Deep-sea sharks: Relation between the liver's buoyancy and red aerobic muscle volumes, a new approach.

Shark's buoyancy depends on two types of force: (i) the hydrostatic force which is mainly provided by their liver filled with low density lipids and (ii) the hydrodynamic force which is provided by the morphology of their body and fins. Shallow-water shark species are usually negatively buoyant, whereas deep-sea shark species have been suggested to display neutral buoyancy. It has been suggested that species that are close to the neutrality would have less red aerobic muscle fibers. Here, we investigated several liver features (the hepatosomatic index, the oil content and the lipid composition) playing a major role regarding the buoyancy of three deep-sea shark species (Etmopterus molleri, Etmopterus spinax and Isistius brasiliensis) and one shallow-water counterpart (Galeus melastomus). We used FT-Raman and FT-MIR spectroscopy to qualify/quantify the lipid composition of their liver. Our results showed that most deep-sea shark species studied have liver features providing more buoyancy than their shallow-water counterparts, appart from E. molleri which shows liver's features that resemble more shallow-water shark species (e.g. G. melastomus). Finally, data regarding liver features of several deep-sea shark species from the literature were added and the red aerobic muscle distribution/proportion of nine species was measured, to reveal how these parameters might be related. Our results showed that sharks characterized by a liver providing more hydrostatic force possess proportionally less red aerobic muscles than sharks having a liver that contributes less to their buoyancy. Therefore, our results i.e. deep-sea shark displaying less red aerobic muscle with a liver providing more buoyancy, support low metabolic rates hence slow swimming speed.

Synchronous fluorescence spectroscopy for detecting blood meal and blood products.

Fluorescence spectroscopy is a powerful method for protein analysis. Its sensitivity and selectivity allow its use for the detection of blood meal and blood products. This study proposes a novel approach for the detection of hemoglobin in animal feed by synchronous fluorescence spectroscopy (SFS). The objective was to develop a fast and easy method to detect hemoglobin powder and blood meal. Analyses were carried out on standard reference material (hemoglobin and albumin) in order to optimize SFS method conditions for hemoglobin detection. The method was then applied to protein extracts of commercial feed material and compound feed. The results showed that SFS spectra of blood meal and blood products (hemoglobin powder and plasma powder) could be used to characterize hemoglobin. Principal component analysis (PCA) applied to area-normalized SFS spectra of artificially adulterated samples made it possible to define a limit of detection of hemoglobin powder or blood meal of 0.5-1% depending on the feed material. The projection in the PCA graphs of SFS spectra of real commercial compound feeds known to contain or to be free from blood-derived products showed that it was possible to discriminate samples according to the presence of hemoglobin. These results confirmed that SFS is a promising screening method for the detection of hemoglobin in animal feed.

Analytical methods used for the authentication of food of animal origin.

Since adulteration can have serious consequences on human health, it affects market growth by destroying consumer confidence. Therefore, authentication of food is important for food processors, retailers and consumers, but also for regulatory authorities. However, a complex nature of food and an increase in types of adulterants make their detection difficult, so that food authentication often poses a challenge. This review focuses on analytical approaches to authentication of food of animal origin, with an emphasis put on determination of specific ingredients, geographical origin and adulteration by virtue of substitution. This review highlights a current overview of the application of target approaches in cases when the compound of interest is known and non-target approaches for screening issues. Papers cited herein mainly concern milk, cheese, meat and honey. Moreover, advantages, disadvantages as well as challenges regarding the use of both approaches in official food control but also in food industry are investigated.

NIR fingerprint screening for early control of non-conformity at feed mills.

The objective of this work was to devise a complete procedure based on chemometrics and the use NIR spectroscopy at the entrance of a feed mill to provide early evidence of non-conformity and unusual ingredients and thus help to achieve cost-savings. The procedure was validated at laboratory level and was adapted for application at the Cargill Animal Nutrition feed mill. The study focused on the characterisation of pure soybean meal with the aim of creating an early control system for detecting and quantifying any unusual ingredient that might be present in the soybean meal, such as melamine, cyanuric acid or whey powder (milk serum). The study results showed that the use of NIR, combined with some simple chemometric tools based on distances and residuals from regression equations, is appropriate for authenticating important feed products (in this case, soybean meal) and detecting the presence of abnormal samples or impurities in both the laboratory and at the feed mill.

Discrimination of grassland species and their classification in botanical families by laboratory scale NIR hyperspectral imaging: preliminary results.

