Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana

ilustraciones, tablas

Autores:
Parra Forero, Diana Marcela
Tipo de recurso:
Fecha de publicación:
2022
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
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oai:repositorio.unal.edu.co:unal/81546
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/81546
https://repositorio.unal.edu.co/
Palabra clave:
630 - Agricultura y tecnologías relacionadas::636 - Producción animal
Forrajes
Búsqueda de alimento
Nutrición animal
forage
foraging
animal nutrition
Forraje
Heces
Marcadores
Nutrición animal
Análisis espectral
animal nutrition
feces
forage
markers
spectral analysis
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openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional
id UNACIONAL2_f1b62908f9e100a4b2e787623e94b1f3
oai_identifier_str oai:repositorio.unal.edu.co:unal/81546
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana
dc.title.translated.eng.fl_str_mv Estimation of voluntary intake and digestibility of organic matter in sheep by means of fecal analysis by near-infrared reflectance spectroscopy
title Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana
spellingShingle Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana
630 - Agricultura y tecnologías relacionadas::636 - Producción animal
Forrajes
Búsqueda de alimento
Nutrición animal
forage
foraging
animal nutrition
Forraje
Heces
Marcadores
Nutrición animal
Análisis espectral
animal nutrition
feces
forage
markers
spectral analysis
title_short Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana
title_full Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana
title_fullStr Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana
title_full_unstemmed Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana
title_sort Estimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercana
dc.creator.fl_str_mv Parra Forero, Diana Marcela
dc.contributor.advisor.none.fl_str_mv Ariza Nieto, Claudia Janeth
dc.contributor.author.none.fl_str_mv Parra Forero, Diana Marcela
dc.contributor.financer.none.fl_str_mv Ministerio de Agricultura y Desarrollo Rural
dc.contributor.researchgroup.spa.fl_str_mv Microbiología y Nutrición Animal del Trópico
dc.subject.ddc.spa.fl_str_mv 630 - Agricultura y tecnologías relacionadas::636 - Producción animal
topic 630 - Agricultura y tecnologías relacionadas::636 - Producción animal
Forrajes
Búsqueda de alimento
Nutrición animal
forage
foraging
animal nutrition
Forraje
Heces
Marcadores
Nutrición animal
Análisis espectral
animal nutrition
feces
forage
markers
spectral analysis
dc.subject.agrovocuri.spa.fl_str_mv Forrajes
Búsqueda de alimento
Nutrición animal
dc.subject.agrovocuri.eng.fl_str_mv forage
foraging
animal nutrition
dc.subject.proposal.spa.fl_str_mv Forraje
Heces
Marcadores
Nutrición animal
Análisis espectral
dc.subject.proposal.eng.fl_str_mv animal nutrition
feces
forage
markers
spectral analysis
description ilustraciones, tablas
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-06-09T14:52:45Z
dc.date.available.none.fl_str_mv 2022-06-09T14:52:45Z
dc.date.issued.none.fl_str_mv 2022
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/TM
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/81546
dc.identifier.instname.spa.fl_str_mv Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv https://repositorio.unal.edu.co/
url https://repositorio.unal.edu.co/handle/unal/81546
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.references.spa.fl_str_mv Acamovic, T., Murray, I., & Paterson, R. M. (1992). The use of NIR in predicting chromic oxide in diets. In Murray I. and A.I., eds. Making light work. Advances in near infrared spectroscopy. Ian Michael Publications, pp 250-252.
Adesogan, A. T., Givens, D. I., & Owens, E. (2000). Measuring chemical composition and nutritive values in forages. Field and laboratory methods for grassland and animal production research. In CAB International (pp. 263–278).
AGROSAVIA. (2017). AlimenTro [Sistema de información].https://Alimentro.Agrosavia.co/
Akdağ, A., & Ocak, N. (2019). Herbage Intake Determination Methods of Grazing Animals. Animal Science, 52 (1).
Allen, M. S. (1996). Physical constrains on voluntary intake of forages by ruminants. Journal Animal Science, 74, 3063–3075.
Allison, C. D. (1985). Factors affecting forage intake by range ruminants: a review. J. Range Manage., 38, 305.
Andueza, D., Picard, F., Dozias, D., & Aufrère, J. (2017). Fecal Near-Infrared Reflectance Spectroscopy Prediction of the Feed Value of Temperate Forages for Ruminants and Some Parameters of the Chemical Composition of Feces: Efficiency of Four Calibration Strategies. Applied Spectroscopy, 71(9), 2164–2176. https://doi.org/10.1177/0003702817712740
Arana, I., Jarén, C., & Arazuri, S. (2005). Maturity, Variety and Origin Determination in White Grapes (Vitis Vinifera L.) Using near Infrared Reflectance Technology. J. Near Infrared Spectrosc., 13(6), 349–357.
Ariza-Nieto, C., Mayorga, O. L., Mojica, B., Parra, D., & Afanador-Tellez, G. (2018). Use of LOCAL algorithm with near infrared spectroscopy in forage resources for grazing systems in Colombia. Journal of Near Infrared Spectroscopy, 26(1), 44–52. https://doi.org/10.1177/0967033517746900
Arthington, J. D., & Brown, W. F. (2005). Estimation of feeding value of four tropical forage species at two stages of maturity. Journal Animal Science, 83, 1726–1731.
Azevedo, E. B., Poli, C. H. E. C., David, D. B., Amaral, G. A., Fonseca, L., Carvalho, P. C. F., Fischer, V., & Morris, S. T. (2014). Use of faecal components as markers to estimate intake and digestibility of grazing sheep. Livestock Science, 165(1), 42–50. https://doi.org/10.1016/j.livsci.2014.04.018
Barnicoat, C. R. (1945). Estimation of apparent digestibility coefficients by means of an inert reference-substance. New Zealand Journal of Science and Technology, 27(A), 202– 212.
Bartiaux-Thill, N., & Oger, R. (1986). The indirect estimation of the digestibility in cattle of herbage from Belgian permanent pasture. Grass Forage Sci, 41, 269–272.
Baumont, R., Prache, S., Meuret, M., & Morand-Fehr, P. (2000). How forage characteristics influence behaviour and intake in small ruminants: a review. Livestock Science, 64, 15–28.
Bender, R. W., Cook, D. E., & Combs, D. K. (2016). Comparison of in situ versus in vitro methods of fiber digestion at 120 and 288 hours to quantify the indigestible neutral detergent fiber fraction of corn silage samples. Journal of Dairy Science, 99(7), 5394–5400. https://doi.org/10.3168/jds.2015-10258
Bettero, V. P., Campos, A. F., Dib, V., del Valle, T. A., Zilio, E. M. C., Teixeira, I. A. M. A., Siqueira, G. R., & Rennó, F. P. (2021). Indigestible neutral detergent fiber evaluation with incubation in different species. Archivos de Zootecnia, 70(269), 14–19. https://doi.org/10.21071/az.v70i269.5413
Blaxter, K. L., Graham, N., & Wainman, F. W. (1956). Some observations on the digestibility of food by sheep and on related problems. Br. J. Nutr., 10, 69–91
Boval, M., Ortega-Jimenez, E., Fanchone, A., & Alexandre, G. (2010). Diet attributes of lactating ewes at pasture using faecal NIRS and relationship to pasture characteristics and milk production. Journal of Agricultural Science, 148(4), 477–485. https://doi.org/10.1017/S0021859610000298
Brogna, N., Palmonari, A., Canestrari, G., Mammi, L., Dal Prà, A., & Formigoni, A. (2018). Technical note: Near infrared reflectance spectroscopy to predict fecal indigestible neutral detergent fiber for dairy cows. Journal of Dairy Science, 101(2), 1234–1239. https://doi.org/10.3168/jds.2017-13319
Cabral, S., Augusto, J., Azevêdo, G., Santos, D., Gustavo, L., Pereira, R., Almeida, F. M. de, Lins, L., & Lima, R. F. de. (2017). Evaluation of internal markers as determinants of fecal dry matter output and digestibility in feedlot sheep. 3331–3340. https://doi.org/10.5433/1679-0359.2017v38n5p3331
Castañeda-Serrano, R. D., Piñeros-Varón, R., & Vélez-Giraldo, A. (2018). Foliage of tropical arboreal species in feeding ovines (Ovis Aries): Intake, digestibility and balance nitrogen. Boletin Cientifico Del Centro de Museos, 22(1), 58–68. https://doi.org/10.17151/bccm.2018.22.1.4
Church, D. C., Pond, W. G., & Pond, K. R. (2002). Fundamentos de nutrición y alimentación de animales.
Coates, D. B., & Dixon, R. M. (2011). Developing robust faecal near infrared spectroscopy calibrations to predict diet dry matter digestibility in cattle consuming tropical forages. J. Near Infrared Spectrosc., 19, 507–519.
Coates, D. B., & Penning, P. (2000). Measuring animal performance (L. Mannetje & R. M. Jones, Eds.; Mannetje L).
Coleman, S. W., Christiansen, S., & Shenk, J. S. (1990). Prediction of botanical composition using nIrS calibrations developed from botanically pure samples. Crop Sci., 30, 202.
Coleman, S. W., Stuth, J. W., & Holloway, J. W. (1989). Monitoring the nutrition of grazing cattle with near-infrared analysis of faeces. XVI International Grassland Congress, Nice, France, 881–882.
Compere, R., Valdivia, J., Hellemans, P., Guns, M., & Vandenbyvang, P. (1992). Comparaison de deux methodes utilisant le Cr2O3 pour estimer la quantite de feces emises par les moutons: pellets de luzerne et bolus CAPTEC-CRD. Bull. Rech. Agron., 27, 365–383.
