Use Of Mid-infrared Spectroscopy Research Articles

Chocolates Produced with Unroasted and Roasted Cocoa Beans: A Comparative Study of the Preservation of Bioactive Compounds

The aim of the present study was to evaluate the effect of roasting and cocoa mass content on the composition of chocolates. Chocolate formulations were developed (40, 50, 60 and 70% cocoa solids) using unroasted and roasted cocoa beans, and analyses were performed: physicochemical, chemical composition, antioxidant capacity, procyanidin content, total phenolic compounds, quantification of theobromine, caffeine, catechin and epicatechin by high performance liquid chromatography (HPLC) and spectroscopic profile by mid-infrared spectroscopy (MIR). The results revealed that higher values of total phenolics, epicatechin and procyanidins, were obtained in chocolates produced with unroasted cocoa beans, with a significant difference in relation to those with roasted cocoa beans. It was observed that increasing the percentage of cocoa in the formulations caused an increase in the content of bioactive compounds. The use of MIR in the differentiation of chocolate samples produced with roasted and unroasted cocoa beans obtained a positive result. This technique associated with principal component analysis (PCA) enabled the separation of chocolates according to the type of cocoa bean (roasted and unroasted) used in production, confirming its importance for a quick evaluation of the parameters.

Usefulness of mid-infrared spectroscopy as a tool to estimate body condition score change from milk samples in intensively fed dairy cows

Directly measuring individual cow energy balance is not trivial. Other traits, like body condition score (BCS) and BCS change (ΔBCS) can, however, be used as an indicator of cow energy status. Body condition score is a metric used world-wide to estimate cow body reserves and the estimation of ΔBCS was, until now, conditional on the availability of multiple BCS assessments. The aim of the present study was to estimate ΔBCS from milk mid-infrared (MIR) spectra and days in milk (DIM) in intensively-fed dairy cows using statistical prediction methods. Daily BCS was interpolated from cubic splines fitted through the BCS records and daily ΔBCS was calculated from these splines. Body condition score change records were merged with milk MIR spectra recorded on the same week. The data set comprised 37,077 ΔBCS phenotypes across 9,403 lactations from 6,988 cows in 151 herds based in Quebec (Canada). Partial least squares regression (PLSR) and a neural network (NN) were then used to estimate ΔBCS from 1) MIR spectra only, 2) DIM only, or 3) MIR spectra and DIM together. ΔBCS data in both the first 120 DIM and 305 DIM of lactation were used to develop the estimates. Daily ΔBCS had a standard deviation of 4.40*10-3 BCS units in the 120-d data set and of 3.63*10-3 BCS units in the 305-d data set. 4-fold cross-validation was used to calibrate and test the prediction equations. External validation was also conducted using more recent years of data. Irrespective of whether based on the first 120 or 305 DIM, or when MIR spectra only, DIM only or MIR spectra and DIM were jointly used as prediction variables, NN produced the lowest root mean square error (RMSE) of cross-validation (1.81*10-3 BCS units and 1.51*10-3 BCS units, respectively, using the 120-d and 305-d data set). Relative to predictions for the entire 305 DIM, the RMSE of cross-validation was 15.4% and 1.5% lower in the first 120 DIM when using PLSR and NN, respectively. Predictions from DIM only were more accurate than those using just MIR spectra data but, irrespective of the data set and of the prediction model used, the combining DIM information with MIR spectral data as prediction variables reduced the RMSE compared with inclusion of DIM alone, albeit the benefit was small (the RMSE from cross-validation was reduced up to 5.5% when DIM and spectral data were jointly used as model features instead of DIM only). However, when predicting extreme ΔBCS records, the MIR spectral data was more informative than DIM. Model performance when predicting ΔBCS records in future years was similar to that from cross-validation demonstrating the ability of MIR spectra of milk and DIM combined to estimate ΔBCS, particularly in early lactation. This can be used to routinely generate estimates of ΔBCS to aid in day-to-day individual cow management.

