A Portable Infrared Attenuated Total Reflection Spectrometer for Food Analysis.

The analytical performance of a compact infrared attenuated total reflection spectrometer using a pyroelectric detector array has been evaluated and compared to a conventional laboratory Fourier transform infrared system for applications in food analysis. Analytical characteristics including sensitivity, repeatability, linearity of the calibration functions, signal-to-noise ratio, and spectral resolution have been derived for both approaches. Representative analytes of relevance in food industries (i.e., organic solvents, fatty acids, and mycotoxins) have been used for the assessment of the performance of the device and to discuss the potential of this technology in food and feed analysis.

Sparse wavelengths data in mid-infrared spectroscopy: Modelling approaches and channel sampling.

Infrared instruments with smaller and cost-effective components such as bandpass filters, single channel detectors, and laser-based light sources are being developed to provide cheaper and faster analysis of biological samples. Such instruments often provide measurements in form of sparse data, which include a collection of single-frequency channels or a collection of channels covering very narrow spectral ranges, called here multi-frequency channels. To keep costs low, the number of channels needs to be kept at a minimum. However, modelling and preprocessing of sparse data needs enough channels to perform the task. The aim of this study therefore was to understand the effect of channels sampling on data modelling results and find optimal modelling algorithm for different type of sparse data. The sparse data was simulated using Fourier Transform Infrared spectra of milk and fungi. Regression models were established to predict fatty acid composition by partial least squares regression (PLSR), multiple linear regression (MLR) and random forest (RF) methods. We observe that PLSR algorithm is very well suited for sparse data such as multi-frequency channels: excellent calibration models were obtained with only three channels comprising three wavenumbers each. The results were comparable to results obtained with full spectra. MLR and RF in turn provided similarly good results using data with single-frequency channels requiring nine channels in total.

Invited review: A comprehensive review of visible and near-infrared spectroscopy for predicting the chemical composition of cheese.

Substantial research has been carried out on rapid, nondestructive, and inexpensive techniques for predicting cheese composition using spectroscopy in the visible and near-infrared radiation range. Moreover, in recent years, new portable and handheld spectrometers have been used to predict chemical composition from spectra captured directly on the cheese surface in dairies, storage facilities, and food plants, removing the need to collect, transport, and process cheese samples. For this review, we selected 71 papers (mainly dealing with prediction of the chemical composition of cheese) and summarized their results, focusing our attention on the major sources of variation in prediction accuracy related to cheese variability, spectrometer and spectra characteristics, and chemometrics techniques. The average coefficient of determination obtained from the validation samples ranged from 86 to 90% for predicting the moisture, fat, and protein contents of cheese, but was lower for predicting NaCl content and cheese pH (79 and 56%, respectively). There was wide variability with respect to all traits in the results of the various studies (standard deviation: 9-30%). This review draws attention to the need for more robust equations for predicting cheese composition in different situations; the calibration data set should consist of representative cheese samples to avoid bias due to an overly specific field of application and ensure the results are not biased for a particular category of cheese. Different spectrometers have different accuracies, which do not seem to depend on the spectrum extension. Furthermore, specific areas of the spectrum-the visible, infrared-A, or infrared-B range-may yield similar results to broad-range spectra; this is because several signals related to cheese composition are distributed along the spectrum. Small, portable instruments have been shown to be viable alternatives to large bench-top instruments. Last, chemometrics (spectra pre-treatment and prediction models) play an important role, especially with regard to difficult-to-predict traits. A proper, fully independent, validation strategy is essential to avoid overoptimistic results.

Composition and aptitude for cheese-making of milk from cows, buffaloes, goats, sheep, dromedary camels, and donkeys.

Bovines produce about 83% of the milk and dairy products consumed by humans worldwide, the rest represented by bubaline, caprine, ovine, camelid, and equine species, which are particularly important in areas of extensive pastoralism. Although milk is increasingly used for cheese production, the cheese-making efficiency of milk from the different species is not well known. This study compares the cheese-making ability of milk sampled from lactating females of the 6 dairy species in terms of milk composition, coagulation properties (using lactodynamography), curd-firming modeling, nutrients recovered in the curd, and cheese yield (through laboratory model-cheese production). Equine (donkey) milk had the lowest fat and protein content and did not coagulate after rennet addition. Buffalo and ewe milk yielded more fresh cheese (25.5 and 22.9%, respectively) than cow, goat, and dromedary milk (15.4, 11.9, and 13.8%, respectively). This was due to the greater fat and protein contents of the former species with respect to the latter, but also to the greater recovery of fat in the curd of bubaline (88.2%) than in the curd of camelid milk (55.0%) and consequent differences in the recoveries of milk total solids and energy in the curd; protein recovery, however, was much more similar across species (from 74.7% in dromedaries to 83.7% in bovine milk). Compared with bovine milk, the milk from the other Artiodactyla species coagulated more rapidly, reached curd firmness more quickly (especially ovine milk), had a more pronounced syneresis (especially caprine milk), had a greater potential asymptotical curd firmness (except dromedary and goat milk), and reached earlier maximum curd firmness (especially caprine and ovine milk). The maximum measured curd firmness was greater for bubaline and ovine milk, intermediate for bovine and caprine milk, and lower for camelid milk. The milk of all ruminant species can be used to make cheese, but, to improve efficiency, cheese-making procedures need to be optimized to take into account the large differences in their coagulation, curd-firming, and syneresis properties.

