Prediction of total fat, fatty acid composition and nutritional parameters in fish fillets using MID-FTIR spectroscopy and chemometrics

Study on the Mechanism of Effect of Protein on Starch Digestibility in Fermented Barley

Previous studies have shown that fermented barley has a lower digestion rate. However, it remains unclear whether the antidigestibility of starch in fermented barley is affected by other nonstarch components. In this paper, the removal of protein, lipid, and β-glucan improved the hydrolysis rate of starch and the protein showed the greatest effect. Subsequently, the inhibitory mechanism of protein on starch digestion was elucidated from the perspective of starch physicochemical properties and structural changes. The removal of protein increased the swelling power of starch from 10.09 to 11.14%. The short-range molecular ordered structure and the helical structure content decreased. The removal of protein reduced the coating and particle size of the starch particles, making the Maltese cross more dispersed. In summary, protein in fermented barley enhanced the ordered structure of starch by forming a physical barrier around starch and prevented the expansion of starch, which inhibited the hydrolysis of starch.

The impact of different soluble endogenous proteins and their combinations with β-glucan on the in vitro digestibility, microstructure, and physicochemical properties of highland barley starch

The impacts of protein types and its interaction with β-glucan on the in vitro digestibility of highland barley starch were investigated through analyzing physicochemical and microstructural properties of highland barley flour (HBF) after sequentially removing water- (WP), salt- (SP), alcohol- (AP) and alkali-soluble (AlkP) proteins. Resistant starch (RS) increased significantly in HBF after removing WP and SP, and RS of HBF was lower than that of without β-glucan. After removing WP, SP and AP, swelling powers of HBF without β-glucan (9.33-9.77) were higher than those of HBF (12.09-15.95). Trends of peak viscosity and peak temperature (thermal degradation temperature) were similar as swelling power, and HBF without AP showed the highest peak temperature (310.33 °C). Removals of different proteins improved the crystalline structure and short-range order of starch. There was a blue shift in T2 values and an opposite change in free water proportion. The matrix on starch surface was mainly formed by AP and AlkP, which could be aggregated by β-glucan. But, the inhibitory effect of AP or AlkP was stronger than that of proteins combined with β-glucan. These results help in the development of starch-based foods with different digestive properties by combining different protein types with β-glucan.

Effect of non-starch components on the structural properties, physicochemical properties and in vitro digestibility of waxy highland barley starch

Highland barley (HB) endosperm with an amylose content of 0-10 % is called waxy HB (WHB). WHB is a naturally slow-digesting grain, and the interaction between its endogenous non-starch composition and the WHB starch (WHBS) has an important effect on starch digestion. This paper focuses on the mechanisms by which the components of β-glucan, proteins and lipids affect the molecular, granular, crystalline structure and digestive properties of WHBS. After eliminating the main nutrients except for starch, the estimated glycemic index (eGI) of the samples rose from 62.56 % to 92.93 %, and the rapidly digested starch content increased from 60.81 % to 98.56 %, respectively. The resistant starch (RS) content, in contrast, dropped from 38.61 % to 0.13 %. Comparatively to lipids, β-glucan and protein contributed more to the rise in eGI and decline in RS content. The crystalline characteristics of starch were enhanced in the decomposed samples. The samples' gelatinization properties improved, as did the order of the starch molecules. Protein and β-glucan form a dense matrix on the surface of WHBS particles to inhibit WHBS digestion. In summary, this study revealed the mechanism influencing the digestibility of WHBS from the perspective of endogenous non-starch composition and provided a theoretical basis to develop slow-digesting foods.

Tenderness of PGI “Ternera de Navarra” Beef Samples Determined by FTIR-MIR Spectroscopy

