Innovative uses of near-infrared spectroscopy in food processing

Chemical composition and fatty acid content in lamb and adult sheep meat

The aim of the present study was to compare the chemical composition and fatty acid (FA) content of the muscle tissues of lambs and adult sheep bred for meat production. Throughout the research period, the animals were managed in a confinement indoor system under uniform environmental conditions. After slaughter, meat samples collected from the musculus biceps femoris were used to determine the basic chemical composition and fatty acid content in the intramuscular fat. The analyses showed that, compared to lambs, meat from adult animals exhibited a more beneficial ratio of n-6 to n-3 FAs, as well as a favorable percentage of OFAs (dietary fatty acids having an undesirable hypercholesterolemic effect on humans). The results of this study support the inclusion of dietitian-recommended mutton into the human diet and the promotion of the production of meat from adult animals as a high-value product. The sheep industry could benefit economically, particularly in countries where this meat type has not enjoyed a high standing in consumer preferences.

Model based optimization of transflection near infrared spectroscopy as a process analytical tool in a continuous flash pasteurizer

Near infrared spectroscopy in combination with a transflection probe was investigated as inline measurement in a continuous flash pasteurizer system with a sugar-water model solution. Robustness and reproducibility of fluctuations of recorded spectra as well as trueness of the chemometric analysis were compared under different process parameter settings. Variable parameters were the flow rate (from laminar flow at 30 L/h to turbulent flow at 90 L/h), temperature (20 to 100 °C) and the path length of the transflection probe (2 and 4 mm) while the pressure was kept constant at 2.5 bar. Temperature and path length were identified as the most affecting parameters, in case of homogenous test medium. In case of particle containing systems, the flow rate could have an impact as well. However, the application of a PLS model, which includes a broad temperature range, and the correction of prediction results by applying a polynomial regression function for prediction errors, was able to compensate these effects. Also, a path length of 2 mm leads to a higher accuracy. The applied strategy shows that by the identification of relevant process parameters and settings as well as the establishment of a compensation strategy, near infrared spectroscopy is a powerful process analytical tool for continuous flash pasteurization systems.

Non-destructive NIR spectral imaging assessment of bone water: Comparison to MRI measurements

Bone fracture risk increases with age, disease states, and with use of certain therapeutics, such as acid-suppressive drugs, steroids and high-dose bisphosphonates. Historically, investigations into factors that underlie bone fracture risk have focused on evaluation of bone mineral density (BMD). However, numerous studies have pointed to factors other than BMD that contribute to fragility, including changes in bone collagen and water. The goal of this study is to investigate the feasibility of using near infrared spectral imaging (NIRSI) to determine the spatial distribution and relative amount of water and organic components in whole cross-sections of bone, and to compare those results to those obtained using magnetic resonance imaging (MRI) methods. Cadaver human whole-section tibiae samples harvested from 18 donors of ages 27-97years underwent NIRSI and ultrashort echo time (UTE) MRI. As NIRSI data is comprised of broad absorbances, second derivative processing was evaluated as a means to narrow peaks and obtain compositional information. The (inverted) second derivative peak heights of the NIRSI absorbances correlated significantly with the mean peak integration of the water, collagen and fat NIR absorbances, respectively, indicating that either processing method could be used for compositional assessment. The 5797cm^-1 absorbance was validated as arising from the fat present in bone marrow, as it completely disappeared after ultrasonication. The MRI UTE-determined bound water content in tibial cortical bone samples ranged from 62 to 91%. The NIRSI water peaks at 5152cm^-1 and at 7008cm^-1 correlated significantly with the UTE data, with r=0.735, p=0.016, and r=0.71, p=0.0096, respectively. There was also a strong correlation between the intensity of the NIRSI water peak at 7008cm^-1 and the intensity of the collagen peak at 4608cm^-1 (r=0.69, p=0.004). Since NIRSI requires minimal to no sample preparation, this approach has great potential to become a gold standard modality for the investigation of changes in water content, distribution, and environment in pre-clinical studies of bone pathology and therapeutics.

Selecting the quality of mule duck fatty liver based on near-infrared spectroscopy

BACKGROUND

"Foie gras" is produced predominantly in France and about 90% of the commercialized product is obtained from male mule ducks. The melting rate (percentage of fat released during cooking) is the main criterion used to determine the quality of "foie gras". However, up to now the melting rate could not be predicted without causing liver damage, which means that selection programs could not use this criterion.

METHODS

Fatty liver phenotypes were obtained for a population of over 1400 overfed male mule ducks. The phenotypes were based on two types of near-infrared spectra (on the liver surface and on ground liver) in order to predict the melting rate and liver composition (ash, dry matter, lipid and protein contents). Genetic parameters were computed in multiple traits with a "sire-dam" model and using a Gibbs sampling approach.

RESULTS

The estimates for the genetic parameters show that the measured melting rate and the predicted melting rate obtained with two near-infrared spectrometer devices are genetically the same trait: genetic correlations are very high (ranging from +0.89 to +0.97 depending on the mule duck parental line and the spectrometer) and heritabilities are comparable. The predictions based on the spectra of ground liver samples using a laboratory spectrometer correlate with those based on the surface spectra using a portable spectrometer (from +0.83 to +0.95 for dry matter, lipid and protein content) and are particularly high for the melting rate (higher than +0.95). Although less accurate than the predictions obtained using the spectra of ground liver samples, the phenotypic prediction of the melting rate based on surface spectra is sufficiently accurate to be used by "foie gras" processors.

