Near-infrared Device Research Articles

Concentration-Dependent NIR emission of Cr3+ in a Two-site Occupancy within K4Ga3Ta(PO4)6

Near-infrared (NIR) light sources have been widely used in spectroscopy. The multi-lattice site occupation strategy is an effective approach to realize the multifunctional application of phosphors. Here, a novel double lattice site-occupied K4Ga3Ta(PO4)6:Cr3+ phosphor is reported. The concentration-dependent luminescence properties of two-site Cr3+ were investigated. The Cr1 site has a dominant role in the luminescence performance of the material. When x = 0.15, the Cr1 site has the highest luminescence percentage, and K4Ga2.85Ta(PO4)6:0.15Cr3+ shows the best luminescence performance. Under 463nm excitation, the emission peak of K4Ga2.85Ta(PO4)6:0.15Cr3+ is centered at 873nm, and the full width at half maximum (FWHM) is 188nm. The fabricated NIR device with this material shows potential applications in night vision, compositional analysis, and bio-imaging.

Fruit Sorting Based on Maturity Reduces Internal Disorders in Vapor Heat-Treated ‘B74’ Mango

Postharvest internal disorders (IDs) in mango fruit present a significant challenge to the industry, with their underlying causes still unclear. This study investigated the relationship between fruit maturity and the susceptibility of vapor heat-treated (VHT) ‘B74’ mangoes to IDs in three experiments. In the first experiment, fruit were categorized into three maturity groups based on dry matter content (DMC): <15%, 15–17%, and >17%, using a handheld near-infrared device. Half of the fruit in each group underwent VHT, while the remainder were untreated controls. Flesh cavity with white patches (FCWP) was the only disorder observed exclusively in VHT fruit. The incidence and severity of FCWP was significantly higher (p < 0.05) in fruit with <15% DMC, with 12.4% incidence and a severity score of 0.2 on a 0–3 scale (0: healthy and 3: severely affected), compared to more mature fruit. In the second experiment, the fruits were harvested at early and late maturity stages, with average DMC values of 14.5% and 17.4%, respectively. The fruit was subjected to no VHT, VHT, and VHT following a 12 h pre-conditioning period at 37 ± 1 °C. Consistent with the first experiment, FCWP was observed only in VHT fruit, with early-harvested fruit displaying a significantly higher (p < 0.05) FCWP incidence (26.9%) and severity (0.3) compared to late-harvested fruit (8.3% incidence and 0.1 severity). Pre-conditioning significantly reduced FCWP, particularly in early-harvested fruit. In the third experiment, fruit maturity sorted based on density was assessed, followed by VHT and simulated sea freight under controlled (CA) and ambient atmospheres. Fruit density did not effectively differentiate maturity considering DMC as a maturity indicator. Storage conditions significantly reduced (p < 0.05) flesh browning incidence from 71.1% under ambient conditions to 33.3% under CA. This study highlights fruit maturity as a key factor in the susceptibility of ‘B74’ mangoes to postharvest IDs following VHT. Therefore, sorting fruit based on DMC at harvest or at the packing facility prior to VHT serves as a valuable decision support for reducing IDs in VHT fruit. Further research will explore advanced technologies to enable rapid and efficient fruit sorting based on DMC.

Handheld NIR Spectroscopy Combined with a Hybrid LDA-SVM Model for Fast Classification of Retail Milk.

The EU market offers different types of milk, distinguished by origin, production method, processing technology, fat content, and other characteristics, which are often detailed on product labels. In this context, ensuring the authenticity of milk is crucial for maintaining standards and preventing fraud. Various food authenticity techniques have been employed to achieve this. Among them, near-infrared (NIR) spectroscopy is valued for its non-destructive and rapid analysis capabilities. This study evaluates the effectiveness of a miniaturized NIR device combined with support vector machine (SVM) algorithms and LDA feature selection to discriminate between four commercial milk types: high-quality fresh milk, milk labeled as mountain product, extended shelf-life milk, and TSG hay milk. The results indicate that NIR spectroscopy can effectively classify milk based on the type of milk, relying on different production systems and heat treatments (pasteurization). This capability was greater in distinguishing high-quality mountain and hay milk from the other types, while resulting in less successful class assignment for extended shelf-life milk. This study demonstrated the potential of portable NIR spectroscopy for real-time and cost-effective milk authentication at the retail level.

