Excitation wavelength selection for quantitative analysis of carotenoids in tomatoes using Raman spectroscopy

Comprehensive experimental and computational analysis of endemic Allium tuncelianum: Phytochemical profiling, antimicrobial activity, and In silico studies for potential therapeutic applications

Allium tuncelianum (TG), an endemic garlic species from Tunceli, Turkey, was investigated using a multidisciplinary approach combining experimental and computational methods. Density Functional Theory (DFT) calculations with B3LYP/def2-SVP/def2-TZVP basis sets were employed to analyze electronic properties, reactivity, and stability under gas and ethanol conditions. Headspace/GC-MS identified 10 major components, with diallyl disulfide (48.03 %) and 1-propene (20.72 %) as predominant. Antimicrobial assays revealed potent activity against MRSA, Salmonella paratyphi A, and E. coli, with MIC values as low as 0.063 mg/mL. Antioxidant capacity, evaluated via DPPH, metal chelating, and FRAP assays, showed promising results, with the water extract exhibiting the highest activity (1.74 mg BHT equivalent/mL). DFT and molecular docking studies highlighted key compounds as potential inhibitors of E. coli Gyrase B, with binding energies of -5.68 and -6.07 kcal/mol. ADME predictions indicated favorable drug-like properties, though some compounds showed potential CYP450 interactions and toxicity. This study provides a comprehensive understanding of TG's biochemical profile and therapeutic potential, offering insights for future research and optimization.

Comparison of excitation wavelengths in surface-enhanced Raman spectroscopy coupled to thin-layer chromatography for tadalafil and vardenafil detection as adulterants in herbal healthcare products

Phosphodiesterase-5 inhibitors (PDE5Is) are frequently adulterated into dietary supplements and herbal healthcare products, in which sildenafil, vardenafil and tadalafil are commonly found. In our previous study, a thin layer chromatography coupled to surface-enhanced Raman spectroscopy (TLC-SERS) method was developed for the detection of sildenafil in herbal products. In the current study, TLC-SERS was further explored for the detection of vardenafil and tadalafil in herbal products. The performances of TLC-SERS using two excitation wavelengths, 633 nm and 785 nm, were also compared for the analysis of these compounds. With the chosen wavelengths of 633 nm for vardenafil and 785 nm for tadalafil, other factors influencing the selectivity and sensitivity of the TLC-SERS method were also optimized. The methods at the chosen analytical conditions were validated and applied to twenty-four real market samples. Two samples were found positive for PDE5Is, and both were adulterated with multiple compounds: one positive for vardenafil and tadalafil and one positive for sildenafil and tadalafil. Parallel analysis by an LC-MS/MS method resulted in the same findings, validating the feasibility of the developed TLC-SERS method.

Quantitative analysis of β-carotene and unsaturated fatty acids in blended olive oil via Raman spectroscopy combined with model prediction

Blended vegetable oil is considered to be a valuable product in the market owing to favourable taste and nutritional composition. The quantification of its contents has notable implications for protecting food safety and consumer interests. Thus, a rapid and non-destructive method is needed to analyse the composition of blended oil. This study established an analytical method combining Raman spectroscopy and prediction models to determine the content of olive oil in a mixture. Competitive adaptive reweighted sampling was employed to select feature bands attributed to β-carotene and unsaturated fatty acids. Various models were used to calculate the mixture proportion, and the importance of characteristic peak intensity affecting the prediction was evaluated via grey relational analysis. The random forest model exhibited superior performance in quantitative analysis, with RMSE and R2 of 0.0447 and 0.9799, respectively. Overall, this approach was proven to effectively identify blended olive oils, exemplifying its potential in food authentication.

