Linear Body Measurements as Indicators for Body Weight in Three Genotypes of Chickens in Zimbabwe
Abstract
Predicting body weight plays a vital role in poultry breeding, as it significantly affects the productivity and economic viability of poultry operations. Within the field of animal breeding, researchers have identified linear body measurements as effective indicators for estimating body weight. A study of 397 mature hens (155 Australorp; 154 Boschveld; 88 Sasso) was conducted to assess body weight and linear body measures, including neck length (NL), Body Circumference (BC), Body Length (BL), Shank Length (SL), and Shank Circumference. The results showed significant differences in BWT, BC, BL, SC, and SL for all chicken breeds, with p-values less than 0.05. However, there was a slight difference in neck length and shank circumference, with p<0.05. Australorp had the highest weight and largest size, followed by Boschveld and Sasso. The study found that Boschveld chickens had the strongest association coefficient with body weight, with a 0.50 correlation between shank circumference and neck length. Sasso chickens showed a positive association with body weight and body dimensions, but the overall relationship was weaker. Australorp chickens can predict body weight by direct selection of the neck length. Australorp chickens had the highest body circumference, body length, shank circumference, and neck length. Linear body measurements as sole predictors of body weight were ineffective, with values ranging from 0.02-0.34, 0.03-0.15, and 0.05-0.27 for SC, AC, and BC, respectively. The most effective multiple linear regression model correlating body weight and linear body measurements was presented by Boschveld (R2 = 0.50). However, its applicability, particularly in smallholder agricultural contexts, remains subject to debate. The study concluded that linear body measurements may not be effective sole predictors of body weight in the Australorp, Boschveld, and Sasso chicken populations of Zimbabwe, and that other predictive models that fit quadratic or cubic growth may need to be explored. Furthermore, the size and body weight of chicken breeds differ, with Australorp being notably larger and heavier. This study illuminates the genetic and environmental elements that affect poultry body weight, allowing breeders to make better-informed choices. Subsequent studies could explore the integration of body weight prediction models with genomic selection techniques to enhance the precision of breeding values and develop prediction models specific to different genotypes in poultry.
How to Cite This Article
Assan N, Mpofu M, Musasira M, Mwareya N, Muteyo E (2025). Linear Body Measurements as Indicators for Body Weight in Three Genotypes of Chickens in Zimbabwe . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 6(2), 508-515. DOI: https://doi.org/10.54660/IJMRGE.2025.6.2.508-515
References
- 1. Abdel-Latif FH. Thelinearassociationbetweenlivebodyweightandsomebodymeasurementsinsomechickenstrains. Plant Archives.2019;19(1\:5959.
- 2. Alemayehu G, Negasi A. Characterizationofscavengingandintensivechickenproductionsystemin Lume District, East Showa Zone, Oromia Regional State, Ethiopia. Int JLivest Prod.2020;11:820.
- 3. Aman G, Bangu B, Bereket Z, Desta G, Abiti T. Productionperformanceof Sasso(distributedbyethiochickenprivatepoultryfarms\and Bovansbrownchickensbreedundervillageproductionsysteminthreeagro-ecologiesof Southern Nations, Nationalities, and Peoples'Regional State(SNNPR\, Ethiopia. Int JLivest Prod.2017;8:14557.
- 4. Bekele F, Dn?y TA, Gj?en HM, Kathle J, Girma A. Productionperformanceofdualpurposecrossesoftwoindigenouswithtwoexoticchickenbreedsinsub-tropicalenvironment. Int JPoult Sci.2010;9(7\:70210.
- 5. Bosch M. Boschveld Village Chicken Management Guide.1sted.;2018.
- 6. Chineke CA, Agaviezor B, Ikeobi CON, Ologun AG. Somefactorsaffectingbodyweightandmeasurementsofrabbitatpreandpostweaningages. In: Proceedingsofthe27th Annual Conferenceofthe Nigerian Societyfor Animal Production;2002. p.13.
- 7. Dawud I, Gebeyehu G, Wondmeneh E, Avigdor C. Dual-purposeproductionofgeneticallydifferentchickencrossbreedsin Ethiopia.
- 1. Parentstocks'feedintake, bodyweight, andreproductiveperformance. Poult Sci.2019;98(5\:311929.
- 8. Dawud ID, Goshu G, Esatu W, Bino G, Abebe T. Comparativestudyofproductionandreproductiveperformanceofvariousstrainsofchickenparentlayersraisedinfloorpens. Eth JAgric Sci.2018;28:241582.