Correa, H. J. (2011). Efecto del manejo del pastoreo y la suplementacion alimenticia en vacas lactantes de sistemas especializados sobre su metabolismo energetico y proteico y el contenido de proteina en la leche.
Correa, H. J., Pabon, M. L., & Carulla, J. E. (2009). Estimación del consumo de materia seca en vacas Holstein bajo pastoreo en el trópico alto de Antioquia Estimation of dry matter intake of lactating Holstein cows under grazing in Antioquia Summary. Livestock Research for Rural Development.
Côrtes, C., Damasceno, J. C., Bechet, G., & Prache, s. (2005). Species composition of ryegrass (Lolium perenne) and tall fescue (Festuca arundinacea) mixtures using various combinations of n‐alkanes. Grass and Forage Science, 60, 254–261. https://doi.org/10.1111/j.1365-2494.2005.00473.x
Cottle, D. (2013). The trials and tribulations of estimating the pasture intake of grazing animals. Animal Production Science, 53, 1209. https://doi.org/10.1071/AN13164
Cozzolino, D., LaMann, A., & VazMartins, D. (2002). Use of near infrared reflectance spectroscopy to analyze bovine faecal samples. J. Near Infrared Spectrosc., 10, 309–314. https://doi.org/doi:10.1255/ jnirs.347
Davies, A. M., & Grant, A. (1987). Near infra‐red analysis of food. International Journal of Food Science & Technology, 22(3), 191–207.
Davison, C., Bowen, J. M., Michie, C., Rooke, J. A., Jonsson, N., Andonovic, I., Tachtatzis, C., Gilroy, M., & Duthie, C. A. (2021). Predicting feed intake using modelling based on feeding behaviour in finishing beef steers. Animal, 15(7). https://doi.org/10.1016/j.animal.2021.100231
de Souza, J., Batistel, F., Welter, K. C., Silva, M. M., Costa, D. F., & Portela Santos, F. A. (2014). Evaluation of external markers to estimate fecal excretion, intake, and digestibility in dairy cows. Tropical Animal Health and Production, 47(1), 265–268. https://doi.org/10.1007/s11250-014-0674-6
Decruyenaere, V., Buldgen, A., & Stilmant, D. (2009). Factors affecting intake by grazing ruminants and related quantification methods : a review. Biotechnol. Agron. Soc. Environ., 13(4), 559–573.
Decruyenaere, V., Lecomte, P., Demarquilly, C., Aufrere, J., Dardenne, P., Stilmant, D., & Buldgen, A. (2009a). Evaluation of green forage intake and digestibility in ruminants using near infrared reflectance spectroscopy (NIRS): Developing a global calibration. Animal Feed Science and Technology, 148(2–4), 138–156. https://doi.org/10.1016/j.anifeedsci.2008.03.007
Decruyenaere, V., Lecomte, P., Demarquilly, C., Aufrere, J., Dardenne, P., Stilmant, D., & Buldgen, A. (2009b). Evaluation of green forage intake and digestibility in ruminants using near infrared reflectance spectroscopy (NIRS): Developing a global calibration. Animal Feed Science and Technology, 148(2–4), 138–156. https://doi.org/10.1016/j.anifeedsci.2008.03.007
Decruyenaere, V., Peters, M., Stilmant, D., Lecomte, P., & Dardenne, P. (2003). Near infrared reflectance spectroscopy applied to faeces to predict dry matter intake of sheep under grazing, comparison with N-alkanes and direct biomass measurement methods. In H.-C. J. & S.-C. C.A. (Eds.), Tropical and Subtropical Agroecosystems: The Sixth International Symposium on the Nutrition of Herbivores: matching herbivore nutrition to ecosystems biodiversity (pp. 471–475). Faculty of Veterinary Medicine & Animal Science Autonomous University of Yucatan, Mexico.
Decruyenaere, V., Planchon, V., Dardenne, P., & Stilmant, D. (2015). Prediction error and repeatability of near infrared reflectance spectroscopy applied to faeces samples to predict voluntary intake and digestibility of forages by ruminants. Animal Feed Science and Technology, 205, 49–59. https://doi.org/10.1016/j.anifeedsci.2015.04.011
Decruyenaere, V., Visser, M., Stilmant, D., Clément, C., & Sinnaeve, G. (2004). Faecal near infrared reflectance spectroscopy for ruminant feed intake prediction. Grass and Forage Science, 1034, 9.
Detmann, E., Gionbelli, M. P., & Huhtanen, P. (2014). A meta-analytical evaluation of the regulation of voluntary intake in cattle fed tropical forage-based diets. Journal Animal Science, 92, 4632–4641. https://doi.org/doi:10.2527/jas2014-7717
Dixon, R., & Coates, D. (2009). Review: Near infrared spectroscopy of faeces to evaluate the nutrition and physiology of herbivores. In Journal of Near Infrared Spectroscopy (Vol. 17, Issue 1, pp. 1–31). https://doi.org/10.1255/jnirs.822
Dixon, R. M., & Coates, D. B. (2005). The use of faecal NIRS to improve nutritional management of cattle in northern Australia. 15, 65–76.
Fanchone, A., Boval, M., & Archimède, H. (2007). Faecal indices based on near infrared spectroscopy to assess intake, in vivo digestibility and chemical composition of the herbage ingested by sheep. 113, 107–113. https://doi.org/10.1255/jnirs.720
Faverdin, P., Delagarde, R., Delaby, L., & Meschy, F. (2007). Alimentation des vaches laitieres. In Alimentation des Bovins, Ovins et Caprins: Besoins des Animaux-Valeur des Aliments. Edi- tions Quae, Versailles Cedex, France. 23–57.
FEDEGAN.(2021).Coyuntura-Ganadera-Semestre-1-2021. https://www.fedegan.org.co/estadisticas/documentos-de-estadistica
Ferrell, C. L., Koong, L. J., & Nienaber, J. A. (1986). Effect of previous nutrition on body composition and maintenance energy cost growing lambs. Br. J. Nutr., 56, 595–605.
Foley, W. J., McLean, S., & Cork, S. J. (1995). Consequences of biotransformation of plant secondary metabolites on acid-base metabolism in mammals- A final common pathway? J. Chem. Ecol., 21, 721–743. https://doi.org/doi:10.1007/BF02033457
Galyean, M. L., & Gunter, S. A. (2016). Predicting forage intake in extensive grazing system. Animal Science, 26–43. https://doi.org/10.2527/jas2016-0523
Glindemann, T., Tas, B., Wang, C., Alvers, S., & Susenbeth, A. (2009). Evaluation of titanium dioxide as an inert marker for estimating faecal excretion in grazing sheep. Animal Feed Science and Technology - ANIM FEED SCI TECH, 152, 186–197. https://doi.org/10.1016/j.anifeedsci.2009.04.010
Goering, H. K., & Van Soest, P. K. (1970). Forage fiber analyses (Apparatus, reagents, procedures, and some applications). In U.S. Department of Agriculture (Issue 379). ARS-USDA.
Gordon I J. (1995). Animal-based techniques for grazing ecology research. Small Ruminant Research, 16(3), 203–214. https://doi.org/10.1016/0921-4488(95)00635-X
Gregorini, P., Gunter, S. A., Masino, C. A., & Beck, P. A. (2007). Effects of ruminal fill on short-term herbage intake rate and grazing dynamics of beef heifers.
Holechek, J. L., Vavra, M., & Piepper, R. D. (1982). Botanical composition determination of range herbivores diets: a review. J. Range Manage, 35(3), 309–315.
Holloway, J. W., Estell, I. I. R. E., & Butts Jr., W. T. (1981). Relationships between fecal components and forage consumption and digestibility. J. Anim. Sci., 52, 836–848.
Illius, A. W., & Jessop, N. S. (1996). Metabolic constraints on voluntary intake in ruminants. Journal of Animal Science, 74(12), 3052–3062. https://doi.org/10.2527/1996.74123052x
Jancewicz, L. J., Swift, M. L., Penner, G. B., Beauchemin, K. A., & Koening, K. M. (2016). Development of NIRS calibrations to estimate fecal composition and nutrient digestibility in beef cattle. Canadian Journal of Animal Science, 403, 1–33.
Jeffery, H. (1976). Effect of the live weight of caged sheep and the amount of feed on offer on estimates of digestibility and ad libitum intake. Australian Journal of Experimental Agriculture and Animal Husbandry, 16(82), 656–660.
Johnson, D. E., Dinusson, W. E., & Bolin, D. W. (1964). Rate of Passage of Chromic Oxide and Composition of Digesta along the Alimentary Tract of Wethers. Journal of Animal Science, 23(2), 499–505. https://doi.org/10.2527/jas1964.232499x
Johnson, J. R., Carstens, G. E., Prince, S. D., Ominski, K. H., Wittenberg, K. M., Undi, M., Forbes, T. D. A., Hafla, A. N., Tolleson, D. R., & Basarab, J. A. (2017). Application of fecal near-infrared reflectance spectroscopy profiling for the prediction of diet nutritional characteristics and voluntary intake in beef cattle. Journal of Animal Science, 95(1), 447. https://doi.org/10.2527/jas2016.0845
Krämer, M., Weisbjerg, M. R., Lund, P., Jensen, C. S., & Pedersen, M. G. (2012). Estimation of indigestible NDF in forages and concentrates from cell wall composition. Animal Feed Science and Technology, 177(1–2), 40–51. https://doi.org/10.1016/j.anifeedsci.2012.07.027
Kyriazakis, I. (2003). What are ruminant herbivores trying to achieve through their feeding behaviour and food intake. In: Herrera-Camacho C.A. and Sandoval-Castro J., eds. VIth International Symposium on the Nutrition of Herbivores (pp. 153–173).
