The application of near infrared spectroscopy to predict faecal nitrogen and phosphorus in multiple ruminant herbivore species
D. R. Tolleson A D and J. P. Angerer B CA Texas A&M AgriLife Research, Sonora Research Station, Sonora, TX 76950, USA.
B Texas A&M AgriLife Research, Blackland Research and Extension Center, Temple, TX 76502, USA.
C Present address: United States Department of Agriculture – Agricultural Research Service (USDA–ARS) Livestock and Range Research Laboratory, Miles City, MT 59301, USA.
D Corresponding author. Email: douglas.tolleson@ag.tamu.edu
The Rangeland Journal - https://doi.org/10.1071/RJ20071
Submitted: 17 July 2020 Accepted: 7 December 2020 Published online: 29 January 2021
Abstract
Near infrared spectroscopy (NIRS) was applied to determine faecal nitrogen and phosphorus using a temporo-spatially diverse dataset derived from multiple ruminant herbivore species (i.e. cattle, bison, deer, elk, goats, and sheep). Single-species NIRS calibrations have previously been developed to predict faecal constituents. Multi-species NIRS calibrations have previously been developed for herbivore faecal nitrogen but not for faecal phosphorus. Faecal samples representing a herd or flock composite were analysed via NIRS (400–2498 nm). Calibration sets for faecal nitrogen and phosphorus were developed from: (1) all samples from all six species, (2) all cattle samples only, (3) all samples except those from bison, (4) all samples except those from deer, (5) all samples except those from elk, (6) all samples except those from goats, and (7) all samples except those from sheep. Validation sample sets included: (1) each of the individual species (predicted with a cattle only-derived calibration), and (2) each of the individual species (other than cattle) predicted with a multi-species calibration constructed from all cattle samples plus those samples from the remaining four species (i.e. ‘leave-one-out’). All multiple coefficient of determination (R2) values for faecal nitrogen calibrations were ≥0.97. Corresponding standard error of cross validation (SECV) values were ≤0.13. Validation simple coefficient of determination (r2) and standard error of prediction (SEP) of each alternate species using the cattle-derived calibration ranged from 0.76 to 0.84, and 0.28 to 0.5 respectively. Similar values for the sequential species leave-one-out validation for faecal nitrogen were 0.67 to 0.89, and 0.17 to 0.47 respectively. All R2 values for faecal phosphorus calibrations were ≥0.79; corresponding SECV were ≤0.14. Validation r2 and SEP of each alternate species using the cattle-derived phosphorus calibration were ≤0.63 and ≥0.13 respectively. Similar values for the sequential species leave-one-out validation were ≤0.66 and ≥0.22 respectively for faecal phosphorus. Multi-species faecal NIRS calibrations can be developed for monitoring applications in which determination of faecal nitrogen is appropriate, e.g. free-ranging herbivore nutrition, nitrogen deposition from animal faeces on rangelands with declining forage quality, or runoff from confined animal feeding operations. Similar calibrations for faecal phosphorus require additional research to ascertain their applicability.
Keywords: environmental pollution, faecal nutrients, faeces, herbivores, monitoring, near infrared spectroscopy, NIRS, nitrogen, nutritional status, phosphorus.
References
Althaus, B., Papke, G., and Sundrum, A. (2013). Technical note: use of near infrared reflectance spectroscopy to assess nitrogen and carbon fractions in dairy cow feces. Animal Feed Science and Technology 185, 53–59.| Technical note: use of near infrared reflectance spectroscopy to assess nitrogen and carbon fractions in dairy cow feces.Crossref | GoogleScholarGoogle Scholar |
Andrés, S., Giraldez, F. J., Lopez, S., Mantecon, 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. Journal of the Science of Food and Agriculture 85, 1564–1571.
| Nutritive evaluation of herbage from permanent meadows by near-infrared reflectance spectroscopy: 1. Prediction of chemical composition and in vitro digestibility.Crossref | GoogleScholarGoogle Scholar |
AOAC (1990) ‘Official Methods of Analysis.’ 15th edn. (Association of Official Analytical Chemists: Arlington, VA, USA.)
Bohnert, D. (2004). Strategic supplementation of crude protein: an economical management strategy for Intermountain cow/calf producers. Special Report 1052. Current Forage and Livestock Production Research, Oregon State University Agricultural Experiment Station, Corvallis, OR, USA. pp. 10–16.
Chataigner, F., Surault, F., Huyghe, C., and Julier, B. (2010). Determination of botanical composition in multispecies forage mixtures by near infrared reflectance spectroscopy. In: ‘Sustainable Use of Genetic Diversity in Forage and Turf Breeding’. (Ed. C. Huyghe.) pp. 199–203. (Springer: Berlin.)
Coates, D. B. (1998). Predicting diet digestibility and crude protein content from the faeces of grazing cattle. Final Report of project CS.253 to the Meat Research Corporation, Sydney, Australia.
Coates, D. B., and Dixon, R. M. (2010). Fecal NIRS calibration for predicting protein and digestibility in the diet of cattle: Fistulate and pen feeding procedures for generating diet–fecal pairs. In: ‘Shining Light on Manure Improves Livestock and Land Management’. (Eds J. Walker and D. Tolleson.) pp. 23–41. (Texas AgriLife Research College Station, TX, and Society for Range Management: Littleton, CO, USA.)
