Herd management information systems to support cattle population research: the VAMPP® case
DOI:
https://doi.org/10.15517/am.v31i1.37062Keywords:
information technology, dairy cattle, tropical zonesAbstract
Introduction. Livestock information systems, besides being indispensable for the daily management of the herd, can serve as a basis for research at the population level. Objective.The objective of the study was to analyze the role of the VAMPP® system as a source of information for cattle population research over 32 years of evolution in Costa Rica. Materials and methods. A statistical analysis of the system database (VAMPP®) covering the period between 1987 and 2018 was carried out. Trends in the dissemination and adoption of the system were evaluated according to period, area, production system, and herd size. The use of information for the exploration of trends by breed and area was exemplified. The contribution of the system at the academy level and production of scientific literature was quantified. Results. 2285 herds (88.8 % specialized dairy and 11.2 % dual purpose) were counted with an average of 9.4±7.9 years of follow-up in the VAMPP® system. The areas with greater diffusion were the very humid premontane forest (29 %) and very humid tropical forest (25 %). The average size of the herd was 124±255 adult cows. The system contains records on 404 316 cows, mostly of Holstein (36.3 %), Jersey (24.6 %), and Holstein×Jersey (20.9 %) breeds. The database includes information on 1,249,557 calvings, 16,223,260 records of daily milk production, and 443,108 health events, predominantly related to mastitis (35.6 %) and laminitis (14.1 %). The system has been used for the elaboration of at least 74 investigations leading to academic degrees and the production of 71 scientific articles, mainly related to health and genetic issues. Conclusion. The information obtained from the VAMPP® system has allowed a detailed characterization of the productive performance of local dairy cattle.
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References
Aguirre-Valverde, J., B. Vargas-Leitón, y J.J. Romero-Zúñiga. 2013a. Efecto de la endogamia sobre parámetros productivos en vacas Holstein y Jersey de Costa Rica. Agron. Costarricense 37:31-44.
Aguirre-Valverde, J., B. Vargas-Leitón, y J.J. Romero-Zúñiga. 2013b. Efectos de la endogamia sobre parámetros reproductivos en vacas Holstein y Jersey de Costa Rica. Agron. Mesoam. 24:245-255. doi:10.15517/AM.V24I2.12523
Baaijen, M., and E. Pérez. 1995. Information technology in the Costa Rican dairy sector: A key instrument in extension and on-farm research. Agric. Hum. Values 12:45-51. doi:10.1007/BF02217296
Cabral-Ribeiro, P.C., A.J. Scavarda, M.O. Batalha, and D. Bailey. 2009. Application of an IT evaluation method: Case studies in American ranches. Int. J. e-Bus. Manag. 3:20-34. doi:10.3316/IJEBM0302024
Cornou, C., and A.R. Kristensen. 2013. Use of information from monitoring and decision support systems in pig production: Collection, applications and expected benefits. Livest. Sci. 157:552-567. doi:10.1016/j.livsci.2013.07.016
Cuevas-Reyes, V., J. Baca-del-Moral, F. Cervantes-Escoto, J.A. Espinosa-García, J. Aguilar-Ávila, y A. Loaiza-Meza. 2013. Factores que determinan el uso de innovaciones tecnológicas en la ganadería de doble propósito en Sinaloa, México. Rev. Mex. Cienc. Pecu. 4:31-46.
Eastwood, C.R., D.F. Chapman, and M.S. Paine. 2009. Farmers as co-developers of innovative precision farming systems. In: A. Bregt et al., editors, Proceedings of the 7th European Federation of Information Technology in Agriculture Conference. European Federation of Information Technology in Agriculture, Wageningen, NLD. p. 585-591.
Fountas, S., G. Carli, C.G. Sørensen, Z. Tsiropoulos, C. Cavalaris, A. Vatsanidou, B. Liakos, M. Canavari, J. Wiebensohn, and B. Tisserye. 2015. Farm management information systems: Current situation and future perspectives. Comput. Electron. Agric. 115:40-50.
Guillén-Gámez, A.A. 2015. Asociación entre variables espaciales y eficiencia productiva en hatos lecheros usuarios del programa VAMPP- bovino- Costa Rica. Tesis M.Sc., Universidad Nacional, Heredia, CRI.
Holdridge, L.R. 1987. Ecología basada en zonas de vida. Trad. por H. Jiménez-Saa. IICA, San José, CRI.
INEC (Instituto Nacional de Estadística y Censos). 2015. VI censo nacional agropecuario: Resultados generales. Instituto Nacional de Estadística y Censos, San José, CRI.
