Determination of economic weights for breeding traits in indigenous Nguni cattle under in-situ conservation

Livestock Science 155 (2013) 8–16

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Determination of economic weights for breeding traits in indigenous Nguni cattle under in-situ conservation O. Tada a, V. Muchenje a,n, J. Madzimure a, K. Dzama b a b

Department of Livestock and Pasture Science, University of Fort Hare, P. Bag X1314, Alice 5700, South Africa Department of Animal Sciences, Stellenbosch University, P. Bag X1, Matieland 7602, South Africa

a r t i c l e in f o

abstract

Article history: Received 4 January 2013 Received in revised form 8 April 2013 Accepted 9 April 2013

This study was conducted to determine the economic weights of most preferred traits in young breeding Nguni bulls and first parity cows. Fifty-four farmers from low-input cattle production enterprises participated in the choice experiment. Sixteen individual animal profiles were formulated from four traits of three levels each using a fractional orthogonal design of SPSS 14.0 (2005). 120 pair-wise choices were deduced for each breeding animal class. A total of 6480 (54
120) observations were obtained for each class of the animals. Data was subjected to multinomial logit (MNL) models using econometric software NLOGIT 4.0.1 Version (2007). All computed economic values for bull traits were significant (p o 0.05). The economic weights of bull traits were poor body condition score (−0.99 7 0.095), good body condition score (0.45 7 0.073), over-conditioned (base level), low tick infestation (0.57 7 0.103), medium tick infestation (0.58 7 0.084), high tick infestation (base level), high aggression and mating behavior (4.417 0.095), average aggression and mating behavior (2.53 7 0.094), and low aggression and mating behavior (base level). The economic weights of first parity cow traits were poor body condition score (−0.06 7 0.055), good body condition score (1.08 7 0.061), over-conditioned (base level), low tick infestation (1.50 7 0.059), medium tick infestation (0.83 7 0.067), high tick infestation (base level), age at first calving of ≤27 months (2.37 7 0.068), age at first calving of 27–36 months (1.30 7 0.076), and age at first calving of 4 36 months (base level). Farmers were willing to pay R37,939 (US$4864) for a bull with high aggression and mating behavior score and R17,185 (US$2203) for a first parity cow of less than 27 months old. Enterprise ownership and demographics factors of the farmers were significant in determining economic weights within trait levels. Economic weights were high for reproductive efficiency of the breeding animals followed by the high adaptive characteristics. The choice experiment procedure can be the tool for determining importance of animal characteristics under low-input production systems. It is recommended to make use of the economic weights of preferential traits in designing selection models. & 2013 Elsevier B.V. All rights reserved.

Keywords: Choice experiment Age at first calving Aggression and mating behavior Body condition score Tick infestation

1. Introduction Diversity of an indigenous genetic resource is a key component for a low-input production system to overcome destabilizing factors of uncertainty over future

n

Corresponding author. Tel.: +27 40602 2059; fax: +27 86 628 2967. E-mail addresses: [email protected], [email protected] (V. Muchenje). 1871-1413/$ - see front matter & 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.livsci.2013.04.011

production environments such as climate change, diseases and changing market demands (Ruto et al., 2008; Kassie et al., 2010; Zander, 2011). The indigenous Nguni cattle breed in South Africa is an example of Animal Genetic Resources (AnGR) currently under in-situ conservation in the communal and small-scale farming enterprises of the Eastern Cape Province (Muchenje et al., 2008; Tada et al., 2012). The majority of the farmers in these sectors (67%) perceived the low-input in-situ conservation as profitable because the indigenous breed possesses traits of economic

