Conjugation of lesser mealworm (Alphitobius diaperinus) larvae protein with polyphenols for the development of innovative antioxidant emulsifiers

Lesser mealworm protein concentrate (LMPC) was conjugated with chlorogenic acid (CA) or tannic acid (TA) using an alkaline method. The impact of polyphenol type and concentration on the physicochemical and structural characteristics, antioxidant, interfacial, and emulsifying properties of the LMPC-polyphenol conjugates were investigated. Under the conditions tested, TA demonstrated higher affinity for LMPC compared to CA. The conjugation of LMPC induced conformational changes as showed by intrinsic fluorescence and FT-MIR raw spectra analysis. The surface hydrophobicity of the conjugates was reduced, leading to increased interfacial tension values for LMPC-TA conjugates without impairment of the emulsifying activity. The antioxidant properties were significantly improved by the conjugation. Flaxseed oil-in-water (O/W) emulsions stabilized by the conjugates and LMPC remained physically stable for 12 days at 50 °C with a notable reduction of secondary oxidation products when conjugates were used. LMPC-TA and LMPC-CA exhibited potential to be used as novel antioxidant emulsifiers in O/W emulsions.

Nondestructive and Rapid Screening of Aflatoxin-Contaminated Single Peanut Kernels Using Field-Portable Spectroscopy Instruments (FT-IR and Raman)

A nondestructive and rapid classification approach was developed for identifying aflatoxin-contaminated single peanut kernels using field-portable vibrational spectroscopy instruments (FT-IR and Raman). Single peanut kernels were either spiked with an aflatoxin solution (30 ppb-400 ppb) or hexane (control), and their spectra were collected via Raman and FT-IR. An uHPLC-MS/MS approach was used to verify the spiking accuracy via determining actual aflatoxin content on the surface of randomly selected peanut samples. Supervised classification using soft independent modeling of class analogies (SIMCA) showed better discrimination between aflatoxin-contaminated (30 ppb-400 ppb) and control peanuts with FT-IR compared with Raman, predicting the external validation samples with 100% accuracy. The accuracy, sensitivity, and specificity of SIMCA models generated with the portable FT-IR device outperformed the methods in other destructive studies reported in the literature, using a variety of vibrational spectroscopy benchtop systems. The discriminating power analysis showed that the bands corresponded to the C=C stretching vibrations of the ring structures of aflatoxins were most significant in explaining the variance in the model, which were also reported for Aspergillus-infected brown rice samples. Field-deployable vibrational spectroscopy devices can enable in situ identification of aflatoxin-contaminated peanuts to assure regulatory compliance as well as cost savings in the production of peanut products.

Monitoring Turkish white cheese ripening by portable FT-IR spectroscopy

The biochemical metabolism during cheese ripening plays an active role in producing amino acids, organic acids, and fatty acids. Our objective was to evaluate the unique fingerprint-like infrared spectra of the soluble fractions in different solvents (water-based, methanol, and ethanol) of Turkish white cheese for rapid monitoring of cheese composition during ripening. Turkish white cheese samples were produced in a pilot plant scale using a mesophilic culture (Lactococcus lactis subsp. lactis, Lactococcus lactis subsp. cremoris), ripened for 100 days and samples were collected at 20-day intervals for analysis. Three extraction solvents (water, methanol, and ethanol) were selected to obtain soluble cheese fractions. Reference methods included gas chromatography (amino acids and fatty acid profiles), and liquid chromatography (organic acids) were used to obtain the reference results. FT-IR spectra were correlated with chromatographic data using pattern recognition analysis to develop regression and classification predictive models. All models showed a good fit (R_Pre ≥ 0.91) for predicting the target compounds during cheese ripening. Individual free fatty acids were predicted better in ethanol extracts (0.99 ≥ R_Pre ≥ 0.93, 1.95 ≥ SEP ≥ 0.38), while organic acids (0.98 ≥ R_Pre ≥ 0.97, 10.51 ≥ SEP ≥ 0.57) and total free amino acids (R_Pre = 0.99, SEP = 0.0037) were predicted better by using water-based extracts. Moreover, cheese compounds extracted with methanol provided the best SIMCA classification results in discriminating the different stages of cheese ripening. By using a simple methanolic extraction and collecting spectra with a portable FT-IR device provided a fast, simple, and cost-effective technique to monitor the ripening of white cheese and predict the levels of key compounds that play an important role in the biochemical metabolism of Turkish white cheese.

Screening of Acrylamide of Par-Fried Frozen French Fries Using Portable FT-IR Spectroscopy

Current assays for acrylamide screening rely heavily on LC-MS/MS or GC-MS, techniques that are not suitable to support point of manufacturing verification because it can take several weeks to receive results from a laboratory. A portable sensor that can detect acrylamide levels in real-time would enable in-house testing to safeguard both the safety of the consumer and the economic security of the agricultural supplier. Our objective was to develop a rapid, accurate, and real-time screening technique to detect the acrylamide content in par-fried frozen French fries based on a portable infrared device. Par-fried French fries (n = 70) were manufactured at times ranging from 1 to 5.5 min at 180 °C to yield a wide range of acrylamide levels. Spectra of samples were collected using a portable FT-IR device operating from 4000 to 700 cm⁻¹. Acrylamide was extracted using QuEChERS and quantified using uHPLC-MS/MS. Predictive algorithms were generated using partial least squares regression (PLSR). Acrylamide levels in French fries ranged from 52.0 to 812.8 µg/kg. The best performance of the prediction algorithms required transformation of the acrylamide levels using a logarithm function with models giving a coefficient of correlation (Rcv) of 0.93 and RPD as 3.8, which means the mid-IR model can be used for process control applications. Our data corroborate the potential of portable infrared devices for acrylamide screening of high-risk foods.

