Portable NIRS Research Articles

Evaluation of a low-cost portable NIRS device for monitoring muscle ischemia.

The main objective of this study is to evaluate the low-cost, open-source HEGduino device as a tissue oximetry monitor to advance the research of somatic NIRS monitoring. Specifically, this study analyzes the use of this portable functional NIRS system for detecting the cessation of blood flow due to vascular occlusion in an upper limb.19 healthy patients aged between 25 and 50 were recruited and monitored using HEGduino device. Participants underwent a vascular occlusion test on one forearm. Raw values collected by HEGduino as well as the processed variables derived from the measurements were registered. Additional variables to characterize the signal noise during the tests were also recorded.The results of the data distribution curves for all the subjects in the study accurately detected the physiological events associated with transient tissue ischemia. The statistical analysis of the recorded data showed that the difference between the baseline values recorded by the red led (RED) and its normalized minimum variable was always different from zero (p < 0.014). Furthermore, the difference between the normalized baseline values recorded by the infrared led (IR) and the corresponding normalized minimum value was also different from zero (p < 0.001). The R-squared coefficient of determination for the noise variables considered in this study on the normalized RED and IR values was 0.08 and 0.105, respectively.The study confirms the potential of HEGduino system to detect an interruption of the blood flow by means of variations in regional tissue oxygen saturation. This study demonstrates the potential of the HEGduino device as a monitoring alternative to advance the study of the applicability of NIRS in muscle tissue oximetry.

Effects of acute aerobic exercise on resting state functional connectivity of motor cortex in college students

This study intends to inspect the effects of acute aerobic exercise (AE) on resting state functional connectivity (RSFC) in motor cortex of college students and the moderating effect of fitness level. Methods: 20 high fitness level college students and 20 ordinary college students were recruited in public. Subjects completed 25 min of moderate- and high-intensity acute aerobic exercise respectively by a bicycle ergometer, and the motor cortex’s blood oxygen signals in resting state were monitored by functional Near Infrared Spectroscopy (fNIRS, the Shimadzu portable Light NIRS, Japan) in pre- and post-test. Results: At the moderate intensity level, the total mean value of RSFC pre- and post-test was significantly different in the high fitness level group (pre-test 0.62 ± 0.18, post-test 0.51 ± 0.17, t(19) = 2.61, p = 0.02, d = 0.58), but no significant change was found in the low fitness level group. At the high-intensity level, there was no significant difference in the difference of total RSFC between pre- and post-test in the high and low fitness group. According to and change trend of 190 “edges”: at the moderate-intensity level, the number of difference edges in the high fitness group (d = 0.58, 23) were significantly higher than those in the low fitness group (d = 0.32, 15), while at high-intensity level, there was a reverse trend between the high fitness group (d = 0.25, 18) and the low fitness group (d = 0.39, 23). Conclusions: moderate-intensity AE can cause significant changes of RSFC in the motor cortex of college students with high fitness, while high fitness has a moderating effect on the relationship between exercise intensity and RSFC. RSFC of people with high fitness is more likely to be affected by AE and show a wider range of changes.

Rapid quality evaluation and geographical origin recognition of ginger powder by portable NIRS in tandem with chemometrics

Ginger powder is an important spice that is susceptible to improper sales such as adulteration or geographical fraud. In this study, a portable near infrared spectroscopy was used to quantitatively predict the 6-gingerol content, an important quality index of ginger, as well as to identify the gingers from three origins in China. Specifically, the optimal preprocessing method was first investigated by comparing the predictions of models. Then three feature variable selection methods including PCA, CARS, and RFrog, on the quantitative analysis of 6-gingerol were also compared, respectively. After comparison, the PLS model established on the S-G combined with SNV preprocessing outperformed the others. The PLS regression of 6-gingerol with variables selected by RFrog possessed the Rc2 of 0.9463, Rp2 of 0.9497, and the RPD of 4.2257, respectively. Moreover, the results further verified that the LDA model by SPA variables extraction successfully identify gingers from different origins with 100 % accuracy.

Assessment of Intercostal Muscle Near-Infrared Spectroscopy for Estimating Respiratory Compensation Point in Trained Endurance Athletes.