O. Tada et al. / Livestock Science 155 (2013) 8–16

and socio-cultural importance (Tada et al., 2012). Informed decisions on sustainable conservation of this genetic resource could be made easier if information on the economic value of traits and breeding objectives were available. The development of breeding objectives has long involved quantification of the levels of economical benefit associated with genetic traits expressed by farmed livestock (Amer, 2007). The breeding objectives determine optimal herd size and direction of genetic changes in production traits. Thus, they considerably influence the need of economic weights of production traits in selection. The economic weights of traits for beef cattle are often disregarded under low-input production systems probably due to the difficulty of measuring and valuing them as reported by Roeleveld (1996). The development and application of adequate tools to economically characterize the traits was therefore important. A review of potential AnGR valuation methods by Roosen et al. (2005) highlighted the potential role of non-market valuation methodologies in developing countries. This follows the premise that many of the benefits derived from the existence of well adapted indigenous breeds are not transacted in any market (Ruto et al., 2008). An indirect stated preference approach, the choice experiment (CE) (Louviere et al., 2000) ,can therefore be used to investigate farmers' preferences over cattle traits in livestock selection markets. Some applications of CEs show that such methodologies reveal useful estimates of the values that are placed on the market, non-market, and potential breed attributes (Scarpa et al., 2003; Tano et al., 2003; Ruto et al., 2008). The contribution of preferred traits in the breeding objective is the basis for determination of their economic weights. The need to include economic weights of traits in a selection model for low-input animal production environments is recognized (Hazell et al., 2007; Zander, 2011). This has not yet been implemented for Nguni cattle and many other indigenous breeds in the developing countries where performance recording systems are minimal. The objective of the study was, therefore, to determine the economic weights of most preferred traits of young breeding Nguni animals by farmers in the low-input production enterprises using a CE approach. It was hypothesized that the contribution of animal traits to the market value of the breeding animal from different enterprise types and farmers of different demographic factors were the same. 2. Materials and methods 2.1. Study area The study was conducted in the Eastern Cape Province of South Africa with representative farmers (75%) from communal and small-scale Nguni cattle enterprises. The enterprises were the beneficiaries of Nguni Cattle Restoration Program that was enacted in 2004 (Raats et al., 2004). The Eastern Cape Province is the second largest Province with an area of 169,580 km², representing 13.9% of South Africa's total land mass (Acocks, 1988). The climate varies according to the distance from the Indian Ocean. The coastal areas enjoy mild

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temperate conditions ranging between 14 and 23 1C, while the inland areas experience slightly more extreme conditions with temperatures of 5–35 1C. Inland mountainous areas experience winter snows and summer rainfalls. 2.2. The rationale of choice experiment and its design Wurzinger et al. (2006) reported that choice experiments are important for identifying selection criteria in traditional production systems where literacy level is low and recording practices are not in place. The breeding goal is generally described as a linear function of traits to be improved as described by Hazel (1943); each of these traits is multiplied by its economic weight (EW) expressing the value of a unit change in the trait while keeping the other traits in the breeding goal constant. Due to the complexity and diversity of the low-input production systems, the lack of good records and good estimates of inputs and outputs, a simplified CE procedure was deemed appropriate to derive EWs of most preferred traits of young breeding Nguni cattle. Choice experiment permits the analysis of farmer's preferences in terms of the benefits that they expect to attain from different genetically determined traits. Hypothetical profiles were described in terms of trait levels. Traits were identified by farmers during a preliminary survey and these are easily recorded at farm level with minimum literacy. The three most important traits identified for, and price ranges of the young breeding Nguni, i.e. first parity cow and 2–3 year old bull, are presented in Table 1. When policy makers promote cattle with desired traits, farmers are likely to conserve the breed and at the same time generate income (Zander, 2011). With four traits of three levels each in both classes of animals, there were 64 (43) possible Nguni cattle profiles in a full factorial design. These were reduced to a manageable size of 16 profiles using a balanced orthogonal i.e. fractional factorial design (SPSS 14.0, 2005). The design ensures the identification of the main effects with a minimum number of profile combinations. A choice set with uncorrelated attributes was then generated. Descriptive cards in Xhosa (vernacular) with pictorial illustrations were used. 2.3. Data collection Data were collected in the form of an in-person survey instrument. Fifty-four respondents representing low-input Nguni cattle conservation enterprises were conveniently sampled. The criteria involved selecting a representative who is literate and willing to implement cattle recording system. Respondents were first exposed to interactive discussions on the value of animal records, traits of economic importance and recording. The demographic data of the respondents were also gathered. Age, education level, gender and ownership pattern have been identified as key demographic parameters affecting selection of animal traits and their pricing under the South African environment (Madzimure, 2011). After a cheap talk script, respondents were introduced to the type of choice task required i.e. a full set of 120 pair-wise choices from 16 individual animal profiles. The respondents were tasked to hypothetically

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Table 1 Description of variables used in the choice experiment. Attribute/Trait