Carotenoids in Paprika Fruits and Ajvar: Chemical Characterization and Biological Activity

In this study, carotenoids from four different paprika genotypes were analyzed at various maturation stages, as well as in Ajvar, a traditional Balkan product made from fully matured roasted paprika fruits. For this purpose, the HPTLC analytical method was used, and five dominant carotenoids were analyzed: β-carotene, lutein, zeaxanthin, capsanthin, and β-cryptoxanthin. Additionally, total carotenoids were analyzed spectrophotometrically, antioxidant capacity was determined, and their bioavailability was assayed using in vitro digestion. Finally, Raman spectroscopy, a non-destructive analytical method, was used to estimate the total carotenoid content. The results showed that the amount of all investigated carotenoids is the highest in the final maturity stage (0.38 g/100 g DM to 1.55 g/100 g DM). On the other hand, the lowest concentration of all investigated carotenoids was detected at the first stage of maturation, ranging from 0.01 g/100 g DM to 0.25 g/100 g DM. However, the analysis of carotenoid content in Ajvar showed a tendency for a decrease in concentration compared to their quantity in fresh fruits, although this was also dependent on the genotype (1.9-66.98% according to HPTLC results and 16.14-82.36% according to spectrophotometry). Antioxidant tests indicated an increase in antioxidant capacity with the ripening of paprika fruits, confirming the role of carotenoids as compounds capable of neutralizing harmful oxygen species (DPPH ranged from 0.21 to 1.50 µmol/g TEAC, CUPRAC ranged from 0.185 to 0.297 mg AsA/g DM, FRP ranged from 9.33 to 25.66 mg AsA/g DM). Quantification of total carotenoids by Raman spectroscopy showed that results were highly correlated with those obtained by HPTLC and the spectrophotometric method, highlighting the potential of Raman spectroscopy for carotenoid quantification. Based on the obtained results, it can be concluded that the traditional product Ajvar represents an important source of carotenoids, which are preserved after heat treatment with high biological activity relative to the final ripening stage of the paprika. Furthermore, the bioavailability of carotenoids from Ajvar is significantly higher compared to the results from fresh paprika analysis.

Research Progress on Methods for Improving the Stability of Non-Destructive Testing of Agricultural Product Quality

Non-destructive testing (NDT) technology is pivotal in the quality assessment of agricultural products. In contrast to traditional manual testing, which is fraught with subjectivity, inefficiency, and the potential for sample damage, NDT technology has gained widespread application due to its advantages of objectivity, speed, and accuracy, and it has injected significant momentum into the intelligent development of the food industry and agriculture. Over the years, technological advancements have led to the development of NDT systems predicated on machine vision, spectral analysis, and bionic sensors. However, during practical application, these systems can be compromised by external environmental factors, the test samples themselves, or by the degradation and noise interference inherent in the testing equipment, leading to instability in the detection process. This instability severely impacts the accuracy and efficiency of the testing. Consequently, refining the detection methods and enhancing system stability have emerged as key focal points for research endeavors. This manuscript presents an overview of various prevalent non-destructive testing methodologies, summarizes how sample properties, external environments, and instrumentation factors affect the stability of testing in practical applications, organizes and analyzes solutions to enhance the stability of non-destructive testing of agricultural product quality based on current research, and offers recommendations for future investigations into the non-destructive testing technology of agricultural products.

Alterations in lipid metabolism accompanied by changes in protein and carotenoid content as spectroscopic markers of human T cell activation

This work aims to understand better the mechanism of cellular processes accompanying the activation of human T cells and to develop a novel, fast, label-free approach to identify molecular biomarkers for this process. The standard methodology for confirming the activation state of T cells is based on flow cytometry and using antibodies recognizing activation markers. The method provide high specificity detection but may be susceptible to background staining or non-specific secondary antibody reactions. Here, we evaluated the potential of Raman-based molecular imaging in distinguishing non-activated and activated human T cells. Confocal Raman microscopy was performed on T cells followed by chemometrics to obtain comprehensive molecular information, while Stimulated Raman Scattering imaging was used to quickly provide high-resolution images of selected cellular components of activated and non-activated cells. For the first time, carotenoids, lipids, and proteins were shown to be important biomarkers of T-cell activation. We found that T-cell activation was accompanied by lipid accumulation and loss of carotenoid content. Our findings on the biochemical, morphological, and structural changes associated with activated mature T cells provide insights into the molecular changes that occur during therapeutic manipulation of the immune response. The methodology for identifying activated T cells is based on a novel imaging method and supervised and unsupervised chemometrics. It unambiguously identifies specific and unique molecular changes without the need for staining, fixation, or any other sample preparation.

