Total Phenolics, Flavonoids, and Antioxidant Activity of Sage (Salvia officinalis L.) Plants as Affected by Different Drying Methods

In the current study, we determined the effects of seven drying methods on total phenolics, flavonoids, individual phenolics, and antioxidant activity of the methanol extract of Salvia officinalis L. As compared with total phenolic content (TPC) of fresh plants, results showed that the highest TPC was recorded in plants dried by microwave (MW) at a power of 800 W/30 g of fresh plant and was 4.2 times higher than that of fresh plants whereas the lowest content was found in the case of plants dried by far-infrared (FIR) at 45 °C. The analysis of the different extracts by RP-HPLC showed a predominance of phenolic acids particularly in fresh plants and those dried by MW (600 W/30 g of fresh plant) whereas flavonoids predominate in the case of plants dried by FIR (65 °C). The assessment of the radical scavenging activity (RSA) against the stable radical 1,1-diphenyl-1-picrylhydrazyl (DPPH) showed an increase in the scavenging effect particularly in MW (800 W/30 g of fresh plant) dried plants with an IC50?=?13.49 μg ml^?1 (IC50 is the concentration required to cause 50 % DPPH inhibition). The complementary assessment of the RSA using the β-carotene/linoleic acid system showed an increase of this activity for all extracts and particularly for the extract derived from MW (600 W/30 g of fresh plant) dried plants as compared to fresh ones. Finally, all the plant extracts showed moderate reducing power as assessed by the ferric-reducing antioxidant potential. These results suggested that MW drying could be applied to retain phenolic contents and to enhance antioxidant activity of sage plant materials.     

Development of a rapid method based on front-face fluorescence spectroscopy for the monitoring of egg freshness: 2—evolution of egg yolk

This preliminary study is devoted to the application of front-face fluorescence spectroscopy to the study of egg yolks during storage. A total of 79 eggs stored for 1, 2, 3, 4, 5, 9, 10, 12, 16, 18, 23, 25 and 29 days at room temperature were analysed. The fluorescence emission spectra of tryptophan residues (excitation: 290 nm; emission: 305–430 nm) of proteins and the excitation spectra of vitamin A (emission: 410 nm; excitation: 270–350 nm) were recorded directly on egg yolk samples. Factorial discriminant analysis (FDA) was used to classify the eggs according to their date after they were laid. Using tryptophan fluorescence spectra, correct classification was observed for 57.1 and 51.9% for the calibration and the validation sets, respectively. Better classification (94.9 and 91.4% of the calibration and validation samples, respectively) was obtained from the vitamin A fluorescence spectra. The first five principal components (PCs) of the principal component analysis (PCA) extracted from each data set (tryptophan and vitamin A fluorescence spectra) were pooled (concatenated) into a single-matrix and analysed by FDA. Correct classifications were obtained for 97.5% of the calibration and 96.3.1% of the validation spectra. The discrimination of the investigated egg yolks according to their storage time was excellent. It was concluded that the concatenation of different fluorescence spectra might be considered as a promising indicator of shell egg freshness when they are used in egg products.     

Effect of heat treatment of rennet skim milk induced coagulation on the rheological properties and molecular structure determined by synchronous fluorescence spectroscopy and turbiscan

Heat treatment applied to milk induces denaturation of whey proteins, leading to a complex mixture of whey protein and whey protein coated casein micelles. The present paper investigates the effects of heat treatment (60 and 80°C during 20min) and rennet-induced coagulation temperature (30 and 40°C) determined by rheology, synchronous fluorescence spectroscopy (SFS) and turbiscan measurements. The gelation times determined by rheology and SFS increased with the increase of heat treatment applied to milk. The rise in temperature induced a decrease in the maximum curd firming rate and an increase in the viscosity of the investigated milk samples. The principal component analysis (PCA) applied, separately, to the SF and turbiscan spectra showed a clear discrimination between: (i) raw milks and heated milks; and (ii) milks renneted at 30°C from those renneted at 40°C. The results showed the ability of SFS as a rapid and non-destructive technique for the: (i) monitoring network structure and molecular interaction during the coagulation process; and (ii) determination of gelation time of rennet-induced coagulation of studied milk samples.     

Effect of Air-Drying Conditions on Physico-chemical Properties of Osmotically Pre-treated Pomegranate Seeds

The drying of pomegranate seeds was investigated at 40 °C, 50 °C and 60 °C with air velocity of 2 m/s. Prior to drying, seeds were osmodehydrated in 55 °Brix sucrose solution for 20 min at 50 °C. The drying kinetics and the effects of osmotic dehydration (OD) and air-drying temperature on antioxidant capacity, total phenolics, colour and texture were determined. Analysis of variance revealed that OD and air-drying temperature have a significant influence on the quality of seeds. Both anthocyanin and total phenolic contents decreased when air-drying temperature increased. The radical diphenylpicril-hydrazyl activity showed the lowest antioxidant activity at 60 °C. Both chromatic parameters (L*, C* and h°) and browning index were affected by drying temperatures, which contributed to the discolouring of seeds. The final product has 22%, 20% and 16% of moisture; 0.630, 0.478 and 0.414 of a _w; 151, 141 and 134 mg gallic acid equivalent/100 g fresh matter (FM) of total phenolics; 40, 24, 20 mg/100 g FM of anthocyanins and 46%, 39% and 31% of antioxidant activity, for drying temperatures of 40 °C, 50 °C and 60 °C, respectively. In view of these results, the temperature of 40 °C is recommended as it has the lowest impact on the quality parameters of the seeds. Differential scanning calorimetry data provided complementary information on the mobility changes of water during drying. Glass transition temperature (Tg′) depends on moisture content and as consequence, on drying conditions. In fact, Tg′ of seeds dried at 60 °C (Tg′ = −21 °C) was higher than those dried at 50 °C (Tg′ = −28 °C) or 40 °C (Tg′ = −31 °C) and osmodehydrated seeds (Tg′ = −34 °C). During OD and drying process, the texture of seeds changed. The thickness of seeds shrank by 55% at 60 °C.     

