Application of Near-Infrared Spectroscopy for the Detection of Metanil Yellow in Turmeric Powder

Turmeric (Curcumina Longa) is a globally traded commodity which is subjected to economically motivated chemically unsafe adulteration, namely metanil yellow. In this work, we report a simplistic and convenient approach to find the adulteration of turmeric with metanil yellow by near-infrared (NIR) spectroscopy coupled with chemometrics. Pure turmeric sample was prepared in the laboratory and spiked with different concentrations of metanil yellow. The reflectance spectra of 248 pure turmeric, metanil yellow, and adulterated samples (1–25%) (w/w) were collected using NIR spectroscopy. The calibration models based on NIR spectra of 144 samples were built for two different regression models, principal component analysis (PCR), and partial least square (PLSR) methods. Another 72 samples were used for external validation. The coefficient of determination (R ²) and root mean square error of calibration for validation and prediction were found to be 0.96–0.99, 0.44–0.91, respectively, for most of the results depending upon different pre-processing techniques and mathematical models used. The original reflectance spectra, the 1st derivative plot, the plot of PLSR regression coefficient (β), and the first three principal component loadings revealed metanil-related absorption regions. To verify the robustness of the models, the figures of merit (FOM) of the models were calculated with the help of net analyte signal (NAS) theory. Overall, it was found that PLSR yielded superior results as compared to the PCR technique. These methods can be applied to other spices also to detect the adulteration rapidly and without any prior sample preparations and with low cost.     

Quality Assessment of Intact Chicken Breast Fillets Using Factor Analysis with Vis/NIR Spectroscopy

Factor analysis (FA) method was tested to assess quality of chicken breast fillets with the visible/near-infrared (Vis/NIR) spectroscopy with wavelength range between 400 and 2500 nm. According to inherent correlation, three factors were extracted from the measured eight quality traits (L*, a*, b*, pH, moisture, drip loss, expressible fluid, and salt-induced water gain). The extracted “grade factor” (F ₁), “color factor” (F ₂), and “moisture factor” (F ₃) could respectively represent the characteristics and the variation tendency of the corresponding quality traits and were defined as three new quality assessment indexes. Furthermore, partial least squares regression (PLSR) models were established to quantitatively relate spectral information to eight individual quality traits and three factors. The results indicated that the models for predicting each factor performed better than those for individual quality traits. Key wavelengths of each quality trait were then selected, and the corresponding spectra were taken to build new PLSR prediction models. The selected key wavelengths showed obvious practical significance, and the new models had comparable predictive performance to those models developed based on the full spectra, among which the new models of F ₁ and F ₂ had acceptable and robust predictive abilities (R²p?=?0.73, RPD?=?1.91; R²p?=?0.74, RPD?=?1.97). Our results in the present study demonstrate the potential for FA and Vis/NIR spectroscopy as a useful method to assess the quality of chicken breast fillets.     

Application of Near-Infrared Hyperspectral Imaging with Variable Selection Methods to Determine and Visualize Caffeine Content of Coffee Beans

Hyperspectral imaging covering the spectral range of 874–1734 nm was used to determine caffeine content of coffee beans. Spectral data of 958.24–1628.89 nm were extracted and preprocessed. Partial least squares regression (PLSR) model on the preprocessed full spectra obtained good performance with coefficient of determination of prediction (R ² _p ) of 0.843 and root mean square error of prediction (RMSEP) of 131.904 μg/g. In addition, 10 variable selection methods were applied to select the best optimal wavelengths. The PLSR models on the different optimal wavelengths obtained satisfactory results. The PLSR model on the wavelengths selected by random frog (RF) performed the best, with R ² _p of 0.878 and RMSEP of 116.327 μg/g. The RF wavelength selection combined with the PLSR model also achieved satisfactory visualization of caffeine content between different coffee beans. The overall results indicated that optimal wavelength selection was an efficient method for spectral data preprocessing, and hyperspectral imaging was illustrated as a potential technique for real-time online determination for caffeine content of coffee beans.     

