Consumer responses for tenderness and overall impression can be predicted by visible and near-infrared spectroscopy, Meullenet–Owens razor shear, and Warner–Bratzler shear force
- 20 February 2010
- journal article
- Published by Elsevier BV in Meat Science
- Vol. 85 (3), 487-492
- https://doi.org/10.1016/j.meatsci.2010.02.020
Abstract
Beef ribeye rolls (n = 40) from Select, low Choice, top (upper 2/3) Choice, and Prime quality grade carcasses were used to determine the relationship of visible and near-infrared spectroscopy (VNIR) reflectance, Warner–Bratzler shear force (WBSF), and Meullenet–Owens razor shear (MORS) with consumer responses for tenderness and overall impression. Steaks (2.54 cm) were cut and assigned to either 14 or 28 d aging (n = 4/aging period). Reflectance in the VNIR spectrum was measured 1 d from the box-date no less than 30 min after cutting, and prior to aging. The steak used for VNIR measurement was designated for WBSF and MORS measurement, whereas three adjacent steaks were cooked for evaluation by a consumer panel (n = 240 members). Steaks from the Select-grade ribeye rolls had the greatest (P = 0.06) WBSF values and lower (P < 0.05) overall impression scores than those from top Choice and Prime quality grades. Consumer panelists evaluated steaks aged 28 d as more tender (P < 0.05) than those aged 14 d. The relationship of mechanical tenderness measurements were higher with consumer panel responses for tenderness than with overall impression, and those relationships were stronger for the Select grade than for quality grades with higher degrees of marbling. The 2nd derivatives of VNIR measurements were more successful at predicting consumer panel responses of tenderness and overall impression than WBSF and MORS; thus, VNIR methodology was less invasive and more predictive than other, more traditional tenderness measurements.Keywords
This publication has 22 references indexed in Scilit:
- Application of near infrared reflectance spectroscopy to predict meat and meat products quality: A reviewMeat Science, 2009
- Near-infrared reflectance spectroscopy for predicting chemical, instrumental and sensory quality of beefMeat Science, 2008
- The use of visible and near infrared reflectance spectroscopy to predict beef M. longissimus thoracis et lumborum quality attributesMeat Science, 2008
- Using the near-infrared system to sort various beef middle and end muscle cuts into tenderness categoriesJournal of Animal Science, 2008
- On-line classification of US Select beef carcasses for longissimus tenderness using visible and near-infrared reflectance spectroscopyMeat Science, 2005
- Prediction of color, texture, and sensory characteristics of beef steaks by visible and near infrared reflectance spectroscopy. A feasibility studyMeat Science, 2003
- Prediction of Cooked Rice Texture Using Extrusion and Compression Tests in Conjunction with Spectral Stress Strain AnalysisCereal Chemistry Journal, 2000
- Differentiation of Beef and Kangaroo Meat by Visible/Near‐Infrared Reflectance SpectroscopyJournal of Food Science, 1999
- National Consumer Retail Beef Study: Palatability Evaluations of Beef Loin Steaks that Differed in MarblingJournal of Food Science, 1987
- Comparison of Subcutaneous Fat Thickness, Marbling and Quality Grade for Predicting Palatability of BeefJournal of Food Science, 1982