REGULAR ARTICLES

Economic values for production and functional traits of SmallEast African goat using profit functions

Samuel Mbuku & Isaac Kosgey & Mwai Okeyo &

Alexander Kahi

Accepted: 27 February 2014 /Published online: 14 March 2014# Springer Science+Business Media Dordrecht 2014

Abstract Economic values for production traits (milk yield,MY, g; 12-month live weight, yLW, kg; consumable meatpercentage, CM, %) and functional traits (mature doe liveweight, DoLW, kg; mature buck live weight, LWb, kg; kid-ding frequency, KF; pre-weaning survival rate, PrSR, %; post-weaning survival rate, PoSR,%; doe survival rate, DoSR, %;and residual feed intake, RFI, kg) were estimated using profitfunctions for the Small East African goat. The scenario eval-uated was a fixed flock size, and the resultant economic values(Kes per doe per year) were 34.46 (MY), 62.35 (yLW), 40.69(CM), 0.15 (DoLW), 2.84 (LWb), 8.69 (KF), 17.38 (PrSR),16.60 (PoSR), 16.69 (DoSR) and −3.00 (RFI). Similarly, theeconomic values decreased by −14.7% (MY), −2.7 % (yLW),−23.9 % (CM), −6.6 % (DoLW), −98 % (LWb), −8.6 % (KF),−8.2 % (PrSR), −8.9 % (PoSR), −8.1 % (DoSR) and 0 %(RFI) when they were risk rated. The economic values forproduction and functional traits, except RFI, were positive,which implies that genetic improvement of these traits wouldhave a positive effect on the profitability in the pastoralproduction systems. The application of an Arrow-Pratt coef-ficient of absolute risk aversion (λ) at the level of 0.02 resultedin a decrease on the estimated economic values, implying that

livestock keepers who were risk averse were willing to acceptlower expected returns. The results indicate that there wouldbe improvement in traits of economic importance, and, there-fore, easy-to-manage genetic improvement programmesshould be established.

Keywords Breeding goal . Economic values . Small EastAfrican goat . Pastoral production systems

Introduction

Livestock production in the tropics and subtropics is a majorsource of livelihood among the livestock keepers and is usu-ally characterised by direct and collateral effects like frequentwater and feed shortages, which ultimately lead to low pro-duction. In Kenya, livestock contributes approximately 11 %to the GDP (MoLD 2012). Indigenous goats are important formajority of households found in the arid and semi-arid lands(ASALs). Successful genetic improvement initiatives for the-se goats should directly address the needs and objectives ofthe livestock keepers (Sousa et al. 2011). Although productionand functional traits are important in genetic improvementprogrammes for the Small East African goat (SEAG), esti-mates of their biological and economic values have not beendetermined so far.

Breeding goals exist in many livestock species; usually,these comprise production and functional traits. Notablebreeding objectives have been defined for various livestockspecies in different countries. e.g. for Valle del Belice dairysheep (Tolone et al. 2011), indigenous chicken (Okeno et al.2012), Creole goat (Gunia et al. 2013) and Aberdeen Anguscattle (Campos et al. 2014) but are lacking for SEAG. Thepresent study estimates economic values based on profit func-tions and specifies incomes and costs arising from productionfor an indigenous SEAG population reared under pastoral

S. MbukuDivision is National Beef Research Centre, Kenya AgriculturalResearch Institute, P.O. Box 3840, Nakuru 20100, Kenya

I. KosgeyLaikipia University, P.O. Box 1100, Nyahururu 20300, Kenya

M. OkeyoInternational Livestock Research Institute, Old Naivasha Road,P.O. Box 30709, Nairobi 01000, Kenya

S. Mbuku (*) : I. Kosgey :A. KahiAnimal Breeding and Genetics Group, Department of AnimalSciences, Egerton University, P.O. Box 536, Egerton 20115, Kenyae-mail: sambuku2002@yahoo.com

Trop Anim Health Prod (2014) 46:789–795DOI 10.1007/s11250-014-0567-8

production system in Kenya. The economic values are thenrisk rated to determine their robustness.

