Génie des Procédés

The aim of this work was to characterize and classify three close regions of olives by direct analysis on the olive without any preliminary treatment. This study was focused on the olive samples picked in the three zones: named Bazaza, oled ayad and oled hamdan, in the Moroccan region of Beni Mellal. All samples were also analysed by FT-IR spectroscopy, the spectral data were subjected to a preliminary derivative transform based on the gap segment algorithm to reduce the noise and extract a largest number of analytical information from spectra. A multivariate statistical procedure based on cluster analysis (CA) coupled to support vector machines (SVM), was elaborated, providing an effective classification method. On the basis of a hierarchical agglomerative CA and principal component analysis (PCA), three distinctive clusters were recognized. The SVM procedure was then applied to classify samples from the same regions. The model resulted able to separate the three classes and classi...

Choice of the harvest date is one of the foundations of vintage quality and good-yield sugar in sugar beet. However, it is difficult to define the harvest date and more precisely the date of maturity of beet roots, in an exact and absolute way. Indeed, maturity is divided into several stages and degrees depending on environmental and climatic conditions such as temperature, precipitation, geographic area, and others. The present study evoked the effect of three harvest dates (at esteemed maturity, 7 days after maturity, and 15 days after maturity) on the technological quality parameters, namely, sucrose, nitrogen, potassium, and sodium, using the most popular chemometric method, principal component analysis (PCA). To do this, samples from the Tadla irrigated perimeter were used. The results of exploratory analyses by the application of PCA clearly showed the influence of harvest date, in an important way, on the three quality parameters, composition of sucrose, potassium, and sodium...

Recently, sesame oil is highly appreciated by consumers due to its sensory qualities, antioxidants activity and nutritional benefits, despite its high price. Also, the detection and quantification of adulteration both are problem with increasing importance in the consumer's health and food industry. The goal of this study was to use Fourier transform mid-infrared (FT-MIR) spectroscopy coupled with chemometrics for the quantification of the adulteration of sesame oil. Adulteration with sunflower oil, soybean oil or colza oil is one of the most difficult to detect due to the similar composition of them and sesame oil. Adulterations of sesame oil with different percentages of sunflower oil, soybean oil and colza oil were measured using ATR-FTIR spectroscopy. Spectral and reference data were firstly analyzed by principal component analysis. Partial least square regression (PLSR) was used to establish calibration models. Excellent correlations between ATR-FTIR analysis and studied ed...

This study aims to create a model of oleaster oil simply and reliably to detect adulteration, which presents a large danger that attacks the food sector and human health. For this reason, a study to detect the falsification of oleaster oil was carried out by Fourier-Transform Infrared Spectroscopy FTIR and chemometric method. The experimental samples are shared into two sets, 32 Training set, 8 Test set (4 calibration samples opposite one for validation), and a falsification interval of 1.5-40%. The treatment of infrared spectral results has been done by chemometrics techniques utilizing Partial Least Squares regression or Projection to Latent Structures (PLSR) and Principal Component Regression (PCR). The results show that the perfect falsification model of oleaster oil by olive-oil and soybean oil is illustrated in the spectral region 3050-2700 cm, with R of 0.999 from PLSR and PCR to soybean-oil, concerning olive-oil shows also the better results for the PLSR technical with R of ...

The aim of this work was to characterize and classify three close regions of olives by direct analysis on the olive without any preliminary treatment. This study was focused on the olive samples picked in the three zones: named Bazaza, oled ayad and oled hamdan, in the Moroccan region of Beni Mellal. All samples were also analysed by FT-IR spectroscopy, the spectral data were subjected to a preliminary derivative transform based on the gap segment algorithm to reduce the noise and extract a largest number of analytical information from spectra. A multivariate statistical procedure based on cluster analysis (CA) coupled to support vector machines (SVM), was elaborated, providing an effective classification method. On the basis of a hierarchical agglomerative CA and principal component analysis (PCA), three distinctive clusters were recognized. The SVM procedure was then applied to classify samples from the same regions. The model resulted able to separate the three classes and classi...

Quantitative analysis of food adulterants is an important for health, wealth and economic issue that needs to be fast, simple and reliable. Attenuated Total Reflectance-Fourier Transform Mid Infrared Spectroscopy (ATR-FTMIR), combined with multivariate analysis, has been used to quantify the Beans content in a binary mixture with Ginger. Blends of Ginger with different percentages (0–30%) of Beans were measured using ATR-FTMIR spectroscopy. Spectral and reference data were firstly analyzed by principal component analysis (PCA) to check outliers samples. Partial least square regression (PLSR) was used to establish calibration model. Excellent correlation between ATR-FTIR analysis and studied blend samples was obtained R = 0.99; with Root Mean Square Errors of Prediction < 1.102, Limit of Detection 3.305%, and Relative Prediction Errors as low as 0.67. These results indicate that ATR-FTMIR spectroscopy combined with chemometrics (multivariate analysis) can be used for rapid predict...