Kaler, J., and A. Ruston. 2019. Technology adoption on farms: Using Normalisation Process Theory to understand sheep farmers’ attitudes and behaviours in relation to using precision technology in flock management. Prev. Vet. Med. 170:104715. doi:10.1016/j.prevetmed.2019.104715
Kristensen, A.R., L. Nielsen, and M.S. Nielsen. 2012. Optimal slaughter pig marketing with emphasis on information from on-line live weight assessment. Livest. Sci. 145:95-108. doi:10.1016/j.livsci.2012.01.003
León-Hidalgo, H. 2015. Rol de la gestión de datos en la ganadería ecoeficiente. UTN Informa 74:76-81.
Mora, M.G., B. Vargas, J.J. Romero, y J. Camacho. 2015. Factores de riesgo para la incidencia de mastitis clínica en ganado lechero de Costa Rica. Agron. Costarricense 39:77-89.
Mora, M.G., B. Vargas, J.J. Romero, y J. Camacho. 2016. Efecto de factores genéticos y ambientales sobre el recuento de células somáticas en ganado lechero de Costa Rica. Agron. Costarricense 40:7-18. doi:10.15517/RAC.V40I2.27346
Noordhuizen, J., and J. Buurman. 1984. VAMPP: a veterinary automated management and production control programme for dairy farms (the application of MUMPS for data processing). Vet. Quarter. 6(2):66-72. doi:10.1080/01652176.1984.9693914
Parker-Gaddis, K.L., J.B. Cole, J.S. Clay, and C. Maltecca. 2012. Incidence validation and relationship analysis of producer recorded health event data from on-farm computer systems in the United States. J. Dairy Sci. 95:5422-5435. doi:10.3168/jds.2012-5572
Parker-Gaddis, K.L., J.B. Cole, J.S. Clay, and C. Maltecca. 2014. Genomic selection for producer-recorded health event data in US dairy cattle. J. Dairy Sci. 97:3190-3199. doi:10.3168/jds.2013-7543
Pérez, E., M.T. Baayen, E. Capella, and H. Barkema. 1989. Development of a livestock information system for Costa Rica. In: H: Kuil et al., editors, Proceedings 4th International Conference of the Institute of Tropical Veterinary Medicine, Livestock production and diseases in the tropics. Institute of Tropical Veterinary Medicine, Utrecht, NED. p. 221-224.
Pérez, A., M. Milla, y M. Mesa. 2006. Impacto de las tecnologías de la información y la comunicación en la agricultura. Cul. Trop. 27:11-17.
Quirós-Quirós, E. 2006. Historia de la ganadería bovina en Costa Rica. StudyLib, ESP. https://studylib.es/doc/4783165/ (consultado 01 Jul. 2016).
Romero-Zúñiga, J.J., J. Rojas-Campos, y S. Estrada-König. 2011. El programa VAMPP bovino como herramienta de apoyo a la toma de decisiones en los sistemas de producción bovinos. Ventana Lechera 16(5):4-14.
Rojas-Campos, J., J.J. Romero-Zúñiga, y S. Estrada-König. 2011. VAMPP: Un programa en constante evolución. Ventana Lechera 16(5):47-56.
Rose, D.C., W.J. Sutherland, C. Parker, M. Lobley, M. Winter, C. Morris, S. Twining, C. Foulkes, T. Amano, and L.V. Dicks. 2016. Decision support tools for agriculture: towards effective design and delivery. Agric. Syst.149:165-174. doi:10.1016/j.agsy.2016.09.009
Ruiz-Jaramillo, J.I. 2017. Variabilidad climática en las regiones norte, central y caribe y su asociación con variables productivas en fincas lecheras costarricenses. Tesis M.Sc., Universidad Nacional, Heredia, Costa Rica.
Saborío-Montero, A., B. Vargas-Leitón, J.J. Romero-Zúñiga, and J. Camacho-Sandoval. 2018. Additive genetic and heterosis effects for milk fever in a population of Jersey, Holstein×Jersey, and Holstein cattle under grazing conditions. J. Dairy Sci.101:9128-9134. doi:10.3168/jds.2017-14234
Saborío-Montero, A., B. Vargas-Leitón, J.J. Romero-Zúñiga, and J.M. Sánchez. 2017. Risk factors associated with milk fever occurrence in grazing dairy cattle. J. Dairy Sci.100:9715-9722. doi:10.3168/jds.2017-13065
Salas-González, J.M., J.A. Leos-Rodríguez, L.M. Sagarnaga-Villegas, y M.J. Zavala-Pineda. 2013. Adopción de tecnologías por productores beneficiarios del programa de estímulos a la productividad ganadera (PROGAN) en México. Rev. Mex. Cienc. Pecu. 4:243-254.