Level description

Body condition score (BCS) Tick infestation (TI)

Poor (BCS 1–3); Good (BCS 4–6) and Over-conditioned (7–9) Low (visible ticks less than 10); Medium (tick count of 10 to 30) and High (tick count of more than 30)

Attributes specific to the first parity cow Age at first calving (AFC) Animal purchase price

o 27 months; 27–36 months; and 436 months R4500; R5500 and R7750 (US$577; US$705 and US$994)

Attributes specific to the young breeding bull Aggression and mating behavior (AMB) Below average; Average and Above average Animal purchase price R5250; R7500 and R9 50 (US$673; US$962 and US$1250) NB: The trait levels used as reference bases are shown in italics. Animal purchase price indicate the market price of the breeding animal, the attribute levels were based on the study by Tada et al. (2012) i.e. lower, medium and upper quartiles.

buy for breeding one of the two available animal profiles. If neither of the animal profiles was found satisfactory, the respondents could choose the ‘I prefer none’ option. Figs. 1 and 2 show the examples of the choice task used. A total of 6480 (54
120) observations were obtained from the respondents for each of the two animal breeding categories i.e. first parity Nguni cow and young breeding Nguni bull. 3. Statistical analyses The choice data were analyzed using econometric software NLOGIT 4.0.1 Version (2007). The multinomial logit (MNL) model is one of the most recognized discrete choice models (Train, 2003; Roessler et al., 2008). It assumes that each individual chooses the alternative that has the highest perceived utility. Individuals are assumed to evaluate choice alternatives on the basis of their attribute levels, finally selecting the alternative they subjectively assess to provide them with highest utility (Roessler et al., 2008). The economic weight of a trait level is represented by linear utility function. Utility is assumed to either increase or decrease according to price and animal traits, depending on how the respondent regards animal characteristics. For an individual n choosing alternative j, the indirect utility is assumed to take the following form

3.1. Part worth values of attributes as estimates of economic values Part worth values reflect the relative importance respondents put on attributes, or trade-offs they are willing to make among them. As the cost was included as an attribute in the CE, it was possible to estimate indirectly the willingness to pay (WTP) or willingness to accept compensation (WTAC) for all other attributes included in the study. The WTP for a certain attribute or attribute level indicates the price (“implicit price”) the respondent was willing to pay for a unit increase in this attribute or the compensation he/she was willing to accept for a decrease in this attribute. The ‘implicit price (W)’ or part worth is the economic value of a trait level and is calculated as follows: W ¼ −1ðβx =βprice Þ, where βx is the estimate for the attribute x from the MNL model, and βprice is the estimated price coefficient. To compare if parameter estimates of the pooled model were different across demographic factors and enterprise types, random parameter MNL models were run to obtain utility functions (economic weight estimates) for each category.

U nj ¼ αnj þ γ j Sn þ β′n xnj þ εnj

4. Results

The obtained indirect utility may vary between choice j and individuals n (the total number of individuals is n¼ 1, …, N). Indirect utility is assumed to consist of a deterministic part Unj ¼αnj+γjSn+β'nxnj and a stochastic part εnj. The deterministic component of the utility function consists of αnj which is the option specific intercept that corresponds to individual n's intrinsic preference for alternative j. The socio-economic and demographic characteristics of the individual, Sn, and the coefficient vector γj correspond to the systematic preference heterogeneity among the individuals in the sample. Altogether, three animal trait attribute coefficients are estimated and, with the price coefficient β′n1, there are four coefficients, (β′n ¼[(β′n1,…, β′n). These coefficients are assumed to be generic (i.e. the coefficients of the explanatory variables do not vary across the options). Hence, an assumption of stable preferences was made.

4.1. Economic values of trait levels in young breeding Nguni bulls The discrete choice (MNL) model used was good with a coefficient of determination of 39%. All the computed economic value estimates were significant (po0.05) with a notable insignificant difference on economic weights between low and medium tick infestation level. The economic weight for poor BCS was negative and subsequently the farmers were willing to accept compensation (WTAC) of R8494.00 (US$1088.97) for such characteristic animal. The most weighted trait level was a high AMB whereby the farmers were willing to pay (WTP) R37,939.00 (US$4863.97) for such a bull. The economic weights relative to the base levels and economic values of all bull trait levels evaluated are shown in Tables 2 and 3. On accounting for heterogeneity in mean economic weight estimates, poor

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Fig. 1. Example of the pair-wise comparison choice set used for first parity Nguni cow.