Craine, J. M., Elmore, A. J., Olson, K. C., and Tolleson, D. R. (2010). Climate change and nutritional stress in cattle. Global Change Biology 16, 2901–2911.
| Climate change and nutritional stress in cattle.Crossref | GoogleScholarGoogle Scholar |
Dagnew, M. D., Crowe, T. G., and Schoenau, J. J. (2004). Measurement of nutrients in Saskatchewan hog manures using near-infrared spectroscopy. Canadian Biosystems Engineering 46, 6.33–6.37.
Dixon, R., and Coates, D. (2009). Near infrared spectroscopy of faeces to evaluate the nutrition and physiology of herbivores. Journal of Near Infrared Spectroscopy 17, 1–31.
| Near infrared spectroscopy of faeces to evaluate the nutrition and physiology of herbivores.Crossref | GoogleScholarGoogle Scholar |
Duckworth, J. (2004). Mathematical data preprocessing. In: ‘Near-infrared Spectroscopy in Agriculture’. (Eds C. A. Roberts, J. Workman, Jr. and J. B. Reeves III.) pp. 115–132. (The American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America: Madison, WI, USA.)
Hofmann, R. R. (1988). Morphological evolutionary adaptations of the ruminant digestive system. In: ‘Comparative Aspects of Physiology of Digestion in Ruminants’. (Ed. A. Dobson.) pp. 1–20. (Cornell University Press: Ithaca, NY, USA.)
Hubbard, R. K., Newton, G. L., and Hill, G. M. (2004). Water quality and the grazing animal. Journal of Animal Science 82, E255–E263.
| 15471806PubMed |
Huston, J. E., and Pinchak, W. E. (1991). Range animal nutrition. In: ‘Grazing Management: An Ecological Perspective’. (Eds R. K. Heitscmidt and J. W. Stuth.) pp. 27–64. (Timber Press: Portland OR, USA.)
Jongbloed, A. W., and Lenis, N. P. (1998). Environmental concerns about animal manure. Journal of Animal Science 76, 2641–2648.
| Environmental concerns about animal manure.Crossref | GoogleScholarGoogle Scholar | 9814905PubMed |
Landau, S., Glasser, T., Dvash, L., and Perevolotsky, A. (2004). Fecal NIRS to monitor the diet of Mediterranean goats. South African Journal of Animal Science 34, 76–80.
Leslie, D. M., and Starkey, E. E. (1987). Fecal indices to dietary quality – a reply. Journal of Wildlife Management 51, 321–325.
| Fecal indices to dietary quality – a reply.Crossref | GoogleScholarGoogle Scholar |
Leslie, D. M., Bowyer, R. T., and Jenks, J. A. (2008). Facts from feces: nitrogen still measures up as a nutritional index for mammalian herbivores. The Journal of Wildlife Management 72, 1420–1433.
| Facts from feces: nitrogen still measures up as a nutritional index for mammalian herbivores.Crossref | GoogleScholarGoogle Scholar |
Li, H., Tolleson, D. R., Stuth, J. W., Bai, K., Mo, F., and Kronberg, S. (2007). Fecal near infrared reflectance spectroscopy to predict dietary protein and digestibility of sheep. Small Ruminant Research 68, 263–268.
Liu, X., Han, L. J., and Yang, Z. L. (2011). Transfer of near infrared spectrometric models for silage crude protein detection between different instruments. Journal of Dairy Science 94, 5599–5610.
| Transfer of near infrared spectrometric models for silage crude protein detection between different instruments.Crossref | GoogleScholarGoogle Scholar | 22032383PubMed |
Lyons, R. K., and Machen, R. V. (2007). What’s limiting: quality or quantity? Rangelands 29, 4–7.
| What’s limiting: quality or quantity?Crossref | GoogleScholarGoogle Scholar |
Mahalanobis, P. C. (1930). On tests and measures of groups divergence. Journal of the Asiatic Society of Bengal 26, 541.
Malley, D. F., Martin, P. D., and Ben-Dor, E. (2004). Application in analysis of soils. In: ‘Near-infrared Spectroscopy in Agriculture’. (Eds C. A. Roberts, J. Workman Jr., and J. B. Reeves III.) pp. 729–784. (The American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America: Madison, WI, USA.)
Malley, D. F., McClure, C., Martin, P. D., Buckley, K., and McCaughey, W. P. (2005). Compositional analysis of cattle manure during composting using a field‐portable near‐infrared spectrometer. Communications in Soil Science and Plant Analysis 36, 455–475.
| Compositional analysis of cattle manure during composting using a field‐portable near‐infrared spectrometer.Crossref | GoogleScholarGoogle Scholar |
Martens, H., and Naes, T. (1987). Multivariate calibration by data compression. In: ‘Near-infrared Technology in the Agricultural and Food Industries’. 1st edn. (Eds P. Williams and K. H. Norris.) pp. 57–87. (American Association of Cereal Chemists: St Paul, MN, USA.)
