Estimating Nitrogen and Acid Detergent Fiber Contents of Grass Species using Near Infrared Reflectance Spectroscopy (NIRS)


1 Faculty of Natural Resources, University of Tehran, Iran

2 Ph.D. Student of Range Management, Faculty of Natural Resources, University of Tehran, Iran

3 Stockbridge School of Agriculture, University of Massachusetts, Amherst, USA

4 Ph.D. Student of Range Management, Faculty of Natural Resources, University of Ardabil, Iran

5 Department of Natural Resources, University of Urmia, Iran


Chemical assessments of forage clearly determine the forage quality; however, traditional methods of analysis are somehow time consuming, costly, and technically demanding. Near Infrared Reflectance Spectroscopy (NIRS) has been reported as a method for evaluating chemical composition of agriculture products, food, and forage and has several advantages over chemical analyses such as conducting cost-effective and rapid analyses with non-destructive sampling and small number of samples. This study aims to estimate Nitrogen (N) and Acid Detergent Fiber (ADF) content of grass species using NIRS.A total of 171 samples of grasses (Poaceae) at vegetative, flowering, and seeding stages were collected from different regions in Iran. The samples were scanned in a NIRS DA 7200 (Perten instruments, Sweden) in a range of 950-1650 nm. The sample set consisted of 110 samples for calibration and 61 samples for validation was used to predict N and ADF. Samples were previously analyzed chemically for Nitrogen (N) and Acid Detergent Fiber (ADF) and then were scanned by NIRS. Calibration models between chemical data and NIRS were developed using partial least squares regression with the internal cross validation. The coefficients of determination (r2) of linear regression between chemical analyses and NIRS were 0.90 and 0.94 for N and ADF, respectively. The standard errors of prediction were 0.30% and 3.10% for N and ADF, respectively. The results achieved from this study indicated that NIRS has a potential to be used in the measurement of N and ADF contents regarding the forage samples.


