Linseed oil presents different patterns of oxidation in real-time and accelerated aging assays.

This study aimed at verifying if the hypothesis that one day at 60°C is equivalent to one month at 20°C could be confirmed during linseed oil aging for 6months at 20°C and 6days at 60°C using the "Schaal oven stability test". Tests were conducted with linseed oil supplemented or not with myricetin or butyl-hydroxytoluene as antioxidants. Oxidation was evaluated with the peroxide and p-anisidine values, as well as the content in conjugated dienes and aldehydes. All four indicators of oxidation showed very different kinetic behaviors at 20 and 60°C. The hypothesis is thus not verified for linseed oil, supplemented or not with antioxidant. In the control oil, the conjugated dienes and the peroxide value observed were respectively of 41.8±0.8 Absorbance Unit (AU)/g oil and 254.3±5.8meq.O2/kg oil after 6months at 20°C. These values were of 18.2±1.3AU/g oil and 65.2±20.3meq.O2/kg after 6days at 60°C.

Evaluation of the overall quality of olive oil using fluorescence spectroscopy.

The fluorescence spectra of some olive oils were examined in their natural and oxidised state, with wavelength range emissions of 300-800 nm and 300-400 nm used as excitation radiation. The fluorescence emissions were measured and an assessment was made of the relationship between them and the main quality parameters of olive oils, such as peroxide value, K232, K270 and acidity. These quality parameters (peroxide value, K232, K270 and acidity) are determined by laboratory methods, which though not too sophisticated, they are required solvents and materials as well as time consuming and sample preparation; there is a need for rapid analytical techniques and a low-cost technology for olive oil quality control. The oxidised oils studied had a strong fluorescence band at 430-450 nm. Extra virgin olive oil gave a different but interesting fluorescence spectrum, composed of three bands: one low intensity doublet at 440 and 455 nm; one strong band at 525 nm; and one of medium intensity at 681 nm. The band at 681 nm was identified as the chlorophyll band. The band at 525 nm was derived, at least partially, from vitamin E. The results presented demonstrate the ability of the fluorescence technique, combined with multivariate analysis, to characterise olive oils on the basis of all the quality parameters studied. Prediction models were obtained using various methods, such as partial least squares (PLS), N-way PLS (N-PLS) and external validation, in order to obtain an overall evaluation of oil quality. The best results were obtained for predicting K270 with a root mean square (RMS) prediction error of 0.08 and a correlation coefficient obtained with the external validation of 0.924. Fluorescence spectroscopy facilitates the detection of virgin olive oils obtained from defective or poorly maintained fruits (high acidity), fruits that are highly degraded in the early stages (with a high peroxide value) and oils in advanced stages of oxidation, with secondary oxidation compounds (high K232 and K270). The results indicate the potential of a spectrofluorimetric method combined with multivariate analysis to differentiate, and even quantify, the levels of oil quality. The proposed methodology could be used to accelerate analysis, is inexpensive and allows a comprehensive assessment to be made of olive oil quality.

Infrared machine vision system for the automatic detection of olive fruit quality.

External quality is an important factor in the extraction of olive oil and the marketing of olive fruits. The appearance and presence of external damage are factors that influence the quality of the oil extracted and the perception of consumers, determining the level of acceptance prior to purchase in the case of table olives. The aim of this paper is to report on artificial vision techniques developed for the online estimation of olive quality and to assess the effectiveness of these techniques in evaluating quality based on detecting external defects. This method of classifying olives according to the presence of defects is based on an infrared (IR) vision system. Images of defects were acquired using a digital monochrome camera with band-pass filters on near-infrared (NIR). The original images were processed using segmentation algorithms, edge detection and pixel value intensity to classify the whole fruit. The detection of the defect involved a pixel classification procedure based on nonparametric models of the healthy and defective areas of olives. Classification tests were performed on olives to assess the effectiveness of the proposed method. This research showed that the IR vision system is a useful technology for the automatic assessment of olives that has the potential for use in offline inspection and for online sorting for defects and the presence of surface damage, easily distinguishing those that do not meet minimum quality requirements.

Detection of the presence of hazelnut oil in olive oil by FT-raman and FT-MIR spectroscopy.

The detection of the presence of refined hazelnut oil in refined olive oil at low percentages is still a challenge with the current official standards. FT-Raman and FT-MIR spectroscopies have been used to determine the level of detection of the presence of hazelnut oil in olive oil. Spectroscopic analysis has been made not only with the entire oil but also with its unsaponifiable matter. Univariate and multivariate statistical models have been designed with this objective. This study shows that a complete discrimination between olive and hazelnut oils is possible and that adulteration can be detected if the presence of hazelnut oil in olive oil is >8% and if the blends are of Turkish olive and hazelnut oils. The limit of detection is higher when the blends are of edible oils from diverse geographical origins.

Detection of banned meat and bone meal in feedstuffs by near-infrared microscopic analysis of the dense sediment fraction.

In this paper we present an alternative method for detection of meat and bone meal (MBM) in feedstuffs by near-infrared microscopic (NIRM) analysis of the particles in the sediment fraction (dense fraction (d >1.62) from dichloroethylene) of compound feeds. To apply this method the particles of the sediment fraction are spread on a sample holder and presented to the NIR microscope. By using the pointer of the microscope the infrared beam is focussed on each particle and the NIR spectrum (1112-2500 nm) is collected. This method can be used to detect the presence of MBM at concentrations as low as 0.05% mass fraction. When results from the NIRM method were compared with the classical microscopic method, a coefficient of determination (R2) of 0.87 was obtained. The results of this study demonstrated that this method could be proposed as a complementary tool for the detection of banned MBM in feedstuffs by reinforcement of the monitoring of feeds.