Economic values of Begait cattle breeding-objective traits under low and medium input production systems in northern Ethiopia

Gebretnsae Mezgebe, Solomon Gizaw¹ and Mengistu Urge²

Department of Animal Sciences, Asosa University, P O Box 18, Asosa, Ethiopia
gebretn12@gmail.com
¹ International Livestock Research Institute, P O Box 5689, Addis Ababa, Ethiopia
² Department of Animal and Range Sciences, Haramaya University, P O Box 138, Dire Dawa, Ethiopia

Abstract

The study was conducted to estimate the economic values (EV) of Begait cattle breeding-objective traits and their effects on the returns to investment in breeding programs using bio-economic model. Production systems were described according to their level of input and sale age, namely, low input herd management (LIHM) and medium input herd management (MIHM) based on fixed herd size for genetic improvement of multiple traits.

Results showed that all considered traits have positive economic values across production systems except pre weaning daily body weight gain (PrDG). However, production systems had significant influence on the magnitude of EV of traits. The MIHM was superior by 100 to 9% to the LIHM system. Regardless of the two production systems, calving interval (CI) had the highest EV followed by dressing percentage (DP) and mature weight (MWT). Although, the overall change of beef trait EV influenced the marginal profit through price and production variable changes at constant MY, the more sensitive change was observed with the changes of MY EV. Traits of milk yield had 1 to 12% increment on profit with 1 to10% improvement in its EV by rising milk price, reduced weaning and reduced culling rates. However, beef traits only made 5.1×10^-7 to 2.3×10 ^-6% raises on profits with 18 to 50% increment in its EV by beef price increment and reduced age at first calving. The higher increments of profit parallel to the EV of milk production trait and mostly simultaneous improvements on CI have a great indication to give priorities on milk yield traits than beef traits in any Begait cattle improvement program. Therefore, improving milk production traits and fecundity traits simultaneously with their market outlet is better to increase the profitability of farmers and sustains the valuable breed in their habitat.

Keywords: beef traits, bio-economic model, milk yield, profit

Introduction

Animal improvement aims to increase the frequency of favorable gene combinations in economically important traits for a given production system and, thereby, increase profitability (Smith 1983). To maximize profit and to produce the desired products for future economic and social circumstances, selection must be directed towards appropriate breeding objectives (Groen et al 2000; Wolfova et al 2007). Since, traits considered in the breeding objective are the basis for the formulation of a profit function from which economic values are derived (Wolf et al., 2011). Breeding objective is described by a profit function that takes genetic values as input and produces profit as outcome (Charfeddine 2000). Profit is a function of income and costs generated by each animal category composing the herd (Wolf et al 2011). This profit may be a bio-economic model of the farm, and then the traits in the profit function should be related as directly as possible to all sources of income and costs (Charfeddine 2000; Bittencourt et al 2006). The economic importance of biological traits to be included in a breeding objective is assessed by their economic values, defined as the expected increase in herd annual profit resulting from a unit increase in a trait due to selection (Jorge-Júnior et al 2007).

In the study area, there was no research work for defining breeding objective of cattle or estimation of their economic traits. Thus, investigating insight information for economically important traits of Begait cattle using different approaches is crucial, especially in designing breeding strategies for the first time to increase the accuracy and acceptance of the identified breeding objectives by farmers. Nielsen et al (2014) stated that defining breeding objectives by combined bio-economic model with preference-based method may increase farmer’s acceptance on the breeding objectives. Duguma et al (2010) confirmed that defining breeding objectives using combination of methods can be precisely captured the breeding objective traits of farmers than single method. Therefore, this study was designed to identify breeding objectives of Begait cattle using bio-economic model under low and medium input farming systems in northern Ethiopia.