Fig. 2. Example of the pair-wise comparison choice set used for a 2–3 years old Nguni bull.

body condition score (BCS) was not significantly affected by the demographics factors of the farmers (p40.05) (Table 4). Type of enterprise had no significant influence on economic weights of BCSs and average AMB (p40.05). The low and

medium TI had significant negative economic weights in communal enterprises. A high AMB was observed to be significantly associated with positive economic weight in communal enterprises (po0.05). Highest education level

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Table 2 Estimates of economic weights and values (in Rands) of trait levels for young breeding Nguni bulls. Trait level

Economic weight 7s.e

p-value

Economic values (WTP/WTAC)

CI lower limit

CI upper limit

Poor body condition score (1–3) Good body condition score (4–6) Over body condition score (7–9) Low tick infestation Medium tick infestation High tick infestation High aggression and mating behavior Average aggression and mating behavior Low aggression and mating behavior Price Constant

−0.99 70.095 0.45 70.073 Base level 0.577 0.103 0.58 70.084 Base level 4.417 0.095 2.53 70.094 Base level −0.007 0.002 10.11 70.375

p o 0.05 p o 0.05

−8494 3849 4645 4927 5001 −9928 37,939 21,807 −59,746

−10104 2619 3225 3190 3586 −11,504 36,342 20,218 −61,339

−6885 5079 6065 6665 6415 −8352 39,535 23,397 −58,153

p o 0.05 p o 0.05 p o 0.05 p o 0.05 p o 0.05 p o 0.05

NB: economic value of trait level used as a base is zero (0). WTP—willingness to pay. WTAC—willingness to accept compensation. CI—confidence interval (95%). US$1.00¼R7.80 (South Africa Reserve Bank, 2011).

Table 3 Heterogeneity in mean variables and derived standard deviation of distributions in young breeding Nguni bulls. Trait level

Parameter: variable (base level)

Coefficient

Standard error

Significance

Poor BCS

Gender: male (female) Age:o50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

−0.07 0.05 0.07 0.11

0.127 0.141 0.166 0.100

NS NS NS NS

Good BCS

Gender: male (female) Age:o50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

0.20 −0.50 −0.06 −0.04

0.105 0.123 0.133 0.078

NS

Gender: male (female) Age:o50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

0.83 −0.72 0.40 −0.38

0.131 0.143 0.170 0.102

nn

Gender: male (female) Age:o50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

0.70 −0.52 0.22 −0.36

0.112 0.128 0.141 0.083

nn

Gender: male (female) Age:o50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

−1.05 0.86 −0.59 0.58

0.138 0.146 0.174 0.106

nn

Gender: male (female) Age:o50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

−0.63 0.63 0.01 0.09

0.134 0.149 0.176 0.106

nn

0.81 0.16 0.03 0.03 0.07 0.41

0.115 0.006 0.166 0.200 0.178 0.202

Low TI

Medium TI

High AMB

Average AMB

Derived standard deviations of parameter distributions Poor BCS NS Good BCS NS Low TI NS Medium TI NS High AMB NS Average AMB NS

nn

NS NS nn n nn

nn

NS nn

nn nn nn

nn

NS NS nn

NS NS NS NS n

NB: heterogeneity co-efficient of variable used as a base is zero (0). NS: not significant at α¼ 0.05. n Significant at p o 0.05. nn Significant at p o0.01.

attained by the farmer significantly influenced preference of TI levels and a high AMB. 4.2. Economic values of trait levels in first parity Nguni cows The MNL model had a coefficient of determination value of 24% and produced significant estimates of economic

weights (po0.05) except on poor BCS (Table 4). The base levels of the three traits used in the model were overconditioned (BCS 7–9), high tick infestation (TI), and age at first calving (AFC) of greater than 36 months. The base levels had negative economic values. The highest economic weight as indicated by a high utility coefficient was observed on breeding cows with less than 27 months AFC. On average the

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Table 4 Estimates of economic weights and values (in Rands) of trait evel sfor first parity breeding Nguni cows. Trait level

Economic weight7 s.e

p-value

Economic value (WTP/WTAC)