Monitoring the ripening attributes of Turkish white cheese using miniaturized vibrational spectrometers

Monitoring the ripening process by prevalent analytic methods is laborious, expensive, and time consuming. Our objective was to develop a rapid and simple method based on vibrational spectroscopic techniques to understand the biochemical changes occurring during the ripening process of Turkish white cheese and to generate predictive algorithms for the determination of the content of key cheese quality and ripening indicator compounds. Turkish white cheese samples were produced in a pilot plant scale and ripened for 100 d, and samples were analyzed at 20 d intervals during storage. The collected spectra (Fourier-transform infrared, Raman, and near-infrared) correlated with major composition characteristics (fat, protein, and moisture) and primary products of the ripening process and analyzed by pattern recognition to generate prediction (partial least squares regression) and classification (soft independent analysis of class analogy) models. The soft independent analysis of class analogy models classified cheese samples based on the unique biochemical changes taking place during the ripening process. partial least squares regression models showed good correlation (R_Pre = 0.87 to 0.98) between the predicted values by vibrational spectroscopy and the reference values, giving low standard errors of prediction (0.01 to 0.57). Portable and handheld vibrational spectroscopy units can be used as a rapid, simple, and in situ technique for monitoring the quality of cheese during aging and provide real-time tools for addressing deviations in manufacturing.

Non-Invasive Monitoring of Ethanol and Methanol Levels in Grape-Derived Pisco Distillate by Vibrational Spectroscopy

Handheld Raman and portable FT-IR spectroscopy devices were evaluated for fast and non-invasive determination of methanol and ethanol levels in Peruvian Pisco. Commercial Peruvian Pisco (n = 171) samples were kindly provided by the UNALM Alliance for Research in Alcohol and its Derivatives (Lima, Peru) and supplemented by purchases at grocery and online stores. Pisco spectra were collected on handheld Raman spectrometers equipped with either a 1064 nm or a 785 nm excitation laser and a portable infrared unit operating in transmission mode. The alcohol levels were determined by GC-MS. Calibration models used partial least-squares regression (PLSR) to develop prediction algorithms. GC-MS data revealed that 10% of Pisco samples had ethanol levels lower than 38%, indicating possible water dilution. Methanol levels ranged from 10 to 130 mg/100 mL, well below the maximum levels allowed for fruit brandies. Handheld Raman equipped with a 1064 nm excitation laser gave the best results for determining ethanol (SEP = 1.2%; RPre = 0.95) and methanol (SEP = 1.8 mg/100 mL; RPre = 0.93). Randomly selected Pisco samples were spiked with methanol (75 to 2800 mg/100 mL), and their Raman spectra were collected through their genuine commercial bottles. The prediction models gave an excellent performance (SEP = 98 mg/100 mL; RPre = 0.97), allowing for the non-destructive and non-contact determination of methanol and ethanol concentrations without opening the bottles.

Application of Mid-Infrared Portable Spectrometer for the Rapid Determination of Trans-Fatty Acid Content in Lipid Extracts of Snack and Bakery Products

In 2015, the US Food and Drug Administration passed a ban on the "generally recognized as safe" status of partially hydrogenated oils (PHOs), and in June 2018, PHOs were prohibited from being used. Our objective was to develop a predictive model to quantify trans-fat concentrations in bakery and snacks products using a portable mid-infrared (MIR) spectrometer. The approach was tested using 24 calibration standards (consisting of trielaidin in triolein and tripalmitin) and 87 bakery and snack products ranging from ND to 65% trans-fat. The fat was extracted by grinding products into powders and extracting the fat using petroleum ether. Gas Chromatography (AOCS Cd 14c-94) was used to determine the fatty acid profile and trans-fat content. Spectra were acquired by directly placing the fat (200 μL) onto the heated (65 ± 1°C) 5-reflection ZnSe crystal of a portable MIR spectrometer. Partial least squares regression (PLSR) models were developed using the calibration standards and extracted fats spectra targeting the signal of the C-H out-of-plane deformation band at 966 cm-1. Best model performances were obtained using the spectra of the extracted fat from bakery and snack products with the standard error of prediction of 0.5 g of trans-fats per 100 g of fat. We found that 25% of products labeled as zero trans-fat/serving did not comply with the maximum tolerance levels based on GC-FAME analysis. Portable FTIR devices operating in attenuated total reflection (ATR) mode can provide the food industry and government food inspectors with rapid, accurate, and high throughput measurements for routine screening to facilitate regulatory compliance.

Non-Destructive Quality Assessment of Tomato Paste by Using Portable Mid-Infrared Spectroscopy and Multivariate Analysis

This research aims to provide simultaneous predictions of tomato paste's multiple quality traits without any sample preparation by using a field-deployable portable infrared spectrometer. A total of 1843 tomato paste samples were supplied by four different leading tomato processors in California, USA, over the tomato seasons of 2015, 2016, 2017, and 2019. The reference levels of quality traits including, natural tomato soluble solids (NTSS), pH, Bostwick consistency, titratable acidity (TA), serum viscosity, lycopene, glucose, fructose, ascorbic acid, and citric acid were determined by official methods. A portable FT-IR spectrometer with a triple-reflection diamond ATR sampling system was used to directly collect mid-infrared spectra. The calibration and external validation models were developed by using partial least square regression (PLSR). The evaluation of models was conducted on a randomly selected external validation set. A high correlation (RCV = 0.85-0.99) between the reference values and FT-IR predicted values was observed from PLSR models. The standard errors of prediction were low (SEP = 0.04-35.11), and good predictive performances (RPD = 1.8-7.3) were achieved. Proposed FT-IR technology can be ideal for routine in-plant assessment of the tomato paste quality that would provide the tomato processors with accurate results in shorter time and lower cost.

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).

Ex Vivo and In Vivo Assessment of the Penetration of Topically Applied Anthocyanins Utilizing ATR-FTIR/PLS Regression Models and HPLC-PDA-MS

Anthocyanins are natural colorants with antioxidant properties, shown to inhibit photoaging reactions and reduce symptoms of some skin diseases. However, little is known about their penetration through the stratum corneum, a prerequisite for bioactivity. The aim was to investigate anthocyanin penetration from lipophilic cosmetic formulations through the skin using a porcine ear model and human volunteers. ATR-FTIR/PLS regression and HPLC-PDA-MS were used to analyze anthocyanin permeation through the stratum corneum. Penetration of all anthocyanins was evident and correlated with molecular weight and hydrophilicity. Lower-molecular-weight (MW) anthocyanins from elderberry (449–581 Da) were more permeable within the skin in both ex vivo and in vivo models (K_p = 2.3–2.4 × 10⁻⁴ cm h⁻¹) than the larger anthocyanins (933-1019 Da) from red radish (K_p = 2.0–2.1 × 10⁻⁴ cm h⁻¹). Elderberry and red radish anthocyanins were found at all levels of the stratum corneum and at depths for activity as bioactive ingredients for skin health.

