Total Reflectance Mid-infrared Spectroscopy Research Articles

Chemometrics-driven monitoring of cheese ripening: A multimodal spectroscopic and scanning electron microscopy investigation.

The integration of spectroscopic techniques with chemometrics offers a means to monitor quality changes in dairy products throughout processing and storage. This study employed Attenuated Total Reflectance–Mid-Infrared Spectroscopy (ATR–MIR) coupled...

Chemical and Nutritional Fat Profile of Acheta domesticus, Gryllus bimaculatus, Tenebrio molitor and Rhynchophorus ferrugineus.

The use of edible insects in the human diet is gaining importance because they are characterized by high nutritional value, and their cultivation is much more environmentally friendly than traditional livestock farming. The objective of this study was to determine the chemical and nutritional fat profile of selected edible insects as follows: house cricket (Acheta domesticus adult), field cricket (Gryllus bimaculatus adult), mealworm (Tenebrio molitor larvae), and palm weevil (Rhynchophorus ferrugineus larvae) which are now commercially available worldwide. Additionally, the degree of implementation of nutrition standards for selected nutrients by these insects was assessed. Freeze-dried insects were studied using infrared-attenuated total reflectance mid-infrared spectroscopy for basic differentiation. The content of fat and fatty acids was determined, and dietary indicators were calculated. The spectroscopic findings align with biochemical data, revealing that Rhynchophorus ferrugineus larvae contain the highest fat content and the least protein. Unsaturated fatty acids (UFAs) predominated in the fat of the assessed insects. The highest content of saturated fatty acids (SFAs), along with the lowest content of polyunsaturated fatty acids (PUFAs), was observed in the larvae of the Rhynchophorus ferrugineus species. From a nutritional standpoint, Tenebrio molitor larvae exhibit the most favorable indicators, characterized by minimal athero- and thrombogenic effects, along with an optimal balance of hypo- and hypercholesterolemic acids. Knowledge of the composition and quantities of fats in different insect species is valuable for planning and preparing meals with accurate nutritional profiles, among other applications.

Critical evaluation of analytical methodologies for the discrimination of hemp and drug-type cannabis

Classification of cannabis samples as hemp- or drug-type is an ever-increasing problem worldwide. Colorimetric tests and infrared spectroscopy were selected and critically compared among the available techniques. Cannabis samples with different THC and CBD concentration were analyzed by paper-based analytical devices (µPAD) using the 4-aminophenol colorimetric reaction, attenuated total reflectance mid infrared spectroscopy (ATR-MIR), and diffuse reflectance near infrared spectroscopy (DR-NIR). For the µPAD analysis, cannabis samples were extracted with methanol and later mixed with reagents to develop the colored complex. On the other hand, MIR and NIR spectra were obtained directly on raw samples, and partial least square discriminant analysis (PLS-DA) was used for cannabis classification. All the selected methodologies successfully discriminate between hemp-type and drug-type samples, being suitable to be used in-field. Additionally, assayed methodologies together a reference gas chromatography mass spectrometry (GC–MS) were evaluated and compared from a Green Analytical point of view using the AGREE criteria.

Quantitative analysis of adulterated pear juice based on attenuated total reflectance mid-infrared spectroscopy and bagging PLS

The methods of pear juice adulteration have evolved from simple adding water to blending based on characteristic spectrum of juice, which greatly increases the difficulty of identification. Herein, a rapid and convenient analytical method based on attenuated total reflectance (ATR) mid-infrared (MIR) spectroscopy and bagging partial least square (PLS) was developed. A total of 63 samples consisted of three kind of adulteration were designed to simulate actual counterfeiting of pear juice. All samples are roughly evenly divided into the calibration and test sets. Three kinds of PLS models including full-spectrum PLS, local PLS with pre feature selection by the ReliefF algorithm and bagging PLS were trained and compared. On the independent test set, the bagging PLS model achieved the best performance, followed by the local PLS model. Specifically, the bagging PLS model with 40 members achieved a root-mean squared error of prediction (RMSEP) of 3.24 %, a 20 % decrease compared to the full spectrum PLS model. Moreover, the error of bagging PLS model on the calibration and test sets is closer, and there is no over-fitting phenomenon, indicating that its robustness is better, with good fitting and generalization. In today's world where computing resources are not a problem, using simple model ensemble is highly desirable.