Development and characterization of reconstituted hydrogel from <Emphasis Type="Italic">Aloe vera</Emphasis> (<Emphasis Type="Italic">Aloe barbadensis</Emphasis> Miller) powder

Structural and rheological characterization of reconstituted hydrogels developed from A. vera non-fibrous alcohol insoluble residue (NFAIR) powder using different methods [viz., shaking (S), heating-shaking (HS), and heating (H)] and concentrations (viz., 0.2–1.6 %, w/v) was carried out. Functional group distribution by FTIR spectroscopy and Congo red (CR) method revealed the presence of acetylated acemannan in A. vera powder. Dynamic oscillation studies of A. vera (NFAIR) fluids at all concentrations of 0.2–1.6 %, w/v, showed gel strength in the order of H > HS > S method. However, in H method, increase in concentration from 0.2 to 1.6 %, w/v showed the conformational transition from semi-diluted solution to weak gel nature. Rheological models described the effect of heating temperatures (HT); 30–90 °C, and times (Ht); 15–60 min on viscoelastic behavior in reconstituted A. vera fluids. The reconstituted A. vera hydrogel prepared with a concentration of 1.6 %, w/v using 50 °C (HT) and 30 min (Ht) condition showed a good agreement with the Power law (storage modulus, G′) and Weak gel model (complex modulus, G*) fitted data (R² > 0.94) resulting higher viscoelastic moduli intercepts; G′₀ (71.5 Pa s ^n′), G″₀ (33.5 Pa s ^n″), lower slopes; n′ (0.22), n″ (0.06), higher network strength (A _F , 121.3 Pa s^1/z ) and number of network (z, 5.3) values. The obtained results suggested that heating at 50 °C/30 min can develop aqueous weak gel networks of A. vera with enhanced gel strength which may be utilized as a novel gelling agent for wide variety of targeted applications in food and pharmaceutical sectors.     

FTNIR-A Robust Diagnostic Tool for the Rapid Detection of <Emphasis Type="Italic">Rhyzopertha dominica</Emphasis> and <Emphasis Type="Italic">Sitophilus oryzae</Emphasis> Infestation and Quality Changes in Stored Rice Grains

Fourier transform infrared spectroscopy (FTNIR) is an excellent mode for evaluation of grain-quality attributes. It enables the nonperturbative molecular information to be diagnosed and allows the explication of images of grains by the passage of the spectral data through an array of computational algorithms. The images are contrived from fingerprint spectra so the conception is that the reflection can conceal the status of the analyzed sample. Rhyzopertha dominica F.- and Sitophilus oryzae-infested and fresh rice grains analyzed with FTNIR within a range of 12,000–4000 cm^?1 were proffered to mathematical processing. Partial least squares regression (PLSR) was used for the estimation of physicochemical parameters of rice grains. Outstanding predictive results were acquired denoting that infested rice grains could be convincingly quantified. The coefficient of correlation, root mean square error of validation, and cross validation for the FTNIR model developed to quantify the quality attribute changes with infestation in rice grains were in the range of 99.85–99.01% (R²), 0.2–1.14% (RMSEE), and 0.3–1.25% (RMSECV). Excellent prediction results of various physico-chemical attributes were obtained for rice grains indicating the fresh and infested samples can be uniquely identified. Also, a paired t test was performed to compare the analytical methods with FTNIR-developed method; no significant difference was found (t_cal 0.025?<?t_cri 2.12; α?=?0.05, RPD >?6) between the two methods. Thus, the results further confirmed the developed FTNIR system to be inherently rapid, clean, and capable of preventing hazardous chemicals which originates from traditional analytical processes and has the potential for monitoring and sorting of rice grains.     