Direct Determination of Lycopene Content in Tomatoes (Lycopersicon esculentum) by Attenuated Total Reflectance Infrared Spectroscopy and Multivariate Analysis

Lycopene is a potent antioxidant that has been shown to play critical roles in disease prevention. Efficient assays for detection and quantification of lycopene are desirable as alternatives to time- and labor-intensive methods. Attenuated total reflectance infrared (ATR-IR) spectroscopy was used for quantification of lycopene in tomato varieties. Calibration models were developed by partial least-squares regression (PLSR) using quantitative measures of lycopene concentration from liquid chromatography as reference method. IR spectra showed a distinct marker band at 957 cm1 for trans Carbon-Hydrogen (CH) deformation vibration of lycopene. PLSR models predicted the lycopene content accurately and reproducibly with a correlation coefficient (σ) of 0.96 and standard error of cross-validation <0.80 mg/100 g. ATR-IR spectroscopy allowed for rapid, simple, and accurate determination of lycopene in tomatoes with minimal sample preparation. Results suggest that the ATR-IR method is applicable for high-throughput quantitative analysis and screening for lycopene in tomatoes.

Nutrient intake and balancing among female Colobus angolensis palliatus inhabiting structurally distinct forest areas: Effects of group, season, and reproductive state

Understanding intraspecific behavioral and dietary variation is critical for assessing primate populations' abilities to persist in habitats characterized by increasing anthropogenic disturbances. While it is evident that some species exhibit considerable dietary flexibility (in terms of species-specific plant parts) in relation to habitat disturbance, it is unclear if primates are characterized by similar variation and flexibility regarding nutrient intake. This study examined the effects of group, season, and reproductive state on nutrient intake and balancing in adult female Colobus angolensis palliatus in the Diani Forest, Kenya. During July 2014 to December 2015, estimates of nutrient intake were recorded for eight females from three groups inhabiting structurally and ecologically distinct forest areas differing in tree species composition and density. There were differences in metabolizable energy (ME) and macronutrient intakes among groups, seasons, and reproductive states. Most notably, females inhabiting one of the more disturbed forest areas consumed less ME and macronutrients compared to females in the more intact forest area. Contrary to prediction, females in early lactation consumed significantly less ME and macronutrients compared to non-lactating and late lactation females. Despite differences in macronutrient intake, the relative contribution of macronutrients to ME were generally more conservative among groups, seasons, and reproductive states. Average daily intake ratios of non-protein energy to available protein ranged from approximately 3.5:1-4.3:1 among groups. These results indicate that female C. a. palliatus demonstrate a consistent nutrient balancing strategy despite significant intergroup differences in consumption of species-specific plant parts. Data from additional colobine species inhabiting different forest types are required to assess the extent to which nutrient balancing is constrained by phylogeny or is more flexible to local ecological conditions.

Corrigendum: Identification of Quercus agrifolia (coast live oak) resistant to the invasive pathogen Phytophthora ramorum in native stands using Fourier-transform infrared (FT-IR) spectroscopy

[This corrects the article on p. 521 in vol. 5, PMID: 25352852.].

A pilot study of health and wellness coaching for fibromyalgia

BACKGROUND

The purpose of this study was to test the hypothesis that a health and wellness coaching (HWC)-based intervention for fibromyalgia (FM) would result in sustained improvements in health and quality of life, and reductions in health care utilization.

METHODS

Nine female subjects meeting American College of Rheumatology criteria for a diagnosis of primary FM were studied. The HWC protocol had two components, which were delivered telephonically over a twelve-month period. First, each patient met individually with a coach during the 12 month study at the patient's preference of schedule and frequency (Range:22-32 × 45-min sessions). Coaches were health professionals trained in health and wellness coaching tasks, knowledge, and skills. Second, each patient participated in bimonthly (first six months) and monthly (second six months) group classes on self-coaching strategies during the 12 month study. Prior to the intervention, and after 6 months and 12 months of coaching, the Revised Fibromyalgia Impact Questionnaire (FIQR) was used to measure health and quality of life, and the Brief Pain Inventory-Short Form (BPI) was used to measure pain intensity and interference with function. Total and rheumatology-related health encounters were documented using electronic medical records. Data were analyzed using repeated measures ANOVA.

RESULTS

All nine patients finished the HWC protocol. FIQR scores improved by 35 % (P = 0.001). BPI scores decreased by 32 % overall (P = 0.006), 31 % for severity (P = 0.02), and 44 % for interference (P = 0.006). Health care utilization declined by 86 % (P = 0.006) for total and 78 % (P < 0.0001) for rheumatology-related encounters.

CONCLUSION

The HWC program added to standard FM therapy produced clinically significant improvements in quality of life measures (FIQR), pain (BPI), and marked reductions in health care utilization. Such improvements do not typically occur spontaneously in FM patients, suggesting that HWC deserves further consideration as an intervention for FM.

Improving the screening of potato breeding lines for specific nutritional traits using portable mid-infrared spectroscopy and multivariate analysis

Efficient selection of potato varieties with enhanced nutritional quality requires simple, accurate and cost effective assays to obtain tuber chemical composition information. In this study, 75 Andean native potato samples from 7 Solanum species with different colors were characterized and quantified for their anthocyanin, phenolics and sugar content using traditional reference methods. IR (infrared) spectra of potato extracts were collected using a portable infrared system and partial least squares regression (PLSR) calibration models were developed. These models were validated using both full cross-validation and an independent sample set giving strong linear correlation coefficients of prediction (rPred)>0.91 and standard error of prediction (SEP) of 24mg/100g phenolics, 7mg/100g monomeric anthocyanins, 0.1g/100g reducing sugars and 0.12g/100g sucrose. Overall, portable infrared system with PLSR showed great potential to facilitate potato breeding and certain aspects of crop management, material selection for potato processing and related research by providing alternative prediction models.