This study aimed to assess the reliability and validity of estimating the respiratory compensation point (RCP) in trained endurance athletes by analyzing intercostal muscles' NIRS-derived tissue oxygenation dynamics. Seventeen experienced trail runners underwent an incremental treadmill protocol on two separate occasions, with a 7-day gap between assessments. Gas exchange and muscle oxygenation data were collected, and the oxygen saturation breakpoint (SmO2BP) measured in the intercostal muscles was compared to the RCP, which was identified by the increase in the VE/V.CO2 slope and the point at which the PetCO2 started to decrease. No statistically significant differences were observed between the two methods for any of the variables analyzed. Bland-Altman analysis showed significant agreement between the NIRS and gas analyzer methods for speed (r = 0.96, p < 0.05), HR (r = 0.98, p < 0.05), V.O2 relative to body mass (r = 0.99, p < 0.05), and %SmO2 (r = 0.98, p < 0.05). The interclass correlation coefficient values showed moderate to good reliability (0.60 to 0.86), and test-retest analysis revealed mean differences within the confidence intervals for all variables. These findings suggest that the SmO2BP measured using a portable NIRS device in the intercostal muscles is a reliable and valid tool for estimating the RCP for experienced trail runners and might be useful for coaches and athletes to monitor endurance training.

Non-destructive testing of mechanical properties of solid wood panel based on partial least squares structural equation modeling transfer method

Calibration transfer between near infrared (NIR) spectrometers is a subtle issue in the chemometrics and process industry. Similar instruments may generate strongly different spectral responses, and regression models developed on a first NIR system can rarely be used with spectra collected by a second apparatus. In this work, two novel methods based on Structural Equation Modeling (SEM), called Enhanced Feature Extraction Approaches for factor analysis (EFEA-FA) and Enhanced Feature Extraction Approaches for spectral space transformation (EFEA-SST), were proposed to perform calibration transfer between NIR spectrometers. They were applied to a NIR nondestructive testing model for solid wood panels mechanical properties. Four different standardization algorithms were evaluated for transferring solid wood panels quality databases between a portable NIRS (InGaAs)-array spectrometer (NIRquest512) and a HSI Camera (SPECIM FX17). The results showed that EFEA-SST yielded the best model evaluation metrics (R2 and Root Mean Square Error of Prediction (RMSEP)) values for tensile strength (RMSEP=11.309, R2=0.865) parameters, while EFEA-FA gave the best fit for flexural strength (RMSEP=10.653, R2=0. 912). These results suggest the potential of two novel quality parameters prediction methods based on spectral databases transferred between diverse NIRS spectrometers.

Convenient detection of white pepper adulteration by portable NIRS and spectral imaging with chemometrics

As an important condiment, the quality of pepper attracts much attentions. Due to the high illegitimate interests, pepper adulteration has become more and more serious. Non-destructive and low-cost adulteration detection is urgently needed in on-site scenario. As required, a portable NIR spectrometer was attempted to establish the grade recognition models by LDA, SVM, PLS-DA and SIMCA. Subsequently, quantitative modeling was carried out on piperine, and the optimal model obtained the R2c of 0.979, R2p of 0.973, and RPD of 6.05, which achieved an excellent quantitative performance. Moreover, to further visualize the adulteration, samples with different adulterant concentrations were scanned by hyperspectral imaging. The MCR-ALS was used to reduce the dimensionality of multivariate data and execute iterative calculation. Finally, the pixel concentrations in the spectral image were reconstructed to obtain the visual distribution of adulterant. Overall results demonstrate that a complete non-destructive detecting solution was provided for the analysis of adulteration of white pepper.