Qualitative analysis of broccoli (Brassica oleracea var. italica) glucosinolates: Investigating the use of mid-infrared spectroscopy combined with chemometrics

Glucosinolates are phytochemicals with important health and nutritional benefits. This study reports the use of high-performance liquid chromatography (HPLC) and mid-infrared (MIR) spectroscopy to characterise and differentiate between broccoli varieties and systems of production (organic vs. non-organic) depending on their glucosinolate content and infrared fingerprint. Broccoli samples (n = 53) from seven varieties were analysed using MIR spectroscopy and HPLC. Differences in the MIR spectra of the individual broccoli varieties were observed in the carbohydrate fingerprint region (950–1100 cm-1) and between 1340 and 1615 cm-1 assigned to specific glucosinolates. Principal component analysis (PCA) of the MIR fingerprint spectra enabled the differentiation between samples with relatively high (200–500 mg/100 g DW) and low (< 200 mg/100 g DW) glucobrassicin content. Linear discriminant analysis (LDA) and PCA-LDA were used to classify broccoli varieties according to the system of production (organic vs. non-organic) and variety (common vs. Tenderstem® broccoli). The classification rates indicated that > 70 % of the samples were correctly classified as organic and non-organic, while > 90 % of the samples were correctly classified as common broccoli and Tenderstem®. This study demonstrates that MIR spectroscopy could be used as a potential tool to classify and monitor broccoli samples according to their variety and system of production.

Building of mid-infrared spectral signature of pesticides using functionally-enhanced derivative spectroscopy (FEDS)

Pesticides are synthetic substances widely used in several processes related to agriculture-based food production. Their monitoring is important to evaluate their impact on environment, ensure the food quality, and for the developing of new methods and strategies that help to understand their dynamics from the moment they are released until their end disposal. In this way, the use of mid-infrared spectroscopy (mid-IR spectroscopy) and chemometric methods have been widely explored. However, the strong overlap of spectral signals in complex analytical matrices is recognized as the main limitation of reflectance-based methods for monitoring of this kind of pollutant. In this work, the use of MID-IR spectroscopy by attenuated total reflectance (ATR), in conjunction with functionally-enhanced derivative spectroscopy (FEDS), is proposed as non-destructive technique for fast and simple monitoring of pesticides. Thus, high-resolution dynamic spectral signature (HDSS) for six pesticides commonly used in tropical crops were used as model substances; as analytical matrix was used the peel of banana (e.g., Musa paradisiaca). In addition, concentration effect was evaluated to mimic real conditions. Data recording was obtained by mid-IR spectroscopy (from 4000 to 600 cm−1) and HDSS were evaluated by Pearson’s correlation coefficient and spectral similarity FEDS index between the spectra and the reference signals. Based on these correlation parameters, some selection criteria are proposed to estimate the spectral zones where the pesticide signature persists even at relative low concentrations. For the six pesticides, the spectral region considered coincide with those bands of high polarity bonds in the pesticide molecules. Additionally, a good linear prediction models that correlate the relative absorbance intensity and the peak area of the mid signal with the pesticide concentration level are obtained in the spectral ranges of interest. The model performance is defined by Pearson’s coefficients rf greater than 0.97, residual prediction deviation RPDs (root mean square errors - RMSEs) greater (lower) than 5 (3), and limits of detection (LODs) lower than 1 g/kg. Furthermore, this methodology and results are successfully employed to detect Chlorpyrifos residues in banana peel.