Quantifying soluble carbohydrates in tropical leaves using a portable mid-infrared sensor: Implications for primate feeding ecology

Identifying the nutritional composition of food items has significant ramifications for primate feeding ecology, which, in turn, influences investigations of primate sociality, cognition, and conservation. The aim of our study was to analyze water soluble carbohydrate (WSC) concentrations in the leaves of trees common to the Diani Forest of Kenya. Many of these leaves are consumed by black and white colobus monkeys (Colobus angolensis palliatus). We assessed whether the infrared spectral data collected using a portable spectrometer can be used to accurately predict WSC concentrations. WSC content was first quantified using the phenol-sulfuric acid method for young and mature leaves of 24 species and ranged from 1.15% to 9.16% dry weight. Spectral data were recorded with a spectrometer equipped with an attenuated total reflectance accessory (Agilent Cary 630) and analyzed using partial least squares regression. The spectral region from 1600 cm(-1) to 1000 cm(-1) gave unique polysaccharide bands associated with carboxyl, acetyl, and glycosidic linkages of sugar residues. The multivariate analysis gave excellent performance parameters with correlation coefficient (r(2) ) of 0.95 and standard error of cross-validation of 0.6% WSC. We found that IR spectroscopy provides a rapid and accurate technique for analyzing WSC concentrations and offers primatologists many advantages over wet chemistry methods for analyzing nutritional composition. Am. J. Primatol. 78:701-706, 2016. © 2016 Wiley Periodicals, Inc.

Authentication of Whey Protein Powders by Portable Mid-Infrared Spectrometers Combined with Pattern Recognition Analysis

The objective of this study was to develop a simple and rapid method to differentiate whey protein types (WPC, WPI, and WPH) used for beverage manufacturing by combining the spectral signature collected from portable mid-infrared spectrometers and pattern recognition analysis. Whey protein powders from different suppliers are produced using a large number of processing and compositional variables, resulting in variation in composition, concentration, protein structure, and thus functionality. Whey protein powders including whey protein isolates, whey protein concentrates and whey protein hydrolysates were obtained from different suppliers and their spectra collected using portable mid-infrared spectrometers (single and triple reflection) by pressing the powder onto an Attenuated Total Reflectance (ATR) diamond crystal with a pressure clamp. Spectra were analyzed by soft independent modeling of class analogy (SIMCA) generating a classification model showing the ability to differentiate whey protein types by forming tight clusters with interclass distance values of >3, considered to be significantly different from each other. The major bands centered at 1640 and 1580 cm(-1) were responsible for separation and were associated with differences in amide I and amide II vibrations of proteins, respectively. Another important band in whey protein clustering was associated with carboxylate vibrations of acidic amino acids (∼1570 cm(-1)). The use of a portable mid-IR spectrometer combined with pattern recognition analysis showed potential for discriminating whey protein ingredients that can help to streamline the analytical procedure so that it is more applicable for field-based screening of ingredients.

PRACTICAL APPLICATION

A rapid, simple and accurate method was developed to authenticate commercial whey protein products by using portable mid-infrared spectrometers combined with chemometrics, which could help ensure the functionality of whey protein ingredients in food applications.

Application of a portable infrared instrument for simultaneous analysis of sugars, asparagine and glutamine levels in raw potato tubers

The level of reducing sugars and asparagine in raw potatoes is critical for potato breeders and the food industry for production of commonly consumed food products including potato chips and French fries. Our objective was to evaluate the use of a portable infrared instrument for the rapid quantitation of major sugars and amino acids in raw potato tubers using single-bounce attenuated total reflectance (ATR) and dial path accessories as an alternative to time-consuming chromatographic techniques. Samples representing a total of 84 experimental and commercial potato varieties harvested in two consecutive growing seasons (2012 and 2013) were used in this study. Samples had wide ranges of sugars determined by HPLC-RID (non-detectable (ND)-7.7 mg glucose, ND-9.4 mg fructose and 0.4-5.4 mg sucrose per 1 g fresh weight), and asparagine and glutamine levels determined by GC-FID (0.7-2.9 mg and 0.3-1.7 mg per 1 g fresh weight). Infrared spectra collected from 64 varieties were used to create partial least squares regression (PLSR) calibration models that predicted the sugar and amino acid levels in an independent set of 16 validation potato varieties. Excellent linear correlations between infrared predicted and reference values were obtained. PLSR models had a high correlation coefficient of prediction (rPred >0.95) and residual predictive deviation (RPD) values ranging between 3.1 and 5.5. Overall, the results indicated that the models could be used to simultaneously predict sugars, free asparagine and glutamine levels in the raw tubers, significantly benefiting potato breeding, certain aspects of crop management, crop production and research.

Identification of Quercus agrifolia (coast live oak) resistant to the invasive pathogen Phytophthora ramorum in native stands using Fourier-transform infrared (FT-IR) spectroscopy

Over the last two decades coast live oak (CLO) dominance in many California coastal ecosystems has been threatened by the alien invasive pathogen Phytophthora ramorum, the causal agent of sudden oak death. In spite of high infection and mortality rates in some areas, the presence of apparently resistant trees has been observed, including trees that become infected but recover over time. However, identifying resistant trees based on recovery alone can take many years. The objective of this study was to determine if Fourier-transform infrared (FT-IR) spectroscopy, a chemical fingerprinting technique, can be used to identify CLO resistant to P. ramorum prior to infection. Soft independent modeling of class analogy identified spectral regions that differed between resistant and susceptible trees. Regions most useful for discrimination were associated with carbonyl group vibrations. Additionally, concentrations of two putative phenolic biomarkers of resistance were predicted using partial least squares regression; >99% of the variation was explained by this analysis. This study demonstrates that chemical fingerprinting can be used to identify resistance in a natural population of forest trees prior to infection with a pathogen. FT-IR spectroscopy may be a useful approach for managing forests impacted by sudden oak death, as well as in other situations where emerging or existing forest pests and diseases are of concern.