Landau, S., Glasser, T., & Dvash, L. (2006). Monitoring nutrition in small ruminants with the aid of near infrared reflectance spectroscopy (NIRS) technology: A review. Small Ruminant Research, 61(1), 1–11. https://doi.org/10.1016/j.smallrumres.2004.12.012
Landau, S., Glasser, T., Dvash, L., & Perevolotsky, A. (2004). Faecal NIRS to monitor the diet of Mediterranean goats. In South African Journal of Animal Science (Vol. 34).
Landau, S., Glasser, T., Muklada, H., Dvash, L., Perevolotsky, A., Ungar, E. D., & Walker, J. W. (2005). Fecal NIRS prediction of dietary protein percentage and in vitro dry matter digestibility in diets ingested by goats in Mediterranean scrubland. Small Ruminant Research, 59(2-3 SPEC. ISS.), 251–263. https://doi.org/10.1016/j.smallrumres.2005.05.009
Langlands, J. P., Corbett, J. L., Mcdonald, I., & Reid, G. W. (1963). Estimation of the faeces output of grazing animals from the concentration of chromium sesquioxide in a sample of faeces. Brit. J. Nutr.
Leng, R. A. (1990). Factors affecting the utilization of poor-quality forages by ruminants particularly under tropical conditions. Nutr. Research Rev., 3, 277–303.
Li, H., Tolleson, D., Stuth, J., Bai, K., Mo, F., & Kronberg, S. (2007). Faecal near infrared reflectance spectroscopy to predict diet quality for sheep. Small Ruminant Res., 68, 263–268.
Lippke, H. (2002). Estimation of forage intake by ruminants on pasture. Crop Science, 42(3), 869-872.
Lippke, H., Barton II, F. E., & Ocumpaugh, W. R. (1989). Near infrared reflectance spectroscopy for estimation of digestible organic matter intake and body weight gain. Proceedings of the XVI International Grassland Congress, Nice, France, 893–894.
Lippke, H., Ellis, W. C., & Jacobs, B. F. (1986). Recovery of indigestible fiber from feces of sheep and cattle on forage diets. Journal of Dairy Science, 69(2), 403–412. https://doi.org/10.3168/jds.S0022-0302(86)80418-0
Lobley, G. E., Harris, P. M., Skene, P. A., Brown, D., Milne, E., Calder, A. G., Anderson, S. E., Garlick, P. J., Nevison, I., & Conell, A. (1992). Responses in tissue protein synthesis to sub and supra-maintenance intake in young, growing sheep: Comparison of large-dose and continuous-infusion techniques. Brit. J. Nutr., 68, 373–388.
Lyons, R. K., Stuth, J. W., & Holloway, J. W. (1992). Fecal NIRS equations for predicting diet quality of free-ranging cattle. J. Range Manage, 45, 238–244. https://doi.org/doi:10.2307/4002970
Magalhães, K. A., Valadares Filho, S. C., Detmann, E., Diniz, L. L., Pina, D. S., Azevedo, J. A. G., Araújo, F. L., Marcondes, M. I., Fonseca, M. A., & Tedeschi, L. O. (2010). Evaluation of indirect methods to estimate the nutritional value of tropical feeds for ruminants. Animal Feed Science and Technology, 155(1), 44–54. https://doi.org/10.1016/j.anifeedsci.2009.10.004
Mayes, R. W., & Dove, H. (2000). Measurement of dietary nutrient intake in free-ranging mammalian herbivores. Nutrition Research Reviews, 44.
Mehtiö, T., Rinne, M., Nyholm, L., Mäntysaari, P., Sairanen, A., Mäntysaari, E. A., Pitkänen, T., & Lidauer, M. H. (2016). Cow-specific diet digestibility predictions based on near-infrared reflectance spectroscopy scans of faecal samples. Journal of Animal Breeding and Genetics, 133(2), 115–125. https://doi.org/10.1111/jbg.12183
Mejia Diaz, E., Mahecha Ledesma, L., & Angulo Arizala, J. (2017). Consumo de materia seca en un sistema silvopastoril de Tithonia diversifolia en trópico alto. Agronomía Mesoamericana, 28(2), 389. https://doi.org/10.15517/ma.v28i2.23561
Mertens, D. R. (2002). Gravimetric determination of amylase-treated neutral detergent fiber in feeds with refluxing in beakers or crucibles: collaborative study. J. Assoc. Off. Anal. Chem. Intern, 85, 1217–1240.
Michael Forbes, J. (2007). A personal view of how ruminant animals control their intake and choice of food: Minimal total discomfort. In Nutrition Research Reviews (Vol. 20, Issue 2, pp. 132–146). https://doi.org/10.1017/S0954422407797834
Mioto Da Costa, M. C., Ítavo, L. C. V., Ferreira Ítavo, C. C. B., Dias, A. M., Petit, H. v., Reis, F. A., Gomes, R. C., Leal, E. S., Niwa, M. V. G., & de Moraes, G. J. (2019). Evaluation of internal and external markers to estimate faecal output and feed intake in sheep fed fresh forage. Animal Production Science, 59(4), 741–748. https://doi.org/10.1071/AN16567
Moore, J. E. (1994). Forage quality indices: development and application. In Fahey, Jr. et al. (Ed.) Forage Quality, Evaluation and Utilization. ASA. CSSA and SSSA., 967–998.
Moreno, L. A., Rueda, C., & Andrade, G. I. (2018). Biodiversidad 2017. Estados y tendencias de la biodiversidad continental de Colombia.
Morgan, C. A., & Campling, R. C. (1978). Digestibility of whole barley and oat grains by cattle of different ages. Animal Production, 27(3), 323–329. https://doi.org/10.1017/S0003356100036217
Nordheim, H., Volden, H., Fystro, G., & Lunnan, T. (2007). Prediction of in situ degradation characteristics of neutral detergent fibre (aNDF) in temperate grasses and red clover using near-infrared reflectance spectroscopy (NIRS). Animal Feed Science and Technology, 139(1–2), 92–108. https://doi.org/10.1016/j.anifeedsci.2006.11.024
Norris, K. H., Barnes, R. F., Moore, J. E., & Shenk, J. S. (1976). Predicting forage quality by Near Infrared Reflectance Spectroscopy. J. Anim. Sci., 43, 889–897
Núñez-Sánchez, N., Carrion, D., Peña Blanco, F., Domenech García, V., Garzón Sigler, A., & Martínez-Marín, A. L. (2016). Evaluation of botanical and chemical composition of sheep diet by using faecal near infrared spectroscopy. Animal Feed Science and Technology, 222, 1–6. https://doi.org/10.1016/j.anifeedsci.2016.09.010
Núñez-Sánchez, N., Martínez Marín, A. L., Hernández, M. P., Carrion, D., Castro, G. G., & Pérez Alba, L. M. (2012). Faecal near infrared spectroscopy (NIRS) as a tool to assess rabbit’s feed digestibility. Livestock Science, 150(1–3), 386–390. https://doi.org/10.1016/j.livsci.2012.07.030
Osborne, B. G., Fearn, P., & Hindle, T. (1993). Practical NIR Spectroscopy with Applications in Food and Beverage Analysis. Longman Scientific and Tecnnical. London, UK.
Oudshoorn, F. W., Cornou, C., Hellwing, A. L. F., Hansen, H. H., Munksgaard, L., Lund, P., & Kristensen, T. (2013). Estimation of grass intake on pasture for dairy cows using tightly and loosely mounted di- and tri-axial accelerometers combined with bite count. Computers and Electronics in Agriculture, 99, 227–235. https://doi.org/10.1016/j.compag.2013.09.013
Owens, F. N., & Hanson, C. F. (1992). External and Internal Markers for Appraising Site and Extent of Digestion in Ruminants. Journal of Dairy Science, 75(9), 2605–2617. https://doi.org/10.3168/jds.S0022-0302(92)78023-0
Ozaki, Y., McClure, W. F., & Christy, A. A. (2007). Near-Infrared Spectroscopy in Food Science and Technology, Wiley Interscience, Hoboken, New Jersey, USA.
Parga, J., Peyraud, J. L., & Delagarde, R. (2002). Age of regrowth affects grass intake and ruminal fermentations in grazing dairy cows. In: Durand J.L., Emile J.C., Huyghe C. and Lemaire G., eds. multi-function grasslands. Quality Forages, Animal Products and Landscape. Grassl. Sci. Eur., 7, 256–257.
Peguero, A. (2010). La espectroscopía NIR en la determinación de propiedades físicas y composición química de intermedios de producción y productos acabados. Universidad Autonoma de Barcelona.
Peripolli, V., Prates, Ê. R., Barcellos, J. O. J., & Neto, J. B. (2011). Fecal nitrogen to estimate intake and digestibility in grazing ruminants. Animal Feed Science and Technology. https://doi.org/10.1016/j.anifeedsci.2010.11.008
Peyraud, J. L., Comerón, E. A., Wade, M. H., & Lemaire, G. (1996). The effect of daily herbage allowance, herbage mass and animal factors upon herbage intake by grazing dairy cows. Ann. Zootech., 45, 201–217.
Pfister, J. A., Provenza, F. D., Manners, G. D., Gardner, D. R., & Ralphs, M. H. (1997). Tall larkspur ingestion: Can cattle regulate intake below toxic levels? J. Chem. Ecol., 23, 759–777. https://doi.org/doi:10.1023/ B: JOEC.0000006409.20279.59
Provenza, F. D., Villalba, J. J., & Dziba, L. E. (2003). Linking herbivore experience, varied diets, and plant biochemical diversity. Small Ruminant Research, 49, 257–274.