Understanding meat quality attribute changes during ageing by using non-destructive techniques is an emergent pursuit in the agroindustry research field. Using beef certified samples from the protected geographical indication (PGI) “Ternera de Navarra”, the primary goal of this study was to use Fourier transform infrared spectroscopy on the middle infrared region (FTIR-MIR) as a tool for the examination of meat tenderness evolution throughout ageing. Samples of the longissimus dorsi muscle of twenty young bulls were aged for 4, 6, 11, or 18 days at 4 °C. Animal carcass classification and sample proximate analysis were performed to check sample homogeneity. Raw aged steaks were analyzed by FTIR-MIR spectroscopy (4000–400 cm⁻¹) to record the vibrational spectrum. Texture profile analysis was performed using a multiple compression test (compression rates of 20%, 80%, and 100%). Compression values were found to decrease notably between the fourth and sixth day of ageing for the three compression rates studied. This tendency continued until the 18th day for C20. For C80 and C100, there was not a clear change in the 11th and 18th days of the study. Regarding FTIR-MIR as a prediction method, it achieved an R² lower than 40%. Using principal component analysis (PCA) of the results, the whole spectrum fingerprint was used in the discrimination of the starting and final ageing days with correct maturing time classifications. Combining the PCA treatment together with the discriminant analysis of spectral data allowed us to differentiate the samples between the initial and the final ageing points, but it did not single out the intermediate points.

Analysis and prediction of the major fatty acids in vegetable oils using dielectric spectroscopy at 5-30 MHz

A dielectric spectroscopy method was applied to determine major fatty acids composition in vegetable oils. Dielectric constants of vegetable oils were measured in the frequency range of 5-30 MHz. After data pre-treatment, prediction models were constructed using partial least squares (PLS) regression between dielectric spectral values and the fatty acids compositions measured by gas chromatography. Generally, the root means square error of validation (RMSECV) was less than 11.23% in the prediction of individual fatty acids. The determination coefficient (R2) between predicted and measured oleic, linoleic, mono-unsaturated, and poly-unsaturated fatty acids were 0.84, 0.77, 0.84, and 0.84, respectively. These results indicated that dielectric spectroscopy coupled with PLS regression could be a promising method for predicting major fatty acid composition in vegetable oils and has the potential to be used for in-situ monitoring systems of daily consumption of dietary fatty acids.

Improvement of Oil Valorization Extracted from Fish By-Products Using a Handheld near Infrared Spectrometer Coupled with Chemometrics

A handheld near infrared (NIR) spectrometer was used for on-site determination of the fatty acids (FAs) composition of industrial fish oils from fish by-products. Partial least square regression (PLSR) models were developed to correlate NIR spectra with the percentage of saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), polyunsaturated fatty acids (PUFAs) and, among them, omega-3 (ω-3) and omega-6 (ω-6) FAs. In a first step, the data were divided into calibration validation datasets, obtaining good results regarding R² values, root mean square error of prediction (RMSEP) and bias. In a second step, all these data were used to create a new calibration, which was uploaded to the handheld device and tested with an external validation set in real time. Evaluation of the external test set for SFAs, MUFAs, PUFAs and ω-3 models showed promising results, with R² values of 0.98, 0.97, 0.97 and 0.99; RMSEP (%) of 0.94, 1.71, 1.11 and 0.98; and bias (%) values of −0.78, −0.12, −0.80 and −0.67, respectively. However, although ω-6 models achieved a good R² value (0.95), the obtained RMSEP was considered high (2.08%), and the bias was not acceptable (−1.76%). This was corrected by applying bias and slope correction (BSC), obtaining acceptable values of R² (0.95), RMSEP (1.09%) and bias (−0.05%). This work goes a step further in the technology readiness level (TRL) of handheld NIR sensor solutions for the fish by-product recovery industry.

Evaluation of Thermochemical Characteristics and Pyrolysis of Fish Processing Waste for Renewable Energy Feedstock