Evaluation of phenolics in the analysis of virgin olive oil using near infrared spectroscopy

Olive oil is an indispensable part of the diet in Mediterranean regions, and is appreciated worldwide for its sensory characteristics, combining a fine aroma and pleasant flavor with the high nutritional value of specific chemical compounds. However, making rapid measurements of phenolic compounds is a major challenge for the olive oil sector. The development of a new method based on near infrared (NIR) spectroscopy may be considered an important advance for the sector, as it is rapid, low-cost, non-contaminant and non-destructive. In this study, three different NIR instruments – one FT-NIR benchtop instrument (671.82–2702.70 nm) and two low-cost portable devices (900–1700 nm and 1350–2150 nm) – were used to analyze a collection of virgin olive oil samples from various Mediterranean regions. To predict both the individual and total concentration of phenols in the olive oil, four signal pretreatment methods and modified partial least squares regression analyses were employed to develop the predictive models. The results showed that the benchtop FT-NIR instrument performed better than the other portable instruments when measuring the phenolic compounds in virgin olive oil. The best models of hydroxytyrosol derivatives, tyrosol derivatives, total phenols and “EFSA phenols” showed R2cv values of 0.84, 0.85, 0.88 and 0.89, while the RPDcv values were 2.51, 2.61, 2.93 and 2.95, respectively. Meanwhile, for the portable NIR instruments, the prediction models for hydroxytyrosol derivatives, total phenols and “EFSA phenols” (the sum of the hydroxityrosol and tyrosol derivatives) showed R2cv values ranging between 0.75 and 0.81 and an RPDcv between 2 and 2.5. These results indicate the great potential of NIR, both with benchtop and portable devices, to detect phenolic compounds in virgin olive oil, which can guarantee the quality of virgin olive oil and thus aid progress in the olive oil industry. Moreover, this is the first published work to determine phenolic compounds in virgin olive oil using portable NIR instruments.

Qualitative and Quantitative Potential of Low-Cost Near-Infrared (NIR) Devices for Rapid Analysis of Infant Formulas for Regular and Special Needs

Qualitative and Quantitative Potential of Low-Cost Near-Infrared (NIR) Devices for Rapid Analysis of Infant Formulas for Regular and Special Needs

Performance Comparison of Two Portable Near-infrared Devices for Rapid Authentication of Aceh Aromatic Rice ‘Sigupai’

Sigupai rice, Indonesia local aromatic rice varieties grown in South-West region of Aceh, is highly valued for its fragrance and quality, making it susceptible to adulteration. This study compares the performance of two portable Near-infrared (NIR) devices, SCiO and NeoSpectra, for rapid authentication of Sigupai rice. We evaluated 86 samples for qualitative analysis (i.e. authentic vs adulterated rice) and 44 samples for quantitative analysis (i.e. the level of adulteration). For the qualitative analysis using partial least squares-discriminant analysis (PLS-DA), the best estimation model could differentiate authentic and adulterated samples with an accuracy, sensitivity, specificity, and false positive rates of 89.29%, 92.86%, 85.71% and 14.29% for the NeoSpectra and 97.44%, 100%, 94.87%, and 5.13% for the SCiO, respectively at the validation stage. For quantitative analysis using partial least squares-regression (PLS-R), the best estimation model could estimate the level of adulteration with a coefficient of determination (R²), RMSEP, RPD, and consistency values of 0.92, 1.50%, 5.93 and 100.69% for the NeoSpectra and 0.96, 1.31%, 6.83 and 104.78% for the SCiO. Both portable NIR devices could be used as a rapid analysis tool for the authenticity of Sigupai rice with high accuracy. However, in this study the SCiO device showed a better performance. Keywords: Portable NIR device, Authentication, Aromatic rice, Rapid analysis, Sigupai variety.

Advancing Glucose Monitoring: A Near-Infrared Device for Continuous Invasive Assessment

Diabetes is a chronic disease that affects millions of people worldwide, with the number of newly diagnosed cases continuing to rise at an alarming rate. Patients diagnosed with diabetes require routine monitoring of their blood glucose levels, which is commonly done through invasive and minimally invasive techniques. However, these methods are often painful, prone to infection, and costly in the long run. Therefore, it is necessary to develop non-invasive, pain-free, affordable glucose monitoring techniques. Near-infrared spectroscopy has emerged as a promising technique among the non-invasive techniques for glucose monitoring, with several studies reporting its efficacy in detecting glucose concentration. This study designed and developed a near-infrared system based on an 1150nm wavelength for continuous non-invasive glucose monitoring. The system gave the output voltages that vary with increased glucose concentrations. It was ascertained from the Clark error grid analysis that the glucose concentration falls within region A and region B. This implies that the device is suitable for measuring glucose concentration non-invasively. As per Bland Altman's analysis, the majority of the data points were within both limits of agreement except one data point that was outside the upper limit of agreement, indicating 93% degree of accuracy, and the residual plot indicates that the regression model for the system is appropriate for predicting non-invasive glucose measurements.