Use of mid-infrared spectroscopy to predict the content of bioactive compounds of a new non-dairy beverage fermented with water kefir

The present work aimed at development and characterization of a functional beverage and the construction of calibration models to predict the content of phenolic compounds, antioxidants, and anthocyanins in the fermented product. Mid-infrared spectra of the samples were obtained for different fermentation times, and PLS regression was applied to elaborate predictive models. The beverages were prepared and characterized by traditional methods, and, later, individual calibration models were built for each parameter analyzed. Through PCA it was possible to obtain a certain separation degree between the samples submitted to different fermentation times. The values of the coefficients of determination (R2) gathered in the validation stage of the models ranged from 0.74 to 0.89 and pointed to a good correlation between the data experimentally collected and the values predicted by the models. The results showed that the best prediction was obtained for estimating the content of total anthocyanins, which presented RMSEP, R2 and RPD values of 0.18, 0.89, and 3.11, respectively. This study demonstrated the applicability of MIR spectroscopy with chemometrics to predict some bioactive compounds of interest during kefir fermentation.

A systematic mid-infrared spectroscopic study of thermally processed SO2 ices.

The use of mid-infrared spectroscopy to characterise the chemistry of icy interstellar and Solar System environments will be exploited in the near future to better understand the chemical processes and molecular inventories in various astronomical environments. This is, in part, due to observational work made possible by the recently launched James Webb Space Telescope as well as forthcoming missions to the outer Solar System that will observe in the mid-infrared spectroscopic region (e.g., the Jupiter Icy Moons Explorer and the Europa Clipper missions). However, such spectroscopic characterisations are crucially reliant upon the generation of laboratory data for comparative purposes. In this paper, we present an extensive mid-infrared characterisation of SO2 ice condensed at several cryogenic temperatures between 20 and 100 K and thermally annealed to sublimation in an ultrahigh-vacuum system. Our results are anticipated to be useful in confirming the detection (and possibly thermal history) of SO2 on various Solar System bodies, such as Ceres and the icy Galilean moons of Jupiter, as well as in interstellar icy grain mantles.

Investigations on Storage and Oxidative Stability of Biodiesel from Different Feedstocks Using the Rancimat Method, Infrared Spectroscopy, and Chemometry

Biodiesel can be altered when exposed to air, light, temperature, and humidity. Other factors, such as microbial or inorganic agents, also interfere with the quality of the product. In the present work, the Rancimat method and mid-infrared spectroscopy associated with chemometry, were used to identify the oxidation process of biodiesel from different feedstocks and to evaluate the antioxidant activity of butylated hydroxytoluene. The study was carried out in four steps: preparation of biodiesel samples with and without the antioxidant agent, degradation of the samples under the effect of light and heating at 70 °C, measurements of the induction period, obtention of infrared spectra, and multivariate analysis. The Fourier transform mid-infrared spectroscopy was used in combination with multivariate analysis, using techniques such as principal component analysis (PCA) and hierarchical clustering analysis (HCA). The Rancimat results showed that babassu biodiesel has a higher resistance to oxidative degradation, while chicken biodiesel is the most susceptible to degradation; on the other hand, the antioxidant activity was more effective with chicken biodiesel, demonstrating that the antioxidant effect depends on the feedstock used in the production of biodiesel. The oxidative stability of babassu oil-, corn oil-, and chicken fat-based biodiesels decreased during storage both in the presence of light and at high temperature. Prior to PCA, all spectra were pre-processed with a combination of Savitzky–Golay smoothing filter with a 7-point window, baseline correction, and mean-centered data. The use of mid-infrared spectroscopy associated with PCA revealed the first two components to explain the greater variability of data, representing over 75% of total variation for all analyzed systems. In addition, it was able to separate the biodiesel samples according to the fatty acid profile of its feedstock, as well as the type of degradation to which it was subjected, the same being confirmed by HCA.

Use of mid-infrared spectroscopy for quality monitoring and the prediction of physicochemical parameters of dry fermented chicken sausages enriched with sesame flour.