A review on mechanisms and impacts of cold plasma treatment as a non-thermal technology on food pigments

Food characteristics like appearance and color, which are delicate parameters during food processing, are important determinants of product acceptance because of the growing trend toward more diverse and healthier diets worldwide, as well as the increase in population and its effects on food consumption. Cold plasma (CP), as a novel technology, has marked a new trend in agriculture and food processing due to the various advantages of meeting both the physicochemical and nutritional characteristics of food products with minimal changes in physical, chemical, nutritional, and sensorial properties. CP processing has a positive impact on food quality, including the preservation of natural food pigments. This article describes the influence of CP on natural food pigments and color changes in vegetables and fruits. Attributes of natural pigments, such as carotenoids, chlorophyll, anthocyanin, betalain, and myoglobin, are presented. In addition, the characteristics and mechanisms of CP processes were studied, and the effect of CP on mentioned pigments was investigated in recent literature, showing that the use of CP technology led to better preservation of pigments, improving their preservation and extraction yield. While certain modest and undesirable changes in color are documented, overall, the exposure of most food items to CP resulted in minor loss and even beneficial influence on color. More study is needed since not all elements of CP treatment are currently understood. The negative and positive effects of CP on natural food pigments in various products are discussed in this review.

In situ Raman characterization of the stability of blueberry anthocyanins in aqueous solutions under perturbations in temperature, UV, pH

Blueberry anthocyanin (BA) is a functional ingredient to enhance the biological activity of food, and the stability of BA is of great interest. BA stability in aqueous solutions stored in polypropylene and glass bottles was analyzed in-situ using confocal Raman spectroscopy, and the acceptable depth of focus was optimized. The Raman characteristics of BA degradation were explained by multivariate analysis. The degradation rate of BA was significantly accelerated by heating above 65 °C for 2 h or ultraviolet irradiation (10 W) for 96 h. The first order kinetic reaction rate was accelerated with the increase of pH value and temperature and the prolongation of ultraviolet irradiation time. The synergistic effect of multiple factors promoted BA degradation. This study provides an in-situ, nondestructive method for the analysis of anthocyanin stability, which has great utility in the food industry to optimize processing, storage, and transportation measures to reduce the degradation of BA.

Comparative study of Raman spectroscopy techniques in blood plasma-based clinical diagnostics: A demonstration on Alzheimer's disease

Nowadays, there are still many diseases with limited or no reliable methods of early diagnosis. A popular approach in clinical diagnostic research is Raman spectroscopy, as a relatively simple, cost-effective, and high-throughput method for searching for disease-specific alterations in the composition of blood plasma. However, the high variability of the experimental designs, targeted diseases, or statistical processing in the individual studies makes it challenging to compare and compile the results to critically assess the applicability of Raman spectroscopy in real clinical practice. This study aimed to compare data from a single series of blood plasma samples of patients with Alzheimer's disease and non-demented elderly controls obtained by four different techniques/experimental setups - Raman spectroscopy with excitation at 532 and 785 nm, Raman optical activity, and surface-enhanced Raman scattering spectroscopy. The obtained results showed that the spectra from each Raman spectroscopy technique contain different information about biomolecules of blood plasma or their conformation and may, therefore, offer diverse points of view on underlying biochemical processes of the disease. The classification models based on the datasets generated by the three non-chiroptical variants of Raman spectroscopy exhibited comparable diagnostic performance, all reaching an accuracy close to or equal to 80%. Raman optical activity achieved only 60% classification accuracy, suggesting its limited applicability in the specific case of Alzheimer's disease diagnostics. The described differences in the outputs of the four utilized techniques/setups of Raman spectroscopy imply that their choice may crucially affect the acquired results and thus should be approached carefully concerning the specific purpose.