Characterization of Apple Juice Adulteration by Attenuated Total Reflection–Mid-Infrared Spectroscopy and Partial Least Squares

Juice counterfeiting not only affects product quality but also deceives consumers into buying low-quality goods at high prices. Here is explored the feasibility of combining attenuated total reflection–mid-infrared (ATR-MIR) spectroscopy and interval-based partial least squares (PLS) and full-spectrum PLS models for identifying the adulteration of apple juice. A sample set composed of 41 concentrations of diluted juice was prepared. The adulteration concentration was obtained based on the juice spectrum and the corresponding model. The changeable moving window PLS model was shown to provide the best performance and may be an alternative to traditional approaches for quality control of juice.

Monitoring Compositional Changes in Black Soldier Fly Larvae (BSFL) Sourced from Different Waste Stream Diets Using Attenuated Total Reflectance Mid Infrared Spectroscopy and Chemometrics.

Black soldier fly (Hermetia illucens, L.) larvae are characterized by their ability to convert a variety of organic matter from food waste into a sustainable source of food (e.g., protein). This study aimed to evaluate the use of attenuated total reflectance (ATR) mid-infrared (MIR) spectroscopy to monitor changes in the composition as well as to classify black soldier fly larvae (BSFL) samples collected from two growth stages (fifth and sixth instar) and two waste stream diets (bread and vegetables, soy waste). The BSFL samples were fed on either a soy or bread-vegetable mix waste in a control environment (temperature 25 °C, and humidity 70%). The frass and BSFL samples harvested as fifth and sixth instar samples were analyzed using an ATR-MIR instrument where frequencies at specific wavenumbers were compared and evaluated using different chemometric techniques. The PLS regression models yield a coefficient of determination in cross-validation (R2) > 0.80 for the prediction of the type of waste used as diet. The results of this study also indicated that the ratio between the absorbances corresponding to the amide group (1635 cm−1) and lipids (2921 + 2849 cm−1) region was higher in diets containing a high proportion of carbohydrates (e.g., bread-vegetable mix) compared with the soy waste diet. This study demonstrated the ability of MIR spectroscopy to classify BSFL instar samples according to the type of waste stream used as a diet. Overall, ATR-MIR spectroscopy has shown potential to be used as tool to evaluate and monitor the development and growth of BSFL. The utilization of MIR spectroscopy will allow for the development of traceability systems for BSFL. These tools will aid in risk evaluation and the identification of hazards associated with the process, thereby assisting in improving the safety and quality of BSFL intended to be used by the animal feed industry.

Non-targeted detection of grape molasses adulteration with sugar and apple molasses by mid-infrared spectroscopy coupled to independent components analysis

In the light of the current food security crisis, food adulteration has resurfaced on the international scene, inflicting potential safety issues and leading more and more consumers into deception. This situation led food control actors to remobilise their potential to face this problem, particularly in terms of analytical chemistry competencies. Similar to honey, grape molasses may be considered very likely to be adulterated leading to quality and authenticity issues, especially in the Eastern Mediterranean, where it is widely consumed as a traditional sweetener. This work reports the use of attenuated total reflectance–mid-infrared spectroscopy (ATR–MIR) coupled to chemometrics, as an alternative to complex, expensive and time-consuming analytical techniques, in the aim of detecting fraudulent glucose, fructose, sucrose and apple molasses additions to pure grape molasses. After collecting a widespread unadulterated grape molasses database, spiked samples with increasing concentrations (w/w) of the selected adulterants were prepared. In order to establish a qualitative model, whose potential is to detect adulteration and discriminate between the different adulterants, samples underwent ATR–MIR analyses without any prior preparation, and the collected spectral data were subjected to independent components analysis (ICA), where Random_ICA was used to retrieve the optimal number of independent components (ICs). Thereupon, the extraction of seven ICs allowed the establishment of a qualitative model with a clear discrimination between molasses adulterated with fructose, sucrose and glucose syrup, relying on MIR specific signals and incorporated ratios of the different adulterants. However, it failed in detecting apple molasses adulteration, calling for the development of a different analytical approach. The developed model underwent a verification step using a control set recorded on a different spectrometer, proving its potential to provide reproducible discrimination and classification rates.