A proposal to identify the maximal metabolic steady state by muscle oxygenation and VO2max levels in trained cyclists

PurposeNear-infrared spectroscopy (NIRS) sensors measure muscle oxygen saturation (SmO2) as a performance factor in endurance athletes. The objective of this study is to delimit metabolic thresholds relative to maximal metabolic steady state (MMSS) using SmO2 in cyclists.MethodsForty-eight cyclists performed a graded incremental test (GTX) (100 W-warm-up followed by 30 W min) until exhaustion. SmO2 was measured with a portable NIRS placed on the vastus lateralis. Subjects were classified by VO2max levels with a scale from 2 to 5: L2 = 45–54.9, L3 = 55–64.9, L4 = 65–71, L5 = > 71, which represent recreationally trained, trained, well-trained, and professional, respectively. Then, metabolic thresholds were determined: Fatmax zone, functional threshold power (FTP), respiratory compensation point (RCP), and maximal aerobic power (MAP). In addition, power output%, heart rate%, VO2%, carbohydrate and fat consumption to cutoff SmO2 point relative to MMSS were obtained.ResultsA greater SmO2 decrease was found in cyclists with > 55 VO2max (L3, L4 and L5) vs. cyclists (L2) in the MMSS. Likewise, after passing FTP and RCP, performance is dependent on better muscle oxygen extraction. Furthermore, the MMSS was defined at 27% SmO2, where a non-steady state begins during exercise in trained cyclists.ConclusionA new indicator has been provided for trained cyclists, < 27% SmO2 as a cut-off to define the MMSS Zone. This is the intensity for which the athlete can sustain 1 h of exercise under quasi-steady state conditions without fatiguing.

Assessment of the Effectiveness of a Portable NIRS Instrument in Controlling the Mixer Wagon Tuning and Ration Management.

Simple SummaryThe total mixed ration is widely adopted in herds feeding, and its success has paved the way for the use of the feed mixer wagon. The increase in milk production demands a higher feed efficiency that considers the chemical and physical quality of the ration, even in terms of fiber physical effectiveness, ration homogeneity, and cow feed sorting. These requirements presuppose a correct ration formulation and accurate preparation, even through an optimal mixer wagon setting. Here, we proposed an efficient, rapid, and easy method for ration preparation and quality control. A portable Near-InfraRed instrument was tested for primary chemical and physical evaluation of the ration, including the particle size and the physical effective fiber content. Moreover, the instrument allowed the calculation of two indexes to evaluate the ration homogeneity and cow sorting activity. Finally, these traits were compared with the feed mixer wagon setting and feed characteristics. As a result, we found that for the overload of the feed mixer wagon, the higher humidity and fiber contents of the ration caused a lower homogeneity, and the higher fiber content facilitated the cow sorting activity.The adoption of the mixer wagon and total mixed ration aimed to decrease dysmetabolic diseases and improve feed efficiency in dairy cows. Differences between theoretical and eaten diets are imputable to errors in diet preparation or cow feed sorting. We proposed a method to measure the chemical composition and particle size distribution of the ration and determined its peNDF content through a portable Near Infra-Red spectrophotometer that allowed the calculation of two indexes: the homogeneity and the sorting indexes. In a cohort of 19 Italian Holstein breeding farms, we studied the correlation of these indexes with the mixer wagon settings. Determination coefficients in the validation (Rv2) for dry matter, crude protein, aNDF, and starch were 0.91, 0.54, 0.86, and 0.67, respectively. The ration fractions (%, w/w of wet weight) retained by the 3.8 and 1.8 mm sieves, and the bottom showed Rv2 of 0.46, 0.49, and 0.53, respectively. The homogeneity index regressed negatively with the mixer wagon load fullness (R2 = 0.374). The homogeneity-binary classification showed an odds ratio of 1.72 for dry matter and 0.39 for aNDF (p < 0.05). The sorting-binary classification showed an odds ratio of 2.54 for aNDF (p < 0.05). The studied farms showed low peNDF values (median = 17.9%).