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review

The quality of tropical fruits and vegetables and the expanding global interest in eating healthy foods have resulted in the continual development of reliable, quick, and cost-effective quality assurance methods. The present review discusses the advancement of non-destructive spectral measurements for evaluating the quality of major tropical fruits and vegetables. Fourier transform infrared (FTIR), Near-infrared (NIR), Raman spectroscopy, and hyperspectral imaging (HSI) were used to monitor the external and internal parameters of papaya, pineapple, avocado, mango, and banana. The ability of HSI to detect both spectral and spatial dimensions proved its efficiency in measuring external qualities such as grading 516 bananas, and defects in 10 mangoes and 10 avocados with 98.45%, 97.95%, and 99.9%, respectively. All of the techniques effectively assessed internal characteristics such as total soluble solids (TSS), soluble solid content (SSC), and moisture content (MC), with the exception of NIR, which was found to have limited penetration depth for fruits and vegetables with thick rinds or skins, including avocado, pineapple, and banana. The appropriate selection of NIR optical geometry and wavelength range can help to improve the prediction accuracy of these crops. The advancement of spectral measurements combined with machine learning and deep learning technologies have increased the efficiency of estimating the six maturity stages of papaya fruit, from the unripe to the overripe stages, with F1 scores of up to 0.90 by feature concatenation of data developed by HSI and visible light. The presented findings in the technological advancements of non-destructive spectral measurements offer promising quality assurance for tropical fruits and vegetables.

Current Application of Advancing Spectroscopy Techniques in Food Analysis: Data Handling with Chemometric Approaches

In today's era of increased food consumption, consumers have become more demanding in terms of safety and the quality of products they consume. As a result, food authorities are closely monitoring the food industry to ensure that products meet the required standards of quality. The analysis of food properties encompasses various aspects, including chemical and physical descriptions, sensory assessments, authenticity, traceability, processing, crop production, storage conditions, and microbial and contaminant levels. Traditionally, the analysis of food properties has relied on conventional analytical techniques. However, these methods often involve destructive processes, which are laborious, time-consuming, expensive, and environmentally harmful. In contrast, advanced spectroscopic techniques offer a promising alternative. Spectroscopic methods such as hyperspectral and multispectral imaging, NMR, Raman, IR, UV, visible, fluorescence, and X-ray-based methods provide rapid, non-destructive, cost-effective, and environmentally friendly means of food analysis. Nevertheless, interpreting spectroscopy data, whether in the form of signals (fingerprints) or images, can be complex without the assistance of statistical and innovative chemometric approaches. These approaches involve various steps such as pre-processing, exploratory analysis, variable selection, regression, classification, and data integration. They are essential for extracting relevant information and effectively handling the complexity of spectroscopic data. This review aims to address, discuss, and examine recent studies on advanced spectroscopic techniques and chemometric tools in the context of food product applications and analysis trends. Furthermore, it focuses on the practical aspects of spectral data handling, model construction, data interpretation, and the general utilization of statistical and chemometric methods for both qualitative and quantitative analysis. By exploring the advancements in spectroscopic techniques and their integration with chemometric tools, this review provides valuable insights into the potential applications and future directions of these analytical approaches in the food industry. It emphasizes the importance of efficient data handling, model development, and practical implementation of statistical and chemometric methods in the field of food analysis.

