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

Volumn 85, Issue 2, 2007, Pages 518-526

  Walker, J W ^a   Campbell, E S ^a   Lupton, C J ^a   Taylor Jr , C A ^a   Waldron, D F ^a   Landau, S Y ^b  

^a TEXAS A AND M UNIVERSITY   (United States)

^b VOLCANI CENTER   (Israel)

Author keywords

Diet composition; Feces; Goat; Juniper; Near infrared reflectance spectroscopy

Indexed keywords

CAPRA HIRCUS; JUNIPERUS;

AGE; ANIMAL; ANIMAL DISEASE; ANIMAL FOOD; ARTICLE; BREEDING; CALIBRATION; CHEMISTRY; COMPARATIVE STUDY; DIET; FECES; FEMALE; GENETICS; GOAT; JUNIPERUS; MALE; NEAR INFRARED SPECTROSCOPY; PHYSIOLOGY; PREDICTION AND FORECASTING; SEX DIFFERENCE;

AGE FACTORS; ANIMAL FEED; ANIMALS; BREEDING; CALIBRATION; DIET; FECES; FEMALE; GOATS; JUNIPERUS; MALE; PREDICTIVE VALUE OF TESTS; SEX FACTORS; SPECTROSCOPY, NEAR-INFRARED;

EID: 34047253915     PISSN: 00218812     EISSN: None     Source Type: Journal    
DOI: 10.2527/jas.2006-202     Document Type: Article

References (27)

1. Castle, E. J. 1956. The rate of passage of food stuffs through the alimentary tract of the goat. I. Studies on adult animals fed on hay and concentrate. Br. J. Nutr. 10:15.
2. Foss. 2000. WinISI II training handbook. Foss NIRSystems, Silver Spring, MD.
3. Geladi, P., D. McDougall, and H. Martens. 1985. Linearisation and scatter correction for near-infrared reflectance spectra of meat. Appl. Spectrosc. 39:491-500.
4. Godfrey, R. W., R. E. Dodson, J. K. Bultman, D. R. Tolleson, J. W. Stuth, and A. J. Norman. 2001. Use of near-infrared reflectance spectroscopy to differentiate pregnancy status and sex of hair sheep in the tropics. J. Anim. Sci. 79(Suppl. I):26.
5. Hays, W. L. 1963. Statistics for Psychologists. Holt, Rinehart & Winston, New York, NY.
6. Holloway, J. W., R. E. Estell, and W. T. Butte, Jr. 1981. Relationships between fecal components and forage consumption and digestibility. J. Anim. Sci. 52:836-848.
7. ISI. 1999. WinISI, the complete software solution for routine analysis, robust calibrations and networking. Version 1.02A. Infrasoft International, Port Matilda, PA.
8. Landau, S., T. Glasser, H. Muklada, L. Dvash, A. Perevolotsky, E. D. Ungar, and J. W. Walker. 2005. Fecal NIRS prediction of dietary protein percentage and in vitro dry matter digestibility in diets ingested by goats in Mediterranean scrubland. Small Rumin. Res. 59:251-263.
9. Leite, E. R., and J. W. Stuth. 1990. Value of multiple fecal indices for predicting diet quality and intake of steers. J. Range Manage. 43:139-143.
10. Lyons, R. K., and J. W. Stuth. 1992. Fecal NIRS equations for predicting diet quality of free-ranging cattle. J. Range Manage. 45:238-244.
11. Mahalanobis, P. C. 1936. On the generalized distances in statistics. Proc. Natl. Inst. Sci. India 12:49-55.
12. Martens, H., and T. Naes. 1987. Multivariate calibration by data compression. Pages 57-87 in Near-Infrared Technology in the Agricultural and Food Industries. P. Williams and K. H. Norris, ed.
13. Morrison, D. F. 1976. Multivariate Statistical Methods. McGraw-Hill Book Company, New York, NY.
14. Naes, T., T. Isakson, T. Feam, and T. Davies. 2002. Validation. Pages 155-177 in A User-Friendly Guide to Multivariate Calibration and Classification. T. Naes, T. Isakson, T. Fearen, and T. Davies, ed. NIR Publications, Chichester, UK.
15. Osborn, R., D. Tolleson, T. Ginnett, S. Cooper, and J. Stuth. 2002. Determination of sex and age in white-tailed deer by near-infrared reflectance spectroscopy of feces. Vol. 115, Pages 44-45 in Proc. 82nd Annu. Conf. Am. Soc. Mammalogists, Lake Charles, LA, 15-19 June 2002, Am. Soc. Mammalogists, Lawrence, KS.
16. Perevolotsky, A., and N. G. Seligman. 1998. Role of grazing in Mediterranean rangeland ecosystems: Inversion of a paradigm. Binscience 48:1007-1017.
17. Taylor, C. A., Jr., E. S. Campbell, C. J. Lupton, D. F. Waldron, and J. W. Walker. 2005. Improving the use of goats to manage juniper. Texas Agric. Exp. Sta. Ann. Rep. Texas Food & Fibers Comm. 8-17.
18. Tolleson, D. R., R. D. Randel, J. W. Stuth, and D. A. Neuendorff. 2005. Determination of sex and species in red and fallow deer by near-infrared reflectance spectroscopy of the feces. Small Rumin. Res. 57:141-150.
19. Tolleson, D. R., T. W. Wilson, R. D. Randel, D. A. Neuendorff, A. W. Lewis, and J. W. Stuth. 2000. Discrimination between physiologically different groups of cattle via near-infrared reflectance spectroscopy of feces. J. Anim. Sci. 78(Suppl. 1):14. (Abstr.)
20. Walker, J. W., D. W. Clark, and S. D. McCoy. 1998. Fecal NIRS for predicting percent leafy spurge in diets. J. Range Manage. 51:450-455.
21. Walker, J. W., and K. C. Hodkinson. 1999. Grazing management: new technologies for old problems. Proc. VI International Rangeland Congress, People and Rangelands Building the Future. Vol. 1:424-430.
22. Walker, J. W., S. D. McCoy, K. L. Launchbaugh, M. J. Fraker, and J. Powell. 2002. Calibrating fecal NIRS equations for predicting botanical composition of diets. J. Range Manage. 55:374-382.
23. Whitworth, W. R. 2002. Estimating redberry and ashe juniper intake using fecal NIRS. MS Thesis, Angelo State Univ., San Angelo, TX.
24. Williams, P. C. 1987. Commercial near-infrared reflectance analyzers. Pages 107-142 in Near-Infrared Technology in the Agricultural and Food Industries. P. Williams and K. H. Norris. ed. Am. Assoc. Cereal Chemists Inc., St. Paul, MN.
25. Williams, P. C. 2001. Implementation of near-infrared technology. Pages 145-170 in Near-Infrared Technology in the Agricultural and Food Industries. 2nd ed. P. Williams and K. H. Norris, ed. Am. Assoc. Cereal Chemists Inc., St. Paul, MN.
26. Williams, P. C., and K. H. Norris. 1987. Qualitative applications of near-infrared reflectance spectroscopy. Pages 241-246 in Near-Infrared Technology in the Agricultural and Food Industries. P. C. Williams and K. H. Norris, ed. Am. Assoc. Cereal Chemists Inc., St. Paul, MN.
27. Wofford, H., J. L. Holechek, M. L. Galyean, J. D. Wallace, and M. Cardenas. 1985. Evaluation of fecal indices to predict cattle diet quality. J. Range Manage. 38:450-454.