Pulina, G., Avondo, M., Molle, G., Dias Francesconi, A. H., Atzori, A. S., & Cannas, A. (2013). Invited Review Models for estimating feed intake in small ruminants
Raymond, W. F., Harris, C. E., & Haurker, V. G. (1953). Studies on the digestibility of herbage. 1. Technique of measurement of digestibility and some observations on factors affecting the accuracy of digestibility data. Journal of the British Grassland Society, 8, 301–314.
Raymond, W. F., Harris, C. E., & Kemp, C. D. (1955). Studies in the digestibility of herbage. VI. The effect of level of herbage intake on the digestibility of herbage by sheep. J. Brit. Grassl. Soc., 10, 19–26.
Rhind, S. M., Archer, Z. A., & Adam, C. L. (2002). Seasonality of food intake in ruminants: recent developments in understanding. Nutr. Research Rev., 15, 43–65.
Rihani, N., Garrett, W. N., & Zinn, R. A. (1993). Influence of level of urea, and method of supplementation on characteristics of digestion of high-fiber diets by sheep. Journal Animal Science, 71, 1657–1665.
Rombach, M., Münger, A., Niederhauser, J., Südekum, K.-H., & Schori, F. (2018). Evaluation and validation of an automatic jaw move- ment recorder (RumiWatch) on unsupplemented or supplemented dairy cows on pasture. J. Dairy Sci., 101, 2463–2475.
Romney, D. L., & Gill, M. (2009). Intake of forages. In Forage evaluation in ruminant nutrition. (Issue 1996, pp. 43–62). https://doi.org/10.1079/9780851993447.0043
Ruuska, S., Kajava, S., Mughal, M., Zehner, N., & Mononen, J. (2016). Validation of a pressure sensor-based system for measuring eating, rumination and drinking behaviour of dairy cattle. Appl. Anim. Behav. Sci., 174, 19–23.
Sampaio, C. B., Detmann, E., Neves, T., & Valente, P. (2011). Fecal excretion patterns and short-term bias of internal and external markers in a digestion assay with cattle. Revista Brasileira de Zootecnia, 657–665.
Selcuk, A., & Suphi, D. (2017). Use of Chromium Oxide and Alkane Indicator Methods for Determination of Feed Intake for Grazing Sheep. Journal of Agricultural Science and Technology A, 7(3). https://doi.org/10.17265/2161-6256/2017.03.008
Shenk, J. S., & Westerhaus, M. O. (1994). THE APPLICATION OF NEAR INFRARED REFLECTANCE SPECTROSCOPY (NIRS) TO FORAGE ANALYSIS.
Shenk, J. S., & Westerhaus, M. O. (1996). Calibration de ISI way. En Near Infrared Spectroscopy: the future waves. In W. P. Davies A.M.C. (Ed.), NIR publications.
Shenk, J. S., & Westrerhaus, M. O. (1991). Population definition, sample selection, and calibration procedures for near-infrared reflectance spectroscopy. Crop Sci., 31, 469–474.
Shenk, J. S., Workman, J. J., & Westerhaus, M. O. (2001). Application of NIR Spectroscopy to Agricultural Products. Handbook of Near Infrared Analysis. Second Edition. Burns D.A. y Ciurczak E.W. (Eds.). Practical Spectroscopy Series, Vol. 27. Marcel Dekker, USA.
Showers, E. E. (1997). Prediction of Diet Quality Parameters of White-tailed Deer Via Near Infrared Reflectance Spectroscopy (NIRS) Fecal Profiling. Texas A&M University.
Smit, H. J., Taweel, H. Z., Tas, B. M., Tamminga, S., & Elgersma, A. (2005). Comparison of Techniques for Estimating Herbage. Journal of Dairy Science, 88(5), 1827–1836. https://doi.org/10.3168/jds.S0022-0302(05)72857-5
Soto-Navarro, S. A., Lancaster, R., Sankey, C., Capitan, B. M., & Holland, B. P. (2014). Comparative digestibility by cattle versus sheep: Effect of forage quality. https://doi.org/10.2527/jas2013-6740
Stuth, J. W., Kapes, E. D., & Lyons, R. K. (1989). Use of near infrared spectroscopy to assess nutritional status of cattle diets on rangeland. XVI International Grassland Congress, Nice, France, 889–890.
UPRA. (2020). Plan de ordenamiento productivo: Analisis prospectivo de la cadena lactea bovina colombiana.
UPRA. (2021). Analisis situacional de la cadena productiva carnica bovina.
Valentine, M. E., Karayilanli, E., Cherney, J. H., & Cherney, D. J. (2019). Comparison of in vitro long digestion methods and digestion rates for diverse forages. Crop Science, 59(1), 422–435. https://doi.org/10.2135/cropsci2018.03.0159
van Soest, P. J., Robertson, J. B., & Lewis, B. A. (1991). Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci., 74, 3583–3597.
Van Wieren, S. E. (1996a). Do large herbivores select a diet that maximizes short-term energy intake rate? Forest Ecol. Manage, 88, 149–156.
Van Wieren, S. E. (1996b). Do large herbivores select a diet that maximizes short-term energy intake rate? Forest Ecol. Manage., 88, 149–156.
Velásquez, A. v, da Silva, G. G., Sousa, D. O., Oliveira, C. A., Martins, C. M. M. R., dos Santos, P. P. M., Balieiro, J. C. C., Rennó, F. P., & Fukushima, R. S. (2018). Evaluating internal and external markers versus fecal sampling procedure interactions when estimating intake in dairy cows consuming a corn silage-based diet. Journal of Dairy Science, 101(7), 5890–5901. https://doi.org/10.3168/jds.2017-13283
Ward, R. G., Smith, G. S., Wallace, J. D., Urquhart, N. S., & Shenk, J. S. (1982). Estimation of intake and quality of grazed range forage by near infrared reflectance spectroscopy. J. Anim. Sci., 54, 399–402.
Williams, P. C. (2001). Implementation of Near- Infrared Technology. En Near-Infrared Technology in the Agricultural and Food Industries, 2nd edition. In American Association of Cereal Chemists, Inc. (P.K. Willi).
Williams, P., Dardenne, P., & Flinn, P. (2017). Tutorial: Items to be included in a report on a near infrared spectroscopy project. Journal of Near Infrared Spectroscopy, 25(2). https://doi.org/10.1177/0967033517702395
Workman, J. J., & Mark, H. (2015). Choosing the Best Regression Model. J. Near Infrared Spectrosc., 30(6).
Yearsley, J., Tolkamp, B. J. N., & Illius, A. W. (2001). Theoretical developments in the study and prediction of food intake. Proc. Nutr. Soc., 60, 145–156.
Minson, D. (1990). Forage in ruminant nutrition. Academic Press Limited.