Qualitative and quantitative application of Fourier transform near-infrared (NIR) and attenuated total reflection mid-infrared (MIR) spectroscopy for the evaluation of pomegranate seed oil quality

ISHS V International Symposium on Pomegranate and Minor Mediterranean Fruits Qualitative and quantitative application of Fourier transform near-infrared (NIR) and attenuated total reflection mid-infrared (MIR) spectroscopy for the evaluation of pomegranate seed oil quality

Development of Attenuated Total Reflectance Mid-Infrared (ATR-MIR) and Near-Infrared (NIR) Spectroscopy for the Determination of Resistant Starch Content in Wheat Grains.

The chemical method for the determination of the resistant starch (RS) content in grains is time-consuming and labor intensive. Near-infrared (NIR) and attenuated total reflectance mid-infrared (ATR-MIR) spectroscopy are rapid and nondestructive analytical techniques for determining grain quality. This study was the first report to establish and compare these two spectroscopic techniques for determining the RS content in wheat grains. Calibration models with four preprocessing techniques based on the partial least squares (PLS) algorithm were built. In the NIR technique, the mean normalization + Savitzky–Golay smoothing (MN + SGS) preprocessing technique had a higher coefficient of determination (Rc2 = 0.672; Rp2 = 0.552) and a relative lower root mean square error value (RMSEC = 0.385; RMSEP = 0.459). In the ATR-MIR technique, the baseline preprocessing method exhibited a better performance regarding to the values of coefficient of determination (Rc2 = 0.927; Rp2 = 0.828) and mean square error value (RMSEC = 0.153; RMSEP = 0.284). The validation of the developed best NIR and ATR-MIR calibration models showed that the ATR-MIR best calibration model has a better RS prediction ability than the NIR best calibration model. Two high grain RS content wheat mutants were screened out by the ATR-MIR best calibration model from the wheat mutant library. There was no significant difference between the predicted values and chemical measured values in the two high RS content mutants. It proved that the ATR-MIR model can be a perfect substitute in RS measuring. All the results indicated that the ATR-MIR spectroscopy with improved screening efficiency can be used as a fast, rapid, and nondestructive method in high grain RS content wheat breeding.

Microplastic adulteration in homogenized fish and seafood - a mid-infrared and machine learning proof of concept

The objective of this study was to assess the ability of utilizing attenuated total reflection mid-infrared (ATR-MIR) spectroscopy in combination with machine learning techniques to classify the presence of different types of microplastics in artificially adulterated fish and seafood samples. Different polymers namely poly-vinyl chloride (PVC), polycarbonate (PC), polystyrene (PS), polypropylene (PP) and low (LDPE) and high-density polyethylene (HDPE) were mixed with homogenized fish and seafood samples. Homogenized samples were analyzed using MIR spectroscopy and classification models developed using machine learning algorithms such as partial least squares discriminant analysis (PLS-DA). The results of this study revealed that it was possible to identify between adulterated and non-adulterated samples as well as the different microplastic types added to the homogenized samples using ATR-MIR spectroscopy. This study confirmed the ability of combining machine learning methods with ATR-MIR spectroscopy to directly analyze microplastic adulteration in fleshy foods such as fish and seafood. This proof-of-concept study can be utilized and extended to monitor the presence of plastics either in a wide range of fleshy foods or along the entire food value chain.