This study aimed to investigate the effects of the supplementation of sesame flour in fermented chicken sausages ('S1' containing 800 g kg-1 chicken fillet, 180 g kg-1 veal fat and 20 g kg-1 sesame flour and 'S2' containing 800 g kg-1 chicken fillet, 160 g kg-1 veal fat and 40 g kg-1 sesame flour) compared with control sausages (containing 800 g kg-1 chicken fillet and 200 g kg-1 veal fat) on the physico-chemical characteristics, texture, and structure during the fermentation stage. The physicochemical parameters of samples belonging to the control, S1, and S2 batches were significantly affected by the addition of sesame flour and the fermentation stage. For instance: (i) the lowest protein content was observed for control samples on day 1 (61.4± 6.52 g kg-1 ) whereas the highest level was noted for S2 samples on day 15 (327.5± 22.2g kg-1 ), and (ii) an inverse trend was observed for the fat content because the lowest content was observed for samples in the S2 batch on day 1 (129.0± 5.30 g kg-1 ) whereas the highest fat content was noted for samples belonging to control batch on day 15 (332.0± 1.29 g kg-1 ). The application of statistical methods to mid-infrared spectroscopy allowed clear discrimination between control, S1, and S2 batches. The addition of sesame flour in the recipes induced some modification in the secondary structure because β-turn levels ranged from 39.30 to 34.50, 36.76 to 34.70, and 38.93 to 34.70 for control, S1, and S2 batches, respectively, throughout the fermentation stage. Sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) showed a similar protein profile pattern in the three batches on days 1 and 5, but on day 10 control and S2 batches showed the most intense degradation of myofibrillar proteins. The results demonstrated that mid-infrared spectroscopy coupled with chemometric tools could be used as a rapid screening tool to assess and monitor the quality of dry chicken sausages enriched with sesame flour throughout the fermentation stage. © 2022 Society of Chemical Industry.

Use of mid infrared spectroscopy to analyze the ripening of Brazilian bananas

Banana is one of the most consumed fruits in the world due to its flavor and nutritional value. The knowledge of the ripening stage of bananas is essential for its commercialization, since, after harvesting it can take days in transportation until reaching their destination. The use of spectroscopic techniques in the infrared region has been widely used in the food industry. In this study, a nondestructive analytical method was developed to monitor the maturation of silver bananas, dwarf bananas, gold bananas and bread bananas using Fourier Transform Mid Infrared spectroscopy. To accompany the ripening of the bananas, 3 regions in each banana were chosen (bottom, middle and top) and from these, 3 measures were taken around the banana perimeter. Beyond the ripening process of the bananas, functional groups are identified as well as the beginning of the stage previous to the mature fruit, characterized by the emission of ethylene and CO2. Principal components analysis allowed the identification of the process irrespective of the banana type which suggest the automation possibility of the process.

A new strategy for canine visceral leishmaniasis diagnosis based on FTIR spectroscopy and machine learning

Visceral leishmaniasis is a neglected disease caused by protozoan parasites of the genus Leishmania. The successful control of the disease depends on its accurate and early diagnosis, which is usually made by combining clinical symptoms with laboratory tests such as serological, parasitological, and molecular tests. However, early diagnosis based on serological tests may exhibit low accuracy due to lack of specificity caused by cross-reactivities with other pathogens, and sensitivity issues related, among other reasons, to disease stage, leading to misdiagnosis. In this study was investigated the use of mid-infrared spectroscopy and multivariate analysis to perform a fast, accurate, and easy canine visceral leishmaniasis diagnosis. Canine blood sera of 20 noninfected, 20 Leishmania infantum, and eight Trypanosoma evansi infected dogs were studied. The data demonstrate that principal component analysis with machine learning algorithms achieved an overall accuracy above 85% in the diagnosis.