Determination of Sex in Ungulate Herbivores via near Infrared Spectroscopy of Hair: Growing Cattle as a Surrogate Model

Abstract Near infrared spectroscopy (NIRS) has been used in a variety of medical and veterinary science applications. In particular, NIRS calibrations have been developed in livestock for steroid content in cattle hair, and wound age or stage of healing in hot iron cattle brands. These NIRS applications also have potential utility in forensic science. Portable NIRS instruments facilitate measurements on live animals and or animal samples in the field. The objective of this study was to evaluate the efficacy of determining sex in growing cattle via NIRS of hair utilizing a portable spectrometer. In two consecutive years, log 1/R spectra (350–2500 nm) were collected using an ASD Field Spec fitted with a contact probe. Experimental subjects were Bos taurus cross calves (n = 12, yr 1; n = 14, yr 2) born to cows grazing central Arizona rangeland. Calf age was approximately 60, 90 and 210 d at branding, estrus synchronization, and weaning, respectively. As cattle were gathered for these routine working events, a total of 7 M and 19 F calves were scanned 3 times each over the left ribcage. A linear discriminant function was applied to spectral data in order to determine sample membership in M or F groups at each collection date. Chi-square procedures were used to determine differences (P &amp;lt; 0.05) in proportion of correct identifications per group and collection date. Overall, 86% of F and 72% of M were correctly (P &amp;lt; 0.05) identified. Corresponding values were 82% for F and 71% for M at branding, 100% for F and 89% for M at estrus synchronization, and 86% for F and 64% for M at weaning. Calf sex was successfully determined using portable NIRS in this proof of concept study. Efficacy of this method should be evaluated for different ungulate herbivores and under additional collection scenarios.

Identification of mahogany sliced veneer using handheld near-infrared spectroscopy device and multivariate data analysis

Abstract The illegal logging of valuable tree species is mainly motivated by a global market that consumes logs, lumber, veneers, and furniture. The use of objective techniques to identify species and the effects of international initiatives such as CITES rules contributes to controlling trade, exploitation, and smuggling of these products. The anatomical identification of wood veneers is limited due to the loss of several anatomical characters in the production process of the veneers. For this reason, we propose the Near-Infrared Spectroscopy technique associated with chemometric tools for the discrimination of wood veneer of woods with similar general characters: Swietenia macrophylla King (mahogany), Carapa guianensis Aubl. (andiroba), Cedrela odorata L. (cedro), Micropholis venulosa Pierre (curupixá), and Hymenaea coubaril L. (jatobá) using a portable spectrometer.The development of the discrimination models was performed using the PLS-DA (Partial Least Squares for Discriminant Analysis) algorithm. The detection and subsequent exclusion of outliers were performed based on Hotelling T2, Q residuals, and errors in estimating class values. The PLS-DA models showed an efficiency between 96.5% and 100% in the samples’ discrimination among the five forest species. In conclusion, the portable NIRS technology and the PLS-DA models were suitable for the rapid identification and discrimination of the wood veneers.

Corrigendum to: Optimisation of dry matter and nutrients in feed rations through use of a near-infrared spectroscopy system mounted on a self-propelled feed mixer

Context Knowledge of the nutrient requirements of dairy cows, and the nutritional composition and physical form of the feed resources used to prepare the total mixed ration (TMR) of basic and concentrated feeds, is essential to achieving high milk yields, health and welfare in modern commercial herds. Grass and maize silage components can vary widely in composition depending on harvesting intervals and weather; thus, the distribution of dry matter (DM) and nutrients in silos may vary greatly, resulting in serious errors during sampling and analysis. In addition, the flow of information from the stored silage stops once the forages are stored in the silo. Aims The objective of this study was to develop a practical approach for measuring variations in DM and silage quality parameters (crude protein, fibre, ash and fat) during the feed-extraction process from a bunker silo by a self-propelled feed mixer, which would ultimately help farmers to optimise the TMR. Methods Near-infrared spectroscopy (NIRS) technology was used to estimate fodder DM and nutrient contents in the material flow. Wet chemical analyses were used for preliminary evaluation of grass and maize silage samples. A portable NIRS was developed to record the spectra of various silage samples. Key results The spans of calibration of sample DM content were 21.3–59.2% for grass and 26–46.7% for maize. Crude protein content had span values of 11.4–18.3% for the grass silage and 5.4–10.8% for the maize silage models. Conclusions NIRS technology was used successfully to estimate the DM and nutrient contents of the fodder. The location for the functional unit on the self-propelled feed mixer may need to be modified for series production because it is not fully accessible. Implications NIRS is a suitable method for measuring DM and nutrient contents continuously during feed extraction from the bunker silo and can be used to help farmers to optimise the TMR.