Raman spectroscopy in crop quality assessment: focusing on sensing secondary metabolites: a review

As a crop quality sensor, Raman spectroscopy has been consistently proposed as one of the most promising and non-destructive methods for qualitative and quantitative analysis of plant substances, because it can measure molecular structures in a short time without requiring pretreatment along with simple usage. The sensitivity of the Raman spectrum to target chemicals depends largely on the wavelength, intensity of the laser power, and exposure time. Especially for plant samples, it is very likely that the peak of the target material is covered by strong fluorescence effects. Therefore, methods using lasers with low energy causing less fluorescence, such as 785 nm or near-infrared, are vigorously discussed. Furthermore, advanced techniques for obtaining more sensitive and clear spectra, like surface-enhanced Raman spectroscopy, time-gated Raman spectroscopy or combination with thin-layer chromatography, are being investigated. Numerous interpretations of plant quality can be represented not only by the measurement conditions but also by the spectral analysis methods. Up to date, there have been attempted to optimize and generalize analysis methods. This review summarizes the state of the art of micro-Raman spectroscopy in crop quality assessment focusing on secondary metabolites, from in vitro to in vivo and even in situ, and suggests future research to achieve universal application.

Place & Play SERS: sample collection and preparation-free surface-enhanced Raman spectroscopy

The ability to perform sensitive, real-time, in situ, multiplex chemical analysis is indispensable for diverse applications such as human health monitoring, food safety testing, forensic analysis, environmental sensing, and homeland security. Surface-enhanced Raman spectroscopy (SERS) is an effective tool to offer the ability by virtue of its high sensitivity and rapid label-free signal detection as well as the availability of portable Raman spectrometers. Unfortunately, the practical utility of SERS is limited because it generally requires sample collection and preparation, namely, collecting a sample from an object of interest and placing the sample on top of a SERS substrate to perform a SERS measurement. In fact, not all analytes can satisfy this requirement because the sample collection and preparation process may be undesirable, laborious, difficult, dangerous, costly, or time-consuming. Here we introduce "Place & Play SERS" based on an ultrathin, flexible, stretchable, adhesive, biointegratable gold-deposited polyvinyl alcohol (PVA) nanomesh substrate that enables placing the substrate on top of an object of interest and performing a SERS measurement of the object by epi-excitation without the need for touching, destroying, and sampling it. Specifically, we characterized the sensitivity of the gold/PVA nanomesh substrate in the Place & Play SERS measurement scheme and then used the scheme to conduct SERS measurements of both wet and dry objects under nearly real-world conditions. To show the practical utility of Place & Play SERS, we demonstrated two examples of its application: food safety testing and forensic analysis. Our results firmly verified the new measurement scheme of SERS and are expected to extend the potential of SERS by opening up untapped applications of sensitive, real-time, in situ multiplex chemical analysis.

One drop only. Easy and rapid Raman evaluation of β-carotene in olive oil and its relevance as an index of olive fly attack

This paper presents, for the first time, a method for the rapid quantification of β-carotene in olive oil by Raman spectroscopy. Using a 532 nm Raman laser source, our procedure requires only one drop (100 µL) of oil, for β-carotene content to be determined. Results show that β-carotene content is associated with the lutein/β-carotene ratio, a parameter whose value describes how healthy the olives were before processing, specifically whether an olive fly attack occurred. Since olive fly attacks are not always visible to the oil producers, this method gives them the means to control the validity of the prevention strategies they adopted.

Confocal Raman spectroscopy at different laser wavelengths in analyzing stratum corneum and skin penetration properties of mixed PEGylated emulsifier systems

