its BV, expressed by an aggregate of genotypes in a selection index that weights the relative economic interest of several traits, instead of its meat value according to its live weight (LW).
In this study, the economic analysis is aimed at the stated objectives. It was carried out in very close to real conditions, although it is considered that these conditions and, in particular, the prices may vary regularly. For these reasons, its execution is aimed at providing a procedure that serves as a basis for future studies that are carried out under even more exact conditions than those considered in this study. The results of this study may serve as a reference, since in Cuba there are no records that link genetic and economic work in genetic evaluations, and their consideration in the establishment of prices.
Materials and Methods
A database was created from the information collected in the performance testing of grazing male buffaloes, initiated between 2011 and 2018, with a total of 241 individuals, from Los Naranjos Genetic Livestock Enterprise, in Cuba. The LW was recorded at weaning at 8 months and at the end, according to the performance testing carried out up to 18 months. The base file that was created was enriched with the BV, the individual selection indices, calculated from the estimated parameters, and the individual economic benefits, respectively.
Statistical analysis. The breeding values of LW at weaning and the final LW with their precision were estimated using a multi-trait model developed with the Proc IML (Interactive Matrix Language of the SAS 2013), which considered a parentage matrix (a total of 250 male and female animals) and the standardized selection indices, which combine BV in an aggregate genotype of 241 animals tested. The standardized selection index represented, according to Hazel (1943), the sum of each of the breeding values, each weighted by its relative economic value. The vector of relative economic values (VER) was estimated by multiple regressions between economic benefits and breeding values.
The processing of the rest of the information in the file was carried out in SAS (2013), according to the Proc Mean procedures, and from the indicators obtained in the cost sheets, as well as in the simple and multiple regressions, obtained through Proc GLM between the individual benefits or the standardized selection index with the breeding values of the analyzed variables. The multi- trait program and index were compiled expressly for this study. Precision was also obtained, which consisted of the correlation between the actual and estimated breeding values, through the index that represents the square root of reliability or R2.
Economic analysis. The benefits were calculated from a balance of the enterprise's annual average expenses and income in the activity of grazing performance testing, during the evaluated period of 8 years. Two analyzes were carried out with two sales prices of the final product (11.20 and 6.40 cuban pesos/kg of live weight of the steers tested), since it was considered that there could be a fluctuation in them, according to Anon (2015). From the benefits, the IEM in cuban pesos/kg were calculated, considering that the individual production values are a multiple linear function of the BV of LW at weaning (BvWW) and the final LW (BvfinalLW), according to the sale price of kg of final LW. In addition, it was taken into account that these benefits represented 52.50 or 38.14 % respectively (methods 1 and 2), or the standardized selection index (method 3), which combined both BV. In methods 2 and 3, fits were made to take into account the precision of the estimation of BV or the selection index. The possible sale prices were calculated from the prices contributed by the LW obtained individually, plus those that would be obtained by the genetic contribution derived from the differences between the IEM maximum and minimum (method 1) or of each individual (methods 2 and 3).
In both cases, the following expenses per animal (cuban pesos) were taken, which considered cost elements: fixed expenses (facilities for grazing fencing) and variables (transport, machinery and fuel, salaries and veterinarians, which were the same for all). Meanwhile, the purchase of animals that started the test, the forage intake and the food and mineral supplement, were individually analyzed according to season of the year under test. The indirect expenses were obtained as an estimate of 10 % of direct expenses. The incomes were estimated based on live weights, produced in accordance with existing prices and regulations in this regard. With these values, the individual benefits per unit of breeding value were obtained for both prices, referring to the obtained LW.
Results and Discussion
Table 1 shows the results of the cost sheets with the two prices. As expected, the benefits are higher when prices per kilogram of LW are higher. The highest variation in the production value is shown, although profits had the highest variation coefficient, if these variation is analyzed based on the mean.
Table 1 Statisticians of individual values for the calculation of production benefit, in the performance testing carried out in six years of execution, CUP
| Production value | Purchase of animals | Forage supply | Mineral intake | Supplementation | Indirect expenses | Benefit | |
|---|---|---|---|---|---|---|---|
| 3546.87 | 650.34 | 580.84 | 9.83 | 94.41 | 139.76 | 1862.19 | |
| 2723.49 | 650.34 | 580.84 | 9.83 | 94.41 | 139.76 | 1038.81 | |
| 350.39 | 45.77 | 44.34 | 0.84 | 8.08 | 8.12 | 250.96 | |
| 9.88 | 7.04 | 7.68 | 8.55 | 8.56 | 5.81 | 12.90 | |
In both cases, the following expenses per animal (cuban pesos) were taken, considered similar for the two valued prices: facilities (113.92), transportation and fuel (9.60), salaries (5.98) and veterinarians (80.00).
Table 2 shows the value of the estimates of the multiple partial regressions or VER, obtained from the benefits shown in the previous table and the BV for the weaning weight (BvWW) and the final weight, at 18 months of age (BvfinalLW). These values are accompanied by their standard errors and the probability of their significance, which are used as a guide to know about their precision; but, above all, to assess the relative importance of including them or not, in the selection indices, assigning relative importance of 1 to the lowest value and the others referred to this These values correspond to the VER used in the calculation of the standardized selection indices (Stind), which were used later (method 3).