Large-Area, Fast-Gated Digital SiPM With Integrated TDC for Portable and Wearable Time-Domain NIRS

We present the design and characterization of a large-area, fast-gated, all-digital single-photon detector with programmable active area, internal gate generator, and time-to-digital converter (TDC) with a built-in histogram builder circuit, suitable for performing high-sensitivity time-domain near-infrared spectroscopy (TD-NIRS) measurements when coupled with pulsed laser sources. We used a novel low-power differential sensing technique that optimizes area occupation. The photodetector is a time-gated digital silicon photomultiplier (dSiPM) with an 8.6-mm2 photosensitive area, 37% fill-factor, and ~300 ps (20%–80%) gate rising edge, based on low-noise single-photon avalanche diodes (SPADs) and fabricated in 0.35- $\mu \text{m}$ CMOS technology. The built-in TDC with a histogram builder has a least-significant-bit (LSB) of 78 ps and 128 time-bins, and the integrated circuit can be interfaced directly with a low-cost microcontroller with a serial interface for programming and readout. Experimental characterization demonstrated a temporal response as good as 300-ps full-width at half-maximum (FWHM) and a dynamic range >100 dB (thanks to the programmable active area size). This microelectronic detector paves the way for a miniaturized, stand-alone, multi-wavelength TD-NIRS system with an unprecedented level of integration and responsivity, suitable for portable and wearable systems.

Monitoring the Processing of Dry Fermented Sausages with a Portable NIRS Device.

This work studies the ability of a MicroNIR (VIAVI, Santa Rosa, CA) device to monitor the dry fermented sausage process with the use of multivariate data analysis. Thirty sausages were made and subjected to dry fermentation, which was divided into four main stages. Physicochemical (weight lost, pH, moisture content, water activity, color, hardness, and thiobarbiruric reactive substances analysis) and sensory (quantitative descriptive analysis) characterizations of samples on different steps of the ripening process were performed. Near-infrared (NIR) spectra (950–1650 nm) were taken throughout the process at three points of the samples. Physicochemical data were explored by distance to K-Nearest Neighbor (K-NN) cluster analysis, while NIR spectra were studied by partial least square–discriminant analysis; before these models, Principal Component Analysis (PCA) was performed in both databases. The results of multivariate data analysis showed the ability to monitor and classify the different stages of ripening process (mainly the fermentation and drying steps). This study showed that a portable NIR device (MicroNIR) is a nondestructive, simple, noninvasive, fast, and cost-effective tool with the ability to monitor the dry fermented sausage processing and to classify samples as a function of the stage, constituting a feasible decision method for sausages to progress to the following processing stage.

Genetic Correlation, Genome-Wide Association and Genomic Prediction of Portable NIRS Predicted Carotenoids in Cassava Roots.

Random forests (RF) was used to correlate spectral responses to known wet chemistry carotenoid concentrations including total carotenoid content (TCC), all-trans β-carotene (ATBC), violaxanthin (VIO), lutein (LUT), 15-cis beta-carotene (15CBC), 13-cis beta-carotene (13CBC), alpha-carotene (AC), 9-cis beta-carotene (9CBC), and phytoene (PHY) from laboratory analysis of 173 cassava root samples in Columbia. The cross-validated correlations between the actual and estimated carotenoid values using RF ranged from 0.62 in PHY to 0.97 in ATBC. The developed models were used to evaluate the carotenoids of 594 cassava clones with spectral information collected across three locations in a national breeding program (NRCRI, Umudike), Nigeria. Both populations contained cassava clones characterized as white and yellow. The NRCRI evaluated phenotypes were used to assess the genetic correlations, conduct genome-wide association studies (GWAS), and genomic predictions. Estimates of genetic correlation showed various levels of the relationship among the carotenoids. The associations between TCC and the individual carotenoids were all significant (P < 0.001) with high positive values (r > 0.75, except in LUT and PHY where r < 0.3). The GWAS revealed significant genomic regions on chromosomes 1, 2, 4, 13, 14, and 15 associated with variation in at least one of the carotenoids. One of the identified candidate genes, phytoene synthase (PSY) has been widely reported for variation in TCC in cassava. On average, genomic prediction accuracies from the single-trait genomic best linear unbiased prediction (GBLUP) and RF as well as from a multiple-trait GBLUP model ranged from ∼0.2 in LUT and PHY to 0.52 in TCC. The multiple-trait GBLUP model gave slightly higher accuracies than the single trait GBLUP and RF models. This study is one of the initial attempts in understanding the genetic basis of individual carotenoids and demonstrates the usefulness of NIRS in cassava improvement.

