Relationships of a Detailed Mineral Profile of Meat with Animal Performance and Beef Quality

Abstract

Mineral profile of beef interests human health, but also animal performance and meat quality. This study analyzes the relationships of 20 minerals in beef (ICP-OES) with 3 animal performance and 13 meat quality traits analyzed on 182 samples of Longissimus thoracis. Animals’ breed and sex showed limited effects. The major sources of variation (farm/date of slaughter, individual animal within group and side/sample within animal) differed greatly from trait to trait. Mineral contents were correlated to animal performance and meat quality being significant 52 out of the 320 correlations at the farm/date level, and 101 out of the 320 at the individual animal level. Five latent factors explained 69% of mineral co-variation. The most important, “Mineral quantity” factor correlated with age at slaughter and with the meat color traits. Two latent factors (“Na+Fe+Cu” and “Fe+Mn”) correlated with performance and meat color traits. Two other (“K-B-Pb” and “Zn”) correlated with meat chemical composition and the latter also with carcass weight and daily gain, and meat color traits. Meat cooking losses correlated with “K-B-Pb”. Latent factor analysis appears be a useful means of disentangling the very complex relationships that the minerals in meat have with animal performance and meat quality traits.

Predicting the Content of 20 Minerals in Beef by Different Portable Near-Infrared (NIR) Spectrometers

“…Descriptive statistics of the concentrations of these 20 minerals are presented in Table 3 . In general, the average contents found here fall within the wide range of results published in the scientific literature and were discussed in detail along with the effects of farm, breed, sex, age, weight, and carcass side in our previous study [ 19 ]. All these factors play a role in increasing the variability in the mineral concentrations of the meat samples, and hence also in building a robust prediction model.…”

“…Other information from the same source adduced in our discussion concerns the covariance among the beef contents of the 20 minerals analyzed, and particularly the five latent explanatory factors explaining the greater part of all covariation. Moreover, to interpret the prediction performances for several minerals, probably derived more from indirect correlations with other traits than from direct vibrational signals, we also cite evidence relating to the correlations of the mineral contents with beef chemical composition, color traits, pH, cooking losses, and shear force illustrated in another study [ 19 ]. To make the text more readable, these two previous studies are not referenced again in the following paragraphs.…”

“…Furthermore, the usefulness of extending the NIR spectrum to the visible spectrum is questionable, as it appears from the results in Table 3 that in terms of R 2 VAL Vis-NIRS does not seem to be any better than NIRS and Micro-NIRS for predicting the minerals more closely correlated with beef color traits, e.g., Fe, Zn, P, and S [ 19 ]. In a large survey comparing the prediction of beef color traits using NIR spectrometry in the abattoir with their corresponding laboratory measures [ 13 ], the Micro-NIRS predictions for color traits displayed the same level of accuracy as Vis-NIRS.…”

“…Details of the experimental design and the selection of farms and animals for the trial were given in a previous study within this project [ 19 ]. The experimental design of this work is summarized in Table 1 .…”

“…The mineral contents of the meat samples were processed in two steps to identify outlier animals (first step) and to identify outlier samples within animals (second step). In the first step, the data were first analyzed with a mixed model that included breed and sex as fixed effects, and herd, animal within herd, and carcass side (residual) within animal as random effects [ 19 ]. Animal standard deviations (ASD) for mineral contents were calculated, resulting in two animals outside the interval mean ± 3 ASD being considered outliers and excluded from further analyses, for all minerals, leaving a maximum of 178 samples (89 animals × 2 carcass sides) for analysis.…”