THE SCHAFFER FORMULA CAN’T PREDICT LIVEWEIGHT IN BACK BELLY SHEEP
Abstract
Keywords
Full Text:
PDFReferences
Arredondo, R.V., Macedo, B.R., Molina, C.J., Magaña, A.J., Prado, R.O., García, M.L.J., Herrera, C.A. and Lee, R.H., 2013. Morphological characterization of Pelibuey sheep in Colima, México. Tropical Animal Health and Production, 45, pp.895-900. https://doi.org/10.1007/s11250-012-0303-1
Costa, R.G., Lima, A.G.V.D.O., Ribeiro, N.L., Medeiros, A.N., Medeiros, G.R., Gonzaga-Neto, S. and Oliveira, R.L., 2020. Predicting the carcass characteristics of Morada Nova lambs using biometric measurements. Revista Brasileira de Zootecnia, 49, p.e20190179. https://doi.org/10.37496/rbz4920190179
Jagdale, V. Y., Thombre, B. M. and Chauhan, D.S., 2018. Studies on linear body measurements of khillar calves in the breeding tract of Maharashtra. International Journal of Chemical Studies, 6(4), pp.3087–95.
Johnson, D.W., 1939. Livestock weights from measurements. Extension Folder 70, Minn Agri Ext.
Karna, D. K., Acharya, A. P., Das, B. C., Nayak, G. and Dibyadarshini, M. R. 2022. Comparison of regression methods and Shaeffer`s formula in prediction of live body weight of Ganjam Goats. The Indian Journal of Animal Sciences, 92(6), pp.770-775. https://doi.org/10.56093/ijans.v92i6.108921
Magaña-Monforte, J.G., Huchin-Cab, M., Ake-López, J.R. and Segura-Correa, J.C., 2013. A field study of reproductive performance and productivity of Pelibuey ewes in Southeastern Mexico. Tropical Animal Health and Production, 45: pp 1771-1776. https://doi.org/10.1007/s11250-013-0431-2
Málková, A., Ptá?ek, M., Chay-Canul, A. and Stádník, L., 2021. Statistical models for estimating lamb birth weight using body measurements. Italian Journal of Animal Science, 20(1), pp. 1063-1068. https://doi.org/10.1080/1828051X.2021.1937720
Navarro, K.L.M., Yostar, E.J., Romero, M.S.I., Smahlij, J.M., Ondo, M.L.M., Revidatti, M.A. and Capellari A., 2023. Predicción del peso corporal en biotipos del nordeste argentino. Actas Iberoamericanas de Conservación Animal, 18, pp. 28-30. https://aicarevista.jimdo.com
R-Core Team, 2023. _R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/
Salazar-Cuytun, R., García-Herrera, R.A., Muñoz-Benitez, A.L., Camacho-Pérez, E., Muñoz-Osorio, G.A., Ptacek, M., Portillo-Salgado, R., Vargas-Bello-Perez, E. and Chay-Canul, A.J., 2021. Relationship between body volume and body weight in Pelibuey ewes. Tropical and Subtropical Agroecosystems, 24(3), pp.125. http://dx.doi.org/10.56369/tsaes.3856
Salazar-Cuytun, R., Portillo-Salgado, R., García-Herrera, R.A., Camacho-Pérez, E., Zaragoza-Vera, C.V., Gurgel, A.L.C. and Chay-Canul, A.J., 2022. Prediction of live weight in growing hair sheep using the body volume formula. Arquivo Brasileiro de Medicina Veterinária e Zootecnia, 74, pp.483-489. https://doi.org/10.1590/1678-4162-12624
Tirink, C., 2022. Comparison of bayesian regularized neural network, random forest regression, support vector regression and multivariate adaptive regression splines algorithms to predict body weight from biometrical measurements in thalli sheep. Kafkas Üniversitesi Veteriner Fakültesi Dergisi, 28, (3) pp. 411-419. https://doi.org/10.9775/kvfd.2022.27164
Vaidya, M.M., Kulkarni, S.S., Dongre, V.B., Kokate, L.S., Khandait, V.N. and Kale, S.B., 2023. Comparative efficacy of three different methods for prediction of live body weight in small ruminants. The Indian Journal of Animal Sciences, 88(5), pp. 602-605. https://doi.org/10.56093/ijans.v88i5.80008
Vazquez-Martinez, I., T?r?nk, C., Salazar-Cuytun, R., Mezo-Solis, J. A., Garcia Herrera, R. A., Orzuna-Orzuna, J.F. and Chay-Canul, A.J., 2023. Predicting body weight through biometric measurements in growing hair sheep using data mining and machine learning algorithms. Tropical Animal Health and Production, 55 (5), pp 307-316. https://doi.org/10.1007/s11250-023-03717-x
Wangchuk, K., Wangdi, J. and Mindu, M., 2018. Comparison and reliability of techniques to estimate live cattle body weight, Journal of Applied Animal Research, 46(1), pp.349-352. https://doi.org/10.1080/09712119.2017.1302876
URN: http://www.revista.ccba.uady.mx/urn:ISSN:1870-0462-tsaes.v27i3.56464
DOI: http://dx.doi.org/10.56369/tsaes.5646
Copyright (c) 2024 Pedro Colorado-Garcia, Alfonso Juventino Chay Canul, José Luis Ponce-Covarrubias, Roberto Carlos Barrientos-Medina, Clauidia V. Zaragoza-Vera, Martiza Zaragoza-Vera, Oswaldo M. Torres-Chable

This work is licensed under a Creative Commons Attribution 4.0 International License.