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spelling Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ariza Nieto, Claudia Janeth16d266bcdea455c19fd9c7e992346460Parra Forero, Diana Marcela63546d31e3291bf99262385a534a5e25Ministerio de Agricultura y Desarrollo RuralMicrobiología y Nutrición Animal del Trópico2022-06-09T14:52:45Z2022-06-09T14:52:45Z2022https://repositorio.unal.edu.co/handle/unal/81546Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, tablasLa digestibilidad y el consumo son dos de los principales parámetros que definen la calidad de un forraje, sin embargo, estos parámetros son difíciles y costosos de estimar. La tecnología NIRS aplicada a las heces (NIRSf) puede ser una alternativa rápida y económica para predecir la digestibilidad y el consumo voluntario en ovinos con suficiente precisión. El objetivo de este trabajo fue calibrar ecuaciones NIRSf para predicción de digestibilidad y consumo voluntario de ovinos. Los bioensayos para evaluar seis regímenes alimenticios: Kikuyo; Ryegrass; Kikuyo+Angleton; Kikuyo+Alfalfa; Kikuyo+Tilo; Kikuyo+Ensilaje de maíz, emplearon cinco ovinos en confinamiento durante seis días de medición. Se utilizaron métodos gravimétricos, uso de marcadores interno (FDNi) y externo (Cr2O3) y análisis por espectroscopia para estimar los parámetros evaluados. El forraje ofrecido, rechazado y la excreción fecal fueron pesados y colectados diariamente. Las muestras secas, molidas y tamizadas a 1 mm fueron escaneadas en el segmento espectral 400-2500 nm. Las lecturas fecales se obtuvieron del promedio de cada animal para cada régimen alimenticio evaluado. El análisis quimiométrico se realizó por el método de mínimos cuadrados parciales modificados, a los espectros se les aplicó pretratamientos matemáticos usando la primera y segunda derivada. Las calibraciones se evaluaron por medio del coeficiente de determinación en la validación cruzada (R2 ), el error estándar de la validación cruzada (SECV) y la desviación predictiva residual (RPD). Se obtuvieron promedios por el método gravimétrico para DMS de 51.5 %, DMO de 53.6%, CVMS de 1.3 kg/d y CVMO de 1.07 kg/d. Se lograron mejores calibraciones para DMS y DMO fue cuando se utilizó como método de referencia el marcador interno FDNi con la segunda derivada (2.4.4.1) y el segmento Vis+NIR con R2 0.67 y 0.71, RPD 1.78 y 1.89, respectivamente. Los mejores modelos predictivos para CVMS y CVMO expresado en kilogramos por día fue cuando se utilizó como referencia el método de marcadores con el tratamiento matemático (2.8.8.1) y el segmento NIR con R2 0.84 y 0.84, RPD 2.58 y 2.52, respectivamente, mientras que para CVMS y CVMO ajustado por el peso metabólico fue cuando se utilizó como referencia el método gravimétrico con el tratamiento matemático (2.8.8.1) y el segmento NIR con R2 0.77 y 0.78, RPD 2.11 y 2.16, respectivamente. Se concluye que el uso de NIRSf tiene potencial para la predicción de la digestibilidad y el consumo en ovinos en confinamiento, que a futuro se puede convertir en una herramienta que pueda facilitar el manejo nutricional de rumiantes en Colombia. (Texto tomado de la fuente)Digestibility and voluntary intake are two of the main parameters that define the quality of a forage, however, these parameters are difficult and expensive to estimate. NIRS technology applied to feces (F-NIRS) can be a fast and cheap alternative to predict digestibility and voluntary intake in sheep with sufficient precision. The objective of this study was to calibrate NIRSf equations for prediction of digestibility and voluntary intake of sheep. Bioassays to evaluate six nutritional regimens: Kikuyu; Ryegrass; Kikuyo+Angleton; Kikuyo+Alfalfa; Kikuyo+Tilo; Kikuyo+corn silage, used five sheep in confinement for six days of measurement. Gravimetric methods, use of internal (iNDF) and external (Cr2O3) markers and spectroscopy analysis were used to estimate the evaluating parameters. Offered and orts forage and fecal excretion were weighed and collected daily. The dried, ground and 1 mm screen samples were scanned in the 400-2500 nm spectral segment. Fecal spectra will be acquired from the average of each animal for each feeding regimen evaluated. The chemometric analysis was performed by the method of partially modified least squares, mathematical pretreatments were applied to the spectra using the first and second derivatives. Calibrations were evaluated using the cross-validation coefficient of determination (R2 ), the cross-validation standard error (SECV), and the residual predictive deviation (RPD). The averages would be increased by the gravimetric method for DMD of 51.5%, OMD of 53.6%, DMVI of 1.3 kg/d and OMVI of 1.07 kg/d. The best calibrations for DMS and OMD were achieved when the internal marker FDNi with the second derivative (2.4.4.1) and the Vis+NIR segment with R2 0.67 and 0.71, RPD 1.78 and 1.89, respectively, were obtained as the reference method. The best predictive models for CVMS and CVMO expressed in kilograms per day was when the marker method was obtained as reference with the mathematical treatment (2.8.8.1) and the NIR segment with R2 0.84 and 0.84, RPD 2.58 and 2.52, respectively, while that for DMVI and OMVI adjusted for metabolic weight was obtained when the gravimetric method with the mathematical treatment (2.8.8.1) and the NIR segment with R2 0.77 and 0.78, RPD 2.11 and 2.16, respectively, were obtained as reference. It is concluded that the use of NIRSf has potential for the prediction of digestibility and consumption in sheep in confinement, which in the future can become a tool that can facilitate the nutritional management of ruminants.MaestríaMagíster en Salud Animal o Magíster en Producción AnimalNutrición Animal92 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Medicina Veterinaria y de Zootecnia - Maestría en Salud y Producción AnimalDepartamento de Ciencias Para La Producción AnimalFacultad de Medicina Veterinaria y de ZootecniaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá630 - Agricultura y tecnologías relacionadas::636 - Producción animalForrajesBúsqueda de alimentoNutrición animalforageforaginganimal nutritionForrajeHecesMarcadoresNutrición animalAnálisis espectralanimal nutritionfecesforagemarkersspectral analysisEstimación del consumo voluntario y digestibilidad de la materia orgánica en ovinos mediante el análisis fecal por espectroscopia de reflectancia infrarroja cercanaEstimation of voluntary intake and digestibility of organic matter in sheep by means of fecal analysis by near-infrared reflectance spectroscopyTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAcamovic, T., Murray, I., & Paterson, R. M. (1992). The use of NIR in predicting chromic oxide in diets. In Murray I. and A.I., eds. Making light work. Advances in near infrared spectroscopy. Ian Michael Publications, pp 250-252.Adesogan, A. T., Givens, D. I., & Owens, E. (2000). Measuring chemical composition and nutritive values in forages. Field and laboratory methods for grassland and animal production research. In CAB International (pp. 263–278).AGROSAVIA. (2017). AlimenTro [Sistema de información].https://Alimentro.Agrosavia.co/Akdağ, A., & Ocak, N. (2019). Herbage Intake Determination Methods of Grazing Animals. Animal Science, 52 (1).Allen, M. S. (1996). Physical constrains on voluntary intake of forages by ruminants. Journal Animal Science, 74, 3063–3075.Allison, C. D. (1985). Factors affecting forage intake by range ruminants: a review. J. Range Manage., 38, 305.Andueza, D., Picard, F., Dozias, D., & Aufrère, J. (2017). Fecal Near-Infrared Reflectance Spectroscopy Prediction of the Feed Value of Temperate Forages for Ruminants and Some Parameters of the Chemical Composition of Feces: Efficiency of Four Calibration Strategies. Applied Spectroscopy, 71(9), 2164–2176. https://doi.org/10.1177/0003702817712740Arana, I., Jarén, C., & Arazuri, S. (2005). Maturity, Variety and Origin Determination in White Grapes (Vitis Vinifera L.) Using near Infrared Reflectance Technology. J. Near Infrared Spectrosc., 13(6), 349–357.Ariza-Nieto, C., Mayorga, O. L., Mojica, B., Parra, D., & Afanador-Tellez, G. (2018). Use of LOCAL algorithm with near infrared spectroscopy in forage resources for grazing systems in Colombia. Journal of Near Infrared Spectroscopy, 26(1), 44–52. https://doi.org/10.1177/0967033517746900Arthington, J. D., & Brown, W. F. (2005). Estimation of feeding value of four tropical forage species at two stages of maturity. Journal Animal Science, 83, 1726–1731.Azevedo, E. B., Poli, C. H. E. C., David, D. B., Amaral, G. A., Fonseca, L., Carvalho, P. C. F., Fischer, V., & Morris, S. T. (2014). Use of faecal components as markers to estimate intake and digestibility of grazing sheep. Livestock Science, 165(1), 42–50. https://doi.org/10.1016/j.livsci.2014.04.018Barnicoat, C. R. (1945). Estimation of apparent digestibility coefficients by means of an inert reference-substance. New Zealand Journal of Science and Technology, 27(A), 202– 212.Bartiaux-Thill, N., & Oger, R. (1986). The indirect estimation of the digestibility in cattle of herbage