Material and methods

Description of Begait Cattle Production System

Characterization of production system of Begait cattle was obtained from the analysis results of well designed structured questioner and repeated data analysis from extensive and intensive farming system, respectively (Gebretnsae et al 2017a, 2017b) in the lowlands of western Tigray regional state, northern Ethiopia were Begait cattle reared dominantly.

Most of Begait cattle herds are kept in mixed crop livestock production systems with little or no supplementary feeding (Gebretnsa et al 2017a). There is no defined breeding season and the bulls remain with the cows and heifers for five to nine years. Calves are weaned between seven and ten months of age, while selling of young bulls done mostly at three years age. However, there are few farmers who practice concentrate supplementation, especially for dairy cows. There is also private indoor enterprise farms, like Hiwet Agricultural Mechanized livestock integrated production system that mostly depend on their crop by products with limited amount (1-3kg) of concentrate supplementation (Gebretnsae et al 2017b) and experimental farms including governmental and non-Governmental ranches. Besides there is a high initiation by the Government to transfer the traditional farming system to modernized farming system through establishing processing plant to expand the beef, milk and skin products for export markets as well as processing of cattle by-products like bone meal and blood meal. There are also planning projects for genetic improvements, disease controlling and feed improvement processes. Therefore, in this study breeding objectives were defined based on the inputs used by farmers in the existed production systems to represent all farmers that used crop livestock mixed farming system and the indoor private farms and the few farmers that are already started confined Begait cattle production:

Low input system: roughage based dual purpose system, producing 36-month young bulls and heifers finished on roughage without supplementation and milk yield being an important trait in the production system; and

Medium input system: roughage supplemented with 3 kg concentrate (4:1:1 ratio’s of wheat bran, noug seedcake and cotton seedcake, respectively) based dual purpose system, producing 24-month young bulls and heifers and milk yield being an important trait in the production system.

Biological traits affecting profitability of Begait cattle production

The model expressed profit through grouping terms by class of cattle (bull, heifer and cow) and calculated revenue and cost per cow per year. Table 1 presents the biological traits affecting revenue and costs in all production systems. In general, the model estimated profitability as follows:

P = R- C

Where P is the profit per cow per year in Ethiopian birr (ETB), R is the revenue per cow per year (ETB) and C is the cost per cow per year (ETB).

The revenues (R) come from sold bulls, surplus heifers, culled cows and milk.

The revenues (R) per cow per year were calculated as follows:

R = {[NbCy x SWb) + (NhCy x SWh) + (CoWT_cull x SWc)]x P_lwt + (MY x P_mlik )}

Where:

N_bCY= number of young bulls attaining sale age, SW_b is the sale weight of young bulls (kg), N_hCy is the number of heifers available for selling, SW_h is the sale weight of heifers (kg), CoWT_cull is the cow weight available for culling (kg), P _lwt is the price per kg of live weight (ETB) and MY = milk yield per cow per year (kg); and P_mlik = price per kg milk (ETB).

The costs (C) were derived from the following equation:

C= [(C_feed-calve + C_{feed for 24 or 36 months bull and surplus heifer}+ C _{feed for 593 or 995 days-AFC}+ 365xC_feed-cow + C_health-calve + C_{health-B and SH +} C_{health-heifer} + C_health-cow
+ C_{reproduction-heifer} + C_{reproduction-cow} + C _{market for beef and milk}) + C_fixed-cost]

Where: C_feed-calve = cost for feeding calve (ETB); C _{feed for 24 or 36 months} = cost for feeding bulls (B) and surplus heifer (SH) from weaned to 24 month sale age for medium input or 36 month for low input (ETB); C_{feed for 863 or 1265 days-AFC} = cost for feeding heifer from weaned to 863 days age at first calving for medium input or 1265 days for low input (ETB); C_feed-cow = cost for feeding cows (ETB); C_health-calve = calve health cost (ETB); C_{health-B and SH} = B and SH health cost (ETB); C_{health-heifer} = heifer health cost (ETB); C_health-cow = cow health cost (ETB); C_{reproduction-heifer} = heifer reproduction cost (ETB); C_{reproduction-cow} = cow reproduction cost (ETB); C _{market for beef and milk} = beef marketing cost per animal and milk marketing cost per day (ETB) and C_fixed-cost = fixed cost including labor and expert that involved in each category of cattle (ETB).