An Infrared Analysis of Terminalia ferdinandiana Exell [Combretaceae] Fruit and Leaves—Towards the Development of Biospectroscopy Tools to Characterise Uniquely Australian Foods

Knowledge about the inherent complexity of the composition, nutrition, and physiology of different plant tissues and parts is required as this will allow for the discovery of new or improved properties (e.g. new bioactive compounds with health-benefitting activities, antimicrobial substances to reduce food spoilage activity). This paper reports the use, analysis and interpretation of the mid-infrared spectra of different plant parts (fruits and leaves) from an Australian native tropical plant, Terminalia ferdinandiana Exell [Combretaceae]. The use of infrared spectroscopy together with chemometric techniques will allow to obtain different levels of information about the chemical composition of leaf and fruit samples associated with maturity. Freeze-dried powder and puree of Terminalia ferdinandiana is commercially available as a functional food ingredient, whereas leaves or any other tissues are not considered as functional ingredients. The use of mid-infrared spectroscopy can provide an initial screening tool for the discovery and development of new ingredients and products. This technology can be an easy to use, cost-effective and high throughout method to ensure quality and authenticity of food products throughout the value chain. The incorporation of these techniques might be considered the base of bio spectroscopy analysis as proxies to study tropical species with distinctive bioactive properties and nutritional value such as Terminalia ferdinandiana.

Considerations on high-throughput cocrystals screening by ultrasound assisted cocrystallization and vibrational spectroscopy.

For industrial production of cocrystals, screening phase is essential, helping to become the process faster, more effective and efficient, reducing the quantity of reactants used and associated costs. High-throughput screening (HTS) methods can analyze a wide range of compounds simultaneously. As an answer to industrial necessity of more efficient screening methods, different methods must be developed and optimized. Vibrational spectroscopic techniques are fast, non-destructive and non-invasive, do not need pre-treatment of the samples and allow obtaining qualitative and quantitative information. They are useful in cocrystal analysis, once they detect weak interaction as hydrogen bonding, the basis of cocrystal formation. Therefore, its application in the analysis of cocrystal screening methods, together with multivariate analysis, should be studied in detail. For this end, a HTS procedure of hydrochlorothiazide (HTZ) cocrystals is performed using a 96-well plate and ultrasound-assisted cocrystallization. Six coformers were tested considering ratios of HTZ:coformer of 1:1 and 1:2. The cocrystallization products were analyzed by mid infrared spectroscopy and Raman microspectroscopy. Nicotinamide and p-aminobenzoic acid formed cocrystals with HTZ. The systems with arginine showed that the coformer suffered amorphization; however, no proof of the solid state of HTZ was obtained. The results were not conclusive for the system with citric acid. Additionally, in the nicotinamide and citric acid systems, the physical mixture of the plate also reacted without the present of solvent. Overall, the use of mid infrared spectroscopy and multivariate data analysis provided important information on cocrystal formation, purity, and correct ratio assessment.

Investigation on the effectiveness of mid-infrared spectroscopy to predict detailed mineral composition of bulk milk

This Research Communication investigated the potential of mid-infrared spectroscopy to predict detailed mineral composition of bovine milk. A total of 153 bulk milk samples were analysed for contents of Ca, Cl, Cu, Fe, K, Mg, Na, P and Zn. Also, soluble and colloidal fractions of Ca, Mg and P were quantified. For each milk sample the mid-infrared spectrum was captured and stored. Prediction models were developed using partial least squares regression and the accuracy of prediction was evaluated using both cross- and external validation. The proportion of variance explained by the prediction models in cross-validation ranged from 34% (Na) to 77% (total P), and it ranged from 13% (soluble Mg) to 54% (Cl−) in external validation. The ratio of the standard deviation of each trait to the standard error of prediction in external validation, which is an indicator of the practical utility of the prediction model, was low and never greater than 2. Results from the current study supported the limited usefulness of mid-infrared spectroscopy to predict minerals present in low concentration in bulk milk. For major mineral components, results from the present research did not match previous findings demonstrating the need for further studies using larger reference datasets.