Table 2 Relative economic value, based on the benefit per animal of indicators that influenced on growth up to 18 months of age, cuban pesos/kg
| Estimate (VER) | SE± | P value | |
|---|---|---|---|
| 1895.68 (3.20) 1072.61 (2.23) |
9.21 6.86 |
<.0001 <.0001 |
|
| -859.91 (-1.00) -871.45 (-1.00) |
161.13 120.08 |
<.0001 <.0001 |
|
| 3083.03(4.59) 2265.90(3.60) |
111.10 82.80 |
<.0001 <.0001 |
Price kg LW=11.20 cuban pesos (top line)
Price kg LW = 6.40 cuban pesos (low line)
It is difficult to compare these VER with others, since until now they have not been calculated in animal production in Cuba, despite the use of some more elementary selection indices in sheep (Ramírez et al. 2018) and pigs (IIP 2015). While, those from other countries depend on different economic conditions, in terms of prices and management and feeding systems used in each of them (Shook 2006), as well as the different types of traits considered and animal species. In buffalo they have not been determined, until now, in growth traits in any country.
Figures 1 and 2 show that animals with better indicators in their standardized indices provide higher economic benefits, which is obtained with high (R2=0.50) reliability (Mrode and Thompson 2005), due to the index used with these traits. This reliability should not be confused with the determination coefficient of the linear fit of the regression of benefits and individual BV, which is also high (0.79-0.85). The above would justify the selection, since according to these results a better performance in the offspring could be expected. Bolivar et al. (2012) also showed in a buffalo population in Colombia the possibility of selection for these indicators, but it was based only on the heritability values reached for these characteristics. There was no information on the economic elements that were taken into account or on how to incorporate them into an index.
BenefitFigure 1 Benefit regression to 11.20 cuban pesos/ kg LW with the standardized selection index
Based on these results, the use of methods that would allow proposing steers prices that were based, in addition to their live weight, on their genetic potential or on a mechanism such as the one proposed in this study would be justified. The IEM could be used, since it expresses the value of an individual, based on the relation between individual benefits and breeding values or their combination in an integral index in cuban pesos. This indicator takes into account the precision of the evaluations or of the index used (two traits, but could integrate more). As it happens with the Net Merit, in the United States; the Total Economic Value, in Canada; the Durable Performance Sum, in the Netherlands; or the global economic merit index, in Spain, which continued with assessments of individual economic merit for different traits (Charfeddine 2001).
In accordance with the previous considerations, the following methods that relate the IEM with the breeding values or the standardized index that combined them were evaluated:
Method 1. IEM and proposal of individual prices of steers, with the use of multiple regression of benefits with breeding values and the difference in benefit/kg of LW between the best and worst individual with two prices per kg of LW.
Method 2. IEM and proposal of individual prices of steers, with the use of the multiple regression equations of the benefits and the BV with the precision and two prices of the kg of LW.
Method 3. IEM and proposal of individual prices of steers through the application of the regression between the profit and the selection index with two prices per kg of LW.
where:
IEM: |
individual economic merit |
BvWW: |
Breeding value of weaning weight |
BvfinalW: |
Breeding value of the final weight |
Final LW: |
Final live weight |
Stind: |
Selection index that combines weaning weight and standardized final LW |
2000/1000: |
Constants that correspond to the approximate Y-axis mean value of profits plotted against BV or indices |
0.25 o R2: |
Precision of the estimation of the breeding values or the selection index (methods 2 and 3). Correlation between the real breeding value and the one estimated by the index. |
Individual precision can be used, when it is different for each individual. That is, when the individual breeding values have a different value, depending on the number of relatives that are considered to estimate their BV.
Various proposals have been made for genetic improvement strategies for the sustainable management of animal genetic resources, according to the FAO (2010). In livestock, efforts have been directed at meat production. It have been developed studies aimed at taking into account economic objectives (Tanaca et al. 2012 and Laske et al. 2012). The prevailing concepts are directed to the use of selection indices that emphasize the total economic merit (TEM), where the genetic parameters of important traits are combined with their net economic values. As Shook (2006) confirms, it is not necessary to use the real economic value, but rather the relative value between the considered characters. This author specifies, on the other hand, that the TEM can be measured in different ways: in terms of profit per month of herd life, lifetime profit, profit during the productive life, economic efficiency (income/costs) or efficiency (costs/incomes). However, it cautions that differences may exist as a result of different markets, production systems, food supply and cost, data availability, and industry objectives.
As it was showed it is necessary to specify more in the individual economic benefits, when selection is practiced, and establish prices in accordance with the genetic potential of future breeders. With the results obtained in the IEM, evaluations can be obtained in which the aspect of individual benefit is emphasized and, in addition, individual price proposals could be made. These proposals should always be based on the new prices that are established, as they regularly vary. With the mentioned, a price would be obtained to which only new ones would have to be added, for subsequent activities with the steers, and that refer to semen quality, reproductive deficiencies, molecular characters incorporated into the evaluation, conformation or availability of additional progeny test information, if it exits. Only with this procedure or a similar one prices more in line with the genetic quality of future stallions and with the economic elements considered in their evaluations could be achieved.