Rapid authentication of concord juice concentration in a grape juice blend using Fourier-Transform infrared spectroscopy and chemometric analysis

Concord grape juice is associated with many health benefits, and so it can be sold at a premium price. However, there is currently no method to verify the percent composition of Concord grape juice in grape juice blends. In order to guard against potential adulteration, a rapid method for authentication is required. Fourier Transform infrared (FT-IR) spectroscopy was used to develop a model which predicts the percent composition of Concord grape juice. The model was based on a training set of 64 samples with Concord concentrations ranging from 50% to 100%. Data was collected on an external validation set with a standard error of prediction of 5.6% using 7 factors. The results suggest the feasibility of using FT-IR coupled with chemometrics as a production-scale tool for authentication claims of Concord in grape juice blends, protecting consumers and businesses against deceptive labelling.

Rapid assessment of quality parameters in processing tomatoes using hand-held and benchtop infrared spectrometers and multivariate analysis

Two portable infrared sensors were evaluated for the rapid determination of quality parameters in processing tomatoes. A total of 370 hot-break juices were prepared from ∼40 processing tomato varieties grown in 5 California counties. The levels of sugars, acids, soluble solids, titratable acidity, and pH in these juices were determined using standard reference methods. Juices were processed, filtered, and directly applied to the FT-IR crystal (15-40 μL) to obtain spectra. Partial least-squares regression (PLSR) was used to generate correlation models, both calibration and validation. The PLS validation models showed good ability (Rval > 0.80; <10% SEP) in estimating the sugars, acids, and especially soluble solids in tomato for both the transmission DialPath portable system and benchtop unit using triple-bounce attenuated total reflectance (ATR). The IR portable unit may provide the tomato processing industry with an efficient method for in-plant, high throughput quantification of quality parameters in tomatoes.

Application of hand-held and portable infrared spectrometers in bovine milk analysis

A simple and fast method for the detection and quantification of milk adulteration was developed using portable and hand-held infrared (IR) spectrometers. Milk samples were purchased from local supermarkets (Columbus, OH, USA) and spiked with tap water, whey, hydrogen peroxide, synthetic urine, urea, and synthetic milk in different concentrations. Spectral data were collected using mid-infrared (MIR) and near-infrared (NIR) spectrometers. Soft independent modeling of class analogy (SIMCA) classification models exhibited tight and well-separated clusters allowing the discrimination of control from adulterated milk samples. Partial least-squares regression (PLSR) was used to estimate adulteration levels, and results showed high coefficients of determination (R(2)) and low standard errors of prediction (SEP). Classification and quantification models indicated that the tested MIR systems were superior to NIR systems in monitoring milk adulteration. This method can be potentially used as an alternative to traditional methods due to their simplicity, sensitivity, low energy cost, and portability.

Use of FTIR for rapid authentication and detection of adulteration of food

Fourier transform infrared (FTIR) spectroscopy is an appealing technology for the food industry because simple, rapid, and nondestructive measurements of chemical and physical components can be obtained. Advances in FTIR instrumentation combined with the development of powerful multivariate data analysis methods make this technology ideal for large volume, rapid screening and characterization of minor food components down to parts per billion (ppb) levels. Because of the use of FTIR techniques in quality and process control applications, the food industry is already familiar with the technology and its potential to expand to monitoring for food adulteration. The aim of this review is to compile the current research on applications of near infrared (NIR) and mid-infrared (MIR) spectroscopy for rapid authentication and detection of adulteration in food.

Multicomponent cleaning verification of stainless steel surfaces for the removal of dairy residues using infrared microspectroscopy

The application of infrared microspectroscopy (IRMS) technology, combined with multivariate analysis, was evaluated to develop sensitive and robust methods to assess cleanability of stainless steel surfaces for the removal of dairy food residues. UHT milk samples (skim, 1%, 2%, and whole) were analyzed for total nitrogen (Kjeldahl) and fat (Babcock) contents. The coupons were manually soiled with serially diluted milk samples resulting in soils ranging from 0.1 to 428.1 μg/cm(2) for protein and 0.1 to 374.17 μg/cm(2) for fat, and then autoclaved to simulate a heated equipment surface. Reflectance spectra were collected from stainless steel coupons by using IRMS, and multivariate analysis was used to develop calibration models based on cross-validated partial least squares regression (PLSR). Statistical analysis for the prediction of protein and fat showed a standard error of cross-validation (SECV) of 0.5 and 0.4 μg/cm(2) for prediction of protein and fat, respectively, and correlation coefficients (rVal) > 0.99. To improve the sensitivity, swabbing and concentration steps were used prior to IRMS analysis obtaining SECV of 0.04 and 0.01 μg/cm(2) for the prediction of protein and fat, respectively, and rVal > 0.99. The PLSR models accurately predicted the levels of protein and fat on autoclaved stainless steel coupons soiled with milk. A simple, reliable, and robust protocol based on IRMS and multivariate analysis was developed for multicomponent characterization of stainless steel surfaces that can contribute to more efficient cleaning verification with regard to contamination on surfaces of processing equipment.

PRACTICAL APPLICATION

We report the application of Fourier transform infrared microspectroscopy (FTIR) for the validation of CIP cleaning efficiency that would provide a basis for better understanding of the mechanisms involved in the removal of physical soil and food residues from different types of equipment surfaces commonly utilized in the biotech, pharmaceutical, and food industries. Reliable calibration models were generated that showed the ability to predict the amounts of dairy soils on the surface of stainless steel coupons. Including a swabbing step of the coupons before infrared spectral acquisition provided improved sensitivity and reproducibility for multicomponent cleaning verification. Results from this research project would allow designing experiments to rapidly evaluate different materials and finishes, the effects of process variables, the influence of food components, and the development of reliable and robust cleaning validation protocols to ensure the safety and quality of the product.

