The invention relates to methods and devices for predicting the tenderness of a selection of meat. In particular, the invention relates to methods and devices for predicting the tenderness of a selection of meat using a blade or blades that penetrate the selection of meat.
Accurately predicting the tenderness of a particular selection of meat when fully cooked, particularly the tenderness of beef and pork cuts, is a major concern within the protein industry. While it is well known that consumers find tender meat cuts more desirable, the tenderness of meat cuts—in particular the tenderness of beef and pork cuts—tends to vary considerably. Tenderness is thus of critical importance to the producer since, due to the higher desirability of more tender meats in the eyes of the consumer, a higher price may be commanded for more tender meats. By accurately identifying the more tender meat cuts during slaughter and processing, the producer may receive the highest return for its meats, while at the same time providing the consumer with the most consistent and desirable product. The importance of an accurate method of predicting meat tenderness has thus been long recognized, and a number of methods have been proposed or developed for making such predictions based on various observations or measurements performed on meat products.
Within the United States, beef is graded by the United States Department of Agriculture (USDA) for yield and quality according to subjective grading criteria. These criteria include the degree of marbling of the beef and the maturity of the animal when slaughtered. Maturity is determined by an inspector based on a visual inspection of the carcass. With respect to quality grading, the higher categories for beef are “prime” and “choice.” A prime meat, the highest quality grade, will come from the carcass of a young animal and will exhibit abundant marbling.
Inspection of a beef carcass according to the USDA's method requires that a series of precise cuts be performed in order to produce a sample for inspection. Because the USDA quality inspection criteria are qualitative and based only on visual inspection, the quality of the results is dependent upon the skill and experience of the inspector. In addition, it will be seen that to the extent that actual meat tenderness does not correlate to the visual criteria used for this inspection, the correlation between the quality grade assigned and the meat tenderness will be low. Specifically, it is known that the USDA quality grading method will typically produce a lower grade for a meat that has a low quantity of intramuscular fat. It is believed, however, that approximately fifty percent of beef carcasses exhibiting low intramuscular fat content will in fact produce relatively tender meats. If those carcasses with more tender meats could be identified from within this group of low intramuscular fat carcasses, they could potentially command a significantly higher return, thereby increasing the value associated with each such carcass, and providing the consumer with a final meat product with a more predictable tenderness.
In addition to qualitative methods such as performed by the USDA, the art also includes a number of attempts to provide quantitative methods for analyzing meat tenderness or overall quality. In particular, a number of methods of predicting meat tenderness based on optical properties have been suggested. For example, U.S. Pat. No. 3,493,774 to Knudsen teaches a method of comparing the color of a meat specimen immediately after a cut is made to a known color sample. U.S. Pat. No. 6,088,114 to Richmond et al. teaches a method based on the principle that connective tissues in meat fluoresce when exposed to particular wavelengths of ultraviolet light. This method involves the insertion of a probe into a carcass where the probe includes an ultraviolet light source. Similarly, U.S. Pat. No. 6,363,328 to Nadeau teaches a meat probe and artificial neural network that predicts tenderness based on collected fluorescence data from meat connective tissue. U.S. Pat. No. 6,563,580 to Aignel et al. teaches a method for determining beef quality based upon the measurement of the absorption properties of the meat in the visible to near-infrared range.
Another class of methods for measuring meat tenderness involves the measurement of various mechanical properties of the meat. Physical probes of various sorts are inserted into the meat for this purpose. For example, U.S. Pat. No. 4,052,890 to Kammlah et al. teaches a method involving a pointed probe that is inserted directly into a cooked round, whereby the force required to penetrate the meat is measured and correlated to tenderness. Another such method of predicting meat tenderness, based on a determination of a “stress relaxation coefficient” of a meat sample, is taught by U.S. Pat. No. 6,001,655 to Spadaro et al. In the Spadaro et al. method, a meat sample is subjected to a compressive force, and the change in force over time and the change in sample size over time is used in order to derive the stress relaxation coefficient. This coefficient is then aggregated with other physical parameters and correlated to meat tenderness. U.S. Pat. No. 4,939,927 to Johnson teaches a meat probe with two separate pistons driving a cone-shaped probe. A scale associated with each piston measures the depth of penetration of the probe and the force required for penetration; these measures are then correlated to tenderness.
