Prediction of the chemical composition of Cenchrus clandestinus grass using Near Infrared Spectroscopy – NIRS

  • Rolando Barahona-Rosales Universidad Nacional de Colombia https://orcid.org/0000-0002-4246-7835
  • Astrid Rivera Rivera Universidad Nacional de Colombia
  • Omar Ceballos Universidad de Antioquia
  • Diana María Bolívar-Vergara Universidad de Antioquia
  • Mario Fernando Cerón-Muñoz Universidad de Antioquia
Palavras-chave: chemometrics; forage quality; milk production.

Resumo

Forage evaluation is important as milk production depends on the availability of highly nutritious forage. The aim of this study was to develop nutrient content prediction equations for kikuyu grass (Cenchrus clandestinus), a universally used forage in Colombian specialized dairy farms, with near-infrared spectroscopy (NIRS). Kikuyu samples obtained from two hundred dairy farms in the North of Antioquia were analyzed for DM, protein, NDF and ADF. Using three-step procedure (calibration, cross validation, and prediction), equations were developed in a NIRS equipment (NIRS DS 2500 monochromator, Foss-NIRsystem, Denmark). The absorbance values (logarithm (1/R), R = reflectance) were analyzed using the software WinISI version 4.8, performing mathematical treatments to generate several equations per chemical component analyzed. The R2v for protein content was 0.96 and SEP was 0.54 indicating an appropriate prediction equation. The R2v for NDF and ADF contents were 0.89 and 0.88 respectively, however the SEP value was lower for ADF (0.69) than NDF (1.88). Chemical composition for protein, NDF and ADF in kikuyu grass can reliably predicted using equations developed in NIRS. However, it was not possible to develop a prediction equation for kikuyu DM.

Downloads

Não há dados estatísticos.

Referências

Ammeter, A., So, K., & Duncan, R. W. (2022). Analysis of cruciferin content in whole seeds of Brassica napus L. by near‐infrared spectroscopy. Journal of the American Oil Chemists’ Society, 99, 655-664. https://doi.org/10.1002/aocs.12616.

Association of Official Analytical Chemists [AOAC] (2002). Official Methods of Analysis of AOAC International. AOAC International.

Apráez Guerrero, J. E., Gálvez Cerón, A., Tapia, E., Jojoa, L., León, J., Zambrano D., Zambrano, H. R., Obando, V., & Aux Moreno, Y. (2012). Determinación de los factores edafoclimáticos que influyen en la producción y calidad del pasto Kikuyo (Pennisetum clandestinum) en condiciones de no intervención. Livestock Research for Rural Development, 24(3), 42.

Arias-Ortiz, N., Bolívar-Vergara, D. M., & Barahona-Rosales, R. (2023). Effect of Sambucus peruviana and Tithonia diversifolia silage on methane emissions by Holstein cows fed Cenchrus clandestinus. Livestock Research for Rural Development, 35(4), 42.

Rosales, R. B., & Sánchez Pinzón, S. (2005). Limitaciones físicas y químicas de la digestibilidad de pastos tropicales y estrategias para aumentarla. Ciencia y Tecnología Agropecuaria, 6(1), 69-82. https://doi.org/10.21930/rcta.vol6_num1_art:39

Brogna, N., Pacchioli, M. T., Immovilli, A., Ruozzi, F., Ward, R., & Formigoni, A. (2009). The use of near-infrared reflectance spectroscopy (NIRS) in the prediction of chemical composition and in vitro neutral detergent fiber (NDF) digestibility of Italian alfalfa hay. Italian Journal of Animal Science, 8(2), 271-273. https://doi.org/10.4081/ijas.2009.s2.271

Brown, W. F., Piacitelli, C. K., & Mislevy, P. (1987). Near Infrared Reflectance Analysis of Nonstructural Carbohydrate Concentration in Tropical Grasses. Crop Science, 27(4), 786-788. https://doi.org/10.2135/cropsci1987.0011183X002700040036x

Burns, J. C., Pond, K. R., & Fisher, D. S. (1994). Measurement of forage intake. Forage quality, evaluation, and utilization, ASA, CSSA, and SSSA Books, 494-532. https://acsess.onlinelibrary.wiley.com/doi/10.2134/1994.foragequality.c12

Correa, H. J., Rodríguez, Y. G., Pabón, M. L., & Carulla, J. E. (2012). Efecto de la oferta de pasto kikuyo (Pennisetum clandestinum) sobre la producción, la calidad de la leche y el balance de nitrógeno en vacas Holstein. Livestock Research for Rural Development, 24(11), 1-13.