Costs were calculated separately for feeding, health, reproduction, marketing and fixed costs for 4 groups of animals (calve, bull, heifer and cow) appropriately. Feeding costs were calculated on basis of daily net energy and protein requirements of maintenance, growth, lactation and pregnancy for the different categories. Health costs included veterinary costs on the basis of head/year. Reproduction costs were calculated using the following equation:

Annual ownership cost (purchase cost - salvage value)/year of service + annual maintenance cost (feed, health, and labor costs) + risk of bull loss (0.2[(purchase cost + salvage value)/2] and then divided by forty considering 1:40 bull to cow ratio.

Figure 1. Composition of Begait herd based on a constant number of N cows joined to the bulls

Derivation of economic values

To evaluate differences between individuals of economic importance based on profit, expressing profit as a function of the component traits are required (Weller, 2000). Economic values were estimated for pre weaning daily body weight gain (PrDG), post weaning daily body weight gain, (PsDG), cow mature weight (MWT), dressing percentage (DP), milk yield (MY), and calving interval (CI). Economic values were calculated based on fixed herd size for both production systems using the following equation.

Where:

EV= the economic value of the trait per unit change;

ΔR = the marginal change in revenues after 1% increase in the trait of interest;

ΔC = the marginal change in costs after 1% increase in the trait of interest;

ΔT = the marginal change in a trait after 1% increase in the trait of interest

Discounting of economic values

All breeding objective traits cannot be expressed at the same time or with the same frequency (Newman et al 1992). This may be accounted for deriving economic values by discounting for both frequency and time lag (Kluyts et al 2003). Discounted expressions can be calculated with different programs, however, gene flow techniques of McClintock and Cunningham (1974) was used in the present study. The gene flow method accounts for the delay between the birth of the animal and the first time of expression of the improvement and additionally for the delay between the joining and birth of the animal (Barwick and Graser 1997). The number of discounted expressions of a trait is a function of the number of progeny or later descendants of the animal in question and the annual discount factor (Kluyts et al 2003). The discount factor accounts for the fact that economic benefit at time t is more valuable than at time t + 1. Therefore, traits expressed sooner after selection should receive more emphasis.

Sensitivity of economic values of traits to price and production variable changes

To make a start in breeding goal definition sensitivity analysis is very useful for searching the major factors that determine the results of the model and then select the relatively robust to the assumptions on market prices and production levels before applying results (Groen 2000). Thus, additional analysis was performed through changing the production variables and prices, such as alternative milk price, beef price, feed price, and production variables (weaning rate, culling rate and age at first calving). Changes of (±) 10% with respect of the original values were considered, one aspect was changed at a time, while keeping all other parameters constant.

Results

Derivation of economic values of breeding objective traits

Economic values per unit increase in genetic merit of traits under fixed herd size for each production system are presented in Table 3. Except pre weaning daily body weight gain (PrDG) all economic values of traits were positive across production systems. However, production systems had significant influence on the amounts of economic values. The medium-input herd management was superior by 100 to 9% than low-input herd management (Table 3). Regardless of the two production systems, calving interval (CI) had highest economic value followed by dressing percentage (DP) and MWT in that order across production systems.

Discounting of economic values

Economic values were estimated and discounted for both production systems. Table 4 presents the discounted economic values for all studied traits.