from Belgian permanent pasture. Grass Forage Sci, 41, 269–272.Baumont, R., Prache, S., Meuret, M., & Morand-Fehr, P. (2000). How forage characteristics influence behaviour and intake in small ruminants: a review. Livestock Science, 64, 15–28.Bender, R. W., Cook, D. E., & Combs, D. K. (2016). Comparison of in situ versus in vitro methods of fiber digestion at 120 and 288 hours to quantify the indigestible neutral detergent fiber fraction of corn silage samples. Journal of Dairy Science, 99(7), 5394–5400. https://doi.org/10.3168/jds.2015-10258Bettero, V. P., Campos, A. F., Dib, V., del Valle, T. A., Zilio, E. M. C., Teixeira, I. A. M. A., Siqueira, G. R., & Rennó, F. P. (2021). Indigestible neutral detergent fiber evaluation with incubation in different species. Archivos de Zootecnia, 70(269), 14–19. https://doi.org/10.21071/az.v70i269.5413Blaxter, K. L., Graham, N., & Wainman, F. W. (1956). Some observations on the digestibility of food by sheep and on related problems. Br. J. Nutr., 10, 69–91Boval, M., Ortega-Jimenez, E., Fanchone, A., & Alexandre, G. (2010). Diet attributes of lactating ewes at pasture using faecal NIRS and relationship to pasture characteristics and milk production. Journal of Agricultural Science, 148(4), 477–485. https://doi.org/10.1017/S0021859610000298Brogna, N., Palmonari, A., Canestrari, G., Mammi, L., Dal Prà, A., & Formigoni, A. (2018). Technical note: Near infrared reflectance spectroscopy to predict fecal indigestible neutral detergent fiber for dairy cows. Journal of Dairy Science, 101(2), 1234–1239. https://doi.org/10.3168/jds.2017-13319Cabral, S., Augusto, J., Azevêdo, G., Santos, D., Gustavo, L., Pereira, R., Almeida, F. M. de, Lins, L., & Lima, R. F. de. (2017). Evaluation of internal markers as determinants of fecal dry matter output and digestibility in feedlot sheep. 3331–3340. https://doi.org/10.5433/1679-0359.2017v38n5p3331Castañeda-Serrano, R. D., Piñeros-Varón, R., & Vélez-Giraldo, A. (2018). Foliage of tropical arboreal species in feeding ovines (Ovis Aries): Intake, digestibility and balance nitrogen. Boletin Cientifico Del Centro de Museos, 22(1), 58–68. https://doi.org/10.17151/bccm.2018.22.1.4Church, D. C., Pond, W. G., & Pond, K. R. (2002). Fundamentos de nutrición y alimentación de animales.Coates, D. B., & Dixon, R. M. (2011). Developing robust faecal near infrared spectroscopy calibrations to predict diet dry matter digestibility in cattle consuming tropical forages. J. Near Infrared Spectrosc., 19, 507–519.Coates, D. B., & Penning, P. (2000). Measuring animal performance (L. Mannetje & R. M. Jones, Eds.; Mannetje L).Coleman, S. W., Christiansen, S., & Shenk, J. S. (1990). Prediction of botanical composition using nIrS calibrations developed from botanically pure samples. Crop Sci., 30, 202.Coleman, S. W., Stuth, J. W., & Holloway, J. W. (1989). Monitoring the nutrition of grazing cattle with near-infrared analysis of faeces. XVI International Grassland Congress, Nice, France, 881–882.Compere, R., Valdivia, J., Hellemans, P., Guns, M., & Vandenbyvang, P. (1992). Comparaison de deux methodes utilisant le Cr2O3 pour estimer la quantite de feces emises par les moutons: pellets de luzerne et bolus CAPTEC-CRD. Bull. Rech. Agron., 27, 365–383.Correa, H. J. (2011). Efecto del manejo del pastoreo y la suplementacion alimenticia en vacas lactantes de sistemas especializados sobre su metabolismo energetico y proteico y el contenido de proteina en la leche.Correa, H. J., Pabon, M. L., & Carulla, J. E. (2009). Estimación del consumo de materia seca en vacas Holstein bajo pastoreo en el trópico alto de Antioquia Estimation of dry matter intake of lactating Holstein cows under grazing in Antioquia Summary. Livestock Research for Rural Development.Côrtes, C., Damasceno, J. C., Bechet, G., & Prache, s. (2005). Species composition of ryegrass (Lolium perenne) and tall fescue (Festuca arundinacea) mixtures using various combinations of n‐alkanes. Grass and Forage Science, 60, 254–261. https://doi.org/10.1111/j.1365-2494.2005.00473.xCottle, D. (2013). The trials and tribulations of estimating the pasture intake of grazing animals. Animal Production Science, 53, 1209. https://doi.org/10.1071/AN13164Cozzolino, D., LaMann, A., & VazMartins, D. (2002). Use of near infrared reflectance spectroscopy to analyze bovine faecal samples. J. Near Infrared Spectrosc., 10, 309–314. https://doi.org/doi:10.1255/ jnirs.347Davies, A. M., & Grant, A. (1987). Near infra‐red analysis of food. International Journal of Food Science & Technology, 22(3), 191–207.Davison, C., Bowen, J. M., Michie, C., Rooke, J. A., Jonsson, N., Andonovic, I., Tachtatzis, C., Gilroy, M., & Duthie, C. A. (2021). Predicting feed intake using modelling based on feeding behaviour in finishing beef steers. Animal, 15(7). https://doi.org/10.1016/j.animal.2021.100231de Souza, J., Batistel, F., Welter, K. C., Silva, M. M., Costa, D. F., & Portela Santos, F. A. (2014). Evaluation of external markers to estimate fecal excretion, intake, and digestibility in dairy cows. Tropical Animal Health and Production, 47(1), 265–268. https://doi.org/10.1007/s11250-014-0674-6Decruyenaere, V., Buldgen, A., & Stilmant, D. (2009). Factors affecting intake by grazing ruminants and related quantification methods : a review. Biotechnol. Agron. Soc. Environ., 13(4), 559–573.Decruyenaere, V., Lecomte, P., Demarquilly, C., Aufrere, J., Dardenne, P., Stilmant, D., & Buldgen, A. (2009a). Evaluation of green forage intake and digestibility in ruminants using near infrared reflectance spectroscopy (NIRS): Developing a global calibration. Animal Feed Science and Technology, 148(2–4), 138–156. https://doi.org/10.1016/j.anifeedsci.2008.03.007Decruyenaere, V., Lecomte, P., Demarquilly, C., Aufrere, J., Dardenne, P., Stilmant, D., & Buldgen, A. (2009b). Evaluation of green forage intake and digestibility in ruminants using near infrared reflectance spectroscopy (NIRS): Developing a global calibration. Animal Feed Science and Technology, 148(2–4), 138–156. https://doi.org/10.1016/j.anifeedsci.2008.03.007Decruyenaere, V., Peters, M., Stilmant, D., Lecomte, P., & Dardenne, P. (2003). Near infrared reflectance spectroscopy applied to faeces to predict dry matter intake of sheep under grazing, comparison with N-alkanes and direct biomass measurement methods. In H.-C. J. & S.-C. C.A. (Eds.), Tropical and Subtropical Agroecosystems: The Sixth International Symposium on the Nutrition of Herbivores: matching herbivore nutrition to ecosystems biodiversity (pp. 471–475). Faculty of Veterinary Medicine & Animal Science Autonomous University of Yucatan, Mexico.Decruyenaere, V., Planchon, V., Dardenne, P., & Stilmant, D. (2015). Prediction error and repeatability of near infrared reflectance spectroscopy applied to faeces samples to predict voluntary intake and digestibility of forages by ruminants. Animal Feed Science and Technology, 205, 49–59. https://doi.org/10.1016/j.anifeedsci.2015.04.011Decruyenaere, V., Visser, M., Stilmant, D., Clément, C., & Sinnaeve, G. (2004). Faecal near infrared reflectance spectroscopy for ruminant feed intake prediction. Grass and Forage Science, 1034, 9.Detmann, E., Gionbelli, M. P., & Huhtanen, P. (2014). A meta-analytical evaluation of the regulation of voluntary intake in cattle fed tropical forage-based diets. Journal Animal Science, 92, 4632–4641. https://doi.org/doi:10.2527/jas2014-7717Dixon, R., & Coates, D. (2009). Review: Near infrared spectroscopy of faeces to evaluate the nutrition and physiology of herbivores. In Journal of Near Infrared Spectroscopy (Vol. 17, Issue 1, pp. 1–31). https://doi.org/10.1255/jnirs.822Dixon, R. M., & Coates, D. B. (2005). The use of faecal NIRS to improve nutritional management of cattle in northern Australia. 15, 65–76.Fanchone, A., Boval, M., & Archimède, H. (2007). Faecal indices based on near infrared spectroscopy to assess intake, in vivo digestibility and chemical composition of the herbage ingested by sheep. 113, 107–113. https://doi.org/10.1255/jnirs.720Faverdin, P., Delagarde, R., Delaby, L., & Meschy, F. (2007). Alimentation des vaches laitieres. In Alimentation des Bovins, Ovins et Caprins: Besoins des Animaux-Valeur des Aliments. Edi- tions Quae, Versailles Cedex, France. 23–57.FEDEGAN.