Ridgetail White Prawn (<Emphasis Type="Italic">Exopalaemon carinicauda</Emphasis>) K Value Predicting Method by Using Electronic Nose Combined with Non-linear Data Analysis Model

In this paper, ridgetail white prawn (Exopalaemon carinicauda) K value predicting model by electronic nose (EN) was studied. Human sensory evaluation (HSE), weight loss, color, total viable counts (TVC), GC-MS, and K value were examined to provide quality references for EN detection. EN responses to prawns were recorded and processed by principal component analysis (PCA) and stochastic resonance (SR). Results indicated that prawn K value rapidly increased due to microbiology propagation. The volatile gases emitted by prawns increased with the increase of storage time based on GC-MS results. PCA method could not discriminate the prawns in different qualities, and SR signal-to-noise ratio (SNR) maximum (SNR_max) values successfully discriminated all samples. K value predicting model was developed by linear fitting regression between K values and SNR_maxvalues (R²?=?0.97). The proposed method will promote the applications of EN in aquatic product quality rapid determination.     

Nutritional,functional, thermal and structural characteristics of <Emphasis Type="Italic">Citrullus lanatus</Emphasis> and <Emphasis Type="Italic">Limonia acidissima</Emphasis> seed flours

Seeds from fruits such as Citrullus (C.) lanatus (watermelon) and Limonia (L.) acidissima (wood apple) are not commonly utilized but could be suitable in numerous food formulations. It was shown that the protein content of defatted seed flours was 71.38 and 49.51 % and that these contained considerable amounts of minerals such as Na, Mn, Mg, K, Cu, Fe and Zn. The defatted L. acidissima seed flour was superior to C. lanatus in essential amino acids. The flours obtained from both seeds were also evaluated for functional properties and characterized by X-ray diffraction, differential scanning calorimeter and scanning electron microscope (SEM). Amorphous nature was observed in defatted C. lanatus and L. acidissima flours due to the low percentage of degree of crystallinity. Spherical morphologies were observed through SEM. The exothermic peak was recorded in defatted C. lanatus and L. acidissima flour.     

Real-Time Monitoring of Organic Carrot (var. Romance) During Hot-Air Drying Using Near-Infrared Spectroscopy

The worldwide consumption of dried carrot (Daucus carota L.) is on a growing trend. Conventional methods for drying carrots include hot-water blanching followed by hot-air drying, which is usually uncontrolled and therefore prone to product quality deterioration. Thus, there is a need for innovative drying systems that yield high-value end products. In this study, the efficacy of NIR spectroscopy for the non-destructive monitoring of physicochemical changes and drying behaviour in organic carrot slices during 8-h hot-air drying at 40 °C was demonstrated using Partial least squares (PLS) regression and PLS discriminant analysis (PLS-DA). The impact of hot-water blanching pre-treatment (at 95 °C for 1.45 min) for enzyme inactivation on performances of both regression and classification models was also evaluated. PLS regression models were successfully developed to monitor changes in water activity (R ² = 0.91–0.96), moisture content (R ² = 0.97–0.98), total carotenoids content (R ² = 0.92–0.96), lightness for unblanched carrots (R ² = 0.80–0.83) and hue angle for blanched samples (R ² = 0.85–0.87). Soluble solids content prediction was poor for both treatments (RMSEP = 3.43–4.40). Classification models were developed to recognise dehydration phases of carrot slices on the basis of their NIR spectral profile using K-means and PLS-DA algorithms in sequence. The performance of each PLS-DA model was defined based on its accuracy, sensitivity and specificity rates. All of the selected models provided from good (> 0.85) to excellent (> 0.95) sensitivity and specificity for the predefined drying phases. Feature selection procedures yielded both regression and classification models with performances very similar to models computed from the full spectrum.     