CI lower limit

CI upper limit

Poor body condition score (1–3) Good body condition score (4–6) Over Body Condition score (7–9) Low tick infestation Medium tick infestation High tick infestation Age at first calving ≤27 months Age at first calving 27–36 months Age at First calving 436 months Price Constant

−0.06 70.055 1.08 7 0.061 Base level 1.50 7 0.059 0.83 7 0.067 Base level 2.37 70.068 1.30 7 0.076 Base level −0.007 0.002 8.9770.310

p 40.05 p o0.05

−413 7834 −7421 10,859 6015 −16,874 17,185 9454 −26,638

−1194 6962 −8247 10,021 5059 −17,771 16,213 8372 −27,665

368 8705 −6595 11,697 6971 −15,977 18,156 10,535 −25,612

p o0.05 p o0.05 p o0.05 p o0.05 p o0.05 p o0.05

NB: economic value of trait level used as a base is zero (0). WTP—willingness To Pay. WTAC—willingness to accept compensation. CI—confidence interval (95%). US$1.00 ¼R7.80 (South Africa Reserve Bank, 2011).

Table 5 Heterogeneity in mean variables and derived standard deviation of distributions in first parity Nguni cows. Trait level

Parameter: variable (base level)

Coefficient

Standard error

Poor BCS

Gender: male (female) Age: o 50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

0.24 0.16 0.26 −0.15

0.072 0.099 0.099 0.060

Good BCS

Gender: male (female) Age: o 50 years (≥50 years) Education: Formal (informal) Ownership: communal (small-scale)

−0.02 −0.13 0.11 0.05

0.081 0.114 0.114 0.069

NS NS NS NS

Low TI

Gender: male (female) Age: o 50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

0.05 0.01 −0.01 −0.11

0.075 0.104 0.104 0.063

NS NS NS NS

Medium TI

Gender: male (female) Age: o 50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

0.01 −0.34 −0.54 −0.06

0.089 0.128 0.131 0.077

NS

Gender: male (female) Age: o 50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

−0.35 −0.11 −0.29 0.37

0.076 0.107 0.108 0.065

Gender: male (female) Age: o 50 years (≥50 years) Education: formal (informal) Ownership: communal (small-scale)

−0.10 0.30 0.08 −0.22

0.088 0.121 0.121 0.075

0.56 0.01 0.03 0.00 0.13 0.48

0.106 0.122 0.157 0.161 0.212 0.131

o27 months AFC

27–36 months AFC

Derived standard deviations of parameter distributions Poor BCS NS Good BCS NS Low TI NS Medium TI NS o27 months AFC NS 27–36 months AFC NS

Significance nn

NS nn n

nn nn

NS nn

NS nn nn

NS n

NS nn

nn

NS NS NS NS nn

NB: heterogeneity co-efficient of variable used as a base is zero (0). NS: not significant at α¼ 0.05. n Significant at p o0.05. nn Significant at po 0.01.

farmers were willing to pay (WTP) up to R17,185.00 (US $2203.21) for such a breeding cow. On average farmers were willing to accept compensation (WTAC) of R26,638.00 (US $3415.13) on breeding cows with an AFC of greater than 36 months. Enterprise type had significant effect on the heterogeneity of economic weights within trait levels as observed

on communal enterprises negatively affecting the poor BCS and AFC of 27–36 months while positively affecting AFC of less than 27 months (po0.05) (Table 5). The gender of the farmer significantly influenced the poor BCS and AFC of less than 27 months (po0.05) where the male farmers had positive and negative economic weights, respectively.