A review of the analytical methods coupled with chemometric tools for the determination of the quality and identity of dairy products

There is an increasing demand of the consumers and actors of the food industry sector to have means of measurement allowing the characterisation of raw materials or food. Dairy products (milk, ice cream, yogurt, butter, cheese, etc.) are in considerable demand, command premium prices and are, therefore, vulnerable to economic adulteration. Authenticity of these products is an important issue for food processors, retailers, regulatory authorities and consumers. It is also valuable for ensuring fair competition and as a mean of protecting consumers against fraud due to mislabelling. Conventional chemical methods are not able to determine the regional provenance of dairy products unambiguously. Therefore, alternative techniques such as spectroscopic techniques i.e., near infrared (NIR), mid infrared (MIR), front face fluorescence spectroscopy (FFFS), stable isotope and nuclear magnetic resonance (NMR)-coupled with chemometric tools have many potential advantages as tools for the evaluation of the identity of such products. This review article discusses the potential of destructive and non-destructive techniques for the determination of the quality and the authenticity of dairy products.     

Mid infrared and fluorescence spectroscopies coupled with factorial discriminant analysis technique to identify sheep milk from different feeding systems

Mid infrared spectroscopy (MIR) combined with multivariate data analysis was used to discriminate between ewes milk samples according to their feeding systems (controls, ewes fed scotch bean and ewes fed soybean). The MIR spectra were scanned throughout the first 11 weeks of the lactation stage. When factorial discriminant analysis (FDA) with leave one-out cross-validation was applied, separately, to the three spectral regions in the MIR (i.e. 3000–2800, 1700–1500 and 1500–900 cm⁻¹), the classification rate was not satisfactory. Therefore, the first principal component (PCs) scores (corresponding to 3, 10 and 10 for, respectively, the 3000–2800, 1700–1500 and 1500–900 cm⁻¹) of the principal component analysis (PCA) extracted from each of the data sets were pooled (concatenated) into a single matrix and analysed by FDA. Correct classification amounting to 71.7% was obtained. Finally, the same procedure was applied to the MIR and fluorescence data sets and 98% of milk samples were found to be correctly classified. Milk samples belonging to control and soybean groups were 100% correctly classified. Regarding milk samples originating from the scotch bean group, only 2 out of 33 samples were misclassified. It was concluded that concatenation of the data sets collected from the two spectroscopic techniques is an efficient tool for authenticating milk samples according to their feeding systems, regardless of the lactation stage.     

Optimizing amplifier placements in a multiwavelength opticalLAN/MAN: the unequally powered wavelengths case

Optical networks based on passive-star couplers and employing WDM have been proposed for deployment in local and metropolitan areas. These networks suffer from splitting, coupling, and attenuation losses. Since there is an upper bound on transmitter power and a lower bound on receiver sensitivity, optical amplifiers are usually required to compensate for the power losses mentioned above. Due to the high cost of amplifiers, it is desirable to minimize their total number in the network. However, an optical amplifier has constraints on the maximum gain and the maximum output power it can supply; thus, optical amplifier placement becomes a challenging problem. In fact, the general problem of minimizing the total amplifier count is a mixed-integer nonlinear problem. Previous studies have attacked the amplifier-placement problem by adding the “artificial” constraint that all wavelengths, which are present at a particular point in a fiber, be at the same power level. This constraint simplifies the problem into a solvable mixed-integer linear program. Unfortunately, this artificial constraint can miss feasible solutions that have a lower amplifier count but do not have the equally powered wavelengths constraint. In this paper, we present a method to solve the minimum-amplifier-placement problem, while avoiding the equally powered wavelength constraint. We demonstrate that, by allowing signals to operate at different power levels, our method can reduce the number of amplifiers required     

Risk based intrusion detection system in software defined networking

Software defined networking (SDN) separates control from data operations. However, this technology adds a new security cost to the network architecture because of the ongoing and developing security vulnerabilities. An intrusion detection system must be continuously improved and integrated into the SDN architecture in order to provide a network defense against attacks. In this study, we propose a continual learning system based on risk assessment to detect intrusion in SDN. We suggest a technique for continually enhancing datasets to produce a more accurate prediction. The proposed system includes various processes, including risk assessment and the selection of the deep learning (DL) approach. We propose assessing the risks related to different intrusion types. Based on the risk value, we can identify which intrusion types are more important and have a dangerous impact. We use the risk values to choose the most appropriate DL approach and for the dataset's continual enrichment. We compare different DL methods using the standard metrics and two proposed metrics. Then, we propose to use a method based on the bit alternation approach to obtain a unique metric for decision-making. Finally, we have studied the efficacy of our system using two case studies.     

MOS cascode-mirror biasing circuit operating at any current levelwith minimal output saturation voltage

A cascode biasing circuit is proposed which fixes the source voltage of the cascode transistor equal to the saturation voltage of the mirror transistor. The mirror can operate at any current level from weak to strong inversion. The design is based on ratios, and is technology-independent. Since the circuit ensures the smallest possible output saturation voltage, it has potential applications in all fields of low-voltage micropower design