Modeling the Inactivation of <Emphasis Type="Italic">Listeria innocua</Emphasis> and <Emphasis Type="Italic">Escherichia coli</Emphasis> in Fresh-Cut Tomato Treated with Pulsed Light

The effectiveness of pulsed light (PL) treatments to inhibit microorganisms on fresh-cut tomatoes (Lycopersicon esculentum Mill., cv. Daniela) was investigated. Tomato slices inoculated with Escherichia coli or Listeria innocua were exposed to PL treatments (4, 6, or 8 J cm^?2 fluence) and kept cold at 4 °C for 20 days. L. innocua and E. coli counts, gases in the headspace of the containers (O₂ and CO₂), pH, titratable acidity, and soluble solid content were monitored throughout the cold storage. The PL treatments reduced significantly (p < 0.05) initial loads of both microbes. The effect of the PL fluence on the survival number of microoganisms was described by a log-linear model (R ² = 0.849–0.999). At any fixed time within the cold storing, the microbial counts for untreated samples were always higher than those cut tomatoes that had been previously PL-treated. The behavior of L. innocua and E. coli during the storage were well adjusted (R ² > 0.930) by Gompertzian models; the studied microorganisms exhibited different patterns during the storage period. On the other hand, O₂ and CO₂ partial pressures in containers with fresh-cut tomatoes were also significantly affected by PL treatments (p < 0.05). The highest PL fluence caused the greatest changes of O₂ and CO₂ contents. In addition, the application of PL triggered an acceleration of the O₂ consumption during the cold stage. PL treatments might be used to effectively extend the safety of fresh-cut tomatoes over 12 days of storage against E. coli and L. innocua growth.     

A mathematical model for moisture movement during continous and intermittent drying of <Emphasis Type="Italic">Eucalyptus saligna</Emphasis>

A modified diffusion-based mathematical model is proposed to describe the moisture movement during continuous and intermittent drying of Eucalyptus saligna. This model includes the temperature change, the surface drying coefficient (β _n ) and 2 diffusion coefficients [from green to FSP (D _f ) and from FSP to dry condition (D _o )] as important parameters. The final model expression obtained was M?=?exp (??25 β _n ² D _t /l²) with the β _n used was 1.5807 kg m^?2 s^?1, the D _f was 2.26?×?10^?11 m² s^?1, and the D _o was 5.85?×?10^?12 m² s^?1. The range of temperature change between heating and non-heating phases in the intermittent drying regimes was from 24.9 to 31.8 °C. The R² values obtained when the model was fitted into the drying data of different intermittent regimes ranged from 71.5 to 85.9%. The R² value was 87.4% when the model was fitted into continuous trial data. The high values of R² indicate that the model can be used to understand the moisture reduction both in intermittent and continuous regimes.     

Determination of Total Sugar Content in Soy-Based Drinks Using Infrared Spectroscopy and Chemometrics

Partial least square (PLS) regression models were developed and compared in order to determine the total sugar content in soy-based drinks using an infrared spectroscopy technique known as attenuated total reflectance Fourier transform infrared (ATR-FTIR). On a spectrophotometer set for analyzing on the middle infrared region, spectral band of 1900 to 900 cm^?1, commercial samples of soy beverage were analyzed, as well as samples with crescent water additions of 5, 10, and 20% v/v. Reference data for total sugars were obtained using the Lane-Eynon method. To construct regression models, algorithms of interval partial least square (iPLS) and synergy of interval partial least square (siPLS) were applied using iToolbox package on Matlab 8.1 environment. Kennard-Stone algorithm was used to the selection of calibration and prediction sets. Two models have been the best obtained: the first was an iPLS with seven latent variables, which selected the spectral band of 1399–900 cm^?1 and presented root mean square error of cross-validation (RMSECV)?=?0.1678% (w/w). The second best model was siPLS with six latent variables, which selected spectral bands of 1025–1150 and 1151–1476 cm^?1 and presented RMSECV?=?0.1963% (w/w). The proposed method presents advantages such as a small-required amount of sample for spectrum achievement, no sample destruction, and a high analytical frequency.     