Sensitivity of economic values to price and production variable changes

Because genetic responses are evaluated with respect to economic profit, the profit and economic values of traits after changing the price and production variables by ±10% for low and medium input production systems were calculated and presented in Tables 5 and 6, respectively. The economic values of milk yield (MY) was significantly raised with increased milk price and reduced feed price, reduced weaning rate, and reduced culling rate in all studied production systems. Similarly, the economic values of CI was raised on average by 2 to 9% in similar trend with MY except in the production variable of weaning rate, which is influenced to rise by 24% and to reduce by 41% for increased and reduced levels, respectively but inversely to MY. The economic values of post weaning daily body weight gain (PsDG), MWT and DP were also increased with increased beef price, reduced feed price, increased weaning rate and increased calling rate. However, PrDG was the only raised economic value with reduced age at first calving (AFC) and mostly show similar trends with milk yield increments.

Although, the overall change of beef trait (PrDG, PsDG, MWT and DP) economic values influenced the marginal profit through price and production variable changes, the more sensitive change was observed with the changes of MY economic values (Tables 5 and 6). Traits of milk yield had 1 to 12% increment on profit with 1 to10% improvement in its EV through the rise of milk price, reduced weaning and reduced culling rates. However, beef traits only made 5.1×10^-7 to 2.3×10^-6% raises on profits with 18 to 50% increment in its EV by beef price increment and reduced age at first calving. Conversely, in increased weaning and increased culling rates, the economic values of PsDG, MWT and DP were raised by 11.3 and 11.5% and 8.3 and 14.4% while the profit is reduced by 4 and 5.6% and 1 and 1.1% in low and medium input production systems, correspondingly.

Discussion

Economic values of Begait cattle breeding objective traits

The economic value of a trait represents the change in profit per unit product as a result of one unit change in the genetic merit of the trait considered (Groen et al 1996). The observed positive economic values of Begait cattle breeding objective traits except PrGD in the studied production systems indicated that a unit increase in genetic merit of these traits had greater influence on revenues than costs. Groen (2000) confirmed that if the economic value of the trait is positive, under a fixed herd size, a higher level of outputs per animal by genetic improvement is expected to maximize the overall profit.

The negative economic values of PrDG across production systems may be due to the higher maternal influence on calve growth by milk production and mothering ability, especially in herds that use calve suckling programme. Evidence has been found that maternal effects can reduce the expected response to selection for growth traits, especially pre-weaning growth rate. Meyer (1992) suggested that early growth rate of cattle, particularly till weaning, are determined not only by its own genetic potential but also by the maternal environment. Cantet (1984), Haile-Mariam and Kassa-Mersha (1995) and Wasike et al (2009) also estimated -0.60 to -0.75, −0.33 to −0.68, −0.14 to −0.58 negative additive genetic correlations between direct additive effects and maternal effects on weaning weight, respectively for Herford cattle, Ethiopian Boran cattle and Kenyan Boran cattle. Thus, omission of PrDG in the selection criteria for long term genetic improvements programme may be important but it may be crucial in commercial farms that are targeted to sale calves at their weaning age.

The economic values of breeding objective traits in low and medium input production systems possessed the same trend from the highest values of CI to the lowest value of PrDG. This is confirmed to the former results of choice experiment (homogenous trait preference with highest value of CI across production systems) (Gebretnsae et al 2017c). This implies that developing the same breeding objective traits for Begait cattle can be addressed both small holder and commercial farmers in the studied production systems.

Sensitivity of economic values to price and production variable changes

The impacts of price and production variable changes on economic values of studied traits and their profit are different among breeding objective traits i.e. some traits have observed with proportional influences on the profit as their magnitude of changes in their economic values, while others have minimal change on the profit with similar change in their economic values.

In multiple trait breeding objectives, traits should be included according to their economic importance under future conditions of production (Fewson 1993; Marshall 2006). Weller (2000) also confirmed that economic values of breeding objectives should be computed through marginal profit criteria that will result in proportionate economic values for all traits under selection. In the current study, the higher profit increment through raising milk price and reduced weaning and reduced culling rates and mostly parallel improvements on CI have a great indication to give priorities on milk yield traits than beef traits in any Begait cattle improvement program. However, the real situation is focused on promoting beef traits rather than milk production. Gebretnsae et al (2017a) confirmed that farmers of Begait cattle have been given due attention for increasing number of calves and their growth rate by reducing the normal frequency of milking time to once per day and limiting the number of milking teats due to shortage of demand on milk and milk products.

