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Description of the subject. The article deals with the use of near-infrared spectroscopy (NIR) on fresh apples to determine the phenolic compounds and dry matter content in peel and flesh powders. Objectives. The aim is the rapid and non-destructive determination of these nutritional parameters. Method. Two hundred twenty-nine fruits from 20 varieties were analyzed with NIR spectroscopy and reference methods. Results. Great variability of total phenolic compounds (TPC) in peel and flesh powders was observed among varieties. The dry matter (DM) content also differed greatly between peel and flesh. Calibration and validation models showed high coefficients of determination for the TPC content, which were slightly higher for the peel than for the flesh (R² val = 0.91 and 0.84 respectively). For the DM content, high coefficients of determination and ratios of prediction to deviation (RPDs) were also observed (R² val = 0.94, RPD = 4.8 and R² val = 0.94, RPD = 4.9 for the peel and flesh respectively). Conclusions. Calibration and validation models allow quantitative predictions to be made for TPC and DM content. They confirm the potential of NIRS for predicting the polyphenol content and highlight its potential for determining the DM content, a parameter often neglected in research into apple quality.

Description of the subject. Phenolic compounds (PCs) are the most abundant secondary metabolites in plants. This work was part of a study that sought to develop rapid screening FT-Raman methods for identifying and quantifying classes and/or types of PCs in the dry extracts of plant products. Objectives. Fourier transform Raman spectroscopy (FT-Raman) coupled with chemometric tools was used to characterize and discriminate four families of phenolic compounds: two important classes of phenolic acids, hydroxybenzoic and hydroxycinnamic acids, as well as their derivatives and flavonoids. Method. For this study, 25 standards of phenolic compounds were used (47 standards in total, taking account of the different brands). Repeatability and reproducibility studies were conducted to verify the Raman assignments of gallic acid. Raman characterization with the most significant spectral bands of phenolic compounds was done using spectra ranging from 1,800 to 50 cm-1. A Fisher test was applied to pre-processed Raman spectra (SNV) and 20 Raman scattering signals were used to differentiate each class of phenolic compounds. Results. Hydroxybenzoic acids, hydroxycinnamic acids, their derivatives and flavonoids have been characterized by Raman spectroscopy; bands have been identified and differentiated within and between groups. Conclusions. The scattering intensities located around 1,600-1,699, 1,300-1,400 and below 200 cm-1 were responsible for differentiating 100% of phenolic compound families, classes and subclasses.

Introduction. For dairy producers who want to transform their milk, the ability of milk to coagulate is an important parameter. It makes it possible to transform milk into cheese. Therefore, it is necessary to understand the coagulation process and the techniques to measure it in order to achieve the best transformation performance. The objective of this review is to describe the milk coagulation process, the factors influencing it and the methods for measuring the coagulation of milk at lab level. Literature. The processing of milk into cheese involves three steps: coagulation, dewatering and refining. Coagulation is a key step which involves the use of rennet and depends on several parameters (pH, calcium content, temperature, etc.). Some milks never coagulate. To measure the coagulation ability of milk and identify different parameters in milk coagulation properties, the Formagraph, the computerized renneting meter and the Optigraph have been developed (reference methods). Equations have been developed using infrared spectrometry to predict the parameters obtained by the reference methods. Conclusions. The milk coagulation mechanism is known. However, the issue of non-coagulating milk persists and represents a real challenge in terms of yield. The use of infrared is a faster alternative to reference methods that measure the coagulation properties of milk, but still requires an improvement in prediction equations.

This review provides an overview of the main scientific outputs of a network (Action) supported by the European Cooperation in Science and Technology (COST) in the field of animal science, namely the COST Action Feed for Health (FA0802). The main aims of the COST Action Feed for Health (FA0802) were: to develop an integrated and collaborative network of research groups that focuses on the roles of feed and animal nutrition in improving animal wellbeing and also the quality, safety and wholesomeness of human foods of animal origin; to examine the consumer concerns and perceptions as regards livestock production systems. The COST Action Feed for Health has addressed these scientific topics during the last four years. From a practical point of view three main scientific fields of achievement can be identified: feed and animal nutrition; food of animal origin quality and functionality and consumers' perceptions. Finally, the present paper has the scope to provide new ideas and solutions to a range of issues associated with the modern livestock production system.