Material and methods

Breed and production system

The SEAG is distributed throughout a wide and diverse rangeof environments in sub-Saharan Africa. The breed groupbelongs to the group of short-eared and small-horned goats.Adult males attain weights up to 43 kg and females 37 kg,although heavier live weights have been observed in bettermanaged flocks (DAGRIS 2013). Pastoral production systemsare predominant in the low potential areas. In these systems,livestock form a pivotal part of the socio-cultural life of thepastoralists. The Small East African and Galla goats are main-ly found in these systems (DAGRIS 2013). Generally, pastoralcommunities attach high value to flock sizes and their surviv-al. Consequently, survival and reproductive traits are impor-tant under this system.

Model overview

A deterministic static model was developed using the Fortran95 programming language written in Microsoft Windows forthe evaluation of the economic aspects of important traits ofthe SEAG under pastoral production systems. The modeldescribed quantitative relationships between levels of geneticmerit for the production and functional traits considered, andlevels of inputs and outputs under the pastoral productioncircumstances. The profitability of the system was described,where the total annual profit of the flock was computed as thedifference between costs and revenues of the system. Table 1presents production, management and price input values forthe pastoral production system.

Flock composition and flows

Figure 1 below shows the flock dynamics for the SEAG withemphasis on composition and flows over 1 year. It was as-sumed that the flock consisted of a constant number of breed-ing does, N, present over the 1 year, and different goat

Table 1 Production, management and price input data for the modela

Variables Abbreviation Value Variables Abbreviation Value

Production variables

Milk yield (g per day) MY 500.00 Mature weight of bucks (kg) LWb 36.00

Consumable meat (%) CM 65.00 Kidding rate (%) KR 87.00

Average daily gain kids (g/day) DGk 85.00 Pre-weaning survival rate (%) PrSR 85.00

Average daily gain yearlings (g/day) DKy 67.00 Post-weaning survival rate (%) PoSR 89.00

Birth weight (kg) BW 1.70 Doe survival rate (% per year) DoSR 88.50

Weaning weight (kg) WW 8.70 Twinning rate (%) tr 23.40

Body weight at 12 months of age (kg) yLW 15.80 Replacement survival (%) ReSR 93.00

Mature weight of does (kg) DoLW 32.00 Mortality rate of bucks (% per year) MoRb 7.00

Management variables

Age at attainment of mature weight (months) AgMW 20.00 Buck culling age (years) - 2.00

Age of doe at first kidding (months) AgFK 20.00 Fraction of cull-for-age does, excluding mortality(10 years)

0.15

Kidding interval (months) KI 9.00 Fraction of cull-for age bucks, excluding mortality(2 years)

1.00

Age at first mating (months) AgFM 14.00 Kidding frequency KF 1.7

Age of replacement stock at selection (months) – 14.00 Weaning age of kids (months) – 4.3

Age of surplus yearlings when sold (months) – 14.00 Doe culling age (years) – 10.00

Management costs (Ch) per adult doe

Dipping (Kes per head per year) Dip 350 Helminth control (Kes per dose per head) Helm 400

Drugs and veterinary service charge (Kes per headper year)

Vet 200

Marketing costs (Cm)

Costs of animal sale and slaughter (Kes per head) Cslt 200 Transport of live animal to market (Kes per head) Ctrans 200

Prices

Meat price (Kes per kg of carcass) Pmeat 220 Labour costs (Kes per shepherd per doe per year) 300

Milk price (Kes per kg) Pmilk 60

a All costs and prices in Kes (Kenya shillings); USD 1 = Kes. 80.000 at the time of the study.

790 Trop Anim Health Prod (2014) 46:789–795

categories were identified according to age. The size of theflock was kept constant over time by equating the number ofreplacement females with culled does and their respectivesurvival rates. The ratio of breeding bucks to breeding doeswas assumed to be 1:35.

Profit equation

The total profitability of the SEAG flock per year (Pf) (Kes)was expressed as a function of k biological traits, with therelated costs and output values described by the followinggeneral Eq. 1 shown below:

P f ¼Xi¼1

k

ni Ri−Cið Þti−F ð1Þ

where ni is the number of expressions for trait i in a year, Ri therevenue per unit per expression of trait i (ti), Ci, the cost perunit per expression of trait i (ti) and F the fixed cost per flockper year (fixed costs in the current study were negligible and,therefore, ignored). All the costs and prices were stated inKenya shillings (Kes).