Carotenoid stability during production and storage of tomato juice made from tomatoes with diverse pigment profiles measured by infrared spectroscopy

Chemical changes in carotenoids and lipids were studied during production and storage of canned tomato juice using ATR infrared spectroscopy and HPLC. Samples from 10 groups of tomatoes with different carotenoid profiles were analyzed fresh, after hot-break and screening, after canning, and at five different time points during 1 year of storage. An apparent increase of carotenoids was observed after hot-break due to improved extraction efficiency. This increase was accompanied by some degree of lipid oxidation and carotenoid isomerization. Canning produced the most intense changes in the lipid profile with breakdown of triglycerides ( approximately 1743 cm(-1)), formation of fatty acids ( approximately 1712 cm(-1)), and degradation and isomerization of trans-carotenoids ( approximately 960 and approximately 3006 cm(-1)). Isomerization was corroborated by the relative increase of HPLC areas corresponding to carotenoid cis isomers. Canning reduced trans-lycopene, trans-delta-carotene, trans-beta-carotene, and trans-lutein by 30, 34, 43, and 67%, respectively. HPLC data indicate that canning causes a drastic reduction of tetra-cis-lycopene and promotes its isomerization to other geometric forms, including all-trans-lycopene. Infrared spectra of tomato juice lipid fractions correlated well with the number of days in storage (SECV < 11 days, r values > 0.99), demonstrating continuous degradation of lipids. Results demonstrated that individual carotenoids and their isomeric forms behave differently during production and storage of canned tomato juice. Information collected by infrared spectroscopy complemented well that of HPLC, providing marker bands to further the understanding of chemical changes taking place during processing and storage of tomato juice.

Rapid profiling of Swiss cheese by attenuated total reflectance (ATR) infrared spectroscopy and descriptive sensory analysis

The acceptability of cheese depends largely on the flavor formed during ripening. The flavor profiles of cheeses are complex and region- or manufacturer-specific which have made it challenging to understand the chemistry of flavor development and its correlation with sensory properties. Infrared spectroscopy is an attractive technology for the rapid, sensitive, and high-throughput analysis of foods, providing information related to its composition and conformation of food components from the spectra. Our objectives were to establish infrared spectral profiles to discriminate Swiss cheeses produced by different manufacturers in the United States and to develop predictive models for determination of sensory attributes based on infrared spectra. Fifteen samples from 3 Swiss cheese manufacturers were received and analyzed using attenuated total reflectance infrared spectroscopy (ATR-IR). The spectra were analyzed using soft independent modeling of class analogy (SIMCA) to build a classification model. The cheeses were profiled by a trained sensory panel using descriptive sensory analysis. The relationship between the descriptive sensory scores and ATR-IR spectra was assessed using partial least square regression (PLSR) analysis. SIMCA discriminated the Swiss cheeses based on manufacturer and production region. PLSR analysis generated prediction models with correlation coefficients of validation (rVal) between 0.69 and 0.96 with standard error of cross-validation (SECV) ranging from 0.04 to 0.29. Implementation of rapid infrared analysis by the Swiss cheese industry would help to streamline quality assurance.

Rapid detection and differentiation of Alicyclobacillus species in fruit juice using hydrophobic grid membranes and attenuated total reflectance infrared microspectroscopy

Pasteurized juices may undergo spoilage during normal shelf life due to Alicyclobacillus spp. Metabolic byproducts during germination of these thermoacidiophilic, endospore-forming bacteria impart off-flavors. The objective was to develop a simple, rapid, and sensitive approach for differentiation of Alicyclobacillus spp. by attenuated total reflectance infrared (ATR-IR) microspectroscopy after isolation onto hydrophobic grid membrane (HGM) filters. Dilutions of four different species of Alicyclobacillus were filtered onto HGM, incubated on orange serum agar (50 degrees C, 36-48 h), and dried under vacuum. Spectra were collected using ATR-IR microspectroscopy and analyzed by multivariate analysis. Results indicated that soft independent modeling of class analogy models exhibited clusters that permitted classification at species and strain levels. The methodology was validated by correctly predicting Alicyclobacillus (100%) in blind tests. The proposed procedure permits chemically based classification of intact microbial cells. Implementation provides the juice industry with a rapid screening procedure to detect and monitor Alicyclobacillus that threatens the quality of pasteurized juices.

Rapid differentiation of Bacillus strains using hydrophobic grid membranes and attenuated total reflectance Infrared microspectroscopy

Bacillus species may be resistant to processing and sanitation procedures, making their control an important issue in the food industry. The objective of this study was to develop a rapid method for the differentiation of Bacillus cells at the strain level using infrared microspectroscopy and multivariate pattern recognition techniques. Aliquots (10 ml) of vegetative cells (approximately 10(3) CFU/ml) from four strains of each of three Bacillus species (B. cereus, B. mycoides, and B. thuringiensis) were filtered onto hydrophobic grid membranes. The membranes were placed on tryptic soy agar and incubated at 42 degrees C for 24 h and then removed from the agar and dried, and the biomass of individual vegetative colonies was directly measured by attenuated total reflectance infrared (ATR-IR) microspectroscopy. Soft independent modeling of class analogy models generated from second derivative transformed spectra in the 1,300 to 900 cm(-1) region exhibited clusters that permitted accurate strain-level classification of all isolates. Major discrimination was related to the signal from phosphate-containing compounds, likely phospholipids. Results indicate that a simple ATR-IR microspectroscopy technique combined with multivariate analysis could provide the food industry with a rapid and reagent-free screening procedure to complement more elaborate molecular identification methods.