In tropical cattle, short lactation length is reported as a major factor for low lactation milk yield. Syrstad (1989) suggested that in tropical cattle, lactation length is not so greatly influenced by calving interval. Since, milk production often ceases several months before next calving and before the depressing effect of gestation on milk production is noticeable. Galloway (2003) confirmed that selection of cattle for genetic improvement under African conditions should be based on production performance and fecundity within African environments. Moreover, shortening the calving interval to an optimal 12months had been maximized returns on production by increasing the number of peak lactations for a cow in its lifetime while extended calving interval results in higher levels of involuntary replacement, veterinary intervention, and reduction in annual production of milk (Safiullah et al 2001; Hare et al 2006; Ali 2011). Therefore, focusing Begait cattle selection criteria on raising milk production traits like increasing daily milk yield and LL and simultaneously reducing dry period of cows with optimum CI is crucial to increase the profitability of farmers in the studied production systems.

Conclusion

• The overall results reveled that each studied breeding objective trait has positive economic values, except PrDG.
  
  
• Increasing economic values of milk production trait has dame parallel improvements on marginal profit and mostly on CI.
  
  
• The improvements of beef trait economic values reduced the overall profit by 1 to 6%, especially in increasing weaning and increasing culling rates.
  
  
• Improving milk production traits and fecundity traits simultaneously with their market outlet is better to increase the profitability of Begait cattle farmers and sustains the valuable breed in their habitat.

References

Ali S 2011 Economic Losses Due to Delayed Conception in Dairy Animals of Small Farmers in District Gujranwala. MSc Thesis, Faisalabad University, Pakistan.

Barwick S A and Graser H 1997 Calculating and interpreting Breed object results. In: Breedobject. Training and Accreditation School Handbook. Animal Genetics and Breeding programs unit, University of New England, Armidale, NSW.

Bittencourt T C C, Lôbo R B and Bezerra L A F 2006 Selection objectives for grazing cattle production systems: economic weights [Economic values for breeding goal traits for Brazilian beef cattle production]. Brazilian Journal of Veterinary and Animal Science, 58(2): 196-204.

Cantet R J C ‎1984 Estimation of maternal effects on birth and weaning weight of Hereford cattle. MSc. thesis Montana State University, United States.

Charfeddine N 2000 Economic aspects of defining breeding objectives in selection programmes. In: D Gabiña (ed.). Analysis and definition of the objectives in genetic improvement programmes in sheep and goats. An economic approach to increase their profitability . Zaragoza : CIHEAM, 2000. p. 9-17.

Duguma G, Mirkena T, Haile A, Iñiguez L, Okeyo A M, Tibbo M, Rischkowsky B, Sölkner J and Wurzinger M 2010 Participatory approaches to investigate breeding objectives of livestock keepers. Livestock Research for Rural Development, 22(64).

Fewson D 1993 Calculation of economic weights. In Design of Livestock Breeding programs. Animal Genetics and Breeding Unit, University of New England, Armidale, NSW.

Galloway D Perera O 2003 Guidelines and recommendations for improving artificial breeding of cattle in Africa. AFRA Working Document. FAO/IAEA Publication.

Gebretnsae M, Solomon G and Mengistu U 2017a Begait cattle production systems and production performances in northern Ethiopia. Paper Submitted to International Journal of Life Science.

Gebretnsae M, Solomon G and Mengistu U 2017b Growth, Reproductive and Productive Performance of Begait Cattle under Different Herd Management Systems in Northern Ethiopia. Paper Submitted to Journal of Tropical Animal Health and production.