Calculation of revenues

The sources of revenues in the pastoral production systemwere from sale of milk, surplus yearlings, cull-for-age bucksand cull-for-age does. The following variables (Eqs. 2–4)were introduced for the purpose of easy computation:

DoWR ¼ KF� KR� PrSR� 1þ tr

100

� �ð2Þ

NKW ¼ DoWR� DoSR ð3Þ

Nydy ¼ PoSR� NKW ð4Þ

where KF=kidding frequency; DoWR=doe weaning rate,(%); KR=kidding rate, (%); PrSR=pre-weaning survival rate(%); tr=twinning rate (%); NKW=number of kids weaned perdoe per year; DoSR=doe survival rate (%); Nydy=number ofyearlings per doe per year; PoSR=post-weaning survival rate(%).

Revenue from surplus yearlings (Ry)

The number of male yearlings per doe per year (Nmydy)attaining selection age was derived as shown in Eq. 5 below:

Nmydy ¼ 0:5� Nydy ð5Þ

and those culled for sale (Nmydy/cull) were calculated as indi-cated in Eq. 6 below:

Nmydy=cull ¼ Nmydy−Rmdy ð6Þ

where Rmdy=number of male replacements per doe per year.The number of female yearlings per doe per year (Nfydy)attaining selection age is equal to Nmydy, and those culledfor sale (i.e. surplus yearlings) (Nfydy/cull) were derived byEq. 7 below:

N fydy=cull ¼ N fydy−R fdy ð7Þ

where Rfdy=number of female replacements per doe per year.The total number of yearlings per doe per year culled for sale(Nfydy/cull) was computed as shown in Eq. 8 below:

Nydy=cull ¼ Nmydy=cull þ N fydy=cull ð8Þ

and, therefore, the total revenue from yearling (Ry) was cal-culated as indicated in Eq. 9 below:

Ry ¼ N ydy=cull � yLW� CMP� Pmeat ð9Þ

where yLW=average live weight of yearlings at 12 months(kg); CMP=consumable meat percentage (meat weight percarcass weight) (%) and Pmeat=price per kg of meat (Kes).

Revenue from cull-for-age breeding bucks (Rb)

The revenue from breeding bucks (Rb) is attained from cull-for-age bucks. The number of replacement bucks per doe peryear (Rbdy) was derived by Eq. 10 below:

Rbdy ¼ Rmdy � Rosr ð10Þ

Expected number of kids per year(0.191*2*3)+(0.809*1*3)= 3.573/2 = 1.79N

1.55N kids born

1.32N weaners (3 months old)

0.51N young female replacements

0.55N surplus males 0.08N surplus females

0.63N off-take

0.87N total off-take

0.03N cull-for-age bucks 0.21N cull-for-age does

0.03N young males replacement

1.17N yearlings (12 months old)

0.03N bucks N does

87% kidding rate

85% survival rate

89% survival rate

93% survival rate

Fig. 1 Flock dynamics of the Small East African goat (SEAG) in Kenya

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where Rosr=survival rate of replacements to breeding (%).Therefore, Rb was calculated as shown in Eq. 11 below:

Rb ¼ Rbdy � LWb � CMP� Pmeat ð11Þ

where LWb=average live weight of bucks at culling (kg).

Revenues from breeding does (Rd)

The total revenue from breeding does was calculated fromEq. 12 below:

Rd ¼ Rdmeat þ Rdmilk ð12Þ

where Rdmeat=revenue from cull-for-age does and Rdmilk, =revenue from milk as derived in Eq. 13 below.

Rdmilk ¼ MY� dmilk � Pmilk ð13Þ

where MY=average daily milk yield per doe (kg); dmilk=number of days in milk and Pmilk=price per kg of milk(Kes); the number of doe replacements per doe per year (Rddy)was calculated from Eq. 14 below:

Rddy ¼ R fdy � Rosr ð14Þ

and, therefore, Rdmeat was computed as shown in Eq. 15below:

Rdmeat ¼ Rddy � DoSR� DoWT� CMP� Pmeat ð15Þ

where DoWT=average live weight of does at culling (kg).