Rapid prediction of composition and flavor quality of cheddar cheese using ATR-FTIR spectroscopy

Multiple methods are required for analysis of cheese flavor quality and composition. Chromatography and sensory analyses are accurate but laborious, expensive, and time consuming. A rapid and simple instrumental method based on Fourier transform infrared (FTIR) spectroscopy was developed for simultaneous analysis of Cheddar cheese composition and flavor quality. Twelve different Cheddar cheese samples ripened for 67 d were obtained from a commercial cheese manufacturer along with their moisture, pH, salt, fat content, and sensory flavor quality data. Water-soluble components were extracted from the cheese, dried on zinc selenide FTIR crystal and scanned (4000 to 700 cm(-1)). Infrared spectra of the samples were correlated with their composition and flavor quality data to develop multivariate statistical regression and classification models. The models were validated using an independent set of ten 67-d-old test samples. The infrared spectra of the samples were well defined, highly consistent within each sample and distinct from other samples. The regression models showed excellent fit (r > 0.92) and could accurately determine moisture, pH, salt, and fat contents as well as the flavor quality rating in less than 20 min. Furthermore, cheeses could also be classified based on their flavor quality (slight acid, whey taint, good cheddar, and so on). The discrimination of the samples was due to organic acids, amino acids, and short chain fatty acids (1800 to 900 cm(-1)), which are known to contribute significantly to cheese flavor. The results show that this technique can be a rapid, inexpensive, and simple tool for predicting composition and flavor quality of cheese.

A candidate serum biomarker for bladder pain syndrome/interstitial cystitis

Reliable diagnostic markers for Bladder Pain Syndrome/Interstitial Cystitis (IC) currently are not available. This study evaluated the feasibility of diagnosing IC in humans and domestic cats from the spectra of dried serum films (DSFs) using infrared microspectroscopy. Spectra were obtained from films from 29 humans and 34 domestic cats to create classification models using Soft Independent Modeling by Class Analogy (SIMCA). Ultrafiltration of serum improved discrimination capability. The classification models for both species successfully classified spectra based on condition (healthy/sick), and a different set of masked spectra correctly predicted the condition of 100% of the subjects. Classification required information from the 1500-1800 cm(-1) spectral region to discriminate between subjects with IC, other disorders, and healthy subjects. Analysis of cat samples using liquid chromatography-mass spectroscopy revealed differences in the concentration of tryptophan and its metabolites between healthy and affected cats. These results demonstrate the potential utility of infrared microspectroscopy to diagnose IC in both humans and cats.

Rapid and simultaneous determination of lycopene and beta-carotene contents in tomato juice by infrared spectroscopy

The rapid quantification of lycopene and beta-carotene in tomato juices by attenuated total reflectance (ATR) infrared spectroscopy combined with multivariate analysis was evaluated. Two sample preparation methods were compared: a direct measurement of the tomato paste and an extraction method using hexane to isolate carotenoids. HPLC was used as the reference method. Cross-validated (leave-one-out) partial least-squares regression (PLSR) was used to create calibration models to predict these phytonutrient concentrations in blind test samples. The infrared spectra showed unique marker bands at 957 and 968 cm(-1) for lycopene and beta-carotene, respectively. Multivariate analysis of the infrared spectral data gave correlation coefficients (r values) of >0.9 between the ATR-IR predicted and HPLC reference values, and standard errors of cross-validation (SECV) of 0.5 and 0.04 mg/100 g of juice for lycopene and beta-carotene, respectively. ATR-IR could provide the tomato industry with a simple, rapid, and high-throughput technique for the determination of tomato quality.

Herbivore-induced volatiles in the perennial shrub, Vaccinium corymbosum, and their role in inter-branch signaling

Herbivore feeding activates plant defenses at the site of damage as well as systemically. Systemic defenses can be induced internally by signals transported via phloem or xylem, or externally transmitted by volatiles emitted from the damaged tissues. We investigated the role of herbivore-induced plant volatiles (HIPVs) in activating a defense response between branches in blueberry plants. Blueberries are perennial shrubs that grow by initiating adventitious shoots from a basal crown, which produce new lateral branches. This type of growth constrains vascular connections between shoots and branches within plants. While we found that leaves within a branch were highly connected, vascular connectivity was limited between branches within shoots and absent between branches from different shoots. Larval feeding by gypsy moth, exogenous methyl jasmonate, and mechanical damage differentially induced volatile emissions in blueberry plants, and there was a positive correlation between amount of insect damage and volatile emission rates. Herbivore damage did not affect systemic defense induction when we isolated systemic branches from external exposure to HIPVs. Thus, internal signals were not capable of triggering systemic defenses among branches. However, exposure of branches to HIPVs from an adjacent branch decreased larval consumption by 70% compared to those exposed to volatiles from undamaged branches. This reduction in leaf consumption did not result in decreased volatile emissions, indicating that leaves became more responsive to herbivory (or "primed") after being exposed to HIPVs. Chemical profiles of leaves damaged by gypsy moth caterpillars, exposed to HIPVs, or non-damaged controls revealed that HIPV-exposed leaves had greater chemical similarities to damaged leaves than to control leaves. Insect-damaged leaves and young HIPV-exposed leaves had higher amounts of endogenous cis-jasmonic acid compared to undamaged and non-exposed leaves, respectively. Our results show that exposure to HIPVs triggered systemic induction of direct defenses against gypsy moth and primed volatile emissions, which can be an indirect defense. Blueberry plants appear to rely on HIPVs as external signals for inter-branch communication.

Improving the screening process for the selection of potato breeding lines with enhanced polyphenolics content

Efficient selection of potato varieties with enhanced nutritional quality requires simple, rapid, accurate, and cost-effective assays to obtain tuber chemical composition information. Our objective was to develop simple protocols to determine phenolics, anthocyanins, and antioxidant capacity in polyphenolic extracts of potatoes using Fourier transform infrared spectroscopy combined with multivariate techniques. Lyophilized potato samples (23) were analyzed. Polyphenolic compounds were extracted from potatoes and applied directly applied onto a three-bounce ZnSe crystal for attenuated total reflectance measurements in the infrared region of 4000 to 700 cm (-1). Robust models were generated (r > or = 0.99) with standard error of cross-validation values of 4.17 mg gallic acid equivalent/100 g (total phenolics), 0.87 mg pelargonidin-3-glucoside/100 g (monomeric anthocyanins), and 130.8 mumol Trolox equivalent/100 g (antioxidant capacity) potato powder. In addition, classification models discriminated potato samples at the species and variety level. Application of a simple infrared spectroscopic protocol allowed simultaneous rapid quantification of specific nutritional components in potatoes and efficient selection of value-added potato varieties.

