Prediction of sensory characteristics of lamb meat samples by near infrared reflectance spectroscopy

Meat Science

Volumn 76, Issue 3, 2007, Pages 509-516

  Andres S ^a   Murray, I ^a   Navajas, E A ^a   Fisher, A V ^b   Lambe, N R ^a   Bunger L ^a  

^a SCOTTISH AGRICULTURAL COLLEGE   (United Kingdom)

^b UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

Chemical composition; Lamb; Meat quality; NIR spectroscopy; Sensory characteristics; Taste panel

Indexed keywords

OVIS ARIES;

EID: 34247202076     PISSN: 03091740     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.meatsci.2007.01.011     Document Type: Article

References (34)

1. Byrne C.E., Downey G., Troy D.J., and Buckley D.J. Non-destructive prediction of selected quality attributes of beef by near-infrared reflectance spectroscopy between 750 and 1098 nm. Meat Science 49 4 (1998) 399-409
2. Cozzolino D., and Murray I. Identification of animal meat muscles by visible and near infrared reflectance spectroscopy. Lebensmittel-Wissenschaft und-Technologie 37 4 (2004) 447-452
3. Cross H.R., and Whittaker A.D. The role of instrument grading in a beef value-based marketing system. Journal of Animal Science 70 (1992) 984-989
4. Defra. (2005). Agricultural quick statistics. Available from: http://statistics.defra.gov.uk/esg/quick/agri.asp.
5. Dewar-Durie, A. (2001). The Scottish sheep industry: a way forward. Report to the Minister of Rural Affairs, Ross Finnie. Available from: http://www.scotland.gov.uk/library3/agri/tssi-01.asp.
6. Downey G., and Hildrum K.I. Analysis of meat. In: Roberts C.A., Workman Jr. J., and Reeves III J.B. (Eds). Near infrared spectroscopy in agriculture agronomy No. 44 (2004), American Society of Agronomy Inc., Crop Science Society of America Inc., Soil Science Society of America Inc, Madison, WI, USA 599-632
7. Dundon, P., Sundstrom, B., & Gaden, R. (2000). Producing and processing quality beef from Australian cattle herds: industry outcomes. Cooperative Research Centre for the Cattle and Beef Industry (Meat Quality).
8. Garci{dotless}́a-Olmo, J., De Pedro, E., Garrido-Varo, A., Jiménez, A., Salas, J., & Santolalla, M. (2000). Fatty acids analysis of Iberian pig fat by near infrared spectroscopy (NIRS). In J. A. Alfonso de Almeida, & J. L. Tirapicos Nunes (Eds.), Tradition and innovation in Mediterranean pig production. International symposium on mediterranean pig (pp. 191-195). 26-28 November 1998, Evora, (Portugal).
9. García-Olmo J., Garrido-Varo A., and De Pedro E. The transfer of fatty acid calibration equations using four sets of unsealed liquid standardisation samples. Journal of Near Infrared Spectroscopy 9 1 (2001) 49-62
10. Geesink G.H., Schreutelkamp F.H., Frankhuizen R., Vedder H.W., Faber N.M., Kranen R.W., et al. Prediction of pork quality attributes from near infrared reflectance spectra. Meat Science 65 1 (2003) 661-668
11. Hildrum K.I., Isaksson T., Næs T., Nielsen B.N., Rødbotten M., and Lea P. Near infrared reflectance spectroscopy in the prediction of sensory properties of meat. Journal of Near Infrared Spectroscopy 3 (1995) 81-87
12. Hildrum K.I., Nielsen B.N., Mielnik M., and Næs T. Prediction of sensory characteristics of beef by near-infrared spectroscopy. Meat Science 38 1 (1994) 67-80
13. Hopkins D.L., Safari E., Thompson J.M., and Smith C.R. Video image analysis in the Australian meat industry - precision and accuracy of predicting lean meat yield in lamb carcasses. Meat Science 67 (2004) 269-274
14. Hoving-Bolink A.H., Vedder H.W., Merks J.W.M., de Klein W.J.H., Reimert H.G.M., Frankhuizen R., et al. Perspective of NIRS measurements early post-mortem for prediction of pork quality. Meat Science 69 3 (2005) 417-423