A preliminary evaluation of the use of mid infrared spectroscopy to develop calibration equations for determining faecal composition, intake and digestibility in sheep

The aim of this study was to investigate the application of Fourier Transform Infrared (FTIR) spectroscopy to provide calibration equations for assessing faecal composition, intake and digestibility in sheep. Four grass-based feed types and corresponding faecal samples were collected from two separate sheep digestibility experiments. The feed (n=41) and faecal samples (n=132) were analysed for chemical composition, digestibility, were scanned using FTIR spectroscopy and intakes were recorded. Data were analysed using principle component analysis and partial least squares (PLS) regression techniques for calibration equation development. Calibration accuracy and performance were assessed by calculating regression coefficient of cross validation (R2cv) and the ratio of performance to deviation (RPD value) respectively. Results indicated that the composition of feed and faecal samples along with associated digestibilities and intakes were significantly different for a number of parameters studied. Some of the PLS regression equations generated were comparable to those reported in the published literature, and based on calibration statistics and performance those developed for faecal ash and neutral detergent fibre were good and could be used for quantification (R2cv=0.9–0.8, RPD=3.0–2.5); those for acid detergent fibre, lignin, feed ash intake and dry matter digestibility (DMD) were adequate for qualitative analysis and screening (R2cv=0.8–0.7, RPD=2.3–2.0); and the calibration equations for dry matter, nitrogen, dry matter intake, gross energy, gross energy intake and gross energy digestibility were poor and unsuitable for prediction (R2cv≤0.7, RPD≤1.8). Further development of calibration equations and in particular the prediction of DMD, could be of benefit to animal scientists and the livestock industry.

Use of mid-infrared spectroscopy to monitor shelf-life of ready-made meals

The objective of this work was to use mid-infrared spectroscopy as a rapid analytical method to monitor the change in stored ready-made meals over time. Six ready-made meals were packaged in two plastic bags, Alu and Alox, and stored at 23 °C at a partial oxygen pressure of 96 kPa. After thawing, samples were directly measured in attenuated total reflectance mid-infrared spectroscopy between 4000 and 650 cm−1. Multivariate analyses applied on spectral data highlighted some changes in the global profile, particularly in Bolognese soup and in mashed potatoes with cheese. Indeed, the Bolognese sauce samples were clearly discriminated (i) according to the storage time and (ii) according to the packaging type presenting a greater oxidation in the Alox packaging. The eigenvectors allowed for the identification of clear absorption bands at 2918, 2850, 1741 and 1164 cm−1 which increased over storage. These absorption bands could be attributed to fats, which thus appeared to have a major effect in sample discrimination. Mid-infrared spectroscopy was shown to be a relevant tool for discriminating the oxidation state of canned ready-made meals and might be used to determine their shelf-life.

Quantification of residual automotive lubricant oil as an adulterant in Brazilian S-10 diesel using MIR spectroscopy and PLS

Diesel, inside all energy matrixes, is considered a valuable resource. Brazilian S-10 diesel can be subject to adulteration by addition of residual automotive lubricant (RAL), to increase the profit margin for distributors and fuel service stations. The use of mid-infrared (MIR) spectroscopy in combination with multivariate calibration methods as a quantitative analytical method can provide satisfactory results in accordance with those found using conventional methods. We report the use of MIR spectroscopy and multivariate calibration using the partial least squares method (PLS) for the quantitative analysis of RAL as an adulterant in Brazilian S-10 diesel. Our results displayed good correlation between the reference values and those calculated using the PLS model with low error values. The model was built in accordance with standard method ASTM E1655-05 and validations of the figures of merit were estimated.