The near-infrared microscope (NIRM) is an instrument that has demonstrated its great ability to detect contaminants not by analyzing a single spectrum but rather by analyzing hundreds or thousands of spectra from individual particles, while at the same time being a non-destructive and easy-to-use technique. It has been used for the detection of meat-and-bone meal (MBM) in compound feeds within the context of the European bovine spongiform encephalopathy (BSE; commonly known as "mad cow disease") crisis. This study describes, for the first time, an application of NIRM instrument standardization using a measurement cell in an inter-laboratory study conducted within the framework of a qualitative determination of animal proteins in compound feeds, based on spectra obtained with eight instruments. The standardization cell was assessed for its ability to produce good optical matching of the instruments and/or to evaluate instrument performance.

For the past few years, research has focused on the application of Near Infrared Spectroscopy (NIR) techniques to analyze the quality of apple varieties. As all fruit quality and nutritional parameters are affected by many factors, to standardize the sampling methods prior to analysis is very important. In this study, the intra-fruit variability of apple varieties in terms of quality parameters (sugar, total polyphenol and vitamin C content) was examined. The adequacy of the protocols usually applied to analyze apple quality (reference analyses of a representative sample of the apple and NIR measurements collected at four points 45° from each other in the equatorial region of the apple) was then investigated. The reference values for the quality parameters showed important intra-fruit variability for all quality parameters analyzed. The results also showed that there was little difference between the mean value at the four points and the mean value of the entire apple. This suggested that a mean value obtained from a representative sample of an apple is enough to assess the variability within the fruit and to estimate, with precision, the content of the quality parameters. The results of NIR spectroscopy showed that measurement at the four target points is suitable for predicting quality parameters precisely. The study concluded that standardized reference analyses should be done on a representative fruit sample of an apple and spectral measurements made at four points 45° from each other in the equatorial region of the apple.

The European Union Reference Laboratory for the detection of animal proteins in feedingstuffs (EURL-AP) has developed an online micrographs collection supporting its network activities within the European Union for the detection of prohibited animal by-products in feed. So far, the only official method for detecting these by-products is light microscopy, which is highly dependent on the skills of a microscopist because it relies on particle recognition. In order to help the microscopist network to achieve high proficiency levels, it was necessary to create an online reference tool based on micrographs and accessible via an Intranet platform. Members of the National Reference Laboratories for animal proteins in feedingstuffs (NRL-AP) and the International Association for Feedingstuff Analysis – Section Feedingstuff Microscopy (IAG) have access to this micrographs collection. This paper describes how the online collection was created and what conditions had to be taken into account in creating such a tool. It also describes how information are periodically updated and managed within the context of the large amount of information included in each micrograph. The need for a robust back-office system as the foundation for all the research activities in this project is also covered, and the evaluation of the use of the online collection is discussed.

Honey is a complex and challenging product to analyze due mainly to its composition consisting on various botanical sources. The discrimination of the origin of honey is of prime importance in order to reinforce the consumer trust in this typical food product. But this is not an easy task as usually no single chemical or physical parameter is sufficient. The aim of our paper is to investigate whether FT-Raman spectroscopy as spectroscopic fingerprint technique combined with some chemometric tools can be used as a rapid and reliable method for the discrimination of honey according to their source. In addition to that, different chemometric models are constructed in order to discriminate between Corsican honeys and honey coming from other regions in France, Italy, Austria, Germany and Ireland based on their FT-Raman spectra. These regions show a large variation in their plants. The developed models include the use of exploratory techniques as the Fisher criterion for wavenumber selection and supervised methods as Partial Least Squares-Discriminant Analysis (PLS-DA) or Support Vector Machines (SVM). All these models showed a correct classification ratio between 85% and 90% of average showing that Raman spectroscopy combined to chemometric treatments is a promising way for rapid and non-expensive discrimination of honey according to their origin.

The European project FAIR-CT96-5053 concerned the application of the Fourier transform Raman and infrared spectroscopy in food chemistry and quality control. Our research mainly concerned the study of the potential of Raman spectroscopy and the comparison with the results achieved in infrared spectroscopy. The discrimination of virgin olive oil from other edible oils and the detection and quantification of virgin olive oil adulteration have been experimented with this new technique of fast and non-destructive analysis.