Calculation of costs

Marketing costs

Costs in the present study arose from feed, husbandry (labourcost, dipping, veterinary care and helminth control) and mar-keting of animals. The average marketing costs (M) per animalsold were described by Eq. 16 below:

M ¼ Nydy þ Rbdy þ Rddy � DoSR�� �� �� ma ð16Þ

where ma is the marketing cost per animal (Kes).

Feed costs

Calculation of feed costs was based on the actual feed intakeexpressed in kg DM. Feed intake was calculated from

estimates of the mean intake of energy value of a feedexpressed in metabolisable energy (ME). The amounts ofenergy required by indigenous goats for different physiolog-ical and weight categories were calculated using Eqs. 17–24below. The energy requirement for maintenance (MEm) wasderived using Eq. 17 below.

MEmi ¼Em

Km¼ 0:315w0:75 þ 0:024w

0:35qm þ 0:53ð17Þ

where Em=energy required for maintenance (MJ/kg DM),w=live weight of the animal (kg) andKm=efficiency of utilisationof MEm. Metabolisability of gross energy (GE) of a diet (i.e.MJ/kg DM in a feed) at maintenance (qm) was derived byEq. 18 below:

qm ¼ ME½ �= GE½ � ð18Þ

where ME=metabolisable energy (MJ/kg DM) of a feed.Energy requirements for growth (MEg) were calculated fromEq. 19 below:

MEgi ¼dg� 4:92þ 0:3274½ �

0:78qm þ 0:006ð19Þ

where dg=daily live weight gain (kg). Energy requirementsfor pregnancy (MEc) were calculated as indicated in Eq. 20below:

MEci ¼0:25wo Et � 0:07372e‐0:00643t½ �

kcð20Þ

and the net energy content of concepta at time t (Et) in MJ wasderived by Eq. 21 below:

log10Et ¼ 3:322‐4:979e‐0:00643t ð21Þ

where wo, total weight of kids at birth (kg); t, number of daysfrom conception; e, exponential function using base e and kc,efficiency for growth of the concepta (= 0.133). Energy re-quirements for lactation (MEl) were computed by Eq. 22below:

MEl ¼ 3:335MY

0:35qm þ 0:420ð22Þ

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Feeding costs per animal (FCi)

Feeding costs per animal (kids, yearlings, replacement males,replacement females and breeding bucks) were derived fromEq. 23 below:

FIi ¼ 0:3

nepþ 0:7

neb

� � Xi¼1

di

MEmi þMEgi þMEci

� � ð23Þ

where di=number of days an animal is present in a year; nep=net energy content in pasture (MJ/kgDM) and neb=net energycontent in browse (MJ/kg DM). Therefore, feed costs (FCi)were calculated as shown in Eq. 24 below:

FCi ¼ N i � FIi � P f ð24Þ

where Pf=price of roughage feed per kg (KSh)

Feeding costs for breeding does (FCd)

Feed intake for does (FId) was derived as the sum of the feedintake during lactation (FId1) and dry period (FId2) as shownin Eqs. 25 and 26 below:

FId1 ¼ dmilk � 0:3

nepþ 0:7

neb

� �MElð Þ ð25Þ

and

FId2 ¼ 365−dmilkð Þ � 0:3

nepþ 0:7

neb

� �MEmð Þ ð26Þ

where MEl=energy for lactation (MJ/kg DM).

Traits of economic importance

The traits of economic importance evaluated in the currentstudy, their units and abbreviations are presented in Table 2.

Estimation of economic values

Conventional economic values

Conventional economic values (CEVs) for the traits consid-ered were calculated for the base situation with a constantnumber of does (fixed flock size). The economic values underfixed flock size were calculated from Eq. 27 below:

EVflock size ¼ δR−δCδt

� ð27Þ

where, EVflock size are the economic values per unit change inthe trait of interest, δR and δC the marginal changes inrevenues and costs after a 1 % increase in the trait of interestand δt the marginal change in trait after 1 % increase.