Data Fusion for Food Authentication. Combining near and Mid Infrared to Trace the Origin of Extra Virgin Olive Oils

Introduction I n recent years, food authentication and food traceability have emerged as issues of primary and common concern for both consumers and producers. Because of this, the number of researchers who tackle these problems by combining chemometrics coupled with a fingerprinting technique continues to increase. This kind of approach, indeed, has the undeniable advantage of allowing, in many cases, the use of rapid and relatively inexpensive analytical techniques that can, nonetheless, lead to reliable and accurate results. Among these analytical methods, an important role is played by the spectroscopic techniques and in particular in the infrared wavelength ranges. These are often chosen as the ideal analytical methods for the development of food quality control methodologies because of their inherent characteristics of non-destructivity, speed and cheapness of analysis, as well as not needing any sample pre-treatment. However, food quality control, in particular when traceability and authentication are concerned, is a complex problem for the chemist, and sometimes the acquisition of a single fingerprinting signal and the subsequent construction of a chemometric classification model is not enough to develop a methodology reliable enough for the intended purpose. In such cases, it is often possible to rely on the possibility of acquiring more than one single signal for each sample, and then to use the combined information from the two (or more) techniques to develop the final chemometric model. In this way, it is possible, sometimes, to benefit from the specific advantages and characteristics of the different techniques to create a more reliable and stable final model, in particular whenever there is complementarity between the information provided by the techniques employed. In these cases, however, the problem of how to combine the different information coming from the various analytical methods, namely the data fusion issue, is of major importance for the accuracy and reliability of the final results of the proposed methodology. In this context, the use of near infrared (NIR) and mid infrared (MIR) spectroscopy to solve authentication or traceability issues has already been described by many researchers, showing the great potential that both these techniques have in the field of food quality control analysis. Moreover, the peculiar characteristics of NIR and MIR, being different from one another, make them perfectly adaptable to being used together. Due to its greater molecular selectivity, the use of MIR spectroscopy often provides easier spectral interpretation than NIR, and it can sometimes be more related to some compound that is typical of the investigated food. NIR spectroscopy is more useful for its peculiarity of giving an overall fingerprint of the entire sample and it is commonly applied for the analysis of foods with excellent results. In this work, the problem of the traceability of extra virgin olive oils coming from the PDO Sabina (Italy), already tackled by the same authors by means of MIR and NIR spectroscopy separately, is handled by means of different strategies of data fusion, in order to improve the results obtained from the two techniques and to demonstrate the synergistic effect of coupling information obtained from the two wavelength regions.

Mid-infrared spectral interpretation of soils: Is it practical or accurate?

There has been an increasing interest in the use of mid-infrared spectroscopy for the quantitative analysis of soils. Understanding the spectral bands can be beneficial both for understanding the basis of the quantitative analysis and soil composition and structure in general. Unfortunately, at least from the standpoint of the organic composition of soils, the spectra of most soils are dominated by the spectra of inorganic fractions such as clays, silica, carbonates, etc. One method used to accentuate the signature of the organic fraction has been to ash soil samples and then use spectral subtraction, in theory leaving only the spectral signature of the organic fraction. The objective of this work was to investigate exactly how accurate/practical this procedure is and is derived from recent comments from reviewers. Results examining silt, clays, silica, calcium carbonate, soils and materials such as cellulose and lignin show that, without considerable prior knowledge of a soil sample, spectral interpretation in most regions of the mid-infrared is highly interpretive/subjective at best. While the region for CH absorptions (3000–2800cm−1) is free of interferences, except for carbonates which can be removed by acidification, and the region between 1750–1600cm−1 can be interpreted despite the presence of strong silica bands, interpretation of the remaining regions of the mid-infrared are deemed very subjective. This is largely, but not entirely, due to the fact that many types of clay undergo extreme spectral changes from ashing and materials with seemingly similar formulas such as kaolinite (Al2Si2O5(OH)4) and pyrophyllite (Al2Si4O10(OH)2) change differently when ashed. Thus unless one knows the exact clay/mineral composition of the soil in question and the effects of ashing on said clay/mineral, accurately interpreting the ash subtracted spectra is nearly impossible. Also, even subtracting silica was found to be difficult due to changing specular effects even with KBr diluted samples. From a practical standpoint, one must conclude that the routine use of ash subtraction is not practical for soils as too much needs to be known to judge the results.

