[en] Arnica montana L. (AM) is considered a medicinal plant, used as hay in feed ration. The aim of this study is to assess the prediction of protein content and in vitro organic matter digestibility value in grass mixtures containing Arnica montana L., and in a second step to check if these values have a positive or negative influence in the mixtures. Crude protein has been selected because it is one of the most important quality parameters of forages as nutritional element used in animal feeding. The protein is required on a daily basis for maintenance, lactation, growth and reproduction, but is important for agriculture too, because a high content of protein makes it an important source of feed. The digestibility is also important, because it refers to the extent to which a feedstuff is absorbed in the animal body as it passes through an animal’s digestive tract. In this study, the Weende system (the Kjeldahl method) for the protein content, together with the enzymatic technique for digestibility, was applied and used in combination with non-destructive methods, like those based on the Near Infrared Spectroscopy (NIRS) or the Near Infrared Hyperspectral Imaging. Based on NIR imaging system data, the PLS-DA was used to discriminate between the classes with AM and classes without AM, as well as to build a model that could be used to predict the composition of mixtures. More than 99% correct prediction for AM was obtained. The crude protein content of the hay determined by classical method decrease from the type of meadow Agrostis capillaris L. - Festuca rubra L. (15.22%) until to the pure sample of Arnica montana L. (11.19%); however, the digestibility was highest in the pure sample of Arnica montana L. (84.13%) and lowest in samples from the type of meadow Agrostis capillaris L. - Festuca rubra L. (57.18%) or in samples with the participation of Arnica montana L. This study should lead to a more important point, which is to verify whether the medicinal properties of Arnica montana L. can be transferred or not to milk production through the dairy cow feed.
Research center :
Animal Science Unit, Gembloux Agro Bio Tech
Disciplines :
Agriculture & agronomy
Author, co-author :
Dale, Laura ; Université de Liège - ULiège > Doct. sc. agro. & ingé. biol.
Fernandez, Juan Antonio
Vermeulen, Philippe
Lecler, Bernard
Bogdan, Anca Dorina
Pacurar, Florin
Rotar, Ioan
Thewis, André ; Université de Liège - ULiège > Sciences agronomiques > Zootechnie
Baeten, Vincent
Language :
English
Title :
Research on crude protein and digestibility of Arnica montana L. using conventional NIR spectrometry and hyperspectral imaging NIR
Collins, M. and Fritz, J. O. 2003. Forages. In Barnes, R. F. (ed.). An Introduction to Grassland Agriculture. 6th edn. Blackwell Publishing Professional, Iowa.
EMEA 1999. Arnica montana L. The European Agency for the Evaluation of Medical Products, Veterinary Medicines Evaluation Unit, Summary Report.
Reif, A., Brinkmann, K., Goia, A., Hoernstein, H., Jaeckle, S., Mohr, B. et al. 2008. Differences of development patterns in Central and Eastern European mountain regions: History of land uses and landscapes in the Southern Black Forest (Germany) and the Central Apuseni Mountains (Romania). Bulletin UASVM, Agriculture 65(1).
Carlier, L., Van Waes, C., Rotar, I., Valhova, M. and Vidican, R. 2009. Forage quality evaluation. Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj Napoca, Agriculture 66(1):216-230.
Hill, N. S., Kissel, D. E., Heusne, G. L., Sonon, L. S., Saha, U. K., Lawton, S. et al. 2010. Common terms used in animal feeding and nutrition. University of Georgia Cooperative Extension and Ft. Valley State 1367:1-20.
Carlier, L., Puia, I. and Rotar, I. 1998. For a Better Grass Production. Risoprint, Cluj-Napoca, pp. 129-131.
Berardo, N. 1997. Prediction of the chemical composition of white clover by near-infrared reflectance spectroscopy. Grass Forage Science 52:27-32.
Park, R., Agnew, R., Gordon, F. and Steen, R. 1998. The use of Near Infrared Reflectance Spectroscopy (NIRS) on undried samples of grass silage to predict chemical composition and digestibility parameters. Animal Feed Science Technology 72:155-167.
Paul, C. and Hausler, A. 2002. Developing the NIRS harvest line concept for forage trials. Grasslans Science Euro. 7:464-465.
Ruano Ramos, A., García Ciudad, A. and García Criado, B. 1999. Determination of nitrogen and ash contents in total herbage and botanical components of grassland systems with near infrared spectroscopy. Journal of Science Food Agriculture 79:137-143.
Fernández Pierna, J. A., Baeten, V. and Dardenne, P. 2006. Screening of compound feeds using NIR hyperspectral data. Chemometrics and Intelligent Laboratory Systems 84(1-2):114-118.