Mosely, J. C., Cook, P. S., Griffis, A. J., and O’Laughlin, J. (1997). Guidelines for managing cattle grazing in riparian areas to protect water quality: review of research and best management practices policy. Idaho Forest, Wildlife and Range Policy Analysis Group, Report No. 15. p.75.
Neumeister, V., Henker, J., Kaltenborn, G., Sprossig, C., and Jaross, W. (1997). Simultaneous determination of fecal fat, nitrogen, and water by near-infrared reflectance spectroscopy. Journal of Pediatric Gastroenterology and Nutrition 25, 388–393.
| Simultaneous determination of fecal fat, nitrogen, and water by near-infrared reflectance spectroscopy.Crossref | GoogleScholarGoogle Scholar | 9327368PubMed |
Nixon, S. W. (1995). Coastal marine eutrophication: a definition, social causes, and future concerns. Ophelia 41, 199–219.
| Coastal marine eutrophication: a definition, social causes, and future concerns.Crossref | GoogleScholarGoogle Scholar |
Ott, R. L. (1984). ‘An Introduction to Statistical Methods and Data Analysis.’ (Duxbury Press: Belmont, CA, USA.)
Plumb, G. E., and Dodd, J. L. (1993). Foraging ecology of bison and cattle on a mixed prairie: implications for natural area management. Ecological Applications 3, 631–643.
| Foraging ecology of bison and cattle on a mixed prairie: implications for natural area management.Crossref | GoogleScholarGoogle Scholar | 27759299PubMed |
Reeves, J. B., and Van Kessel, J. S. (2000). Near-infrared spectroscopic determination of carbon, total nitrogen, and ammonium-N in dairy manures. Journal of Dairy Science 83, 1829–1836.
| Near-infrared spectroscopic determination of carbon, total nitrogen, and ammonium-N in dairy manures.Crossref | GoogleScholarGoogle Scholar | 10984159PubMed |
Roberts, C. A., Stuth, J., and Flinn, P. (2004). Analysis of forages and feedstuffs. In: ‘Near-infrared Spectroscopy in Agriculture’. (Eds C. A. Roberts, J. Workman Jr. and J. B. Reeves III.) pp. 231–268. (The American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America: Madison, WI, USA.)
Shenk, J. S., and Westerhaus, M. O. (1991). Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy. Crop Science 31, 469–474.
| Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy.Crossref | GoogleScholarGoogle Scholar |
Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society. Series B. Methodological 36, 111–133.
| Cross-validatory choice and assessment of statistical predictions.Crossref | GoogleScholarGoogle Scholar |
Strauch, A. M. (2011). Seasonal variability in faecal bacteria of semiarid rivers in the Serengeti National Park, Tanzania. Marine and Freshwater Research 62, 1191–1200.
| Seasonal variability in faecal bacteria of semiarid rivers in the Serengeti National Park, Tanzania.Crossref | GoogleScholarGoogle Scholar |
Villamuelas, M., Serrano, E., Espunyes, J., Fernández, N., López-Olvera, J. R., Garel, M., Santos, J., Parra-Aguado, M. Á., Ramanzin, M., Fernández-Aguilar, X., Colom-Cadena, A., Marco, I., Lavín, S., Bartolomé, J., and Albanell, E. (2017). Predicting herbivore faecal nitrogen using a multispecies near-infrared reflectance spectroscopy calibration. PLoS One 12, e0176635.
| Predicting herbivore faecal nitrogen using a multispecies near-infrared reflectance spectroscopy calibration.Crossref | GoogleScholarGoogle Scholar | 28453544PubMed |
Walker, J. W., Campbell, E. S., Lupton, C. J., Taylor, C. A., Waldron, D. F., and Landau, S. Y. (2007). Effects of breed, sex, and age on the variation and ability of fecal near-infrared reflectance spectra to predict the composition of goat diets. Journal of Animal Science 85, 518–526.
| Effects of breed, sex, and age on the variation and ability of fecal near-infrared reflectance spectra to predict the composition of goat diets.Crossref | GoogleScholarGoogle Scholar | 17235035PubMed |
Westerhaus, M. O. (1989). Interpretation of regression statistics. In: ‘Near infrared reflectance spectroscopy (NIRS): analysis of forage quality’. USDA, ARS, Agricultural Handbook No. 643. pp. 39–40. (USDA.)
Williams, P. C. (2001). Implementation of near-infrared technology. In: ‘Near-infrared Technology in the Agricultural and Food Industries’. 2nd edn. (Eds P. Williams and K. Norris.) pp. 145–170. (American Association of Cereal Chemists, Inc.: St. Paul, MN, USA.)
Xu, R., Tian, H., Pan, S., Dangal, S. R., Chen, J., Chang, J., Lu, Y., Skiba, U. M., Tubiello, F. N., and Zhang, B. (2019). Increased nitrogen enrichment and shifted patterns in the world’s grassland: 1860–2016. Earth System Science Data 11, 175–187.
| Increased nitrogen enrichment and shifted patterns in the world’s grassland: 1860–2016.Crossref | GoogleScholarGoogle Scholar |
