ACCEPTABILITY OF VARIOUS GROUND BEEF AND PORK PRODUCTS EXTENDED WITH MECHANICALLY SEPARATED BEEF

Six blends of ground beef and six blends of ground pork containing 0, 15, 30, 45, 60 or 75% mechanically separated beef (MSB) were prepared. Also five batches of fermented sausage and spiced luncheon loaf containing 0, 5, 10, 15 and 20% MSB were formulated. Level of MSB was not related to juiciness rating or mealiness scores of cooked beef/MSB or pork/MSB patties. The level of MSB significantly affected overall eating satisfaction ratings for each blend of MSB patties. MSB at levels of 15% or more had a negative effect on flavor acceptability of cooked ground beef or pork. Fermented sausage products could be extended with only 5% MSB without creating defects in visual appearance or sensory properties. However, the inclusion of 20% MSB yielded a spiced luncheon loaf which was higher in eating quality than an all-beef control. The beef/MSB patties, fermented sausage, and spiced luncheon loaves containing 15% MSB were acceptable for visual appearance. Based on this study, MSB produced from a press type machine, can be blended up to 15% with ground beef, ground pork and sausage products without significantly decreasing raw appearance, sensory properties or storage life. Since MSB is a red meat product available at a similar low cost as textured vegetable protein, the red meat industry would benefit from expanded use of this high protein extender.     

Weighted Estimation of Harmonic Components in a Musical Sound Signal

The study of musical sound has become a popular research field. Harmonic regression signal plus noise statistical models have been used to analyze sound signals. However, it is common to give estimates of harmonic parameters without indications of their uncertainties. Least squares estimates for harmonic models have been studied and asymptotic variance expression have been developed. In practice, window-based estimates are used. This paper studies the statistical properties of such estimates; in particular, we use asymptotic variance expressions to develop standard errors and construct confidence intervals. We present applications and examples of the statistical techniques to musical sound signal analysis.