Aiken, G. E., Pote, D. H., Tabler, S. F. and Tabler, T. C. 2005. Application of near-infrared reflectance spectroscopy to estimate chemical constituents in broiler litter. Jour. Communication in Soil Science and Plant Analysis, 36: 2529-2539.
Alomar, D., Fuchslocher, R. and Stockebrands, J., 1999. Effect of oven- or freeze-drying on chemical composition and NIR spectra of pasture silage. Jour. Animal Feed Science & Technology, 80: 309-319.
Alomar, D., Madrones, R., Cuevas, E., Fuchslocher, R. and Cuevas, J., 2009. Prediction of the composition of fresh pastures by near infrared reflectance or interactance-reflectance spectroscopy. Chilean Jour. Agriculture Research, 69: 198-206.
Andrés, S., Javier Giráldez, F., López, S., Mantecón, A. R. and Calleja, A., 2005. Nutritive evaluation of herbage from permanent meadows by near-infrared reflectance spectroscopy: 1. Prediction of chemical composition and in vitro digestibility. Jour. Science Food Agriculture, 85: 1564-1571.
Andrieu, J., Demarquilly, C. and Wegat-Litre´, E., 1981. "Tables de prÈvision de la valeur alimentaire des fourrages". In: Prévision de la valeur nutritive des aliments des ruminants. Ed. INRA, 345-577 pp.
Arzani, H., Zohdi, M., Fish, E., Zahedi Amiri, Gh., Nikkhah, A. and Wester, D., 2004. Phenological effects on forage quality of five grass species. Jour. Range Management, 57: 624-629.
Arzani, H., Motamedi, J. and Zare Chahouki, M. A., 2011. Forage quality of Iranian rangeland species. Forest, Rangeland and Watershed Management Organization and University of Tehran, Iran. 234 pp. (In Persian).
Arzani, H., Sour, A. and Motamedi, J., 2012. Potential of Near-Infrared Reflectance Spectroscopy (NIRS) to Predict Nutrient Composition of Bromus tomentellus. Jour. Rangeland Science, 2(4): 635-642.
Bain, K.F. Vergés, A. and Poore, A.G.B., 2013. Using near infra-red reflectance spectroscopy (NIRS) to quantify tissue composition in the seagrass Posidonia australis". Jour. Aquatic Botany, 111: 66-70.
Ball, D. M., Collins, M., Lacefield, G. D., Martin, N. P., Mertens, D. A., Olson, K. E., Putnam, D. H., Undersander, D. J. and Wolf, M. W., 2001. Understanding forage quality, American Farm Bureau Federation Publication 1-01, Park Ridge, IL: 11-18 pp.
Batten, G. D., 1998. Plant analysis using near-infrared reflectance spectroscopy: the potential and the limitations. Australian Jour. Experimental Agriculture, 38: 697–706.
Brereton, R. G., 2003. Chemometrics: Data analysis for the laboratory and chemical plant, West Sussex, UK: John Wiley, 504 pp.
Calderon, F. J., Vigil, M. F., Reeves, J. B. and Poss, D. J., 2009. Mid-infrared and near-infrared calibrations for nutritional parameters of triticale (Triticosecale) and pea (Pisum sativum). Jour. agriculture and food chemistry, 57: 5136-5142.
Charehsaz, N., Jafari, A.  A., Arzani, H. and Azarnivand, H., 2010. Evaluation of the changes  in  the  water  soluble  carbohydrate  percentage  in  three  species  Bromus  tomentellus,  Agropyron  intermedium  and  Dactylis  glomerata  in  three  phenological Stage. Rangeland Jour, 4: 121-129. (In Persian).
Cozzolino, D., Fassio, A., Fernandez, E., Restaino, E. and La Manna, A., 2006. Measurement of chemical composition in wet whole maize silage by visible and near infrared reflectance spectroscopy. Jour. Animal Feed Science and Technology, 129: 329–336.
Cozzolino, D., Cynkar, W. U., Dambergs, R. G., Mercurio, M. D. and Smith, P. A., 2008. Measurement of condensed tannins and dry matter in red grape homogenates using near infrared spectroscopy and partial least squares. Jour. Agriculture and Food Chemistry, 56: 7631-7636.
Cunniff, P., 1995. Official methods of analysis, 15th ed. Arlington, VA: International AOAC.
Dardenne, P., Sinnaeve, G. and Baeten, V., 2000. Multi calibration and chemometrics for near infrared spectroscopy: which method. Jour. Near Infrared Spectroscopy, 8(4): 229-237.
Deaville, G. D. and Flinn, P. C. 2000. Near infrared spectroscopy: an alternative approach for the estimation of forage quality and voluntary intake. In: Forage Evaluation in Ruminant Nutrition Givens D.I., Owen E, Axford RFE, Omed HM. (ed) 301-320 CABI Publishing, Wallingford, UK.
Eldin, A., 2011. "Near Infra-Red Spectroscopy", Wide Spectra of Quality Control, In Tech Publishers, Croatia, 238-248 pp.
Fassio, A., La Manna, A., Cozzolino, D., Fernández, E. G. and Restaino, E. A., 2009. Predicting the nutritive value of high moisture grain corn by near infrared reflectance spectroscopy. Jour. Computers Electronics Agriculture, 67: 59-63.
Fearn, T., 2002. Assessing calibrations: SEP, RPD, RER and R2. NIR News, 13: 12-14.
Garcia Ciudad, A., Ruano, A., Becerro, F., Zabalgogeazcoa, I., Vazquez de Aldana, B. R. and Garcia-Criado, B., 1999. Assessment of the potential of NIR spectroscopy for the estimation of nitrogen content in grasses from semiarid grasslands. Jour. Animal Feed Science and Technology, 77: 91-98.
Garcia Ciudad, A., Fernandez Santos, B., Vazquez de Aldana, B. R., Zabalgogeazcoa, I., Gutierrez, M. Y. and Garcia Criado, B., 2004. Use of near infrared reflectance spectroscopy to assess forage quality of a Mediterranean shrub. Jour. Communication in Soil Science and Plant Analysis, 35: 665-678.