Can Infrared Spectroscopy Detect Adulteration of Kakadu Plum (Terminalia ferdinandiana) Dry Powder with Synthetic Ascorbic Acid?

Kakadu plum (Terminalia ferdinandiana) fruit is characterised by its high levels of natural ascorbic acid compared with other domesticated plants in the world (e.g. more than 75 times that of oranges). The concentration of ascorbic acid is one of the main factors that define the price of this fruit (as fresh or dry powder) in the market. As many other specialty foods and commodities, this food is not exempt against adulteration. Adulteration can be simply performed by the addition of water (dilution), low-quality fruit and synthetic ascorbic acid and other chemical products. The ability of attenuated total reflectance mid infrared spectroscopy (ATR-MIR) was evaluated as a tool to detect the level of adulteration of Kakadu plum powder with a synthetic source of ascorbic acid. The coefficient of determination (R2) and the standard error of cross validation (SECV) obtained for the prediction of level and source of adulteration were 0.85 (3.2%), and 0.83 (0.30%) respectively. This study demonstrated that the integration of ATR-MIR spectroscopy with chemometric analysis could be a valuable method to identify the adulteration of Kakadu plum powder with synthetic sources of ascorbic acid.

Fiber Probe for Simultaneous Mid-Infrared and Fluorescence Spectroscopic Analysis

A multispectral fiber optic probe has been developed that enables simultaneous analysis of various liquid and solid samples using attenuated total reflection mid-infrared spectroscopy and fluorimetry. The probe design was optimized using ray-tracing simulation of the light propagation. Technical evaluation of the probe has confirmed its output signal quality that was comparable to that of respective probes for single methods. The capability of the probe to deliver complementary chemical information from the same measurement point has been illustrated using model samples of biological tissue. Qualitative analysis of the biological tissue is one of the most important applications of the developed multispectral probe.

Checking counterfeiting of pharmaceutical products by attenuated total reflection mid-infrared spectroscopy

Pharmaceutical products serve as the cornerstone of our healthcare system. Product quality is of paramount importance to safety and efficacy of the patients. The success of pharmaceuticals has led to attempts by dubious manufacturers to gain via counterfeiting of the products, while risking the lives of the billions of patients that depend on these products. As a result, there is critical need for an analytical tool that is simple to operate, is robust and lends itself to yielding a rapid fingerprint of a pharmaceutical. In this paper we suggest use of attenuated total reflection (ATR) mid-infrared spectroscopy as a tool for rapid fingerprinting of pharmaceuticals. Antibiotics have been used as a case study to demonstrate the utility of this approach. ATR mid-infrared spectra obtained from powdered solid pharmaceutical products were classified using multivariate data analysis. A partial least-squares discriminant analysis model was developed and tested using 57 pharmaceutical products (27 antibiotics). The model was able to predict antibiotic present in pharmaceutical formulation irrespective of brand or manufacturing process with a classification accuracy of 87.3%. This indicated that the model is robust with respect to variability in pharmaceutical formulations. In addition, the brand/manufacturing company of an antibiotic could be predicted by training a principal component analysis model for specific antibiotic to a classification accuracy of 90%. The results demonstrate the utility of the proposed approach, which can be used by the appropriate authorities for checking on counterfeiting of pharmaceutical products.

