Definition of breeding objectives and optimum crossbreeding levels for goats in the smallholder production systems

Bett, R.C.; Kosgey, I.S.; Kahi, A.K.; Peters, Kurt J.

doi:10.1016/j.smallrumres.2010.11.008

Cited by 26 publications

(20 citation statements)

References 18 publications

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“…Single kidded does tended to be heavier that those of the twinkidded does. The body weight of Norduz does is heavier than those of Longling Yellow goats (Leng et al 2010) and local goats in Kenya (Bett et al 2011). The Norduz does were lighter than the Hair goats in Amasya district of Turkey (Cam et al 2010).…”

Section: Resultsmentioning

confidence: 92%

Some productive characteristics and body measurements of Norduz goats of Turkey

Bingöl

Gökdal

Aygün

et al. 2011

Trop Anim Health Prod

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Productive characteristics and body measurements of Norduz goats, a native genetic resource in Turkey, were measured. The animals studied were brought from natural habitats to the farm of the Animal Science Department of Agricultural Faculty, Yüzüncü Yıl University. Least squares means of withers height (WH), body length (BL), chest width at back of withers (CWBW), chest depth (CD), chest girth (CG) and leg girth (LG) of Norduz does were 65.9 ± 1.08, 67.2 ± 1.08, 21.1 ± 0.88, 30.8 ± 0.62, 88.9 ± 1.78 and 60.4 ± 1.28 cm, respectively. Least squares means of body weights after parturition of does were 41.3 ± 2.01 kg. The means of lactation length and lactation milk yield were 226. ± 7.2 days and 347 ± 40.1, respectively. Twinning rate, fertility, fecundity, litter size and litter size at weaning were 30%, 98%, 1.27, 1.30 and 1.28, respectively. Means of WH, BL, CWBW, CD, CG, LG and body weights of Norduz bucks were 73.9 ± 2.61, 75.6 ± 2.23, 21.4 ± 0.67, 33.9 ± 1.15, 95.0 ± 2.34, 69.8 ± 2.69 cm and 58.7 ± 3.91 kg, respectively.

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Section: Resultsmentioning

confidence: 92%

Some productive characteristics and body measurements of Norduz goats of Turkey

Bingöl

Gökdal

Aygün

et al. 2011

Trop Anim Health Prod

View full text Add to dashboard Cite

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“…In Kenya, effective improvement programmes are absent for any cattle breed because of constraints like low effective population size, high cost of reproductive technologies, lack of systematic identification, poor animal performance and pedigree recording, genotype by environment interaction and organizational shortcoming, among others (Kosgey et al, 2011;. A study by Okeno et al, (2010) evaluated the breeding strategies for improvement of dairy cattle in Kenya and used the breeding objective and economic values from a study by .…”

Section: Introductionmentioning

confidence: 99%

Economic and Biological Values for Pasture-Based Dairy Cattle Production Systems and their Application in Genetic Improvement in the Tropics

Wahinya¹,

Okeno²,

Kosgey³

et al. 2015

J. Anim. Prod. Adv.

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Economic and biological values for milk yield (MY), milk butter fat (FY), daily gain (DG), weaning weight (WWT), mature live weight (MLW), calving interval (CI), pre-weaning survival rate (PreSR), post-weaning survival rate (PostSR), age at first calving (AFC), and productive life time (PLT) were estimated under fixed herd (FH) and pasture (FP) production circumstances assuming milk marketing based on volume, and volume and butter fat. Further, economic values were estimated involving risk using the Arrow Pratt coefficients at two levels. For the former economic values for the traits ranged from KSh.-17.246 to 100.536 while the biological values ranged between-1.29 to 0.791. Economic values with higher Arrow-Prat coefficient of absolute risk aversion (λ=0.02) were lower than those reported under λ=0.0001 indicating that the uncertainty of the future market is important and should be considered during the estimation of economic values. Genetic improvements targeting MY and growth traits would be recommended to production system with unlimited feed supply for profit maximization. However, since dairy production systems in the tropics are characterised by feed scarcity, fixing the herd and concentrating on genetically improved animals would result to more profitability than increasing animal populations.

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“…The reduction of areas for livestock production, due to population growth has created new opportunities to promote the dairy goat rearing through government initiatives (Devendra 2010, Bett et al 2011). Bett et al (2009a have shown that the largest goat dairy producing areas are located in environments of medium to high rainfall.…”

Section: Multivariate Approachmentioning

confidence: 99%

Spatialization of climate, physical and socioeconomic factors that affect the dairy goat production in Brazil and their impact on animal breeding decisions

et al. 2012

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1073 em melhoramento animal.] O Brasil possui diversidade edafoclimática e realidades socioeconômicas e políticas distintas. Isto contribui para diferenciar as regiões polí-tico administrativas do país. Objetivou-se espacializar os fatores ϐísicos, climáticos e socioeconômicos que melhor discriminam a produção de caprinos leiteiros no Brasil. Foram analisados índice de produção de leite por cabra; ín-dice de produção de caprinos; índice de produção de leite, amplitude da temperatura; temperatura média; precipitação; índice normalizado de diferença vegetativa; umidade relativa do ar; altitude; estabelecimentos agropecuários; estabelecimentos com pastagem nativa; estabelecimentos com pastagens de boa qualidade; estabelecimentos com recursos hídricos; estabelecimentos que recebem orientação técnica; estabelecimentos de agricultura familiar; estabelecimentos de agricultura não familiar e índice de desenvolvimento humano. Brazil has high climate, soil and environmental diversity, as well as distinct socioeconomic and political realities, what results in differences among the political administrative regions of the country. The objective of this study was to determine spatial distribution of the physical, climatic and socioeconomic aspects that best characterize the production of dairy goats in Brazil. Production indices of milk per goat, goat production, milk production, as well as temperature range, mean temperature, precipitation, normalized difference vegetation index, relative humidity, altitude, agricultural farms; farms with native pasture, farms with good quality pasture, farms with water resources, farms that receive technical guidance, family farming properties, non-familiar farms and the human development index were evaluated. The multivariate analyses were carried out to spatialize climatic, physical and socioeconomic variables and so differenciate the Brazilian States and Regions. The highest yields of milk and goat production were observed in the Northeast. The Southeast Region had the second highest production of milk, followed by the South, Midwest and North. Multivariate analysis revealed distinctions between clusters of political-administrative regions of Brazil. The climatic variables were most important to discriminate between regions of Brazil. Therefore, it is necessary to implement animal breeding programs to meet the needs of each region.

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Definition of breeding objectives and optimum crossbreeding levels for goats in the smallholder production systems

Cited by 26 publications

References 18 publications

Some productive characteristics and body measurements of Norduz goats of Turkey

Some productive characteristics and body measurements of Norduz goats of Turkey

Economic and Biological Values for Pasture-Based Dairy Cattle Production Systems and their Application in Genetic Improvement in the Tropics

Spatialization of climate, physical and socioeconomic factors that affect the dairy goat production in Brazil and their impact on animal breeding decisions

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