György Bázár

NIR detection of honey adulteration reveals differences in water spectral pattern

High fructose corn syrup (HFCS) was mixed with four artisanal Robinia honeys at various ratios (0-40%) and near infrared (NIR) spectra were recorded with a fiber optic immersion probe. Levels of HFCS adulteration could be detected accurately using leave-one-honey-out cross-validation (RMSECV=1.48; R(2)CV=0.987), partial least squares regression and the 1300-1800nm spectral interval containing absorption bands related to both water and carbohydrates. Aquaphotomics-based evaluations showed that unifloral honeys contained more highly organized water than the industrial sugar syrup, supposedly because of the greater variety of molecules dissolved in the multi-component honeys. Adulteration with HFCS caused a gradual reduction of water molecular structures, especially water trimers, which facilitate interaction with other molecules. Quick, non-destructive NIR spectroscopy combined with aquaphotomics could be used to describe water molecular structures in honey and to detect a rather common form of adulteration.

Detection of UV-induced cyclobutane pyrimidine dimers by near-infrared spectroscopy and aquaphotomics

Ultraviolet (UV) radiation causes cellular DNA damage, among which cyclobutane pyrimidine dimers (CPDs) are responsible for a variety of genetic mutations. Although several approaches have been developed for detection of CPDs, conventional methods require time-consuming steps. Aquaphotomics, a new approach based on near-infrared spectroscopy (NIRS) and multivariate analysis that determines interactions between water and other components of the solution, has become an effective method for qualitative and quantitative parameters measurement in the solutions. NIR spectral patterns of UVC-irradiated and nonirradiated DNA solutions were evaluated using aquaphotomics for detection of UV-induced CPDs. Groups of UV-irradiated and nonirradiated DNA samples were classified (87.5% accuracy) by soft independent modeling of class analogy (SIMCA). A precise regression model calculated from NIR water spectral patterns based on UVC doses (r Val = 0.9457) and the concentration of cis-syn cyclobutane thymine dimers (cis-syn T<>Ts; r Val = 0.9993) was developed using partial least squares regression (PLSR), while taking advantage of water spectral patterns, particularly around 1400–1500 nm. Our results suggested that, in contrast to DNA, the formation of cis-syn T<>Ts increased the strongly hydrogen bonded water. Additionally, NIRS could qualitatively and quantitatively detect cis-syn T<>Ts in isolated DNA aqueous solutions upon UVC exposure.

Water spectral pattern as holistic marker for water quality monitoring.

Online water quality monitoring technologies have been improving continuously. At the moment, water quality is defined by the respective range of few chosen parameters. However, this strategy requires sampling and it cannot provide evaluation of the entire water molecular system including various solutes. As it is nearly impossible to monitor every single molecule dissolved in water, the objective of our research is to introduce a complimentary approach, a new concept for water screening by observing the water molecular system changes using aquaphotomics and Quality Control Chart method. This approach can continuously provide quick information about any qualitative change of water molecular arrangement without taking into account the reason of the alteration of quality. Different species and concentrations of solutes in aqueous systems structure the water solvent differently. Aquaphotomics investigates not the characteristic absorption bands of the solute in question, but the solution absorption at vibrational bands of waters covalent and hydrogen bonds that have been altered by the solute. The applicability of the proposed concept is evaluated by monitoring the water structural changes in different aqueous solutions such as acid, sugar, and salt solutions at millimolar concentration level and in ground water. The results show the potential of the proposed approach to use water spectral pattern monitoring as bio marker of water quality. Our successful results open a new venue in water quality monitoring by offering a quick and cost effective method for continuous screening of water molecular arrangement. Instead of the regular analysis of individual physical or chemical parameters, with our method - as a complementary tool - the structural changes of water molecular system used as a mirror reflecting even small disturbances in water can indicate the necessity of further detailed analysis by conventional methods.

Monitoring of Water Spectral Pattern Reveals Differences in Probiotics Growth When Used for Rapid Bacteria Selection

Development of efficient screening method coupled with cell functionality evaluation is highly needed in contemporary microbiology. The presented novel concept and fast non-destructive method brings in to play the water spectral pattern of the solution as a molecular fingerprint of the cell culture system. To elucidate the concept, NIR spectroscopy with Aquaphotomics were applied to monitor the growth of sixteen Lactobacillus bulgaricus one Lactobacillus pentosus and one Lactobacillus gasseri bacteria strains. Their growth rate, maximal optical density, low pH and bile tolerances were measured and further used as a reference data for analysis of the simultaneously acquired spectral data. The acquired spectral data in the region of 1100-1850nm was subjected to various multivariate data analyses – PCA, OPLS-DA, PLSR. The results showed high accuracy of bacteria strains classification according to their probiotic strength. Most informative spectral fingerprints covered the first overtone of water, emphasizing the relation of water molecular system to cell functionality.