Performance of different portable and hand-held near-infrared spectrometers for predicting beef composition and quality characteristics in the abattoir without meat sampling.

The availability of portable and handheld NIR instruments on the market opens up new possibilities in meat analysis. However, there is lack of research comparing different NIR instruments for evaluating beef characteristics from spectra obtained directly on the meat surface. Our aim, therefore, was to build and test calibration and prediction models for predicting beef characteristics, and to compare the performances of three NIR instruments differing in size and characteristics: a transportable visible-NIR spectrometer (Vis-NIRS), a portable (NIRS), and a hand-held Micro-NIRS. Spectra were collected from 178 beef samples (Longissimus thoracis muscle) from the meat surface in the abattoir. The spectra were subjected to different mathematical pretreatments then partial least square regressions. The results showed that all instruments predicted dry matter, protein and lipids with R2VAL 0.23 to 0.70; pH and cooking loss R2VAL 0.19 to 0.25; and color R2VAL 0.35 to 0.77. Overall, the prediction performances of the three instruments were similar, although Micro-NIRS performed better in some respects.

Purebreeding with sexed semen and crossbreeding with semen from double-muscled sires to improve beef production from dairy herds: Live and slaughter performances of crossbred calves.

The use of sexed semen to produce purebred replacement heifers allows a large proportion of dairy cows to be mated to beef sires, and quantitative and qualitative improvements to be made to beef production from dairy herds. The major dairy and beef breeds are undergoing rapid genetic improvement as a result of more efficient selection methods, prompting a need to evaluate the meat production of crossbred beef × dairy cattle produced using current genetics. As part of a large project involving 125 commercial dairy farms, we evaluated the combined use of purebreeding with sexed semen and crossbreeding with semen from beef sires, particularly double-muscled breeds. A survey of 1,530 crossbred calves revealed that, whereas purebred dairy calves are destined almost exclusively for veal production, beef × dairy crossbred calves are also destined for beef production after fattening on either the dairy farm of birth or by specialized fatteners. In veal production, compared with Belgian Blue-sired calves (taken as the reference), double-muscled INRA 95-sired calves had a lighter slaughter weight (303 vs. 346 kg), but a greater dressing percent (62.3 vs. 58.4%). Limousin (also known as Limousine)-sired calves had a smaller average daily gain (1.26 vs. 1.34 kg/d), and lighter slaughter (314 vs. 346 kg) and carcass weights (182 vs. 201 kg). Last, Simmental-sired calves had a similar growth rate, but lighter carcass weight (177 vs. 201 kg), smaller dressing percentage (55.3 vs. 58.4%), and smaller muscularity scores (3.25 vs. 3.72). In the case of young bulls and heifers fattened on the dairy farm of birth, Belgian Blue-, Piemontese (also known as Piedmontese)-, and Limousin-sired calves performed similarly; the only exception was that Piemontese-sired calves had a greater dressing percentage. Belgian Blue- and Limousin-sired calves performed similarly when fattened by specialized beef producers. In both veal and beef production, the effects of dam breed were less important than sire breed. Considering the entire project, we can conclude that the combined use of sexed semen for purebreeding and conventional beef semen for terminal crossbreeding improves meat production from dairy herds, especially when the sires are double-muscled beef breeds.

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

The aim of this study was to test the predictability of a detailed mineral profile of beef using different portable near-infrared spectrometers (NIRS). These devices are rapid, chemical waste-free, cheap, nondestructive tools that can be used directly on the meat surface in the work environment without the need to take samples. We compared a transportable Visible-NIRS (weight 5.6 kg; wavelength 350-1830 nm), a portable NIRS (2.0 kg; 950-1650 nm), and a hand-held Micro-NIRS (0.06 kg; 905-1649 nm) to predict the contents of 20 minerals (measured by ICP-OES) in 178 beef samples (Longissimus thoracis muscle) using different mathematical pretreatments of the spectra and partial least square regressions. The externally validated results show that Fe, P, Mg, S, Na, and Pb have some potential for prediction with all instruments (R2VAL: 0.40-0.83). Overall, the prediction performances of the three instruments were similar, although the smallest (Micro-NIRS) exhibited certain advantages.

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

The mineral profile of beef is a subject of human health interest, but also animal performance and meat quality. This study analyzes the relationships of 20 minerals in beef inductively coupled plasma-optical emission spectrometry (ICP-OES) with three animal performance and 13 beef 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 beef 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 beef color traits. Two latent factors ("Na + Fe + Cu" and "Fe + Mn") correlated with performance and beef color traits. Two other ("K-B-Pb" and "Zn") correlated with beef chemical composition and the latter also with carcass weight and daily gain, and beef color traits. Beef 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 beef have with animal performance and beef quality traits.