Risk-rated economic values

Amodel and input variables utilised in the estimation of CEVsabove for traits of SEAG under pastoral production circum-stances were used. The model was revised to incorporate riskand producers’ risk attitude. Equation 28 below was used inthe derivation of risk-rated profit by incorporating an Arrow-Pratt coefficient of risk aversion to represent farmers’ riskattitude and variance of profit to represent risk.

yr¼E ytð Þ−0:5λE yt‐E ytð Þ½ �2 ð28Þ

where yr is a risk-rated profit, E(yt) is the expected profit, λ isthe Arrow-Pratt coefficient of absolute risk aversion and E[yt‐E(yt)]

2 is the variance of profit.

Table 2 List of breeding goal traits evaluated in the study

Trait Unit Abbreviation

Milk yield g/day MY

Consumable meat Consumable meat output as a percentage of live weight at slaughter CM

Twelve-month live weight kg yLW

Mature doe live weight kg DoLW

Mature doe live weight kg LWb

Kidding frequency Average number of kiddings per doe per year KF

Pre-weaning survival rate Kids surviving to weaning as a percentage of kids born] (%) PrSR

Post-weaning survival rate Kids surviving to 12 months of age as a percentage of kids weaned (%) PoSR

Doe survival rate Does surviving as a percentage of does present over the year DoSR

Residual feed intake kg DM per doe per year, i.e. summed over all animal categories in the flockand then expressed on per ewe basis

RFI

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Variances on prices and price indices (Kenya shillings—Kes, where 1 USD=Kes 80) for the period 2009–2013 wereadjusted to 2007, and their co-variances were assumed(Republic of Kenya 2013). Standard deviations of outputprices and input prices were material input price indices=Kes 9, service inputs price indices=Kes 9, milk prices=Kes2.28/kg and meat prices=Kes 12.54/kg.

Results and discussion

Estimated revenues, costs and profitability

Revenues, costs and profits for the fixed flock-size situationevaluated are presented in Table 3. The cost for 0.63 surplusyearlings was Kes 442.73 (feed), Kes 337.50 (husbandry) andKes 272.76 (marketing). The cost of breeding does per doe peryear was Kes 653.49 (feed) and Kes 1,250.00 (husbandry)whereas the total profit was Kes 194.98. The highest contri-bution of breeding does to these costs is associated to theirhigh numbers throughout the year. Variable costs were themost important cost of production, with husbandry costs(53.80 %) being the highest.

The revenue arose from meat sources and were Kes1,540.68 (sale of 0.63 surplus yearlings), Kes 960.96 (saleof 0.21 cull-for-age does) and Kes 143.63 (sale of 0.03 cull-for-age bucks). Surplus yearlings sold for meat contributedhigher revenue because of the high off-take while cull-for-agebucks contributed the least because of their low numbers.

Breeding does had an advantage over the other categories ofanimals because of the extra revenue from milk of Kes1,800.00.

Economic values for traits

Table 4 shows economic values for traits derived with andwithout considering risk and producers’ risk attitude with aconstant number of does. The economic values for productiontraits (yLW, CM and MY) were highest and positive in thebase situation evaluated in this study. Positive economicvalues for the traits were entirely due to an increase in netreturns from meat and milk production. The economic valuefor CM was relatively high (40.69), and this was expectedbecause it was not used in the estimation of feed intake for thedifferent categories of animals. The CM might become morerelevant due to market dynamics in the long run and maytrigger its inclusion in the breeding goal at some later stage(Wolfová andWolf 2013). The yLW had the highest economicvalue (62.35) as expected.

Interestingly, the economic values for functional traits(DoLW, LWb, KF, PoSR, DoSR) were positive except forRFI (−3.00). The positive economic value for DoLW indicatesthat breeding for increased live weights could still increase theprofitability of does under pastoral production systems.However, it would be necessary to determine the optimumsize of a doe under pastoral production systems where feed isscarce (Renaudeau et al. 2012). Among the functional traits,PoSR (16.60) and DoSR (16.69) had the highest positive

Table 3 Estimated costs, revenues and profits (Kes)a per doe per year under the pastoral production system