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Age of the farmer had no significant effect on economic weights except for the positive effect on AFC of 27–36 months. The highest level of education attained by the farmer had significant influence on economic weights of cow traits. Farmers with primary education had negative scores on medium TI and AFC of less than 27 months while having a positive scores on poor BCS (po0.05). 5. Discussion The pooled models of both breeding bulls and cows had a negative price utility co-efficient, which is good evidence that farmers did not want expensive breeding animals. The farmers were observed to have a limited source of income and therefore practice low-input agriculture production system (Tada et al., 2012) that would mean a constrained budget on expenses. Furthermore, farmers in the study came from rural communities whereby expenditure of breeding stock is less likely especially for indigenous and non-descript genotypes which are thought to be climatically adapted where natural selection is at play. The fitted models were considered good with a co-efficient of determination (R2) of 24% and 39% on cows and bulls, respectively. This suggests fewer inconsistencies in the responses (List et al., 2006). The likelihood models are known to have a high co-efficient of variation due to the nature of respondents of which differences in the demographic and psychological factors lead to an array of variability in responses as reported in breed and trait preference studies with indigenous cattle kept under traditional production systems (Kassie et al., 2010; Desta et al., 2011). The values obtained may have been influenced by a higher number of responses from individual farmers. A total of 120 choice sets from 16 animal profiles per breeding animal class with no missing responses indicated a full fractional orthogonal design that can maximize R2 values. The utility co-efficient, which translate to economic weights, of poor BCS, high TI and low AMB in breeding bulls, were negative. This gives an indication that the trait levels were not desirable to the farmers and can be selected against (Roessler et al., 2008; Moyo and Masika, 2009). The highest economic weight observed was on high AMB level (4.41 70.095), which is a signal that farmer's decision on buying a breeding bull is strongly influenced by the AMB. This is consistent with the preliminary survey results obtained when farmers were ranking traits of economic importance in these rural enterprises as well as studies by Desta et al. (2011) on indigenous Sheko cattle in Ethiopia. Breeding bulls are known to have a major influence on the enterprise as they leave more progeny than breeding cows. The farmers realised the importance of this trait and were willing to pay up to R37,939 (US $4864) for a high performing bull despite the fact that they are resource-limited. The economic value of this trait level was consistent with auction prices of proven pedigree bulls of the same Nguni breed across the country. The prices of the breeding bulls ranged from R30,000 to R55,000 (US$3846–US$7051) during the auctions held under the auspices of the Nguni Cattle Breed Society in the year 2011, the period this research data was gathered (Nguni Cattle Breeders Society, 2011).

The second highest economic weight was observed on bulls of average AMB (2.53 70.094), this indicated that farmers compromise for an average performing bull before considering the low TI, medium TI and good BCS. The low AMB level attracted the worst negative economic value of –R59,746 (–US$7660). This signifies a complete displeasure by the farmers for a breeding bull with such unproductive characteristics. The low and medium TI had similar economic values (Table 2) as these can be thought to be controllable at minimum cost unlike the high TI which attracted a negative economic value of up to −–R9928 (US $1273). A positive economic value for high BCS and a negative economic value on poor BCS is evidence that farmers prefer to buy an over-conditioned than an underconditioned bull. An over-conditioned bull can maintain acceptable BCS with minimum costs whilst conditioning a poor bull is associated with costs from farmers who already have limited sources of income (Tada et al., 2012). Enterprise ownership pattern and demographic factors of the farmers did not significantly influence the preference of an over-conditioned bull. This suggests that farmers would not buy poor-conditioned breeding bulls. Younger (o50 years) and old farmers (≥50 years) had contrasting decisions on buying a good-conditioned, low and medium TI, and high and average AMB levels. The young farmers can be the class of farmers that prefer overconditioned breeding bulls as management practices targeting maintenance of body condition may fail and settle for the ideal condition. These results on low and medium TI can suggest some levels of inconsistencies from the responses of this category. Inconsistencies have been reported in choice experiments (CE) and drastically reduce R2 values under field conditions mainly because of lesseffective cheap talk scripts and less time spent in evaluating the choice sets (List et al., 2006). The young farmers significantly preferred buying high and average AMB bulls more than old farmers which can suggest the correlation of sexual behavior of humans as related to animals. Contrasting views across gender patterns were observed as male farmers indicated lesser emphasis of high and average AMB as well as the low and medium TI in breeding bulls. Primary and secondary educated farmers were consistent on the responses for low TI. This can be attributed to the experience and knowledge of animal husbandry acquired formally and/or informally through the activities of the Eastern Cape Department of Rural Development and Agrarian Reform (ECDRDAR). Kassie et al. (2010) and Wollny (2003) postulated a likelihood of different needs, perceptions and preferences by which village communities in Ethiopia and Africa in general make decisions for mating or sale of animals. Primary educated farmers did not prefer high AMB bulls which can be a revelation that aggression nature of the bulls can be misunderstood yet it offers the naturally fit and naturally selected bull a chance to leave more progeny. Communal and small-scale enterprises had contrasting preferences on low to medium TI levels. The small-scale enterprises were located in Land Redistribution and Agriculture Development (LRAD) farms which may not be the primary target by the ECDRDAR due to logistical issues as