Emulsifier mixtures are widely used in cosmetics and pharmaceutics and thus, brought extensive studies for their performances on skin applications. PEG-20cetyl ether (C20) is recently proposed to induce skin irritation and is of interest to study its skin interactions when mixed with other emulsifiers. PEG-2oleyl ether (O2) and PEG-20stearyl ether (S20) are selected and in specific, 50 mM of C20, O2, S20 as well as Mix1 (50 mM C20 mixed with 50 mM O2) and Mix2 (50 mM C20 mixed with 50 mM S20) solutions were applied on skin samples. Confocal Raman spectroscopy (CRS) analyses of stratum corneum (SC) thickness and SC lipid content were performed after 4 h skin treatments. In parallel, skin penetration properties were also evaluated via CRS by applying procaine solutions with/without emulsifiers on skin samples for 24 h. In terms of the CRS measurements, two excitation wavelengths of 532 nm and 785 nm are both utilized in this study and we secondly aimed to compare their results and suitability in SC and skin analyses. Based on the experimental observations, comparable results are obtained by using both excitation wavelengths of 532 nm and 785 nm demonstrating their suitability in analyzing SC and skin samples. Thereinto, 785 nm laser wavelength shows the advantage of deeper skin penetration and allows the measurements of fluorescent skin samples; 532 nm laser wavelength enables simple measurement performance without substrate and coverslip interference. With regards to the results of emulsifier mixtures, the addition of S20 and O2 reduced the skin interactions and penetration enhancing ability of C20, giving us the hint to build milder systems with emulsifier mixtures. Besides, the CRS results of stronger skin interruption were also correlated with the higher critical micelle concentration (CMC) values of emulsifiers and their mixtures, which may provide evidence in explaining the interactions between emulsifiers and skin.

Insights on the role of chemometrics and vibrational spectroscopy in fruit metabolite analysis

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The use of vibrational spectroscopy combined with data analytics is discussed.

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The measure of bioactive compounds metabolites in fruit samples is presented.

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Advantages and limitations of these techniques are discussed.

The last three decades have demonstrated the ability of combining data analytics (e.g. big data, machine learning) with modern analytical instrumental techniques such as vibrational spectroscopy (VIBSPEC) (e.g. NIR, Raman, MIR) and sensing technologies (e.g. electronic noses and tongues, colorimetric sensors) to analyse, measure and monitor a wide range of properties and samples. Developments in instrumentation, hardware and software have placed VIBSPEC as a useful tool to quantify several bioactive compounds and metabolites in a wide range of fruit and plant samples. With the incorporation of hand-held and portable instrumentation, these techniques have been valuable for the development of in-field and high throughput applications, opened new frontiers of analysis in fruits and plants. This review will present and discuss some of the current applications on the use of VIBSPEC techniques combined with data analytics on the measurement bioactive compounds and plant metabolites in different fruit samples.

Recognition of chronic renal failure based on Raman spectroscopy and convolutional neural network

PURPOSE

Chronic renal failure (CRF) is a disease with a high morbidity rate that can develop into uraemia, resulting in a series of complications, such as dyspnoea, mental disorders, hypertension, and heart failure. CRF may be controlled clinically by drug intervention. Therefore, early diagnosis and control of the disease are of great significance for the treatment and prevention of chronic renal failure. Based on the complexity of CRF diagnosis, this study aims to explore a new rapid and noninvasive diagnostic method.

METHODS

In this experiment, the serum Raman spectra of samples from 47 patients with CRF and 53 normal subjects were obtained. In this study, Serum Raman spectra of healthy and CRF patients were identified by a Convolutional Neural Network (CNN) and compared with the results of identified by an Improved AlexNet. In addition, different amplitude of noise were added to the spectral data of the samples to explore the influence of a small random noise on the experimental results.

RESULTS

A CNN and an Improved AlexNet was used to classify the spectra, and the accuracy was 79.44 % and 95.22 % respectively. And the addition of noise did not significantly interfere with the classification accuracy.

CONCLUSION

The accuracy of CNN of this study can be as high as 95.22 %, which greatly improves its accuracy and reliability, compared to 89.7 % in the previous study. The results of this study show that the combination of serum Raman spectrum and CNN can be used in the diagnosis of CRF, and small random noise will not cause serious interference to the data analysis results.