The necessity of energy is continuously increasing, whereas fossil fuel sources are gradually depleting. To mitigate this problem, fish processing waste of the bluespotted stingray (Neotrygon kuhlii), available in the Borneo region, was investigated for an alternative feedstock of bioenergy production. The fish wastes are hazardous for the environment, whereas the biodiesel from fish waste is pollution-free and produces less contaminant gas and carbon dioxide than fossil fuel. From the proximate analysis, the moisture content, volatile matter, fixed carbon, and ash content of the fish waste were achieved as 4.88%, 63.80%, 15.03%, and 16.29%, respectively. The proportion of carbon, hydrogen, nitrogen, sulfur, and oxygen was found as 42.06%, 5.99%, 10.77%, 0.91%, and 40.27%, respectively, from the ultimate analysis. The calorific value was 21.53 MJ/kg, which would be highly effective in biofuel production. The morphology analysis results of the biomass are favorable for renewable energy sources. The major bondage between carbon and hydrogen and oxygen was found using Fourier transform infrared spectroscopy. The thermogravimetric analysis and derivative thermogravimetry revealed that the highest weight loss occurred at 352 °C temperature with a decomposition rate of 4.57 wt.%/min in pyrolysis circumstances, and at 606 °C temperature with a decomposition rate of 3.77 wt.%/min in combustion conditions. In the pyrolysis process for 25 °C/min heating rate, the yield of biochar, bio-oil, and bio-syngas was found as 33.96, 29.34, 23.46% at 400 °C, 47.72, 49.32, 33.87% at 500 °C, and 18.32, 21.34, 42.37% at 600 °C, respectively. The characteristics and pyrolysis yields of fish waste are suitable for being an effective renewable energy source.

Extraction and characterization of Argentine red shrimp (Pleoticus muelleri) phospholipids as raw material for liposome production

Phospholipids rich in omega-3 fatty acids from Argentine red shrimp waste were explored as a source to produce food-grade liposomes. Partially purified phospholipids (PL-AS), hexane-soluble (HxSE) and acetone-soluble (Ac-SE) lipid co-extracts, were characterized in terms of extraction yield (2.0%, 1.46% and 4.51%, respectively), chemical composition (fatty acids, tocopherols, sterols, astaxanthin) and thermal stability. Based on lipid fractionation, PL-AS presented 85% phospholipids, while neutral lipids were mostly present in HxSE (75%) and free FA in AcSE (34%), the latter suggesting significant fat hydrolysis. Palmitic, oleic, eicosapentaenoic (EPA) and docosahexaenoic (DHA) acids predominated in the phospholipid fraction of PL-AS, mainly constituted by phosphatidylcholine (PC) (96%). The most abundant phospholipid was identified at m/z 760.59, composed of PC, with C16:0/C18:1 as the most probable FA combination. Unilamellar spherical liposomes were successfully made of PL-AS (≈140 nm, 0.248 PDI, -68.5 mV ζ potential), showing high stability for 28 days at 4 °C.

Evaluating low- mid- and high-level fusion strategies for combining Raman and infrared spectroscopy for quality assessment of red meat

The implementation of Raman and infrared spectroscopy with three data fusion strategies to predict pH and % IMF content of red meat was investigated. Raman and FTIR systems were utilized to assess quality parameters of intact red meat. Quantitative models were built using PLS, with model performances assessed with respect to the determination coefficient (R²), root mean square error and normalized root mean square error (NRMSEP). Results obtained on validation against an independent test set show that the high-level fusion strategy had the best performance in predicting the observed pH; with R_P² and NRMSEP values of 0.73 and 12.9% respectively, whereas low-level fusion strategy showed promise in predicting % IMF (NRMSEP = 8.5%). The fusion of data from more than one technique at low and high level resulted in improvement in the model performances; highlighting the possibility of information enhancement.

Sensing Technology for Fish Freshness and Safety: A Review

Standard analytical methods for fish freshness assessment are based on the measurement of chemical and physical attributes related to fish appearance, color, meat elasticity or texture, odor, and taste. These methods have plenty of disadvantages, such as being destructive, expensive, and time consuming. All these techniques require highly skilled operators. In the last decade, rapid advances in the development of novel techniques for evaluating food quality attributes have led to the development of non-invasive and non-destructive instrumental techniques, such as biosensors, e-sensors, and spectroscopic methods. The available scientific reports demonstrate that all these new techniques provide a great deal of information with only one test, making them suitable for on-line and/or at-line process control. Moreover, these techniques often require little or no sample preparation and allow sample destruction to be avoided.