Matching portable NIRS instruments for in situ monitoring indicators of milk composition

The real time knowledge of dairy milk composition can be used as a tool to guarantee milk quality and safety, offering additional information for dairy producers and consumers. To carry out these in situ analyses, methodologies based on Near Infrared (NIR) portable sensors have a great potential as an advisory tool. The main goals of the present work have been to develop a methodology using a hand-held portable NIR spectrophotometer to collect raw milk spectra, including the development of calibration models for the analysis of protein, fat and solids-non-fat (SNF) of raw milk and further to transfer the developed models to another portable unit. A total of 542 fresh milk samples were scanned over the NIR spectral range (1600–2400 nm) using a hand-held MicroPhazir™ (MP) NIR spectrometer and different instrumental configurations. The best results for repeatability and reproducibility calculated as root mean squared (RMS) were obtained using a 17 mm cuvette thickness. The displayed predictive ability of calibration models measured as Standard error of prediction/Standard error of cross validation were 0.96; 0.72 and 0.83 for fat, protein and SNF contents, respectively. For cloning purposes an additional MP unit (satellite) has been used. A standardization set of 10 samples enabled standardization of both instruments. After applying standardization matrix, Standard error of differences between master and satellite reached great reduction, 68% for fat, 66% for protein and 54% for SNF. Moreover, the demonstrated ability of sharing calibration models among several units is essential for implementation of portable instruments for in-situ analysis to provide indicators of milk composition at farm level.

Bootstrap Analyses of Anxiety Index Measuring the Prefrontal Cortex of Subjects at Rest with Two-Channel Portable NIRS Device

ABSTRACTThis article presents statistical analyses of a mental stress index obtained with a two-channel portable near-infrared spectroscopy device placed on the forehead of a subject at rest. Using nonparametric bootstrap analyses, the authors show that the distribution of the Pearson correlation coefficient between the target NIRS-based index and the State Trait Anxiety Inventory index is positive. Further, they show that the correlation coefficient is statistically invariant to age, gender, and location, insofar as the null hypothesis—that is, when the two distributions are equivalent—is not rejected. Finally, they show that there is a sharper distribution to the Pearson correlation coefficient and a higher mean value for subjects under mental stress than for subjects at rest. Because the device is easy to wear, and because the proposed index is relatively simple, the target index can be used in conjunction with the device to help users (regardless of age, gender, and location) to manage mental stress.

Gender and Age Analyses of NIRS/STAI Pearson Correlation Coefficients at Resting State.

According to the valence asymmetry hypothesis, the left/right asymmetry of PFC activity is correlated with specific emotional responses to mental stress and personality traits. In a previous study we measured spontaneous oscillation of oxy-Hb concentrations in the bilateral PFC at rest in normal adults employing two-channel portable NIRS and computed the laterality index at rest (LIR). We investigated the Pearson correlation coefficient between the LIR and anxiety levels evaluated by the State-Trait Anxiety Inventory (STAI) test. We found that subjects with right-dominant activity at rest showed higher STAI scores, while those with left dominant oxy-Hb changes at rest showed lower STAI scores such that the Pearson correlation coefficient between LIR and STAI was positive. This study performed Bootstrap analysis on the data and showed the following statistics of the target correlation coefficient: mean=0.4925 and lower confidence limit=0.177 with confidence level 0.05. Using the KS-test, we demonstrated that the correlation did not depend on age, whereas it did depend on gender.