Effect of Raman exposure time on the quantitative and discriminant analyses of carotenoid concentrations in intact tomatoes

The significant worldwide expansion of the health food market, which includes functional fruits and vegetables, requires a simple and rapid analytical method for the on-site analysis of functional components, such as carotenoids, in fruits and vegetables, and Raman spectroscopy is a powerful candidate. Herein, we clarified the effects of Raman exposure time on quantitative and discriminant analysis accuracies. Raman spectra of intact tomatoes with various carotenoid concentrations were acquired and used to develop partial least squares regression (PLSR) and partial least squares discriminant analysis (PLS-DA) models. The accuracy of the PLSR model was superior (R² = 0.87) when Raman spectra were acquired 10 s, but decreased with decreasing exposure time (R² = 0.69; 0.7 s). The accuracy of the PLS-DA model was unaffected by exposure time (hit rate: 90%). We conclude that Raman spectroscopy combined with PLS-DA is useful for the on-site analysis of carotenoids in fruits and vegetables.

Can Coupling Multiple Complementary Methods Improve the Spectroscopic Based Diagnosis of Gastrointestinal Illnesses? A Proof of Principle Ex Vivo Study Using Celiac Disease as the Model Illness

Spectroscopic methods are a promising approach for providing a point-of-care diagnostic method for gastrointestinal mucosa associated illnesses. Such a tool is desired to aid immediate decision making and to provide a faster pathway to appropriate treatment. In this pilot study, Raman, near-infrared, low frequency Raman, and autofluoresence spectroscopic methods were explored alone and in combination for the diagnosis of celiac disease. Duodenal biopsies (n = 72) from 24 participants were measured ex vivo using the full suite of studied spectroscopic methods. Exploratory principal component analysis (PCA) highlighted the origin of spectral differences between celiac and normal tissue with celiac biopsies tending to have higher protein relative to lipid signals and lower carotenoid spectral signals than the samples with normal histology. Classification of the samples based on the histology and overall diagnosis was carried out for all combinations of spectroscopic methods. Diagnosis based classification (majority rule of class per participant) yielded sensitivities of 0.31 to 0.77 for individual techniques, which was increased up to 0.85 when coupling multiple techniques together. Likewise, specificities of 0.50 to 0.67 were obtained for individual techniques, which was increased up to 0.78 when coupling multiple techniques together. It was noted that the use of antidepressants contributed to false positives, which is believed to be associated with increased serotonin levels observed in the gut mucosa in both celiac disease and the use of selective serotonin reuptake inhibitors (SSRIs); however, future work with greater numbers is required to confirm this observation. Inclusion of two additional spectroscopic methods could improve the accuracy of diagnosis (0.78) by 7% over Raman alone (0.73). This demonstrates the potential for further exploration and development of a multispectroscopic system for disease diagnosis.

A Four-Level Maturity Index for Hot Peppers (Capsicum annum) Using Non-Invasive Automated Mobile Raman Spectroscopy for On-Site Testing

A handheld Raman spectrometer was used to determine the ripeness of peppers. Raman spectra were recorded non-invasively on the fruit surface. The spectroscopic data were transformed into a classification scheme referred to as the maturity index which allowed for attribution of the fruit stadium to four levels from immature to fully mature. Hot pepper and tomato ripening includes pectic polysaccharide depolymerization, chlorophyll degradation and carotenoid formation, among others. The latter were followed non-invasively by Raman spectroscopy. Two portable systems and one benchtop system were compared for their applicability and robustness to establish a suitable maturity index. Spectral acquisition, data treatment and multivariate data analysis were automated using a Matlab script on a laptop computer. The automated workflow provided a graphic visualization of the relevant parameters and results on-site in real time. In terms of reliability and applicability, the chemometric model to determine the maturity of fruits was compared to a univariate procedure based on the average intensity and ratio of three characteristic signals. Portable Raman spectrometers in combination with the maturity index or a chemometric model should be suitable to assess the stage of maturing for carotenoid-containing fruits and thus to determine ripeness on-site or during a sorting process in an automated manner.