(2021).Coyuntura-Ganadera-Semestre-1-2021. https://www.fedegan.org.co/estadisticas/documentos-de-estadisticaFerrell, C. L., Koong, L. J., & Nienaber, J. A. (1986). Effect of previous nutrition on body composition and maintenance energy cost growing lambs. Br. J. Nutr., 56, 595–605.Foley, W. J., McLean, S., & Cork, S. J. (1995). Consequences of biotransformation of plant secondary metabolites on acid-base metabolism in mammals- A final common pathway? J. Chem. Ecol., 21, 721–743. https://doi.org/doi:10.1007/BF02033457Galyean, M. L., & Gunter, S. A. (2016). Predicting forage intake in extensive grazing system. Animal Science, 26–43. https://doi.org/10.2527/jas2016-0523Glindemann, T., Tas, B., Wang, C., Alvers, S., & Susenbeth, A. (2009). Evaluation of titanium dioxide as an inert marker for estimating faecal excretion in grazing sheep. Animal Feed Science and Technology - ANIM FEED SCI TECH, 152, 186–197. https://doi.org/10.1016/j.anifeedsci.2009.04.010Goering, H. K., & Van Soest, P. K. (1970). Forage fiber analyses (Apparatus, reagents, procedures, and some applications). In U.S. Department of Agriculture (Issue 379). ARS-USDA.Gordon I J. (1995). Animal-based techniques for grazing ecology research. Small Ruminant Research, 16(3), 203–214. https://doi.org/10.1016/0921-4488(95)00635-XGregorini, P., Gunter, S. A., Masino, C. A., & Beck, P. A. (2007). Effects of ruminal fill on short-term herbage intake rate and grazing dynamics of beef heifers.Holechek, J. L., Vavra, M., & Piepper, R. D. (1982). Botanical composition determination of range herbivores diets: a review. J. Range Manage, 35(3), 309–315.Holloway, J. W., Estell, I. I. R. E., & Butts Jr., W. T. (1981). Relationships between fecal components and forage consumption and digestibility. J. Anim. Sci., 52, 836–848.Illius, A. W., & Jessop, N. S. (1996). Metabolic constraints on voluntary intake in ruminants. Journal of Animal Science, 74(12), 3052–3062. https://doi.org/10.2527/1996.74123052xJancewicz, L. J., Swift, M. L., Penner, G. B., Beauchemin, K. A., & Koening, K. M. (2016). Development of NIRS calibrations to estimate fecal composition and nutrient digestibility in beef cattle. Canadian Journal of Animal Science, 403, 1–33.Jeffery, H. (1976). Effect of the live weight of caged sheep and the amount of feed on offer on estimates of digestibility and ad libitum intake. Australian Journal of Experimental Agriculture and Animal Husbandry, 16(82), 656–660.Johnson, D. E., Dinusson, W. E., & Bolin, D. W. (1964). Rate of Passage of Chromic Oxide and Composition of Digesta along the Alimentary Tract of Wethers. Journal of Animal Science, 23(2), 499–505. https://doi.org/10.2527/jas1964.232499xJohnson, J. R., Carstens, G. E., Prince, S. D., Ominski, K. H., Wittenberg, K. M., Undi, M., Forbes, T. D. A., Hafla, A. N., Tolleson, D. R., & Basarab, J. A. (2017). Application of fecal near-infrared reflectance spectroscopy profiling for the prediction of diet nutritional characteristics and voluntary intake in beef cattle. Journal of Animal Science, 95(1), 447. https://doi.org/10.2527/jas2016.0845Krämer, M., Weisbjerg, M. R., Lund, P., Jensen, C. S., & Pedersen, M. G. (2012). Estimation of indigestible NDF in forages and concentrates from cell wall composition. Animal Feed Science and Technology, 177(1–2), 40–51. https://doi.org/10.1016/j.anifeedsci.2012.07.027Kyriazakis, I. (2003). What are ruminant herbivores trying to achieve through their feeding behaviour and food intake. In: Herrera-Camacho C.A. and Sandoval-Castro J., eds. VIth International Symposium on the Nutrition of Herbivores (pp. 153–173).Landau, S., Glasser, T., & Dvash, L. (2006). Monitoring nutrition in small ruminants with the aid of near infrared reflectance spectroscopy (NIRS) technology: A review. Small Ruminant Research, 61(1), 1–11. https://doi.org/10.1016/j.smallrumres.2004.12.012Landau, S., Glasser, T., Dvash, L., & Perevolotsky, A. (2004). Faecal NIRS to monitor the diet of Mediterranean goats. In South African Journal of Animal Science (Vol. 34).Landau, S., Glasser, T., Muklada, H., Dvash, L., Perevolotsky, A., Ungar, E. D., & Walker, J. W. (2005). Fecal NIRS prediction of dietary protein percentage and in vitro dry matter digestibility in diets ingested by goats in Mediterranean scrubland. Small Ruminant Research, 59(2-3 SPEC. ISS.), 251–263. https://doi.org/10.1016/j.smallrumres.2005.05.009Langlands, J. P., Corbett, J. L., Mcdonald, I., & Reid, G. W. (1963). Estimation of the faeces output of grazing animals from the concentration of chromium sesquioxide in a sample of faeces. Brit. J. Nutr.Leng, R. A. (1990). Factors affecting the utilization of poor-quality forages by ruminants particularly under tropical conditions. Nutr. Research Rev., 3, 277–303.Li, H., Tolleson, D., Stuth, J., Bai, K., Mo, F., & Kronberg, S. (2007). Faecal near infrared reflectance spectroscopy to predict diet quality for sheep. Small Ruminant Res., 68, 263–268.Lippke, H. (2002). Estimation of forage intake by ruminants on pasture. Crop Science, 42(3), 869-872.Lippke, H., Barton II, F. E., & Ocumpaugh, W. R. (1989). Near infrared reflectance spectroscopy for estimation of digestible organic matter intake and body weight gain. Proceedings of the XVI International Grassland Congress, Nice, France, 893–894.Lippke, H., Ellis, W. C., & Jacobs, B. F. (1986). Recovery of indigestible fiber from feces of sheep and cattle on forage diets. Journal of Dairy Science, 69(2), 403–412. https://doi.org/10.3168/jds.S0022-0302(86)80418-0Lobley, G. E., Harris, P. M., Skene, P. A., Brown, D., Milne, E., Calder, A. G., Anderson, S. E., Garlick, P. J., Nevison, I., & Conell, A. (1992). Responses in tissue protein synthesis to sub and supra-maintenance intake in young, growing sheep: Comparison of large-dose and continuous-infusion techniques. Brit. J. Nutr., 68, 373–388.Lyons, R. K., Stuth, J. W., & Holloway, J. W. (1992). Fecal NIRS equations for predicting diet quality of free-ranging cattle. J. Range Manage, 45, 238–244. https://doi.org/doi:10.2307/4002970Magalhães, K. A., Valadares Filho, S. C., Detmann, E., Diniz, L. L., Pina, D. S., Azevedo, J. A. G., Araújo, F. L., Marcondes, M. I., Fonseca, M. A., & Tedeschi, L. O. (2010). Evaluation of indirect methods to estimate the nutritional value of tropical feeds for ruminants. Animal Feed Science and Technology, 155(1), 44–54. https://doi.org/10.1016/j.anifeedsci.2009.10.004Mayes, R. W., & Dove, H. (2000). Measurement of dietary nutrient intake in free-ranging mammalian herbivores. Nutrition Research Reviews, 44.Mehtiö, T., Rinne, M., Nyholm, L., Mäntysaari, P., Sairanen, A., Mäntysaari, E. A., Pitkänen, T., & Lidauer, M. H. (2016). Cow-specific diet digestibility predictions based on near-infrared reflectance spectroscopy scans of faecal samples. Journal of Animal Breeding and Genetics, 133(2), 115–125. https://doi.org/10.1111/jbg.12183Mejia Diaz, E., Mahecha Ledesma, L., & Angulo Arizala, J. (2017). Consumo de materia seca en un sistema silvopastoril de Tithonia diversifolia en trópico alto. Agronomía Mesoamericana, 28(2), 389. https://doi.org/10.15517/ma.v28i2.23561Mertens, D. R. (2002). Gravimetric determination of amylase-treated neutral detergent fiber in feeds with refluxing in beakers or crucibles: collaborative study. J. Assoc. Off. Anal. Chem. Intern, 85, 1217–1240.Michael Forbes, J. (2007). A personal view of how ruminant animals control their intake and choice of food: Minimal total discomfort. In Nutrition Research Reviews (Vol. 20, Issue 2, pp. 132–146). https://doi.org/10.1017/S0954422407797834Mioto Da Costa, M. C., Ítavo, L. C. V., Ferreira Ítavo, C. C. B., Dias, A. M., Petit, H. v., Reis, F. A., Gomes, R. C., Leal, E. S., Niwa, M. V. G., & de Moraes, G. J. (2019). Evaluation of internal and external markers to estimate faecal output and feed intake in sheep fed fresh forage. Animal Production Science, 59(4), 741–748. https://doi.org/10.1071/AN16567Moore, J. E. (1994). Forage quality indices: development and application. In Fahey, Jr. et al. (Ed.) Forage Quality, Evaluation and Utilization. ASA. CSSA and SSSA., 967–998.Moreno, L. A., Rueda, C., & Andrade, G. I. (2018). Biodiversidad 2017. Estados y tendencias de la biodiversidad continental de Colombia.Morgan, C. A., & Campling, R. C. (1978). Digestibility of whole barley and oat grains by cattle of different ages. Animal Production, 27(3), 323–329. https://doi.org/10.1017/S0003356100036217Nordheim, H., Volden, H., Fystro, G., & Lunnan, T. (2007). Prediction of in situ degradation characteristics of neutral detergent fibre (aNDF) in temperate grasses and red clover using near-infrared reflectance spectroscopy (NIRS). Animal Feed Science and Technology, 139(1–2), 92–108. https://doi.org/10.1016/j.anifeedsci.2006.11.024Norris, K. H., Barnes, R. F., Moore, J. E., & Shenk, J. S. (1976). Predicting forage quality by Near Infrared Reflectance Spectroscopy. J. Anim. Sci., 43, 889–897Núñez-Sánchez, N., Carrion, D., Peña Blanco, F., Domenech García, V., Garzón Sigler, A., & Martínez-Marín, A. L. (2016). Evaluation of botanical and chemical composition of sheep diet by using faecal near infrared spectroscopy. Animal Feed Science and Technology, 222, 1–6. https://doi.org/10.1016/j.anifeedsci.2016.09.010Núñez-Sánchez, N., Martínez Marín, A. L., Hernández, M. P., Carrion, D., Castro, G. G., & Pérez Alba, L. M. (2012). Faecal near infrared spectroscopy (NIRS) as a tool to assess rabbit’s feed digestibility. Livestock Science, 150(1–3), 386–390. https://doi.org/10.1016/j.livsci.2012.07.030Osborne, B. G., Fearn, P., & Hindle, T. (1993). Practical NIR Spectroscopy with Applications in Food and Beverage Analysis. Longman Scientific and Tecnnical. London, UK.Oudshoorn, F. W., Cornou, C., Hellwing, A. L. F., Hansen, H. H., Munksgaard, L., Lund, P., & Kristensen, T. (2013). Estimation of grass intake on pasture for dairy cows using tightly and loosely mounted di- and tri-axial accelerometers combined with bite count. Computers