Animal categoryb

Kids Yearlingsoff-take

Replacement Breeding does Cull doesc Breedingbucks

Cull bucksc Totald Percentageof the total

Females Males

Proportion of animals to ewes 1.32 0.63 0.51 0.03 1.00 0.21 0.03 0.03

Input

feed – 442.73 418.13 24.60 653.49 – 56.64 – 1,595.59 37.54

Husbandry 326.07 337.50 318.75 18.75 1,250.00 – 35.71 – 2,286.78 53.80

marketing – 272.76 – – – 84.00 – 11.16 367.92 8.66

total (a) 326.07 1,052.99 736.88 43.35 1,903.49 84.00 92.35 11.16 4,250.29 100.00

Output

milk – – – – 1,800.00 – – – 1,800.00 40.49

Meat – 1,540.68 – – – 960.96 – 143.63 2,645.27 59.51

Total (b) – 1,540.68 – – 1,800.00 960.96 – 143.63 4,445.27 100.00

Profit (b–a) – 474.19 −749.63 −44.1 −153.49 960.96 −93.78 132.47 194.98

a USD 1=Kes 80.00 at the time of the studyb See text above for description of animal categoryc Accounted for in the breeding groupsdWeighted by animal proportions

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economic values. Improvement for these traits would result ina greater influence on revenues than on costs because of theincreased off-take rates of surplus animals. The PrSR had apositive economic value (17.38), and that was expected be-cause survival traits influenced the flock composition and thereplacement rates. The negative economic value for the RFI(−0.30) was not a surprise because an increase in the geneticmerit of the trait did not affect revenue but resulted in anincrease on feed costs only.

The resultant risk-rated economic values when an Arrow-Pratt coefficient of absolute risk aversion (λ) of 0.02 wasapplied were comparable to the economic values estimatedwithout risk. With consideration of a higher risk aversion of0.02, these changes were approximately −2.8, −23.9, −14.7,−20.6, −35.6, −8.6, −8.2, −8.1 and −8.2 % for yLW, CM,MY,DoLW, LWb, KF, PoSR, DoSR and PrSR, respectively. Thisclearly implies that livestock keepers who are risk averse werewilling to accept lower expected returns to avoid the oppor-tunity of unfavourable outcomes. However, larger differencesin economic values for traits predicted suggest that when riskis not accounted for, the economic values for traits areoverestimated, and, therefore, risk should be included in theirestimation.

Conclusion

This study found most of the production and functional traitsimportant, justifying their inclusion in the breeding goal toimprove on the overall production efficiency of the pastoralproduction systems utilising the SEAG. The positive econom-ic values for most traits under fixed flock-size scenario indi-cated that a unit increase in genetic merit for the traits wouldhave a positive effect on the profitability. The main challengewould be actualising the concept of ‘production adaptability’and detail on how to balance higher productivity with im-proved functional traits like survival, reproductive and feed

intake-related traits at the same time in order to achieve a moresustainable production. Overall, the primary policy would,therefore, be to encourage the establishment of easy-to-manage genetic improvement programmes for the SEAG thatcould later be upgraded overtime under pastoral productionsystems and other areas with similar productioncircumstances.

Acknowledgments The fieldwork for this study was supported by jointfunds from the Kenya Arid and Semi-Arid Lands (KASAL) programmethrough the Kenya Agricultural Research Institute and Kenya’s NationalCouncil for Science and Technology. We are also grateful to the GermanAcademic Exchange Service (DAAD) for providing the first author witha sandwich scholarship in collaboration with Universität Kassel, Germa-ny. Our gratitude is to the many pastoralists who shared with us theirexperiences and plight.

Conflict of interest All authors declare that there are no actual orpotential conflicts of interest among the authors and other people ororganisations that could inappropriately bias their work.

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Table 4 Conventionaland risk rated (λ=0.02)economic values fortraits evaluated in thestudy

a See Table 2 for defini-tion of units and abbre-viations of traitsb Conventional economicvaluesc Risk-rated economicvalues

aTrait bCEVs cREVs

MY 34.46 29.41

CM 40.69 30.99

yLW 62.35 60.62

DoLW 15.28 12.14

LWb 2.84 1.83

KF 8.69 7.94

PrSR 17.38 15.96

PoSR 16.60 15.24

DoSR 16.69 15.33

RFI −3.00 −3.00

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