To the inventor's knowledge, none of these prior art devices have proven successful in the marketplace. For example, an independent evaluation of the Johnson meat probe (known as the “Tendertec” instrument) performed by researchers at Colorado. State University concluded that the device failed to consistently detect tenderness differences in steaks derived from a large number of carcasses. The inventor hereof believes that one of the fundamental problems with these devices is their inherent lack of accuracy and repeatability. The two-spring arrangement of the Tendertec instrument, for example, is not believed to provide sufficiently accurate and repeatable force measurements to discriminate between tender and tough meats consistently. In addition, the inventor hereof believes that the shape of the probe in such devices appears inappropriate for measuring tenderness, as it does not imitate the interaction of human teeth with meats of varying tenderness.
A razor blade shear method of predicting tenderness has recently been developed by L. C. Cavitt and others for use with respect to cooked poultry meat. In this method, a sharpened razor blade is inserted into a cooked breast fillet and the shear force and shear energy associated with the insertion of the blade is measured. This method offers advantages in that no sample cutting or weighing is required in order to conduct the test, and the test is minimally destructive since only a small blade incision is made in the test sample. This method is not believed to be effective, however, in predicting the tenderness of raw meats.
Within the beef industry, the instrument-based tenderness prediction method most commonly employed today is the Warner-Bratzler shear method. This method has been employed within the industry as an adjunct to USDA tenderness grading for many years. Like the Cavitt poultry method described above, the Warner-Bratzler method is performed with respect to a cooked meat sample that has been previously collected from a carcass. Preferably, this sample is an approximately one-inch thick steak removed from the longissimus dorsi muscle, which is then cooked to a pre-determined internal temperature. Cores are then collected from the cooked steak, typically six to eight in total, with each core being removed parallel to the orientation of the muscle fibers and being of a precise size, typically 1.27 cm in diameter. A specialized shear machine is then employed to measure the resistance of the core sample to a cutting force applied across its surface. The core is sheared perpendicular to the muscle fibers by a triangular-shaped, blunt-ended blade. The Warner-Bratzler method has been shown to produce accurate tenderness predictions for cooked meats, but has not been shown effective in predicting tenderness from testing of raw meats.
A newer instrument-based method for predicting beef tenderness has been developed by S. D. Shackleford and others at the Roman L. Hruska U.S. Meat Animal Research Center at Clay Center, Nebraska. This method is generally analogous to the Warner-Bratzler method, except that a 1 cm thick, 5 cm long slice is removed from each of the samples parallel to the muscle fibers. These slices are then sheared perpendicular to the fibers by a flat, half-round blade. Like the Warner-Bratzler method, this method has been shown by experimental results to accurately categorize carcasses into tenderness groups. Also like the Warner-Bratzler method, however, this method is limited to testing on cooked samples removed from the beef carcass.
While the Warner-Bratzler and Shackleford instrument-based methods for predicting beef tenderness described above have proven to be good predictors, it will be seen from the above description that these methods involve a lengthy and expensive process for the meat producer. Steaks must be cut from the carcass, the steaks must be cooked, and then samples must be precisely cut from those steaks and sheared. In addition, the validity of the shear measurements depends strongly upon the ability of the operator to determine fiber orientation within the sample. The steaks cut for the tenderness evaluation are lost, thereby reducing the yield from every tested carcass. What is desired then is an instrument-based, quantitative method for predicting meat tenderness, particularly beef and pork tenderness, that may be performed quickly and inexpensively, specifically could be performed with respect to uncooked meat, and ideally could be performed upon a beef or pork carcass without ruining the usability of any of the meat from the carcass and without slowing down production in the processing plant where the predictive method is being performed. Such a method could ideally be employed in conjunction with the standard. USDA visual tenderness grading process.