Effects of polymer molecular weight on curcumin amorphous solid dispersion; at-line monitoring system based on attenuated total reflectance mid-infrared and near-infrared spectroscopy

The aim of this study was to investigate the effects of the molecular weight (Mw) of hydroxypropyl cellulose (HPC) and grinding duration on solid dispersions (SDs) formation and their characteristics. In this study, ternary amorphous SD systems containing curcumin (CUR), HPC, and sodium dodecyl sulfate (SDS) were developed using the milling method and characterized their physicochemical and mechanochemical properties. After 120-min grinding, the particle size reduced to under 1 μm and the GMs totally transformed into amorphous phase. The release behavior of CUR depended on the grade of HPCs due to their Mw and corresponding viscosity. During the SD formation process, the grinding time and Mw of HPC could be monitored by analyzing data obtained from MIR and NIR spectra based on chemometrics. There were two steps in SD formation: (1) simple dispersion with grinding time under 30 min and (2) random dispersion of mixtures with grinding time from 30 to 120 min. The HPC-M (700,000 Da) resulted in more effectively forming SD systems.

Transforming data to information: A parallel hybrid model for real-time state estimation in lignocellulosic ethanol fermentation.

Operating lignocellulosic fermentation processes to produce fuels and chemicals is challenging due to the inherent complexity and variability of the fermentation media. Real‐time monitoring is necessary to compensate for these challenges, but the traditional process monitoring methods fail to deliver actionable information that can be used to implement advanced control strategies. In this study, a hybrid‐modeling approach is presented to monitor cellulose‐to‐ethanol (EtOH) fermentations in real‐time. The hybrid approach uses a continuous‐discrete extended Kalman filter to reconciliate the predictions of a data‐driven model and a kinetic model and to estimate the concentration of glucose (Glu), xylose (Xyl), and EtOH. The data‐driven model is based on partial least squares (PLS) regression and predicts in real‐time the concentration of Glu, Xyl, and EtOH from spectra collected with attenuated total reflectance mid‐infrared spectroscopy. The estimations made by the hybrid approach, the data‐driven models and the internal model were compared in two validation experiments showing that the hybrid model significantly outperformed the PLS and improved the predictions of the internal model. Furthermore, the hybrid model delivered consistent estimates even when disturbances in the measurements occurred, demonstrating the robustness of the method. The consistency of the proposed hybrid model opens the doors towards the implementation of advanced feedback control schemes.

Application of ATR-FT-MIR for Tracing the Geographical Origin of Honey Produced in the Maltese Islands.

Maltese honey has been produced, marketed, and sold as an exclusive local gourmet food product for countless years. Yet, thus far, no study has evaluated the individuality of this local food product. The evaluation of the parameters and properties which characterise the provenance and floral source of honey have been the subject of various studies worldwide, owing to the price and potential beneficial properties of this food product. Models analysing the potential of attenuated total reflection mid-infrared (ATR-FT-MIR) spectroscopy in discriminating and classifying local honey from that of foreign origin were investigated using 21 Maltese honey samples and 49 honey samples collected from abroad (Sicily, Greece, Sweden, Italy, France, Estonia and other samples of mixed geographical origin). Through a combination of spectroscopic techniques, spectral transformations, variable selection and partial least squares discriminant analysis (PLS-DA), chemometric models which successfully classified the provenance of local and non-local honey were developed. The results of these models were also corroborated with other classification and pattern recognition techniques, such as linear discriminate analysis (LDA), support vector machines (SVM) and feed-forward artificial neural networks (FF-ANN).

Rapid discrimination and classification of edible insect powders using ATR-FTIR spectroscopy combined with multivariate analysis

Insects are being proposed as an alternative way to ensure world’s food and feed security. Methods to determine edible insect powder’s origin and species will be needed for quality control purposes. Infrared spectroscopy has been extensively used in rapid chemical fingerprinting of food products. The present research explores a new approach to discriminate and classify commercial edible insect powders using attenuated total reflectance mid-infrared spectroscopy combined with multivariate analysis. Infrared spectra of seven commercial edible insect powders from different species (Tenebrio molitor, Alphitobius diaperinus, Gryllodes sigillatus, Acheta domesticus andLocusta migratoria) and origins (the Netherlands and New Zealand) were collected to build up soft independent modelling of class analogy (SIMCA) models. SIMCA models clearly discriminated insects by their species and origin linking their differences to lipids and chitin. SIMCA models performance was tested using five spectra of each class not used to build up the training set. 100% correct predictions were obtained for all the samples analysed with the exception of one sample ofAlphitobius diaperinus. Infrared spectroscopy coupled to multivariate analysis provided a powerful method for the assurance of insect powder’s authenticity.