and Electronics in Agriculture, 99, 227–235. https://doi.org/10.1016/j.compag.2013.09.013Owens, F. N., & Hanson, C. F. (1992). External and Internal Markers for Appraising Site and Extent of Digestion in Ruminants. Journal of Dairy Science, 75(9), 2605–2617. https://doi.org/10.3168/jds.S0022-0302(92)78023-0Ozaki, Y., McClure, W. F., & Christy, A. A. (2007). Near-Infrared Spectroscopy in Food Science and Technology, Wiley Interscience, Hoboken, New Jersey, USA.Parga, J., Peyraud, J. L., & Delagarde, R. (2002). Age of regrowth affects grass intake and ruminal fermentations in grazing dairy cows. In: Durand J.L., Emile J.C., Huyghe C. and Lemaire G., eds. multi-function grasslands. Quality Forages, Animal Products and Landscape. Grassl. Sci. Eur., 7, 256–257.Peguero, A. (2010). La espectroscopía NIR en la determinación de propiedades físicas y composición química de intermedios de producción y productos acabados. Universidad Autonoma de Barcelona.Peripolli, V., Prates, Ê. R., Barcellos, J. O. J., & Neto, J. B. (2011). Fecal nitrogen to estimate intake and digestibility in grazing ruminants. Animal Feed Science and Technology. https://doi.org/10.1016/j.anifeedsci.2010.11.008Peyraud, J. L., Comerón, E. A., Wade, M. H., & Lemaire, G. (1996). The effect of daily herbage allowance, herbage mass and animal factors upon herbage intake by grazing dairy cows. Ann. Zootech., 45, 201–217.Pfister, J. A., Provenza, F. D., Manners, G. D., Gardner, D. R., & Ralphs, M. H. (1997). Tall larkspur ingestion: Can cattle regulate intake below toxic levels? J. Chem. Ecol., 23, 759–777. https://doi.org/doi:10.1023/ B: JOEC.0000006409.20279.59Provenza, F. D., Villalba, J. J., & Dziba, L. E. (2003). Linking herbivore experience, varied diets, and plant biochemical diversity. Small Ruminant Research, 49, 257–274.Pulina, G., Avondo, M., Molle, G., Dias Francesconi, A. H., Atzori, A. S., & Cannas, A. (2013). Invited Review Models for estimating feed intake in small ruminantsRaymond, W. F., Harris, C. E., & Haurker, V. G. (1953). Studies on the digestibility of herbage. 1. Technique of measurement of digestibility and some observations on factors affecting the accuracy of digestibility data. Journal of the British Grassland Society, 8, 301–314.Raymond, W. F., Harris, C. E., & Kemp, C. D. (1955). Studies in the digestibility of herbage. VI. The effect of level of herbage intake on the digestibility of herbage by sheep. J. Brit. Grassl. Soc., 10, 19–26.Rhind, S. M., Archer, Z. A., & Adam, C. L. (2002). Seasonality of food intake in ruminants: recent developments in understanding. Nutr. Research Rev., 15, 43–65.Rihani, N., Garrett, W. N., & Zinn, R. A. (1993). Influence of level of urea, and method of supplementation on characteristics of digestion of high-fiber diets by sheep. Journal Animal Science, 71, 1657–1665.Rombach, M., Münger, A., Niederhauser, J., Südekum, K.-H., & Schori, F. (2018). Evaluation and validation of an automatic jaw move- ment recorder (RumiWatch) on unsupplemented or supplemented dairy cows on pasture. J. Dairy Sci., 101, 2463–2475.Romney, D. L., & Gill, M. (2009). Intake of forages. In Forage evaluation in ruminant nutrition. (Issue 1996, pp. 43–62). https://doi.org/10.1079/9780851993447.0043Ruuska, S., Kajava, S., Mughal, M., Zehner, N., & Mononen, J. (2016). Validation of a pressure sensor-based system for measuring eating, rumination and drinking behaviour of dairy cattle. Appl. Anim. Behav. Sci., 174, 19–23.Sampaio, C. B., Detmann, E., Neves, T., & Valente, P. (2011). Fecal excretion patterns and short-term bias of internal and external markers in a digestion assay with cattle. Revista Brasileira de Zootecnia, 657–665.Selcuk, A., & Suphi, D. (2017). Use of Chromium Oxide and Alkane Indicator Methods for Determination of Feed Intake for Grazing Sheep. Journal of Agricultural Science and Technology A, 7(3). https://doi.org/10.17265/2161-6256/2017.03.008Shenk, J. S., & Westerhaus, M. O. (1994). THE APPLICATION OF NEAR INFRARED REFLECTANCE SPECTROSCOPY (NIRS) TO FORAGE ANALYSIS.Shenk, J. S., & Westerhaus, M. O. (1996). Calibration de ISI way. En Near Infrared Spectroscopy: the future waves. In W. P. Davies A.M.C. (Ed.), NIR publications.Shenk, J. S., & Westrerhaus, M. O. (1991). Population definition, sample selection, and calibration procedures for near-infrared reflectance spectroscopy. Crop Sci., 31, 469–474.Shenk, J. S., Workman, J. J., & Westerhaus, M. O. (2001). Application of NIR Spectroscopy to Agricultural Products. Handbook of Near Infrared Analysis. Second Edition. Burns D.A. y Ciurczak E.W. (Eds.). Practical Spectroscopy Series, Vol. 27. Marcel Dekker, USA.Showers, E. E. (1997). Prediction of Diet Quality Parameters of White-tailed Deer Via Near Infrared Reflectance Spectroscopy (NIRS) Fecal Profiling. Texas A&M University.Smit, H. J., Taweel, H. Z., Tas, B. M., Tamminga, S., & Elgersma, A. (2005). Comparison of Techniques for Estimating Herbage. Journal of Dairy Science, 88(5), 1827–1836. https://doi.org/10.3168/jds.S0022-0302(05)72857-5Soto-Navarro, S. A., Lancaster, R., Sankey, C., Capitan, B. M., & Holland, B. P. (2014). Comparative digestibility by cattle versus sheep: Effect of forage quality. https://doi.org/10.2527/jas2013-6740Stuth, J. W., Kapes, E. D., & Lyons, R. K. (1989). Use of near infrared spectroscopy to assess nutritional status of cattle diets on rangeland. XVI International Grassland Congress, Nice, France, 889–890.UPRA. (2020). Plan de ordenamiento productivo: Analisis prospectivo de la cadena lactea bovina colombiana.UPRA. (2021). Analisis situacional de la cadena productiva carnica bovina.Valentine, M. E., Karayilanli, E., Cherney, J. H., & Cherney, D. J. (2019). Comparison of in vitro long digestion methods and digestion rates for diverse forages. Crop Science, 59(1), 422–435. https://doi.org/10.2135/cropsci2018.03.0159van Soest, P. J., Robertson, J. B., & Lewis, B. A. (1991). Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci., 74, 3583–3597.Van Wieren, S. E. (1996a). Do large herbivores select a diet that maximizes short-term energy intake rate? Forest Ecol. Manage, 88, 149–156.Van Wieren, S. E. (1996b). Do large herbivores select a diet that maximizes short-term energy intake rate? Forest Ecol. Manage., 88, 149–156.Velásquez, A. v, da Silva, G. G., Sousa, D. O., Oliveira, C. A., Martins, C. M. M. R., dos Santos, P. P. M., Balieiro, J. C. C., Rennó, F. P., & Fukushima, R. S. (2018). Evaluating internal and external markers versus fecal sampling procedure interactions when estimating intake in dairy cows consuming a corn silage-based diet. Journal of Dairy Science, 101(7), 5890–5901. https://doi.org/10.3168/jds.2017-13283Ward, R. G., Smith, G. S., Wallace, J. D., Urquhart, N. S., & Shenk, J. S. (1982). Estimation of intake and quality of grazed range forage by near infrared reflectance spectroscopy. J. Anim. Sci., 54, 399–402.Williams, P. C. (2001). Implementation of Near- Infrared Technology. En Near-Infrared Technology in the Agricultural and Food Industries, 2nd edition. In American Association of Cereal Chemists, Inc. (P.K. Willi).Williams, P., Dardenne, P., & Flinn, P. (2017). Tutorial: Items to be included in a report on a near infrared spectroscopy project. Journal of Near Infrared Spectroscopy, 25(2). https://doi.org/10.1177/0967033517702395Workman, J. J., & Mark, H. (2015). Choosing the Best Regression Model. J. Near Infrared Spectrosc., 30(6).Yearsley, J., Tolkamp, B. J. N., & Illius, A. W. (2001). Theoretical developments in the study and prediction of food intake. Proc. Nutr. Soc., 60, 145–156.Minson, D. (1990). Forage in ruminant nutrition. Academic Press Limited.Uso integral de estrategias tecnológicas para el fortalecimiento y sostenibilidad de la ganadería colombiana desde la críaMinisterio de Agricultura y Desarrollo RuralEstudiantesInvestigadoresORIGINAL1069723407.2022.pdf1069723407.2022.pdfTesis de Maestría en Producción animalapplication/pdf1083322https://repositorio.unal.edu.co/bitstream/unal/81546/4/1069723407.2022.pdfc411ad7a86db90256a14842e5b0bd752MD54LICENSElicense.txtlicense.txttext/plain; charset=utf-84074https://repositorio.unal.edu.co/bitstream/unal/81546/5/license.txt8153f7789df02f0a4c9e079953658ab2MD55THUMBNAIL1069723407.2022.pdf.jpg1069723407.2022.pdf.jpgGenerated Thumbnailimage/jpeg6162https://repositorio.unal.edu.co/bitstream/unal/81546/6/1069723407.2022.pdf.jpg44289a56a10088d622ddf54e648113f4MD56unal/81546oai:repositorio.unal.edu.co:unal/815462023-08-05 23:03:37.294Repositorio Institucional Universidad Nacional de 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EVESURBIFBPUiBMQSBTRUNSRVRBUsONQSBHRU5FUkFMLiAqTEEgVEVTSVMgQSBQVUJMSUNBUiBERUJFIFNFUiBMQSBWRVJTScOTTiBGSU5BTCBBUFJPQkFEQS4gCgpBbCBoYWNlciBjbGljIGVuIGVsIHNpZ3VpZW50ZSBib3TDs24sIHVzdGVkIGluZGljYSBxdWUgZXN0w6EgZGUgYWN1ZXJkbyBjb24gZXN0b3MgdMOpcm1pbm9zLiBTaSB0aWVuZSBhbGd1bmEgZHVkYSBzb2JyZSBsYSBsaWNlbmNpYSwgcG9yIGZhdm9yLCBjb250YWN0ZSBjb24gZWwgYWRtaW5pc3RyYWRvciBkZWwgc2lzdGVtYS4KClVOSVZFUlNJREFEIE5BQ0lPTkFMIERFIENPTE9NQklBIC0gw5psdGltYSBtb2RpZmljYWNpw7NuIDE5LzEwLzIwMjEK

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