Estimation of Fatty Acids in Intramuscular Fat of Beef by FT-MIR Spectroscopy

The aim of this research was to estimate the fatty acid (FA) content of intramuscular fat from beef by Fourier transform mid-infrared (FT-MIR) spectroscopy. Four diets were supplemented in 10% linseed (LS) and/or 2% conjugated linoleic acid (CLA): CON (without L or CLA), LS, CLA, and LS+CLA. For each diet, 12 young Holstein bulls were allocated. The spectral response of the beef samples was analyzed applying FT-MIR spectroscopy (from 400 to 4000 cm⁻¹) and predictive models were developed using partial least square regression with cross-validation. The obtained coefficients (R²) for some FA, such as α-linolenic acid with a R² = 0.96 or n-3 polyunsaturated fatty acids (n-3 PUFA) with R² = 0.93, demonstrate that FT-MIR spectroscopy is a valid technique to estimate the content of FA. In addition, samples were correctly classified according to the animal diet using discriminant analysis in the region 3000–1000 cm⁻¹. The obtained results suggest that the FT-MIR spectroscopy could be a viable technique for routine use in quality control because it provides fast and sustainable analysis of FA content. Furthermore, this technique allows the rapid estimation of the FA composition, specifically n-3 PUFA and CLA, of nutritional interest in meat. It also allows the classification of meat samples by the animal diet.

Comparison of the chemical and micromechanical properties of Larix spp. after eco-friendly heat treatments measured by in situ nanoindentation

Heat treatment is a green, environmentally friendly and mild pyrolysis process that improves the dimensional stability and durability of wood. In this study, Larix spp. Samples were heated at 180 °C and 210 °C for 6 h with nitrogen, air or oil as heat-conducting media. The influence of high-temperature heat treatment on the microstructure, chemical components, and micromechanical properties was investigated. The mass loss rate increased with increasing temperature, and the degradation of wood components resulted in cracks in the cell walls. Samples treated with air showed more cracks in cell walls than were observed in the cells walls of wood treated with the other heat-conducting media. The hardness of the cell walls increased after all heat treatments. In addition, the results showed that heat treatment reduced creep behavior compared to that of untreated wood.

Geographical discrimination of palm oils (Elaeis guineensis) using quality characteristics and UV-visible spectroscopy

This preliminary study demonstrated the possibility of discriminating geographical origin of palm oils using conventional quality characteristics and UV-visible spectroscopy. A total of 60 samples, 20 from each region (North (N), South (S), and Central (C)) of Ondo State Nigeria, were analyzed for their quality characteristics and UV-visible spectra. Principal component analysis (PCA) and orthogonal projection to latent structure discriminant analysis (OPLS-DA) were applied to elaborate the data. Models were built on the most informative portion of the spectra (250-550 nm) as: untreated (without pretreatment) and standard normal variate-second-derivative-treated (SNV+2der) data matrices. OPLS-DA classification models were validated by independent prediction sets and cross-validation. PCA score plots of both chemical and spectral data matrices revealed geographical distinction between the palm oil samples. Significantly high carotene content, free fatty acids, acid value, and peroxide value distinguished Central palm oils. K extinction values, color density, and chlorophyll content were the most important quality parameters separating North oil samples. In the discriminant models, over 95% and 85% percent correct classification were recorded for spectral and chemical data, respectively. These results cannot be considered exhaustive because of the limited sample size used. However, the study suggested a potential analytical technique suitable for geographical origin authentication of palm oils with additional advantages that include the following: speed, low cost, and minimal waste.

Study on the Characteristic Spectral Properties for Species Identification of Animal-Derived Feedstuff Using Fourier Transform Infrared Spectroscopy

The objective of the present study was to explore the effective spectral bands related to lipid characteristics in spectra of raw animal-derived feedstuff and figure out which marked spectral regions (single or combined) contributed more to species discrimination. A total of 82 meat and bone meals, including porcine, poultry, bovine, ovine, and fish, were studied. Raw materials, extracted lipid, and defatted samples were simultaneously analyzed and calculated using Fourier transform infrared (FT-IR) spectroscopy in combination with chemometric methods. Taking the spectra of lipid as references, five marked spectral regions considered the main lipid characteristic regions were found in the raw animal-derived feedstuff spectra. In the study, single and combined marked spectral bands were investigated and proved to have better performance than the whole spectra of raw terrestrial animal-derived feedstuff and fishmeal. For the discrimination of five animal species, the regions of 1800-1650 cm^-1, 1500-1330 cm^-1, 1260-1060 cm^-1, and 790-640 cm^-1 presented better results; for the classification of three categories, the regions of 3100-2800 cm^-1, 1800-1650 cm^-1, and 1500-1330 cm^-1 showed the best results.