Comparative inactivation studies of <Emphasis Type="Italic">Aegle marmelos</Emphasis> (<Emphasis Type="Italic">bael</Emphasis>) peroxidase in crude extract of fruit by heat processing and ultrasonication treatment

Bael (Aegle marmelos) is considered as a holy fruit comprised of vast number of phytonutrients. Whole bael tree including all its parts has medicinal significance. Lack of awareness and seasonal nature makes its processing rather challenging. Conventional heat processing may lead to inactivation of quality hampering enzymes such as peroxidase, but at the cost of loss in essential phytonutrients. In the present work it was observed that thermal inactivation of bael peroxidase obeyed first order kinetics with enzyme activation energy of 7.7 kJ mol^?1. Complete inactivation of bael peroxidase was achieved within 11 min at 85?°C while ultrasound treatment attained in lesser time of 4 min at 64.07 W cm^?2 ultrasonic intensity. Loss of marmelosin a well-known phytonutrient in bael fruit was found to be 83.29?% by heat (11 min, 85?°C) and only 50.20?% by ultrasonication (4 min, 64.07 W cm^?2 ultrasonic intensity). Ultrasonication has potential to overcome harmful effects of heat processing with retention of phyto-constituents and hence has promising future in various food processing applications.     

Non-destructive Assessment of Guava (<Emphasis Type="Italic">Psidium guajava</Emphasis> L.) Maturity and Firmness Based on Mechanical Vibration Response

Storage potential and eating quality of guava (Psidium guajava L.) fruit depend on its maturity. Segregation of guava according to maturity and firmness measured using non-destructive technologies would help the industry to designate ripe fruit to immediate market and less ripe fruit for distant market (e.g., exportation). This research was conducted to evaluate the potential of experimental resonant frequency (f _e) and elasticity index (EI) to estimate fruit firmness, which has been reported to be inversely correlated to its maturity. A maturity index (I _m) was calculated as the ratio of total soluble solids/titratable acidity (TSS/TA). It was proved that TSS, TA, and I _m were significantly correlated (P?<?0.05) to skin firmness (F _s), flesh firmness (F _f), stiffness (S), and analytical resonant frequency (ω _n ), being S the attribute best fitted to I _m (R ²?=?0.77). Since it was observed that f _e and EI were sensitive to changes in fruit firmness, both of them were explored as alternatives to predict F _s, F _f, S, and ω _n of guava fruit. In some cases, EI improved the models to predict guava firmness traits (e.g., F _s vs f _e had a coefficient of determination of R ²?=?0.58, whereas for F _s vs EI, it was R ²?=?0.62). The best model occurred when plotting ω _n vs f _e (R ²?=?0.86), followed by S vs EI (R ²?=?0.84), making these promising features for the development of a new practical application using frequency response measurement as a non-destructive method to assess guava maturity.     

A regression model describing the effect of pH,NaCl and temperature on<Emphasis Type="Italic"> D</Emphasis> values of<Emphasis Type="Italic"> Bacillus stearothermophilus</Emphasis> spores

A new microbiological predictive model was developed, relating pH, NaCl concentration and temperature (T) with the decimal reduction coefficient D as dependent variable, using data previously reported by [1]. The model was obtained by multiple linear regression using only three predictor variables (T ², pH² and NaCl), easily computed from the basic variables pH, NaCl concentration and temperature (T). The fitted model is robust, stable and satisfies all the basic hypotheses of the regression models. It also provides simplicity when compared with previously published models based on multiple linear regression tools.     