- 9. Dzungwe JT, Gwaza DS, Egahi JO. Statisticalmodelingofbodyweightandbodylinearmeasurementsofthe Frenchbroilerguineafowlinthehumidtropicsof Nigeria. Poult Fish Wildl Sci.2018;6(2\:25.
- 10. Dzungwe JT, Kof Tozo K, Chrysostome C. Growthperformance, mortality, andcarcassyieldevaluationofpureandreciprocalcrossesbetween Sassoand Wassachechickens. Trop Anim Health Prod.2022;54:298. doi:10.1007/s11250-022-03272-x.
- 11. FAO. Phenotypiccharacterizationofanimalgeneticresources. FAOAnimal Productionand Health Guidelines No.
- 11. Rome: FAO;2012.
- 12. Ganner A, Schatzmayr G. Capabilityofyeastderivativestoadhereenteropathogenicbacteriaandtomodulatecellsoftheinnateimmunesystem. Appl Microbiol Biotechnol.2012;95(2\:28997. doi:10.1007/s00253-012-4140-y.
- 13. Gondwe TNP, Wollny CBA. Comparativeproductivityof Black Australorpandindigenouschickensunderfree-rangingvillageconditionsin Malawi. In: Deutscher Tropentag2003; G?ttingen;2003.
- 14. Maciejowski J, Zeiba T. Geneticsandanimalbreeding. Amsterdam-Oxford-New York: PWN-Polish Scientific Publishers;1982.
- 15. Melkamu BY. Theeffectofdriedbloodrumencontentmixture(DBRCM\oncarcasscharacteristicsof SASSOC44broilerchicks. Eur Sci J.2016;12(16\:166.
- 16. Nesamvumi AE, Malaudzi J, Ramanyimi ND, Taylor G. Estimationofbodyweightin Ngunu-typecattleundercommunalconditions. SAfr JAnim Sci.2000;30(suppl\.
- 17. Okoro VMO, Ravhuhali KE, Mapholi TH, Mbajiorgu EF, Mbajiorgu CA. Effectofageonproductioncharacteristicsof Boschveldindigenouschickensof South Africarearedintensively. SAfr JAnim Sci.2017;47(2\:15767.
- 18. Parte P, Sahoo SK, Dubey PP, Kaur S, Mukhopadhyay CS. Effectofgeneticgroupsandgenderonbodyweightanddifferentmorphometrictraitsinpoultry. Birds.2024. doi:10.18805/ag. D-5981.
- 19. Patbandha TK, Garg DD, Marandi S, Vaghamashi DG, Patil SS. Effectofchickweightandmorphometrictraitsongrowthperformanceofcolouredbroilerchicken. Anim Sci Adv.2017;5(6\:127881.
- 20. Pinheiro RRS, Watanabe PH, Ara?jo LRS, etal Structuredlipidsfromfishvisceraandcoconutoilsimproveweightgainandintestinalmorphologyofpigletsatnurseryphase. Trop Anim Health Prod.2024;56:403. doi:10.1007/s11250-024-04235-0.
- 21. Sadick AM, Aryee G, Poku PA, Kyere CG. Relationshipbetweenbodyweightandlinearbodymeasurementsinthe Cobbbroilerchicken. World JBiol Pharm Health Sci.2020;4(2\:16.
- 22. Semacula J, Lusembo P, Kugonza DR, Mutetikka D, Ssennyonjo J, Mwesigwa M. Estimationoflivebodyweightusingzoometricalmeasurementsforimprovedmarketingofindigenouschickeninthe Lake Victoriabasinof Uganda.2011.
- 23. SPSS. Statisticalpackageforsocialsciencesstudy SPSSfor Windows, Version
- 20. Chicago: SPSSInc;2001.
- 24. Tyasi TL, Mashiloane K, Mokoena K. Humansecurityinthelightofthecurrentclimateagenda. Sib JLife Sci Agric.2021;13(1\:13443. doi:10.12731/2658-6649-2021-13-1-134-143.
- 25. Washaya S, Bvirwa W, Nyamushamba GB. Herd International Journalof Multidisciplinary Researchand Growth Evaluationwww. allmultidisciplinaryjournal. com515|Pagedynamics, phenotypiccharacteristicsofindigenousbeefcattlebreeds(Bosindicus\in Gokwe North. Trans RSoc SAfr.2022;77(2\:19.
- 26. Weimer SL, Mauromoustakos A, Karcher DM, Erasmus MA. Differencesinperformance, bodyconformationandwelfareofconventionalandslow-growingbroilerchickensraisedat2stockingdensities. Poult Sci.2020;99(9\:4398407.