Quality evaluation of fish and other seafood by traditional and nondestructive instrumental methods: Advantages and limitations

Although being one of the most vulnerable and perishable products, fish and other seafoods provide a wide range of health-promoting compounds. Recently, the growing interest of consumers in food quality and safety issues has contributed to the increasing demand for sensitive and rapid analytical technologies. Several traditional physicochemical, textural, sensory, and electrical methods have been used to evaluate freshness and authentication of fish and other seafood products. Despite the importance of these standard methods, they are expensive and time-consuming, and often susceptible to large sources of variation. Recently, spectroscopic methods and other emerging techniques have shown great potential due to speed of analysis, minimal sample preparation, high repeatability, low cost, and, most of all, the fact that these techniques are noninvasive and nondestructive and, therefore, could be applied to any online monitoring system. This review describes firstly and briefly the basic principles of multivariate data analysis, followed by the most commonly traditional methods used for the determination of the freshness and authenticity of fish and other seafood products. A special focus is put on the use of rapid and nondestructive techniques (spectroscopic techniques and instrumental sensors) to address several issues related to the quality of these products. Moreover, the advantages and limitations of each technique are reviewed and some perspectives are also given.

Rapid Prediction of Fatty Acid Content in Marine Oil Omega-3 Dietary Supplements Using a Portable Fourier Transform Infrared (FTIR) Device and Partial Least-Squares Regression (PLSR) Analysis

Using a portable field device, a Fourier transform infrared spectroscopy (FTIR) and partial least-squares regression (PLSR) method was developed for the rapid (<5 min) prediction of major and minor fatty acid (FA) concentrations in marine oil omega-3 dietary supplements. Calibration models were developed with 174 gravimetrically prepared samples. These models were tested using an independent validation set of dietary supplements. FAs analyzed included eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA); the sums of saturated, branched-chain, and monounsaturated FAs; and n-6, n-4, n-3, n-1, and trans polyunsaturated FA. The spectral ranges 650-1500 or 650-1500 and 2800-3050 cm^-1 provided reliable predictions for FA components in 34 neat oil products: standard error of prediction, 0.73-1.58%; residual predictive deviation, 6.41-12.6. This simple, nondestructive quantitative method is a rapid screening tool and a time and cost-saving alternative to gas chromatography for verifying label declarations and in quality control.

The Application of FT-IR Spectroscopy for Quality Control of Flours Obtained from Polish Producers

Samples of wheat, spelt, rye, and triticale flours produced by different Polish mills were studied by both classic chemical methods and FT-IR MIR spectroscopy. An attempt was made to statistically correlate FT-IR spectral data with reference data with regard to content of various components, for example, proteins, fats, ash, and fatty acids as well as properties such as moisture, falling number, and energetic value. This correlation resulted in calibrated and validated statistical models for versatile evaluation of unknown flour samples. The calibration data set was used to construct calibration models with use of the CSR and the PLS with the leave one-out, cross-validation techniques. The calibrated models were validated with a validation data set. The results obtained confirmed that application of statistical models based on MIR spectral data is a robust, accurate, precise, rapid, inexpensive, and convenient methodology for determination of flour characteristics, as well as for detection of content of selected flour ingredients. The obtained models' characteristics were as follows: R² = 0.97, PRESS = 2.14; R² = 0.96, PRESS = 0.69; R² = 0.95, PRESS = 1.27; R² = 0.94, PRESS = 0.76, for content of proteins, lipids, ash, and moisture level, respectively. Best results of CSR models were obtained for protein, ash, and crude fat (R² = 0.86; 0.82; and 0.78, resp.).

Anaerobic Codigestion of Sludge: Addition of Butcher's Fat Waste as a Cosubstrate for Increasing Biogas Production

Fat waste discarded from butcheries was used as a cosubstrate in the anaerobic codigestion of sewage sludge (SS). The process was evaluated under mesophilic and thermophilic conditions. The codigestion was successfully attained despite some inhibitory stages initially present that had their origin in the accumulation of volatile fatty acids (VFA) and adsorption of long-chain fatty acids (LCFA). The addition of a fat waste improved digestion stability and increased biogas yields thanks to the higher organic loading rate (OLR) applied to the reactors. However, thermophilic digestion was characterized by an effluent of poor quality and high VFA content. Results from spectroscopic analysis suggested the adsorption of lipid components onto the anaerobic biomass, thus disturbing the complete degradation of substrate during the treatment. The formation of fatty aggregates in the thermophilic reactor prevented process failure by avoiding the exposure of biomass to the toxic effect of high LCFA concentrations.