Rapid measurement of microplastic contamination in chicken meat by mid infrared spectroscopy and chemometrics: A feasibility study

Microplastic detection has been acknowledged as challenging so far, particularly regarding in-situ analysis. Although much effort on the use of rapid analytical methods to analyse and identify microplastics in the environment, less has been done on the identification and measurement of microplastics contained in the food matrix. The objective of this study was to evaluate the use of a rapid method based on attenuated total reflection mid infrared (ATR-MIR) spectroscopy combined with chemometric techniques to identify the level of contamination in homogenised chicken meat with microplastics polystyrene (PS, particle size 100 μm) and polyvinyl chloride (PVC, 3 μm, 100 μm and 2–4 mm). We have evaluated the contamination of chicken meat with various amount of microplastics using MIR spectroscopy. Despite the moderate detection sensitivity of the method, the ATR-MIR can be a rapid and reliable analytical tool to detect and quantify high levels (between 1 up to 10%) of addition/contamination of microplastics to chicken meat. This is the first study to explore the feasibility of measuring microplastics within the context of chicken meat. The method once optimised with improved sensitivity would in future greatly enhance the applicability of measuring microplastics in an organism or tissue sample without damaging its original form, or even the possibility of detection in living organisms.

Antioxidative properties and macrochemical composition of five commercial mungbean varieties in Australia

AbstractMungbeans are growing in popularity among Australian consumers, driven by their beneficial nutritional and phytochemical composition. However, data on the antioxidative, mineral, and phytochemical content of Australian mungbeans at the point of consumer purchase remains scarce. Here, five commercial mungbean samples were analysed for total antioxidant capacity, total phenolics, and total monomeric anthocyanins. Attenuated total reflectance midinfrared spectroscopy was utilised as a rapid and reliable method of obtaining information about the macrochemical composition of the mungbean hulls. Total antioxidant capacity ranged from 170 to 570 mg Trolox equivalents per 100 g, total phenolic content from 130 to 240 mg gallic acid equivalents per 100 g, and anthocyanin content from 10 to 40 mg cyanidin‐3‐glucoside equivalents per 100 g. There was a significant difference between varieties in all measures of antioxidant, phenolic and anthocyanin contents. Using principal component analysis, the midinfrared spectra for the five mungbean varieties could be isolated, highlighting the differences in their phytochemical composition. In general, whole Australian mungbeans appear to have the highest antioxidant, phenolic, and anthocyanin contents. Midinfrared spectroscopy appears to be a valuable method of obtaining and comparing the macrochemical composition of mungbeans. This technology is likely to be of increasing use in the future.

Authentication of cocoa bean shells by near- and mid-infrared spectroscopy and inductively coupled plasma-optical emission spectroscopy

The aim of this study was to evaluate the efficacy of a multi-analytical approach for origin authentication of cocoa bean shells (CBS). The overall chemical profiles of CBS from different origins were characterized using diffuse reflectance near-infrared spectroscopy (NIRS) and attenuated total reflectance mid-infrared spectroscopy (ATR-FT-IR) for molecular composition identification, as well as inductively coupled plasma-optical emission spectroscopy (ICP-OES) for elemental composition identification. Exploratory chemometric techniques based on Principal Component Analysis (PCA) were applied to each single technique for the identification of systematic patterns related to the geographical origin of samples. A combination of the three techniques proved to be the most promising approach to establish classification models. Partial Least Squares-Discriminant Analysis modelling of fused PCA scores of three independent models was used and compared with single technique models. Improved classification of CBS samples was obtained using the fused model. Satisfactory classification rates were obtained for Central African samples with an accuracy of 0.84.