Solano-López, M., B. Vargas-Leitón, A. Saborío-Montero, y D. Pichardo-Matamoros. 2018. Factores genéticos y ambientales en lesiones podales del ganado lechero en Costa Rica. Agron. Mesoam. 29:123-140. doi:10.15517/ma.v29i1.28027
Tomaszewski, M.A., M.A.P.M. van-Asseldonk, A.A. Dijkhuizen, and R.B.M. Huirne. 2000. Determining farm effects attributable to the introduction and use of a dairy management information system in The Netherlands. Agric. Econ. 23:79-86. doi:10.1111/j.1574-0862.2000.tb00085.x
Tsiropoulos, Z., G. Carli, E. Pignatti, and S. Fountas. 2017. Future perspectives of farm management information systems In: S.M. Pedersen, and K.M. Lind, editors, Precision agriculture: Technology and economic perspectives, progress in precision agriculture. Springer International Publishing, Cham, SWE. p. 181-200. doi:10.1007/978-3-319-68715-5_9
Udo, H.M.J., and B.O. Brouwer. 1993. A computerised method for systematically analysing the livestock component of farming systems. Comp. Electron. Agric. 9:335-356. doi:10.1016/0168-1699(93)90050-B
Vargas-Leitón, B. 2012. Mejoramiento genético del ganado lechero: el contexto global y local. InfoHolstein 2012(Diciembre):6-14.
Vargas-Leitón, B. 2013. Mejoramiento genético: herramienta para incrementar la productividad del hato lechero. UTN Informa 66:6-14.
Vargas-Leitón, B., y M. Cuevas-Abrego. 2009. Modelo estocástico para estimación de valores económicos de rasgos productivos y funcionales en ganado lechero. Agrociencia 43:881-893.
Vargas-Leitón, B., Y. Marín-Marín, y J.J. Romero-Zúñiga. 2012. Comparación bioeconómica de grupos raciales Holstein, Jersey y F1 Holstein×Jersey en la zona de vida Bosque muy Húmedo Premontano. Agron. Mesoam. 23:329-342. doi:10.15517/AM.V23I2.6533
Vargas-Leitón, B., y J. Romero-Zúñiga. 2010. Efectos genéticos aditivos y no aditivos en cruces rotacionales entre razas lecheras. Agron. Mesoam. 21:223-234. doi:10.15517/AM.V21I2.4885
Vargas-Leitón, B., O. Solís-Guzmán, F. Saénz-Segura, y H. León-Hidalgo. 2013. Caracterización y clasificación de hatos lecheros en Costa Rica mediante análisis multivariado. Agron. Mesoam. 24:257-275. doi:10.15517/am.v24i2.12525
Vargas-Leitón, B., O. Solís-Guzmán, F. Saénz-Segura, y H. León Hidalgo. 2015. Eficiencia técnica en hatos lecheros de Costa Rica. Agron. Mesoam. 26:1-15. doi:10.15517/AM.V26I1.16886
Verstegen, J.A.A.M. 1997. Outlining economic modules for farm management information systems in Costa Rica: Report of a LEI-DLO mission to the Veterinary School of the National University of Costa Rica. Wageningen University and Research, Wageningen, NDL. https://library.wur.nl/WebQuery/wurpubs/fulltext/400407 (accessed Jul. 01, 2016)
Vilaseca, J., J. Torrent, y Á Díaz. 2002. La economía del conocimiento: paradigma tecnológico y cambio estructural. Un análisis empírico e internacional para la economía española. Working Paper Series WP02-003. Universitat Oberta de Catalunya, ESP. http://www.uoc.edu/in3/dt/20007/index.html (consultado 01 Jul. 2016).
Zwald, N.R., K.A. Weigel, Y.M. Chang, R.D. Welper, and J.S. Clay. 2004a. Genetic selection for health traits using producer-recorded data. I. Incidence rates, heritability estimates, and sire breeding values. J. Dairy Sci. 87:4287-4294. doi:10.3168/jds.S0022-0302(04)73573-0
Zwald, N.R., K.A. Weigel, Y.M. Chang, R.D. Welper, and J.S. Clay. 2004b. Genetic selection for health traits using producer-recorded data. II. Genetic correlations, disease probabilities, and relationships with existing traits J. Dairy Sci. 87:4295-4302. doi.org/10.3168/jds.S0022-0302(04)73574-2
Zwald, N.R., K.A. Weigel, Y.M. Chang, R.D. Welper, and J.S. Clay. 2006. Genetic analysis of clinical mastitis data from on-farm management software using threshold models. J. Dairy Sci. 89:330-336. doi.org/10.3168/jds.S0022-0302(04)73574-2
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