Development of hyperspectral imaging coupled with chemometric analysis to monitor K value for evaluation of chemical spoilage in fish fillets

K value is an important freshness index widely used for indication of nucleotide degradation and assessment of chemical spoilage. The feasibility of hyperspectral imaging (400-1000 nm) for determination of K value in grass carp and silver carp fillets was investigated. Partial least square (PLS) regression and least square support vector machines (LS-SVM) models established using full wavelengths showed excellent performances and the PLS model was better with higher determination coefficients of prediction (R(2)P = 0.936) and lower root mean square errors of prediction (RMSEP = 5.21%). The simplified PLS and LS-SVM models using the seven optimal wavelengths selected by successive projections algorithm (SPA) also presented good performances. The spatial distribution map of K value was generated by transferring the SPA-PLS model to each pixel of the images. The current study showed the suitability of using hyperspectral imaging to determine K value for evaluation of chemical spoilage and freshness of fish fillets.

Direct determination of major components in human diets and baby foods

A fast method has been developed for the determination of fat, proteins, carbohydrates, and energy value in baby food, infant fast food, and canteen menus, using near-infrared (NIR) and mid-infrared (MIR) spectroscopy measurements and multivariate calibration methods based on partial least square regression. Reference standard methods were employed to build and validate the infrared methods for direct determination of nutrients. Coefficients of determination obtained between predicted values and reference ones for total fat, proteins, carbohydrates, and energy value were 96.7, 98.1, 98.9, and 96.5 for NIR and 91.0, 93.0, 92.0, and 84.1 for MIR, respectively, with relative root mean square error of prediction (RRMSEP) below or equal to 9 % for NIR and 16 % for MIR. Results obtained indicate that both NIR and MIR techniques have good predictive capabilities, with the NIR method being the most accurate and simple.

Differentiation of fresh and frozen-thawed fish samples using Raman spectroscopy coupled with chemometric analysis

The potential of Raman spectroscopy was investigated in terms of its capability to discriminate the species of the fish samples and determine their freshness according to the number of freezing/thawing cycles they exposed. Species discrimination analysis was carried out on sixty-four fish samples from six different species, namely horse mackerel (Trachurus trachurus), European anchovy (Engraulis encrasicolus), red mullet (Mullus surmuletus), Bluefish (Pomatamus saltatrix), Atlantic salmon (Salmo salar) and flying gurnard (Trigla lucerna). Afterwards, fish samples were exposed to different numbers of freezing/thawing cycles and separated into three batches, namely (i) fresh, (ii) once frozen-thawed (OF) and (iii) twice frozen-thawed (TF) samples, in order to perform the freshness analysis. Raman data collected were used as inputs for chemometric analysis, which enabled us to develop two main PCA models to successfully terminate the studies for both species discrimination and freshness determination analysis.

Application of multivariate chemometric techniques for simultaneous determination of five parameters of cottonseed oil by single bounce attenuated total reflectance Fourier transform infrared spectroscopy

Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent.

FT-IR/ATR univariate and multivariate calibration models for in situ monitoring of sugars in complex microalgal culture media

The objective of this work is to develop a quick and simple method for the in situ monitoring of sugars in biological cultures. A new technology based on Attenuated Total Reflectance-Fourier Transform Infrared (FT-IR/ATR) spectroscopy in combination with an external light guiding fiber probe was tested, first to build predictive models from solutions of pure sugars, and secondly to use those models to monitor the sugars in the complex culture medium of mixotrophic microalgae. Quantification results from the univariate model were correlated with the total dissolved solids content (R(2)=0.74). A vector normalized multivariate model was used to proportionally quantify the different sugars present in the complex culture medium and showed a predictive accuracy of >90% for sugars representing >20% of the total. This method offers an alternative to conventional sugar monitoring assays and could be used at-line or on-line in commercial scale production systems.