Givens, D. I. and Deaville, E. R., 1999. The current and future role of near infrared reflectance spectroscopy in animal nutrition: a review. Australian. Jour. Agriculture Research, 50: 1131-1145.
Gonzalez-Martin, I., Hernandez-Hierro, J. M., and Gonzalez-Cabrera, J. M., 2007. Use of NIRS technology with a remote reflectance fibre-optic probe for predicting mineral composition (Ca, K, P, Fe, Mn, Na, Zn), protein and moisture in alfalfa. Jour. Anal. Bioanal. Chem, 387: 2199–2205.
Míka, V., Pozdíšek, J., Tillmann, P., Nerušil, P., Buchgraber, K. and Gruber, L., 2003. Development of NIR calibration valid for two different grass sample collections. Czech Jour. Animal Science, 48(10): 419-424.
Moore, K. J., Roberts, C. A. and Fritz, J. O., 1990. Indirect estimation of botanical composition of alfalfa-smooth bromegrass mixtures. Agronomy Jour. 82: 287–290.
Norris, K. H., Barnes, R. F., Moore, J. E. and Shenk, J. S., 1976. Predicting forage quality by infrared reflectance spectroscopy. Jour. Animal Science, 43: 889–897.
Pilon, R., Klumpp, K., Carrere, P. and Picon-Cochard, C., 2010. Determination of aboveground net primary productivity and plant traits in grasslands with near-infrared reflectance spectroscopy. Jour. Ecosystem, 13: 851-859.
Reeves, J. B, III., 2012. Potential of near-and mid-infrared spectroscopy in biofuel production. Jour. Communication in Soil Science and Plant Analysis, 43: 478-495.
Richardson, A. D. and Reeves, J.B, III., 2005. Quantitative reflectance spectroscopy as an alternative to traditional wet lab analysis of foliar chemistry: near-infrared and mid-infrared calibrations compared. Canadian Jour. Forage Research, 35: 1122-1130.
Roberts, C. A., Stuth, J. W. and Flinn, P., 2004. Analysis of forages and feedstuffs. In Near-infrared spectroscopy in agriculture, Roberts C.A., Workman, Jr, J. and Reeves J.B., III (ed). Agronomy 44, Madison, WI: American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. 231-267 pp.
Ru, Y. J. and Glatz, P. C., 2000. Application of near infrared spectroscopy (NIR) for monitoring the quality of milk, cheese, meat and fish: a review. Asian-Australian Jour. Animal Science, 13: 1017- 1025.
Ruiz-Barrera, O., Rodríguez Muela, C., Arzola-Alvarez, C., Torres-Rivas, A., Castillo-Castillo, Y. and Holguin-Licón, C., 2005. Predicting nutritive value of irrigated pasture using near infrared reflectance spectrophotometer. Jour. American Society Animal Science, 56: 281-282.
Scholtz, G. D. J., Merwe, H. J. V. and Tylutki, T. P., 2009. Prediction of chemical composition of South African Medicago sativa L. hay from a near infrared reflectance spectroscopy spectrally structured sample population. South African Jour. Animal Science, 39: 183-187.
Shenk, J. S. and Westerhaus, M. O., 1993. Near-infrared reflectance analysis with single product and multiproduct calibrations. Jour. Crop Science, 33: 582-584.
Shenk, J. S. and Westerhaus, M. O., 1994. The application of near infrared reflectance spectroscopy (NIRS) to forage analysis. In: Forage quality evaluation and utilization. Fahey G. C., Jr. (ed) Madison, WI: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America. 406-449 pp.
Stubbs, T. L., Kennedy, A. C. and Fortuna, A. M., 2010. Using NIRS to predict fiber and nutrient content of dryland cereal cultivars. Jour. Agricultural and Food Chemistry, 58: 398–403.
Stuth, J., Jama, A. and Tolleson, D., 2003. Direct and indirect means of predicting forage quality through near infrared reflectance spectroscopy. Jour. Field Crop Research, 84: 45–56.
Valdés, C., Garcia, R., Calleja, A., Andrés, S. and Javier Giraldez, F., 2006. Potential use of visible and near infrared reflectance spectroscopy for the estimation of nitrogen fractions in forages harvested from permanent meadows. Jour. the Science of Food and Agriculture, 86: 308–314.
Van Soest, P. J., 1963. Use of detergents in the analysis of fibrous feeds. II. A rapid method for the determination of fiber and lignin. Jour. Association Official Agriculture Chemistry, 46: 829-835.
Ward, A., Nielsen, A. L. and Møller, H., 2011. Rapid assessment of mineral concentration in meadow grasses by near infrared reflectance spectroscopy. Jour. Sensors, 11: 4830-4839.
Westerhaus. M., Workman. J. J. R., Reeves, J. B. and Mark, H., 2004. Quantitative analysis. In: Near infrared spectroscopy in agriculture, Roberts C. A., Workman J. and Reeves, III, J. B. (ed.). Agronomy Monograph No. 44 in the series. Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. 133–174 pp.
Williams, P. C., 2001. Implementation of near-infrared technology. In: Near Infrared Technology in the Agricultural and Food Industries, Williams P. C. and Norris K. (ed) 145-171. American Association of Cereal Chemist St. Paul, Minnesota, USA.
Williams, P. C. and Sobering, D. C., 1996. How do we do it: a brief summary of the methods we use in developing near infrared calibration. In: Near infrared spectroscopy: The future waves, Davis A. M. C., and Williams P. C. (ed). NIR Publications, Chichester, UK. 185-188 pp.
Woolnough, A. P. and Foley, W. J., 2002. Rapid evaluation of pasture quality for a critically endangered mammal, the northern hairy-nosed wombat (Lasiorhinus krefftii). Jour. Wildlife Research, 29: 91-100.