Corson, D. C., Waghorn, G. C., Ulyatt, M. J., & Lee J. (1999). NIRS: Forage Analysis and Livestock Feeding. Proceedings of New Zealand Grassland Association, 61, 127-132. http://www.grassland.org.nz/publications/nzgrassland_publication_507.pdf

Cozzolino D. (2002). Uso de la espectroscopía de reflectancia en el infrarrojo cercano (NIRS) en el análisis de alimentos para animales. Agrociencia, 6(2), 25-32.

Gómez Urrego, J. M., Correa Londoño, G., & Barahona rosales, R. (2014). Evaluación del residuo del cultivo de Agaricus bisporus como alimento de vacas lecheras en lactancia media. Revista Facultad Nacional de Agronomía Medellín, 67(2), 7331-7343.

Herrero, M., Murray, I., Fawcett, R. H., & Dent, J. B. (1996). Prediction of the in vitro gas production and chemical composition of kikuyu grass by near-infrared reflectance spectroscopy. Animal Feed Science and Technology, 60(1-2) 51-67.

Jiménez Torres, P. A. (2007). Identificación de harinas de yuca (Manihot esculenta Crantz) con alto contenido proteico mediante espectroscopia de infrarrojo cercano (NIRS) (p. 71). MSc tesis, Universidad Nacional de Colombia, Sede Palmira. https://repositorio.unal.edu.co/handle/unal/2473

Jung, H. G., Mertens, D. R., & Buxton, D. R. (1998). Forage quality variation among maize inbreds: in vitro fiber digestion kinetics and prediction with NIRS. Crop Science, 38(1), 205-210. https://doi.org/10.2135/cropsci1998.0011183X003800010034x

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

Marten, G. C., Brink, G. E., Buxton, D. R., Halgerson, J. L., & Hornstein, J. S. (1984). Near Infrared Reflectance Spectroscopy Analysis of Forage Quality in Four Legume Species 1. Crop Science, 24(6), 1179-1182. https://doi.org/10.2135/cropsci1984.0011183X002400060040x

Ortega Monsalve, M, Rodríguez Monroy, T. R., Galeano-Vasco, L., Medina-Sierra, M., & Cerón-Muñoz, M. (2024). Determination of Grass Quality Using Spectroscopy: Advances and Perspectives. In: Grasslands - Conservation and Development. United Kingdom: IntechOpen. https://doi.org/10.5772/intechopen.112990

Sandoval-Mejía, L. A., Bueso-Uclés, F. J., & Vélez-Nauer, M. (2008). Predicción nutricional para pastos tropicales por espectroscopía de reflectancia en el infrarrojo cercano. Agronomía Mesoamericana, 19(2), 221-225. https://doi.org/10.15517/am.v19i2.5003

Sossa Sánchez, C. P., Correa Londoño, G. A., & Barahona Rosales, R. (2015). Consumo y excreción de nutrientes en novillos de carne pastoreando en trópico de altura con y sin suplementación energética. Zootecnia Tropical, 33(2), 117-28. http://www.publicaciones.inia.gob.ve/index.php/zootecniatropical/article/view/355

Williams, P. C. (1975). Application of near infrared reflectance spectroscopy to analysis of cereal grains and oilseeds. Cereal Chemistry, 52(4), 561-576.

Windham, W. R. (1987). Influence of grind and gravimetric technique on dry matter determination of forages intended for analysis by near infrared reflectance spectroscopy 1. Crop Science, 27(4), 773-776. https://doi.org/10.2135/cropsci1987.0011183X002700040033x

Kondal, V., Jain, A., Garg, M., Kumar, S., Singh, A. K., Bhardwaj, R., & Singh, G. P. (2024). Gap derivative optimization for modeling wheat grain protein using near‐infrared transmission spectroscopy. Cereal Chemistry, 101(5), 991-999. https://doi.org/10.1002/cche.10795

Publicado
2025-06-06
Como Citar
Barahona-Rosales, R., Rivera Rivera, A., Ceballos, O., Bolívar-Vergara, D. M., & Cerón-Muñoz, M. F. (2025). Prediction of the chemical composition of Cenchrus clandestinus grass using Near Infrared Spectroscopy – NIRS. Acta Scientiarum. Animal Sciences, 47(1), e71799. https://doi.org/10.4025/actascianimsci.v47i1.71799
Seção
Forragicultura

0.9
2019CiteScore
 
 
29th percentile
Powered by  Scopus