Comparative Study on the Inactivation and Photoreactivation Response of <Emphasis Type="Italic">Listeria monocytogenes</Emphasis> Seafood Isolates and a <Emphasis Type="Italic">Listeria innocua</Emphasis> Surrogate after Pulsed Light Treatment

The inactivation and photoreactivation response of six seafood-isolated Listeria monocytogenes and one Listeria innocua strain after pulsed light (PL) treatment was evaluated. The lower inactivation levels found after exposure of treated samples to daylight during the first 90 min of storage confirmed that both L. innocua and L. monocytogenes have the capability to photorepair PL-induced DNA damage upon appropriate conditions. Photoreactivation levels from 0.2 to 2.1 log CFU cm^?2 were observed depending on treatment intensity (fluence) and Listeria strain. Complete photorepair of PL-caused damage was not found even after treatments inducing low inactivation levels. Photoreactivation increased up to 2.1 log with the applied fluence up to a threshold able to cause between 2.4 and 5.4 log reductions under dark storage. Photorepair was not avoided but lower photoreactivation was observed after higher fluence inducing more than 6 log reductions under dark storage. Both L. innocua and L. monocytogenes serotype 1/2b exhibited the highest photoreactivation levels whereas serotypes 1/2a showed the lowest ones. The overall inactivation and photoreactivation responses of tested Listeria strains were comparable indicating that L. innocua may be a good surrogate for the safe evaluation, optimization and validation of PL technology to control L. monocytogenes in food products and food processing facilities.     

Characterization of <Emphasis Type="Italic">Ficus sycomorus</Emphasis> tannin using ATR-FT MIR,MALDI-TOF MS and <Superscript>13</Superscript>C NMR methods

The Ficus sycomorus bark tannin was extracted and characterized using Attenuated Total Reflectance Fourier Transform Middle Infrared (ATR-FT MIR) spectra in the 1800 and 600 cm^?1 range, Matrix Assisted Laser Desorption Ionisation Time of Flight Mass Spectrometry (MALDI-TOF MS) and Carbon-13 Nuclear Magnetic Resonance (¹³C NMR) spectroscopy methods. Ficus sycomorus species have a very high percentage (46%) yield of tannin. These three characterization methods have shown that the Ficus sycomorus bark tannin is condensed and particularly a procyanidin type. It is composed of quercetin, apigenin, fisetinidin, catechin, gallocatechin, chalcone, radicinin, catechin gallate units with the presence of carbohydrates, quinone and gallic acid residues. The analysis results revealed that quercetin are the major constituents of Ficus sycomorus bark tannin. This procyanidin type tannin can give good wood adhesives.     

Evaluation of Drying Methods with Respect to Drying Kinetics,Mineral Content,and Color Characteristics of Savory Leaves

Sun, oven (50 °C), and microwave oven (700 W) drying of savory leaves (Satureja thymbra L.) were carried out to monitor the drying kinetics, changes in mineral content, and color degradation of the product. Oven and microwave oven drying shortened the drying time over than approximately 70% and 99% when compared to the sun and oven drying methods, respectively. Fresh and dried savory leaves had high amounts of K (8875.2–28468.0 mg/kg), Ca (3681.6–9852.03 mg/kg), Mg (1388.0–3102.0 mg/kg), and P (2313.2–5045.8 mg/kg) minerals. K, Ca, P, and Mg were the most abundant elements in savory samples. Mineral content of oven-dried savory were higher than the sun and microwave dried samples. Midilli and Küçük model was shown to give a good fit to the sun and oven drying. The Midilli and Küçük, modified page and page models exhibited high coefficient of determination (R ² ) values ranging between 0.9995 and 0.9997, to the experimental microwave oven drying data of savory. Microwave oven drying revealed optimum color values. Oven drying resulted in a considerable decrease in color quality of savory.     

Steady- and Unsteady-State Determination of the Water Vapor Permeance (<Emphasis Type="Italic">WVP</Emphasis>) of Polyethylene Film to Estimate the Moisture Gain of Packed Dry Mango