Potential of Mid-Infrared Spectroscopy for On-Line Monitoring of Mammalian Cell Culture Medium Components

This study proposed a methodology to evaluate the potential of midinfrared (MIR) spectroscopy as a process analytical technology (PAT) tool for in situ (in-line) monitoring of cell culture media constituents, paving the way for on-line bioprocess monitoring and control of mammalian cell cultures. The methodology included a limit of detection (LOD) analysis and external influence investigation in addition to the calibration model development. The LOD analysis in the initial step provided a detailed procedure by which to evaluate the monitoring potential of the instrument of choice, for the application in question. The external influence study highlighted the potential difficulties when applying this technique to a typical mammalian cell culture. A comparative investigation between a fixed conduit immersion probe and flexible fiber-optic immersion probe was also carried out. Limitations associated with the use of MIR spectroscopy in the cell culture environment were also examined. A preliminary investigation, on components typically found in mammalian cell cultures, involving spectral characterization and limit of detection analysis was completed. It was evident at this initial stage that glutamine, could not be accurately detected at levels typically found in a mammalian cell culture medium. Results for glucose and ammonia, however, proved promising. A seven-concentration-level experimental design was used, and partial least squares regression employed, to develop calibration models. Optimized model results echoed the results of the preliminary analysis with the percentage error of prediction for glucose as low as 6.03% with the fixed conduit probe and glutamine having a higher error of 63.06% for the same probe. Comparison of the model results obtained from both probes supported the fixed conduit as the more accurate of the two probes for this experimental setup. The effect of external influences on the MIR spectra and hence the concentrations predicted by the model were also examined. These were subjected to statistical analysis to determine the significance of the effect. This study demonstrates that MIR spectroscopy as a PAT tool has limited potential for mammalian cell culture monitoring due to low concentrations of analytes present and outlines a method to allow the system to be evaluated.

Determination of total phenolic content and antioxidant capacity of onion (Allium cepa) and shallot (Allium oschaninii) using infrared spectroscopy

Total phenolic content (TPC) and total antioxidant capacity (TAC) of four onion varieties (red, white, yellow and sweet) and shallot from selected locations (Washington, Idaho, Oregon, Texas and Georgia) were determined using Fourier transform infrared (FT-IR) spectroscopy (4000–400cm−1). The Folin–Ciocalteu (F–C) assay was used to quantify TPC and three assays were used to determine TAC, including 2,2-diphenyl-picrylhydrazyl (DPPH) assay, Trolox equivalent antioxidant capacity (TEAC) assay and ferric reducing antioxidant power (FRAP) assay. Partial least squares regression (PLSR) with cross-validation (leave-one-out) was conducted on onion and shallot extracts (n=200) and their corresponding F–C, DPPH, TEAC and FRAP values were employed to obtain four independent calibration models for predicting TPC and TAC for the extracts. Spectra from an extra 19 independent extracts were used as an external validation set for prediction. A correlation of r>0.95 was obtained between FT-IR predicted and reference values (by F–C, DPPH, TEAC and FRAP assay) with standard errors of calibration (SEC) and standard errors of cross-validation (SECV) less than 2.85, 0.35 and 0.45μmolTrolox/g FW of extracts for TEAC, FRAP and DPPH assay, respectively; and 0.36mggallic acid/g FW of extracts for the F–C assay. In addition, cluster analysis (principal component analysis (PCA)) and discriminant function analysis (DFA) could differentiate varieties of onions and shallot based upon infrared spectral features. Loading plots for the various chemometrics models indicated that hydroxyl and phenolic functional groups were most closely correlated with antioxidant capacity. The use of mid-infrared spectroscopy to predict the total antioxidant capacity of vegetables provides a rapid and precise alternative to traditional wet chemistry analysis.