Application of Fourier transform infrared spectroscopy for monitoring short-chain free fatty acids in Swiss cheese

Short-chain free fatty acids (FFA) are important sources of cheese flavor and have been reported to be indicators for assessing quality. The objective of this research was to develop a simple and rapid screening tool for monitoring the short-chain FFA contents in Swiss cheese by using Fourier transform infrared spectroscopy (FTIR). Forty-four Swiss cheese samples were evaluated by using a MIRacle three-reflection diamond attenuated total reflectance (ATR) accessory. Two different sampling techniques were used for FTIR/ATR measurement: direct measurement of Swiss cheese slices (approximately 0.5 g) and measurement of a water-soluble fraction of cheese. The amounts of FFA (propionic, acetic, and butyric acids) in the water-soluble fraction of samples were analyzed by gas chromatography-flame ion-ization detection as a reference method. Calibration models for both direct measurement and the water-soluble fraction of cheese were developed based on a cross-validated (leave-one-out approach) partial least squares regression by using the regions of 3,000 to 2,800, 1,775 to 1,680, and 1,500 to 900 cm(-1) for short-chain FFA in cheese. Promising performance statistics were obtained for the calibration models of both direct measurement and the water-soluble fraction, with improved performance statistics obtained from the water-soluble extract, particularly for propionic acid. Partial least squares models generated from FTIR/ATR spectra by direct measurement of cheeses gave standard errors of cross-validation of 9.7 mg/100 g of cheese for propionic acid, 9.3 mg/100 g of cheese for acetic acid, and 5.5 mg/100 g of cheese for butyric acid, and correlation coefficients >0.9. Standard error of cross-validation values for the water-soluble fraction were 4.4 mg/100 g of cheese for propionic acid, 9.2 mg/100 g of cheese for acetic acid, and 5.2 mg/100 g of cheese for butyric acid with correlation coefficients of 0.98, 0.95, and 0.92, respectively. Infrared spectroscopy and chemometrics accurately and precisely predicted the short-chain FFA content in Swiss cheeses and in the water-soluble fraction of the cheese.

Midinfrared spectroscopy for juice authentication-rapid differentiation of commercial juices

The determination of food authenticity is a crucial issue for food quality and safety. Midinfrared spectroscopy provides rapid chemical profiling of agricultural products and could become an effective tool for authentication when coupled to chemometrics. This study developed a simple protocol for classifying commercial juices using attenuated total reflectance infrared spectroscopy. Spectra from a total of 52 juices together with their extracted sugar-rich and phenol-rich fractions were obtained to construct multivariate models [hierarchical cluster analysis (HCA) and soft independent modeling of class analogy (SIMCA)] for pattern recognition analysis and prediction. Spectra of the sugar-rich fraction, comprised primarily of sugars and simple acids, almost superimposed the whole juice spectra. Solid-phase extraction enriched phenol compounds and provided signature-like spectral information that substantially improved the SIMCA modeling power over the whole juice or sugar-rich fraction models and allowed for the differentiation of juices with different origins. Zero percent misclassification was achieved by the phenol-rich fraction model. HCA successfully recognized the natural grouping of juices based on ingredients similarity. The infrared technique assisted by a simple fractionation and chemometrics provided a promising analytical method for the assurance of juice quality and authenticity.

Effect of selective growth media on the differentiation of Salmonella enterica serovars by Fourier-Transform Mid-Infrared Spectroscopy

Salmonella enterica serovars are prevalent foodborne pathogens responsible for high numbers of salmonellosis each year. Complex Fourier-transform infrared (FTIR) spectra offer unique biochemical fingerprints of bacteria with bands due to major cellular components. Growth media effects on discrimination of Salmonella serovars by FTIR spectroscopy were investigated and a novel sample preparation technique was developed. S. enterica strains from six serovars were grown on xylose lysine desoxycholate (XLD), Miller-Mallinson (MM), and plate count (PCA) agar as a control (37 degrees C, 24 h). Isolated colonies were suspended in 50% acetonitrile and centrifuged; the remaining pellet was placed on an AMTIR (attenuated total reflectance) crystal and dried under vacuum. Classification models (Soft Independent Modeling of Class Analogy, SIMCA), generated from derivatized infrared spectra (1300-900 cm-1 or 1200-900 cm-1), successfully discriminated among Salmonella strains with major discrimination from 1000-970 cm-1 associated to stretching modes of O-specific polysaccharide chains of lipopolysaccharides. Sample treatment with acetonitrile enhanced safe handling of the bacteria, removed interfering signals and improved the discriminating ability of SIMCA. All media were able to discriminate the S. enterica strains studied, varying in discriminating peaks and class distances in SIMCA classification. This methodology, with the production of large libraries of pathogenic bacteria, could be applied for the rapid monitoring of bacterial contamination in food with minimal sample manipulation.

Direct determination of lycopene content in tomatoes (Lycopersicon esculentum) by attenuated total reflectance infrared spectroscopy and multivariate analysis

Lycopene is a potent antioxidant that has been shown to play critical roles in disease prevention. Efficient assays for detection and quantification of lycopene are desirable as alternatives to time- and labor-intensive methods. Attenuated total reflectance infrared (ATR-IR) spectroscopy was used for quantification of lycopene in tomato varieties. Calibration models were developed by partial least-squares regression (PLSR) using quantitative measures of lycopene concentration from liquid chromatography as reference method. IR spectra showed a distinct marker band at 957 cm(-1) for trans Carbon-Hydrogen (CH) deformation vibration of lycopene. PLSR models predicted the lycopene content accurately and reproducibly with a correlation coefficient (sigma) of 0.96 and standard error of cross-validation <0.80 mg/100 g. ATR-IR spectroscopy allowed for rapid, simple, and accurate determination of lycopene in tomatoes with minimal sample preparation. Results suggest that the ATR-IR method is applicable for high-throughput quantitative analysis and screening for lycopene in tomatoes.