The water vapor permeance (WVP; g m^?2 d^?1 Pa^?1) of packaging films quantifying the water vapor transfer rate between foods and its surroundings is usually determined in units operating under steady-state conditions that do not necessarily reflect food handling scenarios. This study evaluated the determination of the WVP of a polyethylene (PE) film by steady-state method ASTM F1249-06 using a permeability cell and unsteady-state method ASTM E96/E96M in which 102 vacuum-sealed PE bags containing silica gel were stored (37.8 °C, 75% relative humidity) and weighed over 25 days. Average steady-state WVP (2.935 ± 0.365 × 10^?3, n = 4) fell within the 95% quantiles of unsteady-state WVP values (1.818–3.183 × 10^?3, n = 2142). Moisture uptake of dehydrated mango stored at 37.8 °C and 75% relative humidity was predicted with WVP values obtained by both methods. Predictions were validated by monitoring over 25 days the weight gain of 100 PE bags with dry mango. Experimental moisture averages during storage fell within one standard deviation of predictions using the unsteady-state WVP (R ² = 0.974). The same was observed only until day 15 for predictions obtained with the steady-state WVP. Calculations for days 20–25 overestimated the moisture uptake by 6.0–7.2%, resulting in registered R ² = 0.924. The unsteady-state WVP determination is low-cost, uses large numbers of film samples, and allowed more accurate predictions of dry mango moisture uptake. Knowledge of the moisture uptake controlled by the film WVP is essential when predicting the safety and quality changes limiting the shelf-life of foods.     

Characterization of Biodegradable Films Based on <Emphasis Type="Italic">Salvia hispanica</Emphasis> L. Protein and Mucilage

Biodegradable films of chia by-products (mucilage and protein-rich fraction (PF)) incorporated with clove essential oil (CEO) were obtained and characterized. The effects of polymer concentration (PC; 1.0–3.0 %, w/v) and CEO concentration (0.1–1.0 %, v/v) were evaluated as well as the pH (7–10), using a 2³ factorial design with four central points. The films exhibited moisture values between 11.6 and 52.1 % (d.b.), which decreased (p?<?0.05) with increasing PC and CEO. The thickness of the films increased (p?<?0.05) with increasing PC. PC and pH influenced (p?<?0.05) the lightness (L) and variation in color between red and green (a). The orientation of the color to yellow-blue hues (b) decreased significantly (p?<?0.05) with increasing PC. Transparency was significantly lower and higher (p?<?0.05) than PC and CEO, respectively. The film surface morphology was evaluated using atomic force miscrocope images, and thermogravimetric analysis (TGA) was performed to study the thermal stability of the films. The displacement and tensile strength were significantly lower (p?<?0.05) at higher concentrations of CEO, this variable being the only one with a significant effect. The chemical composition of the films was confirmed utilizing Fourier transform infrared (FTIR) spectroscopy. The proportion of CEO added to the films had a significant influence on antimicrobial activity, inhibiting the growth of both Escherichia coli and Staphylococcus aureus.     

Application of Curve Fitting and Wavelength Selection Methods for Determination of Chlorogenic Acid Concentration in Coffee Aqueous Solution by Vis/NIR Spectroscopy

Coffee is considered as a functional food due to its being rich in bioactive compounds, mainly chlorogenic acid (CGA). CGA concentration in coffee aqueous solution was investigated based on visible/near-infrared (Vis/NIR) spectroscopy in this research. To enhance the spectral difference among different samples and increase the signal to noise ratio, Lorentz function curve fitting was applied to fit raw Vis/NIR spectra of samples. Then, the fitting parameters were used to correct raw full spectra. Partial least squares (PLS) regression method was used to develop calibration models of CGA concentration. Full-spectrum models were built with raw and fitting parameter-corrected spectra, respectively. Further, wavelength selection methods, such as genetic algorithms (GAs) and success projection algorithms (SPAs), were applied to eliminate redundancy information and identify relevant information from full spectra. Calibration models based on the effective wavelengths selected by GA and SPA methods were developed. The overall results showed that LFPs a/b-corrected spectra had a better performance compared with other processing methods. Performance of the selected wavelength model was better than that of the full-spectrum model. Final results indicated that the SPAs-PLS method provided a more precise prediction model of CGA concentration with R _c of 0.913 and R _cv of 0.795.