The objective of this study was to discriminate by a NIR line scan hyperspectral imaging, taxonomic plant families comprised of different grassland species. Plants were collected from semi-natural meadows of the National Apuseni Park, Apuseni Mountains, Gârda area (Romania) according to botanical families. Chemometric tools such as PLS-DA were used to discriminate distinct grassland species, and assign the different species to botanical families. Species within the Poacea family and other Botanical families could be distinguished (R(2)=0.91 and 0.90, respectively) with greater accuracy than those species in the Fabacea family (R(2)=0.60). A correct classification rate of 99% was obtained in the assignment of the various species to the proper family. Moreover a complete study based on wavelength selection has been performed in order to identify the chemical compound related to each botanical family and therefore to the possible toxicity of the plant. This work could be considered as a first step for the development of a complete procedure for the detection and quantification of possible toxic species in semi-natural meadows used by grazing animals.

Evaluation of FT-NIR and ATR-FTIR spectroscopy techniques for determination of minor odd- and branched-chain saturated and trans unsaturated milk fatty acids.

Determination of nutritionally important trans MUFA, CLA, and OBCFA milk fatty acids (often present in amounts lower than 1.0 g/100 g of total fat) using fast and nondestructive analytical methods would enhance their use as diagnostic tools in dairy herd and human health management. Here, PLS regression using ATR/FTIR spectra indicated potential for determination of trans-11 C18:1 and trans-12 C18:1 (Rcv² ≥ 0.80), and trans-9 C18:1 in very minor concentration (Rcv² > 0.82), as well as anteiso C15:0 (Rcv² = 0.57) and iso C17:0 (Rcv² = 0.61). Furthermore, the main cis-9,trans-11 CLA isomer was predicted well despite the high trans MUFA concentration. Differentiation between the CLA and the trans MUFA signals was evident (based on specific cis/trans bands), and branched-chain saturated fatty acid methyl esters revealed specific iso and anteiso ATR/FTIR absorbance bands. None of the minor FA PLS results with FT-NIR showed interesting potential, except satisfactory predictions for trans-9 C18:1 and cis-9,trans-11 CLA. Overall, ATR/FTIR resulted in better calibrations and provided more specific information for determination of minor milk fatty acids.

Determining milk isolated and conjugated trans-unsaturated fatty acids using fourier transform Raman spectroscopy.

The feasibility of Raman spectroscopy in combination with partial least-squares (PLS) regression for the determination of individual or grouped trans-monounsaturated fatty acids (trans-MUFA) and conjugated linoleic acids (CLA) in milk fat is demonstrated using spectra obtained at two temperature conditions: room temperature and after freezing at -80 °C. The PLS results displayed capability for direct semiroutine quantification of several individual CLA (cis-9,trans-11 and trans-10,cis-12 C18:2) and trans-MUFA (trans-4-15 C18:1) in minor concentrations (below 1.0 g/100 g of milk fat). Calibration models were based on reference data cross-correlation or determined by specific scattering signals in the Raman spectra. Distinct bands for trans-MUFA (1674 cm(-1)) and CLA (1653 cm(-1)) from the trans isolated and cis,trans conjugated C ═ C bonds were identified, as well as original evidence for the temperature effect (new bands, peak shifts, and higher intensities) on the Raman spectra of fatty acid methyl ester and triacylglyceride standards, are supplied.

A Backward Variable Selection method for PLS regression (BVSPLS).

Variable selection has been discussed in many papers and it became an important topic in areas as chemometrics and science in general. Here a backward iterative step-by-step wrapper method is proposed using PLS. The root-mean-square error of prediction (RMSEP) for an independent test set is used as selection criterion to quantify the gain obtained using the selected range of variables. The method has been applied to different data sets and the results obtained revealed that one can improve or at least keep constant the prediction performances of the PLS models compared to the full-spectrum models. Moreover with the advantage that the number of variables is reduced driving to an easier interpretation of the relationship between model and sample composition and/or properties. The aim is not to compare to other variable selection methods but to show that a simple one can improve or at least keep constant the prediction performances of the PLS models by using only a limited number of variables.

Prediction of source rock origin by chemometric analysis of fourier transform infrared-attenuated total reflectance spectra of oil petroleum: evaluation of aliphatic and aromatic fractions by self-modeling mixture analysis.

This study describes a new methodology for the interpretation of Fourier transform infrared (FT-IR) attenuated total reflectance (ATR) spectra of Algerian, Brazilian, and Venezuelan crude oils. It is based on a comparative study between a chemometric treatment and the classical one, which refers to indices calculation. In fact, the combined use of FT-IR indices and principal component analysis (PCA) has led to the classification of the studied samples in terms of geographic distribution. Quantitative analysis has been successfully realized by the supervised method partial least squares (PLS), which has permitted the prediction of the locations of oils. We have also applied another mathematical processing method, simple-to-use interactive self-modeling mixture analysis (SIMPLISMA), to evaluate the aromatic and aliphatic composition of the oils by extracting pure spectra representative of the different fractions.