Raman spectroscopy: A rapid method to assess the effects of pasture feeding on the nutritional quality of butter

The animal diet is a critical variable affecting the composition and functionality of dairy products. As "Grass-Fed" labeling becomes more prominent on the market, rapid and label-free methods for verification of feeding systems are required. This work proposes the use of Raman spectroscopy to study the effects of 3 different experimental cow feeding systems-perennial ryegrass pasture, perennial ryegrass with white clover pasture, and an indoor total mixed ration diet (TMR)-on the nutritional quality of sweet cream butter. The results demonstrate that Raman spectroscopy coupled with multivariate analysis is a promising approach to distinguish butter derived from pasture or conventional TMR feeding systems. A Pearson correlation analysis confirmed high positive correlations between the spectral bin at 1,657 cm^-1, ascribed to the stretching vibrations of C=C bonds, and concentrations of α-linolenic acid and conjugated linolenic acid (CLA) in butter, and in general with the concentration of n-3 and n-3+CLA fatty acids and polyunsaturated fatty acids in the samples. The yellow color indicative of the presence of carotenoids in butter, which has previously been suggested as a biomarker of pasture or "Grass-Fed" feeding, was also positively correlated with the data obtained from the Raman spectra. Raman spectroscopy could also be used to accurately predict indicators of the nutritional quality of butter, such as the thrombogenic index, which showed a strong negative correlation with the spectral bin at 3,023 cm^-1.

High-Throughput Phenotyping Approach for Screening Major Carotenoids of Tomato by Handheld Raman Spectroscopy Using Chemometric Methods

Our objective was to develop a rapid technique for the non-invasive profiling and quantification of major tomato carotenoids using handheld Raman spectroscopy combined with pattern recognition techniques. A total of 106 samples with varying carotenoid profiles were provided by the Ohio State University Tomato Breeding and Genetics program and Lipman Family Farms (Naples, FL, USA). Non-destructive measurement from the surface of tomatoes was performed by a handheld Raman spectrometer equipped with a 1064 nm excitation laser, and data analysis was performed using soft independent modelling of class analogy (SIMCA)), artificial neural network (ANN), and partial least squares regression (PLSR) for classification and quantification purposes. High-performance liquid chromatography (HPLC) and UV/visible spectrophotometry were used for profiling and quantification of major carotenoids. Seven groups were identified based on their carotenoid profile, and supervised classification by SIMCA and ANN clustered samples with 93% and 100% accuracy based on a validation test data, respectively. All-trans-lycopene and β-carotene levels were measured with a UV-visible spectrophotometer, and prediction models were developed using PLSR and ANN. Regression models developed with Raman spectra provided excellent prediction performance by ANN (r_pre = 0.9, SEP = 1.1 mg/100 g) and PLSR (r_pre = 0.87, SEP = 2.4 mg/100 g) for non-invasive determination of all-trans-lycopene in fruits. Although the number of samples were limited for β-carotene quantification, PLSR modeling showed promising results (r_cv = 0.99, SECV = 0.28 mg/100 g). Non-destructive evaluation of tomato carotenoids can be useful for tomato breeders as a simple and rapid tool for developing new varieties with novel profiles and for separating orange varieties with distinct carotenoids (high in β-carotene and high in cis-lycopene).

A facile water-induced complexation of lycopene and pectin from pink guava byproduct: Extraction, characterization and kinetic studies

The redfleshed pulp discarded from pink guava puree industry is a rich source of lycopene and pectin. In this study, we developed a facile extraction process employing water as the primary extraction medium to isolate the lycopene and pectin from pink guava decanter. When the decanter was suspended in water, the complexation of lycopene and pectin formed the cloudy solution, where the colloidal complexes were recovered through centrifugation. The presence of lycopene and pectin in the complex was confirmed by the spectroscopic, microscopic and chromatographic analyses. The lycopene fractionated from the complexes had a purity level of 99% and was in all-trans configuration. The colloidal complexes yielding the highest concentration of lycopene was obtained at pH 7, 1% (w/v) solid loading and 25 °C. The experimental data of time-course extraction of lycopene-pectin complex were best fitted with two-site kinetic model, hinting the fast- and slow-release phases in the extraction process.