CONCLUSIONS

Near-infrared spectrometry is an efficient tool to select liver quality in breeding programs because animals can be ranked according to their liver melting rate without damaging their livers. Thus, these original results will help breeders to select ducks based on the liver melting rate, a crucial criterion that defines the quality of the liver and for which there was previously no accurate predictor.

Beer fermentation: monitoring of process parameters by FT-NIR and multivariate data analysis

This work investigates the capability of Fourier-Transform near infrared (FT-NIR) spectroscopy to monitor and assess process parameters in beer fermentation at different operative conditions. For this purpose, the fermentation of wort with two different yeast strains and at different temperatures was monitored for nine days by FT-NIR. To correlate the collected spectra with °Brix, pH and biomass, different multivariate data methodologies were applied. Principal component analysis (PCA), partial least squares (PLS) and locally weighted regression (LWR) were used to assess the relationship between FT-NIR spectra and the abovementioned process parameters that define the beer fermentation. The accuracy and robustness of the obtained results clearly show the suitability of FT-NIR spectroscopy, combined with multivariate data analysis, to be used as a quality control tool in the beer fermentation process. FT-NIR spectroscopy, when combined with LWR, demonstrates to be a perfectly suitable quantitative method to be implemented in the production of beer.

Near infrared spectroscopic evaluation of water in hyaline cartilage

In diseased conditions of cartilage such as osteoarthritis, there is typically an increase in water content from the average normal of 60-85% to greater than 90%. As cartilage has very little capability for self-repair, methods of early detection of degeneration are required, and assessment of water could prove to be a useful diagnostic method. Current assessment methods are either destructive, time consuming, or have limited sensitivity. Here, we investigated the hypotheses that non-destructive near infrared spectroscopy (NIRS) of articular cartilage can be used to differentiate between free and bound water, and to quantitatively assess water content. The absorbances centered at 5200 and 6890 cm(-1) were attributed to a combination of free and bound water, and to free water only, respectively. The integrated areas of both absorbance bands were found to correlate linearly with the absolute water content (R = 0.87 and 0.86) and with percent water content (R = 0.97 and 0.96) of the tissue. Partial least square models were also successfully developed and were used to predict water content, and percent free water. These data demonstrate that NIRS can be utilized to quantitatively determine water content in articular cartilage, and may aid in early detection of degenerative tissue changes in a laboratory setting, and with additional validations, possibly in a clinical setting.

Near infrared and fluorescence spectroscopic methods and electronic nose technology for monitoring foods

There is a clear need for application of proper methods for measuring food quality and safety in the globalized food-webs. Numerous instrumental methods have been established in the course of the 20th century and are developing further, together with data analysis techniques, for such purposes. Among them, near-infrared and fluorescence spectroscopic methods and chemical sensor arrays called electronic noses show particular promise for rapid, non-destructive, non-invasive and cost-effective ways for assessing changes and enhancing control during processing and storage of foods. Their key advantages as analytical tools are 1) their relatively high speed of analysis, 2) the lack of a need to carry out complex sample preparation or processing, 3) their relatively low cost, and 4) their suitability for on-line monitoring or quality control. The present survey attempts to demonstrate examples from the above areas, limiting itself mainly to monitoring some quality indices which contribute to the functionality or acceptability of foods as affected by alternative processing technologies, or loss of freshness/microbial safety, or developing spoilage during storage and marketing. These instrumental methods are correlative techniques: they must be calibrated first against (traditional) reference properties, and the instrumental data are evaluated with the help of chemometric methods. Near-infrared (NIR) spectroscopy can be used in either the reflectance or the transmittance mode. NIR spectra transformed to mathematical derivatives allows subtle spectrum changes to be resolved. Selected examples from the extensive NIRS literature relate to assessment of the quality of frozen fish, predicting cooking loss of chicken patties, detecting complex physico-chemical changes of minced meat as a function of the intensity of high hydrostatic pressure treatment, comparing changes of NIR spectrometric “fingerprints” caused by gamma radiation or high pressure pasteurization of liquid egg white. Changes of NIR spectra reflect several parameters which suit the evaluation of loss of freshness, and onset of spoilage of various foods. NIR spectroscopy shows an application potential for rapid detection of bacterial or mould contamination. It may serve as a tool for detecting initial stages of mobilization processes during germination of cereal grains, or even for GMO screening. Spectrofluorometic measurements have shown potential, e.g. to monitor lipid oxidation and development of meat rancidity, to differentiate between raw and processed milks, and to monitor fish and egg freshness. Electronic noses containing chemical sensor arrays offer a rapid method for evaluation of head-space volatiles of food samples, important for characterizing quality and safety. Such gas sensors may be able to classify storage time, and determine spoilage, either earlier or at the same time as the human senses, or “sniffing out” bacterial pathogens or (toxigenic) fungal growth on certain foods. Electronic nose sensing is also a promising method for detecting quality changes of fruit- and vegetable products non-destructively. In relation to some examples to be presented in the paper, certain software developments as qualitative classification tools made by Hungarian scientists will be pointed out.