Schut, A., Van der Heijden, G., Hoving, I., Stienezen, M., Van Evert, F., and Meleman, J. 2006. Imaging spectroscopy for on-farm measurement of grassland yield and quality. Agronomy Journal 98(5):1318-1325.
FOSS Analytical 2005. Cyclotec 1093 sample mill complete with sample bottles (125 ml) with snap-on lid (2) screens 0.5 and 1.0 mm, allen keys 4 and 6 mm seal for grinding chamber, paper bag for dust collection, seal for sample bottle, 200-230 v, 50 hz. Users' Manual, PN 99990730. E, (2 gb).
Vermeulen, P., Fernández Pierna, J. A., Burger, J., Tossens, A., Dardenne, P. and Baeten, V. 2010. NIR hyperspectral imaging and chemometrics as a lab tool for the quality control of agricultural products. In Chemometrics in Analytical Chemistry (CAC 2010). Antwerp, Belgium.
Association of Official Analytical Chemists (AOAC) 1990. Methods of Analysis. 15th edn. Washington DC.
De Boever, J., Cottyn, B.G., Buysse, F.X., Wainman, F.W. and Vanacker, J.M. 1986. The use of an enzymatic technique to predict digestibility, metabolisable and net energy of compound feedstuffs for ruminants. Animal Feed Science and Technology 14:203-214.
De Boever, J., Cottyn, B., Andries, J., Buysse, F. X. and Vanacker, J. 1988. The use of a cellulase technique to predict digestibility, metabolizable and net energy of forages. Animal Feed Science and Technology 19(3):247-260.
Minson, D. J. 1990. Forage in Ruminant Nutrition. Academic Press, San Diego, Sydney, Australia, 483 p.
Jean Blain, C. 2002. Introduction a la nutrition des animaux domestiques. Technique et Documentation, Paris.
Moore, J. E., Adesogan, A. T., Coleman, S. W. and Undersander, D. J. 2007. Predicting forage quality. In Barnes, R. F., Nelson, J. C., Moore, K. J. and Collins, M. (eds). Forages: The Science of Grassland Agriculture. Vol II. 6th edn. Blackwell Publishing, Ames, IA, pp. 553-568.
Decruyenaere, V., Lecomte, P., Demarquilly, C., Aufrere, J., Dardenne, P., Stilmant, D. et al. 2008. Evaluation of green forage intake and digestibility in ruminants using Near Infrared Reflectance Spectroscopy (NIRS): Developing a global calibration. Animal Feed Science and Technology 148:138-156.
Guide Pratique 2007. Alimentation des bovins, ovins et caprins, besoins des animaux: Valeurs des aliments, tables INRA. Editions Quae, Versailles, Paris, France.
De Boever, J., Cottyn, B., De Brabander, D., Vancker, J. and Boucque, C. 1999. Equations to predict digestibility and energy value of grass silages, maize silages, grass hays, compound feeds and raw materials for cattle. Nutrition Abstracts and Reviews 69:835-850.
Stuth, J., Jama, A. and Tolleson, D. 2003. Direct and indirect means of predicting forage quality through Near Infrared Reflectance Spectroscopy. Field Crops Research 84:45-56.
Gillespie, J. R. and Flanders, F. B. 2009. Modern Livestock and Poultry Production. 8th edn. Delmar, Cengage Learning, Canada, USA.
Pàcurar, F. 2005. Cercetàri privind dezvoltarea sustenabilà (durabilà) a satului Gheţari, comuna Gârda prin îmbunàtàţirea pajiştilor naturale şi a unor culturi agricole. PhD Thesis. Cluj Napoca.
Walshaw, J., Mathison, G. W., Fenton, T., Sedgwick, G., Hsu, H., Recinos Díaz, G. et al. 1998. Characterization of forages by differential scanning calorimetry and prediction of their chemical composition and nutritive value. Animal Feed Science Technology 71:309-323.
Iantcheva, N., Steingass, H., Todorov, N. and Pavlov, D. 1999. A comparison of in vitro rumen fluid and enzymatic methods to predict digestibility and energy value of grass and alfalfa hay. Animal Feed Science and Technology 81:333-344.
Vidican, R., Rotar, I. and Sima, N. 2000. Tehnica NIRS (Near Infrared Reflectance Spectroscopy) si aplicaţiile sale în analiza calitàţii furajelor. Symposium "Agriultura si Alimentaţia".
Gosselink, J., Dulphy, J., Poncet, C., Jailler, M., Tamminga, S. and Cone, J. 2004. Prediction of forage digestibility in ruminants using in situ and in vitro techniques. Animal Feed Science and Technology 115(3):227-246.
Norris, K. H., Barnes, R. F., Moore, J. E. and Shenk, J. S. 1976. Predicting forage quality by infrared reflectance spectroscopy. J. Animal Sci. 43:889-897.