The Analysis of the Brain State Measuring by NIRS-based BMI in Answering yes-no Questions

Abstract In recent years, Brain-Machine Interface (BMI) has been improved with the rapid development of the cerebral function measurement technologies. BMI is used for measuring the brain activity of the subjects and inferring his/her intention. These measuring results can control the devices such as the electric wheelchair or the electric arm directly. Previous studies have such problems that BMI device is not portable, and it takes much time to attach a lot of sensor nodes on the head of the subject. Therefore, we use portable NIRS, because it is easy for the subjects to mount it and their burden is low. This paper describes the analytical method for cerebral blood flow during imagining affirmative or negative answers to the questions. It was verified whether it is possible to use the NIRS as BMI to discriminate the yes answer or no without voice and gesture. In our study, a subject keeps watching the display which shows a yes-no question, he/she imagines affirmative or negative answer to the questions. In the experiment, one test trial is in 30 seconds and it includes 10 seconds task between 10 seconds rests. Each test set consists of 10 trials. One subject has five test set. In our study, we used Wearable Optical Topography WOT-100 as measurement device of NIRS which has 10 channels (ch7-16) of prefrontal cortex. The NIRS data analysis procedure is as follows; in the first step, we used a band-pass filter to select the data of frequencies from 0.02 Hz up to 0.1 Hz. In the second step, measured NIRS data of each task set is divided into 10 blocks which are included 5 seconds data before the task and 10 seconds data after the task. In the third step, we calculated baseline of measured data from 5 seconds of the beginning and the end of the task blocks, and this baseline fitting is applied to the original data. In the last step, the neural network learned the important elements of the training data and classified the test data. Our method can discriminate between imagining affirmative or negative answers with 70% accuracy. At result, NIRS is useful to discriminate the yes-no answer of the questions.

Non destructive spectral sensors for authentication of the feeding regime of Iberian hams during the salting process

The authentication of the feeding regime followed by Iberian pigs during the stage prior to their slaughtering is critical and necessary for each of the stages of the production process of the ham. The high price of this product demands the study of non-destructive methods that can be applied by the industry and its members. This paper reports on the performance of a handheld micro-electro-mechanical system (MEMS)-based spectrometer (1600–2400 nm) for in situ and non-destructive authentication of the feeding regime (“Acorn” vs. “Feed”) on meat (Adductor muscle) and skinfree fat of Iberian hams at two different stages of the processing – before and after salting. A total of 560 spectra (280 spectra before and 280 after salting) from 140 Iberian pigs hams raised under different feeding regimes (60 fed on “Feed” and 80 fed on “Acorn”) were recorded on meat and fat tissue. Various mathematical and scatter correction treatments were tested and used to develop Partial Least Squares Discriminant Analysis (PLS2-DA) models for the authentication of the feeding regime for meat and fat tissue, before and after salting. PLS2-DA models developed for meat and fat tissue showed excellent results reaching values of 98.3–100% of correct classifications. The methodology presented here, based on discriminant analysis using a portable NIRS device provides the industry with a reliable, fast and affordable means of authenticating the feeding regime of Iberian hams throughout the critical salting process.

Calibration transfer of intact olive NIR spectra between a pre-dispersive instrument and a portable spectrometer

The recent development of new portable devices enables the establishment of NIRS technology at industrial setting (on-line). However, the numerous existing NIRS databases based on a particular parameter, have been constructed with laboratory instruments (off-line), which have required a considerably effort in terms of time, labor and costs. For this reason, the transfer of calibrations between devices of different characteristics is a clearly crucial step. In this study, three different standardization algorithms: Slope/Bias Correction (SBC), Piecewise Direct Standardization (PDS) and Transfer by Orthogonal Projection (TOP) were tested and evaluated for transferring olives quality databases between an off-line NIRS monochromator (FOSS NIRSystem 6500) and a portable NIRS diode-array spectrometer (CORONA 45 visNIR). The results obtained showed that the use of TOP yielded the best Standard Error of Prediction (SEP) values for the fat content (1.97%) and free acidity (2.52%) parameters, while PDS for moisture content (2.24%). These results suggest that good calibration models for quality evaluation in intact olives can be obtained, based on spectral databases transferred between diverses NIRS spectrometers.