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the LRAD farms were relatively a new method of empowering emerging farmers. The work by the ECDRDAR on helping the rural communities with dipping infrastructure and chemicals/ acaricides (Tada et al., 2012; Moyo and Masika, 2009) could have made the communal enterprises think that low and medium TI are not that crucial compared to responses from small-scale enterprises. The enterprise ownership patterns were not consistent on the need of a high AMB bulls. The communal enterprises were most vocal because the services of the Nguni bulls were dearly needed as noted in the previous studies on breeding concerns bulling rates and herd structure (Tada et al., 2012). The respondents in the study had cattle enterprises that were yet to payback the nucleus herd animals to the program. Ideally, animals that quickly reproduce are most favored. This could be one of the main reasons why highest economic weights of trait levels in buying a first parity Nguni cow was observed in AFC of less than 27 months. A balanced birth sex ratio postulated through Mendelian principles for the enterprise animals across ownership patterns indicates the need to have highly reproductive animals to meet program objectives as well as generating potential breeding bulls for performance testing and or slaughter steer production system. The farmers realised that Nguni cattle within the enterprises had never been selected and therefore were not uniform in performance. By considering top-notch breeding cows using AFC with a reported medium to high heritability trait value of 27–37% in beef cattle (Bourmann and Wilson, 2010; Gergovska and Yordanova, 2011) genetic progress was fore-seen. This translated to a high economic value of up to R17,185 (US$2203). This price was consistent with auction prices of the breed society (Nguni Cattle Breeders Society, 2011). The realization of the importance of tick control under communal low-input production systems was shown by the second ranking of this low TI level (Table 4). Tick infestation is regarded as a measure of disease resistance and therefore adaptability of the animals, therefore the economic value of the trait level observed was positive at R10,859 (US$1398). Cows with an undesirable high TI had high negative economic values which the resource-limited farmers were not likely to accept as the animal would be a liability to the enterprise. Farmers had the notion of choosing animals which would offer benefits at the least possible cost. This notion was supported by a negative economic value observed on over-conditioned and poorconditioned cows that are known to have problems with regard to cow productivity (Veerkamp et al., 2001; Desta et al., 2011). Male and female farmers concurred on the negative effects to the enterprise of cows with a poor BCS with males having a bigger voice. With regard to the highly weighted trait level, o27 months AFC, male farmers contributed less on valuing this characteristic cow as well as farmers who attended primary education. A stronger response was observed on breeding cows of poor BCS with farmers who attended only primary education than secondary education. On the medium TI and o27 months AFC, farmers who attended secondary education level were more influential in valuing the breeding cow. Communal enterprises were negatively inconsistent with

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small-scale enterprises on poor BCS and 27–36 month AFC, which could be attributed to the notion that communal enterprises thought it was a normal case for animals to have a poor condition and calve after 3 years (Nguni Cattle Breeders Society, 2011). The small-scale enterprises had less positive influence on choosing o27 months AFC, which can be due to a higher influence on 27–36 month AFC. 6. Conclusion and recommendation The utility co-efficient of the trait levels translated to the economic weight while the implicit price or part worth value translated to the economic value of the trait levels. Farmers indicated high economic weight on reproductive efficiency of the breeding animals followed by the adaptive characteristics. A high and medium AMB resulted in the highest economic value for Nguni breeding bulls while a low AMB and a high TI were discouraged by the farmers. Enterprise ownership patterns and demographic factors had significant influence in making choice of Nguni breeding bulls. The most treasured trait levels in Nguni breeding cows were the reproductively efficient cows with a good condition score and highly adaptive to the local ticks. To realize high incomes, farmers are urged to keep animal performance records and sell their breeding stock at competitive prices especially at formal auctions thereby sustaining an enabling policy for sustainable management of indigenous cattle genetic resources. It is recommended to make use of the economic weights of preferential traits in designing selection models and mating strategies. Conflict of interest statement All authors declare that there are no actual or potential conflicts of interest between the authors and other people or organizations that could inappropriately bias their work.

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