Aquagrams of raw milk for oestrus detection in dairy cows.

The purpose of this research was to develop rapid and cost-effective method for oestrus detection in dairy cows by means of near infrared spectroscopy and aquaphotomics, using raw milk from individual cows. We found that aquaphotomics approach showed consistent specific water spectral pattern of milk at the oestrus periods of the investigated Holstein cows. Characteristic changes were detected especially in foremilk collected at morning milking. They were reflected in calculated aquagrams of milk spectra where distinctive spectral pattern of oestrus showed increased light absorbance of strongly hydrogen-bonded water. Results showed that monitoring of raw milk near infrared spectra provides an opportunity for analysing hormone levels indirectly, through the changes of water spectral pattern caused by complex physiological changes related to fertile periods.

Individual and Combined Effects of Fumonisin B1, Deoxynivalenol and Zearalenone on the Hepatic and Renal Membrane Lipid Integrity of Rats

(1) Background and (2) Methods: A 14-day in vivo, multitoxic (pure mycotoxins) rat experiment was conducted with zearalenone (ZEA; 15 μg/animal/day), deoxynivalenol (DON; 30 μg/animal/day) and fumonisin B1 (FB1; 150 μg/animal/day), as individual mycotoxins, binary (FD, FZ and DZ) and ternary combinations (FDZ), via gavage in 1 mL water boluses. (3) Results: Body weight was unaffected, while liver (ZEA↑ vs. DON) and kidney weight (ZEA↑ vs. FDZ) increased. Hepatocellular membrane lipid fatty acids (FAs) referred to ceramide synthesis disturbance (C20:0, C22:0), and decreased unsaturation (C22:5 n3 and unsat. index), mainly induced by DON and to a lesser extent by ZEA. The DON-FB1 interaction was additive on C20:0 in liver lipids. In renal phospholipids, ZEA had the strongest effect on the FA profile, affecting the saturated (C18:0) and many n6 FAs; ZEA was in an antagonistic relationship with FB1 (C18:0) or DON (C18:2 n6, C20:1 n9). Hepatic oxidative stress was the most expressed in FD (reduced glutathione and glutathione peroxidase), while the nephrotoxic effect was further supported by lipid peroxidation (malondialdehyde) in the DON treatment. (4) Conclusions: In vivo study results refer to multiple mycotoxin interactions on membrane FAs, antioxidants and lipid peroxidation compounds, needing further testing.

Monitoring of water spectral patterns of lactobacilli development as a tool for rapid selection of probiotic candidates

Nowadays a quick and inexpensive method, which allows rapid, in vivo comprehensive probiotic bacteria identification, is needed. To elucidate a new concept to evaluate probiotic bacteria, near infrared spectroscopy with aquaphotomics were applied to monitor the growth of eight Lactobacillus bulgaricus and one Lactobacillus gasseri bacteria strains. Their resistance to low pH (1.8) in the presence of pepsin and bile were measured and further used as reference data for analysis of the simultaneously acquired spectral data. The acquired spectral data in the region of 1100–1300 nm were subjected to various methods for multivariate data analyses—principal component analysis, linear discriminant analysis, soft independent modeling of class analogy, and partial least squares regression. The results showed high accuracy of bacteria strains classification according to their resistance and the potential of the tested wavelength region for rapid selection and prediction of some basic phenotypic characteristics of probiotic candidates. Results of the current study also revealed different suitability of each growth stage when using near infrared spectra for the classification of bacteria strains.

Identification of traditionally reared Mangalica pig's meat by near infrared spectroscopy using generalised partial least squares in open source R Project-a feasibility model study

The possibility for near infrared spectroscopy-based discrimination of meats originating from the extensively reared autochthonous breed of Mangalica and intensively reared commercial genotypes (Landrace, Large White, Landrace × Large White crossbreed) was investigated. Since there was a considerable difference between the intramuscular fat content of Mangalica and intensively-reared meats (average of 19.1 DM% vs 9.3 DM%, resp.), several sample selection options were applied to explore the impact of fat content on the results of NIR analysis. The system for discrimination was able to identify the different groups even when the discriminator equation was generated on very different samples and was tested on samples with overlapping fat content. The ratio of correctly classified samples was above 90% during cross-validation or for independent test samples of all comparisons, both in fresh or freeze-dried samples. Over 90% of independent fresh pork samples were correctly identified when the discriminator equation was generated with 70 randomly selected samples. This ratio increased up to over 95% when freeze-dried samples were applied. The generalised partial least squares package of open-source R Project seems to be a useful tool for qualitative analysis of NIR data recorded from meat samples.