Strain-level characterization of nonstarter lactic acid bacteria in Norvegia cheese by high-resolution melt analysis.

The nonstarter lactic acid bacteria (NSLAB) constitute an important microbial group found during cheese ripening and they are thought to be fundamental to the quality of cheese. Rapid and accurate diagnostic tests for NSLAB are important for cheese quality control and in understanding the cheese ripening process. Here, we present a novel rapid approach for strain-level characterization through combined 16S rRNA gene and repetitive sequence-based high-resolution melt analysis (HRM). The approach was demonstrated through the characterization of 94 isolates from Norvegia, a Gouda-type cheese. The HRM profiles of the V1 and V3 variable regions of the 16S rRNA gene of the isolates were compared with the HRM profiles of 13 reference strains. The HRM profile comparison of the V1 and V3 regions of the 16S rRNA gene allowed discrimination of isolates and reference strains. Among the cheese isolates, Lactobacillus casei/paracasei (62 isolates) and Lactobacillus plantarum/Lactobacillus pentosus (27 isolates) were the dominant species, whereas Lactobacillus curvatus/Lactobacillus sakei were found occasionally (5 isolates). The HRM profiling of repetitive sequence-based PCR using the (GTG)(5) primer was developed for strain-level characterization. The clustering analysis of the HRM profiles showed high discriminatory power, similar to that of cluster analysis based on the gel method. In conclusion, the HRM approach in this study may be applied as a fast, accurate, and reproducible method for characterization of the NSLAB microflora in cheese and may be applicable to other microbial environments following selective plate culturing.

Technical note: comparing calibration methods for determination of protein in goat milk by ultraviolet spectroscopy.

A rapid spectroscopic method to determine total protein in bovine and buffalo milk using UV spectra of guanidine-hydrochloride mixed milk has previously been reported and validated. The method was based on mixed calibration samples and univariate calibrations of fourth derivative (4D) spectra. In this study the same method was compared and tested for determination of total protein in goat milk. Calculations based on multivariate calibration (partial least squares regression) on full spectra of goat milk were used. The method was tested on 2 UV instruments. The comparison resulted in a significantly more robust (i.e., better) transferability between UV instruments for the partial least squares regression method on full spectra compared with previous univariate calibration of 4D spectra. Local (1 instrument) calibrations gave similar, significantly not different (chi-squared test) cross-validated prediction error results for the 2 methods. It can be concluded that there is no need for fourth derivation. Partial least squares regression on full spectra was equal or superior to using the 4D spectra.

Studies on the structure of water using two-dimensional near-infrared correlation spectroscopy and principal component analysis.

The structure of water molecules in the pure liquid state has been subjected to extensive research for several decades. Questions still remain unanswered, however, and no single model has been found capable of explaining all the anomalies of water. In the present study, near-infrared spectra of water in the temperature region 6-80 degrees C have been analyzed by use of principal component analysis and two-dimensional correlation spectroscopy in order to study the dynamic behavior of a band centered around 1,450 nm at room temperature, which is due to the combination of symmetric and antisymmetric O-H stretching modes (first overtone) of water. It has been found that the wavelengths 1,412 and 1,491 nm account for more than 99% of the spectral variation, representing two major water species with weaker and stronger hydrogen bonds, respectively. A third species located at 1438 nm, whose concentration was relatively constant as a function of temperature, is also indicated. A somewhat distorted two-state structural model for water is suggested.

Increase in bombesin-like peptides in the spinal cord after dexamethasone treatment of adrenalectomized rats.

The potential influence of corticosteroids on the bombesin (BN)-like peptide family is unknown. Therefore, the effects of adrenalectomy (ADX) on the nervous system of Sprague-Dawley rats, some of them being treated with high doses of the synthetic glucocorticoid dexamethasone (DEX), were investigated. After 8-10 days of treatment, the rats were sacrificed and tissues were prepared for radioimmunoassay (RIA) and immunohistochemical examination. We found an increase in BN-like immunoreactivity in the superficial layers of the dorsal horn of the lumbar spinal cord in the ADX + DEX animals. This increase was confirmed by RIA (P < 0.05). The observations show that the expression of BN-like peptides is influenced by glucocorticoids. The altered levels of BN-like peptides may be related to the trophic and antinociceptive effects previously reported for these peptides.

On-line NIR analysis of fat, water and protein in industrial scale ground meat batches.

Fat, water and protein contents in industrial scale meat batches were determined on-line by near infrared (NIR) reflectance spectroscopy. The NIR instrument was mounted at the outlet of a large meat grinder, and the measurements were performed in an industrial environment. Beef and pork samples, with chemical compositions of 7-26% fat, 58-75% water and 15-21% protein, were processed with hole diameters of 13mm in the grinder plate. Calibrations were made both for a combined set of beef and pork samples, and for separate sets of beef and pork samples. Validations were either done by full cross validation of the calibration set, or by bias corrected prediction of a test set. Prediction errors for the two sample sets, expressed as root mean square errors of cross validation or standard error of prediction, were in the ranges 0.82-1.49% fat, 0.94-1.33% water and 0.35-0.70% protein, depending of sample set and species of animal. The presented application is an improvement to the existing manual meat standardisation procedure, and has been implemented for regular use in a Norwegian meat manufacturing plant.

Determination of endpoint temperatures in previously heat treated beef using reflectance spectroscopy.

Heat processing endpoint temperature affects several quality parameters of meat. The present paper focuses on using near-infrared and visual light reflectance spectroscopy at 400-2500 nm to determine the endpoint temperature in previously heated ground beef. Glass fibre filters with beef juice centrifuged from m. longissimus lumborum were used as samples for the technique Dry Extract Spectroscopy by Infrared Reflection (DESIR). Combined with multivariate analysis, this method gave prediction errors down to ± 0.74 °C in the temperature range 65.6-75.6 °C, showing that DESIR is a potential screening method. The dominant part of the predictive information was in the visual part of the spectra.

On-line, proximate analysis of ground beef directly at a meat grinder outlet.

The fat, moisture and protein contents of ground beef were determined on-line by a diffuse reflectance near infrared (NIR) spectroscopy instrument at the outlet of a meat grinder. Beef samples in the range of 6.2-21.7% fat, 59.6-72.9% moisture and 18.1-20.7% protein were studied. Calibrations from samples ground with hole diameters of 4, 8, 13 or 19 mm in the grinder plate were validated. In addition, calibrations of combinations of these samples from the different hole diameters were validated. Prediction errors, expressed as root mean square error of cross validation of the beef samples, were 0.73-1.50% for fat, 0.75-1.33% for moisture and 0.23-0.32% for protein, depending on the hole diameter of the grinder plate. Calibrations from samples ground with the smallest hole diameters gave lowest prediction errors. The present prediction error results are only slightly higher compared to reported prediction error results using conventional at- and off-line NIR instruments. It is concluded that the on-line NIR prediction results were acceptable for samples ground with grinder plates of 4, 8 or 13 mm hole diameter.

Multivariate techniques in the analysis of meat quality.

The present paper discusses the use of multivariate statistical methods in meat science. Three examples are given illustrating some of the most important areas of use. The three examples are i) interpretation of large data matrices, ii) prediction of chemical constituents from multivariate spectral data and iii) finding relationships between multivariate data matrices.