15. Leroy B., Lambotte S., Dotreppe O., Lecocq H., Istasse L., and Clinquart A. Prediction of technological and organoleptic properties of beef longissimus thoracis from near-infrared reflectance and transmission spectra. Meat Science 66 1 (2003) 45-54
16. Liu Y.L., Lyon B.G., Windham W.R., Realini C.E., Pringle T.D.D., and Duckett S.K. Prediction of color, texture, and sensory characteristics of beef steaks by visible and near infrared reflectance spectroscopy. A feasibility study. Meat Science 65 3 (2003) 1107-1115
17. Mitsumoto M., Maeda S., Mitsuhashi T., and Ozawa S. Near-infrared spectroscopy determination of physical and chemical characteristics in beef cuts. Journal of Food Science 56 6 (1991) 1493-1496
18. MLC (2002). Sheep Yearbook 2002. MLC, Milton Keynes, Buckinghamshire.
19. Næs T., and Hildrum K.I. A comparison of multivariate calibration and discriminant analysis for determining tenderness of meat by NIR spectroscopy. Applied Spectroscopy 51 (1997) 350-357
20. Navajas E., Glasbey C.A., McLean K.A., Fisher A.V., Charteris A.J.L., Lambe N.R., et al. In vivo measurements of muscle volume by automatic image analysis of spiral computed tomography scans. Animal Science 82 (2005) 545-553
21. Park B., Chen Y.R., Hruschka W.R., Shackelford S.D., and Koohmaraie M. Near infrared reflectance analysis for predicting beef longissimus tenderness. Journal of Animal Science 76 (1998) 2115-2120
22. Park B., Chen Y.R., Hruschka W.R., Shackelford S.D., and Koohmaraie M. Principal components regression of near infrared reflectance spectra for beef tenderness prediction. Transactions of the American Society of Agricultural Engineers 43 3 (2001) 609-615
23. Rødbotten R., Mevik B.H., and Hildrum K.I. Prediction and classification of tenderness in beef from non-invasive diode array detected NIR spectra. Journal of Near Infrared Spectroscopy 9 (2001) 199-210
24. Rødbotten R., Nielsen B.N., and Hildrum K.I. Prediction of beef quality attributes from early post-mortem near infrared reflectance spectra. Food Chemistry 69 (2000) 427-436
25. Schwarze, H. (1996). Report no. 996-10-1. Third European symposium on near infrared (NIR) spectroscopy: continuous fat analysis in the meat industry (pp. 43-49).
26. Shackelford S.D., Wheeler T.L., and Koohmaraie M. Development of optimal protocol for visible and near-infrared reflectance spectroscopic evaluation of meat quality. Meat Science 68 (2004) 371-381
27. Shenk J.S., Westerhaus M.O., and Workman J.J. Application of NIR spectroscopy to agricultural products. In: Burns D.A., and Ciurczak E.W. (Eds). Handbook of near infrared analysis (1992), Marcel Dekker Inc, New York 383-431
28. Stanford K., Richmond R.J., Jones S.D.M., Robertson W.M., Prince M.A., and Gordon A.J. Video image analysis for on-line classification of lamb carcasses. Animal Science 67 (1998) 311-316
29. Swatland H.J. On-line evaluation of meat (1995), Technomic Publishing Company, Pennsylvania
30. Varnam A.H., and Sutherland J.P. Meat and meat products: Technology, chemistry, and microbiology (1995), Chapman and Hall, London
31. Vatansever L., Kurt E., Enser M., Nute G.R., Scollan N.D., Wood J.D., et al. Shelf life and eating quality of beef form cattle of different breeds given diets differing in n-3 polyunsaturated fatty acid composition. Animal Science 71 (2000) 471-482
32. Venel C., Mullen A.M., Downey G., and Troy D.J. Prediction of tenderness and other quality attributes of beef by near infrared reflectance spectroscopy between 750 and 1100 nm; further studies. Journal of Near Infrared Spectroscopy 9 (2001) 185-198
33. Warriss P.D. Meat science: An introductory text (2000), CABI Publishing, Wallingford
34. Wood J.D., Richardson R.I., Nute G.R., Fisher A.V., Campo M.M., Kasapidou E., et al. Effects of fatty acids on meat quality: a review. Meat Science 66 (2003) 21-32