Gebretnsae M, Solomon G and Mengistu U2017c Identification of preferable traits for small-scale and large-scale Begait cattle farmers using choice experiment in northern Ethiopia. Paper at manuscript level.

Groen A F 2000 Breeding goal definition. Developing Breeding Strategies for Lower Input Animal Production Environments. In: S Galal, J Boyazoglu and K Hammond (Eds.). ICAR, Villa del Ragno, Via Nomentana 134, 00162 Rome, Italy.

Groen A F, Steine T, Colleau J, Pederson J, Pribyl J and Reinsch N 1997 Economic values in dairy cattle breeding, with special reference to functional traits. Annual meeting of the EAAP, 26-29 August1996, Lillehammer.

Haile-Mariam M and Kassa-Mersha H 1995 Estimates of direct and maternal (co)variance components of growth traits in Boran cattle. Journal of Animal Breeding and Genetics, 112 (1-6): 43- 52.

Hare E, Norman H D and Wright J R 2006 Trends in calving ages and calving intervals for dairy cattle breed in the United States. Journal of Dairy Science, 89: 365-370.

Jorge-Júnior J, Cardoso V L and Albuquerque L G 2007 Selection objectives and economic values in beef cattle production systems in Brazil. Brazilian Journal of Animal Science, 36(5): 1549-1558.

Kluyts J F, Neser F W C and Bradfield M J 2003 Development of breeding objectives for beef cattle breeding: Derivation of economic values. South African Journal of Animal Science, 33 (3): 142-158.

Marshall K 2006 Multiple trait selection. IAEA regional training course on selective breeding and gene technologies, Korea pp56-71.

McClintock A E and Cunningham E P 1974 Selection in dual purpose cattle populations: defining the breeding objective. Journal of Animal Production 18, 237-247.

Meyer K 1992 Variance components due to direct and maternal effects for growth traits of Australian beef cattle. Journal of Livestock Production Science, 31: 179-204.

Newman S, Morris C A, Baker R L and Nicoll G B 1992 Genetic improvement of beef cattle in New Zealand: Breeding objectives. Journal of Livestock Production Science, 32, 111-130.

Nielsen H M, Amer P R and Byrne T J 2014 Approaches to formulating practical breeding objectives for animal production systems. Acta Agricultural Scand Section A, 64(1): 2-12.

Safiullah A M, Prabaharan R and Sadasivam P 2001 Economic analysis of calving interval of Hungarian dairy cattle. Journal of Applied Animal Research, 19(2): 237-246.

Smith C 1983 Effects of changes in economic weight on the efficiency of index selection. Journal of Animal Science, 56: 1057-1064.

Syrstad O and Ruane J 1998 Prospects and strategies for genetic improvement of the dairy potential of tropical cattle by selection. Tropical Animal Health and Production, 30, 257-268.

Wasike CB, Ilatsia ED, Ojango J M K and Kahi A K 2009 Direct and maternal (co)variance components and genetic parameters for growth and reproductive traits in the Boran cattle in Kenya. Tropical Animal Health and Production, 41 (5): 741–748.

Weller J 2000 Economic evaluation of straight and cross-breeding programmes. Developing Breeding Strategies for Lower Input Animal Production Environments. In: S Galal, J Boyazoglu and K Hammond (Eds.). ICAR, Technical Series No. 3, Rome, Italy.

Wolf J, Wolfová M, Krupová Z and Krupa E 2011 User’s Manual for the Program ECOWEIGHT (C programs for calculating economic weights in livestock), Version 5.1.1. Part 2: Program EWSH1 for Sheep, Version 1.1.6.

Wolfova´ M, Wolf J, Kvapilik J and Kica J 2007 Selection for Profit in Cattle: I. Economic Weights for Purebred Dairy Cattle in the C

Received 3 November 2017; Accepted 17 December 2017; Published 1 January 2018

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