Non-destructive prediction of fertility and sex in chicken eggs using the short wave near-infrared region

The objective of this study was to evaluate the ability of a handheld near-infrared device (900–1600 nm) to predict fertility and sex (male and female) traits in-ovo. The NIR reflectance spectra of the egg samples were collected on days 0, 7, 14 and 18 of incubation and the data was analysed using principal component analysis (PCA), linear discriminant analysis (LDA) and support vector machines classification (SVM). The overall classification rates for the prediction of fertile and infertile egg samples ranged from 73 % to 84 % and between 93 % to 95 % using LDA and SVM classification, respectively. The highest classification rate was obtained on day 7 of incubation. The classification between male and female embryos achieved lower classification rates, between 62 % and 68 % using LDA and SVM classification, respectively. Although the classification rates for in-ovo sexing obtained in this study are higher than those obtained by chance (50 %), the classification results are currently not sufficient for industrial in-ovo sexing of chicken eggs. These results demonstrated that short wavelengths in the NIR range may be useful to distinguish between fertile and infertile egg samples at days 7 and 14 during incubation.

Measurement errors and implications for preprocessing in miniaturised near-infrared spectrometers: Classification of sweet and bitter almonds as a case of study

Near-infrared (NIR) spectroscopy is a well-established analytical technique that has been used in many applications over the years. Due to the advancements in the semiconductor industry, NIR instruments have evolved from benchtop instruments to miniaturised portable devices. The miniaturised NIR instruments have gained more interest in recent years because of the fast and robust measurements they provide with almost no sample pretreatments.However, due to the very different configurations and characteristics of these instruments, they need a dedicated optimization of the measurement conditions, which is crucial for obtaining reliable results. To comprehensively grasp the capabilities and potentials offered by these sensors, it is imperative to examine errors that can affect the raw data, which is a facet frequently overlooked. In this study, measurement error covariance and correlation matrices were calculated and then visually inspected to gain insight into the error structures associated with the devices, and to find the optimal preprocessing technique that may result in the improvement of the models built.This strategy was applied to the classification of sweet and bitter almonds, which were measured with the three portable low-cost NIR devices (SCiO, FlameNIR+ and NeoSpectra Micro Development Kit) after removing the shelled, since their classification is of utmost importance for the almond industry. The results showed that bitter almonds can be classified from sweet almonds using any of the instruments after selecting the optimal preprocessing, obtained through inspection of covariance and correlation matrices. Measurements obtained with FlameNIR + device provided the best classification models with an accuracy of 98 %. The chosen strategy provides new insight into the performance characterization of the fast-growing miniaturised NIR instruments.

Comparative analysis of NIR point source and surface array probes in two-phase flow measurement model

As one of the most significant parameters, phase fraction is of great importance for ensuring the accuracy of two-phase flow measurement. Although near-infrared (NIR) technology has been widely used, its accuracy remains limited. Two methods have been proposed to reduce the energy loss of near-infrared light transmission signal in two-phase flow: the point light source method, which shortens optical path and the array light source method for increasing light source area. Experiments were conducted on single phase flow and gas–liquid two-phase flow, and the results indicated that the signal transmission effect of the point source near-infrared device was better. Using the experimental results from the point source near-infrared device, phase fraction models for bubble flow, annular flow, and slug flow were established. Validation results demonstrate that the relative measurement error of the three phase fraction models is within ± 4.96 %.

Validation of a handheld near-infrared spectrophotometer for measurement of chemical intramuscular fat in Australian lamb

The objective of the study was to independently validate a calibrated commercial handheld near infrared (NIR) spectroscopic device and test its repeatability over time using phenotypically diverse populations of Australian lamb. Validation testing in eight separate data sub-groups (n = 1591 carcasses overall) demonstrated that the NIR device had moderate precision (R2 = 0.4–0.64, RMSEP = 0.70–1.22%) but fluctuated in accuracy between experimental site demonstrated by variable slopes (0.50–0.94) and biases (−0.86–0.02). The repeatability experiment (n = 10 carcasses) showed that time to scan post quartering affected NIR measurement from 0 to 24 h (P < 0.001). On average, NIR IMF% was 0.97% lower (P < 0.001) at 24 h (4.01% ± 0.166), compared to 0 h. There was no difference (P > 0.05) between Time 0 and 1 h or Time 0 and 4 h or between replicate scans within each time point. This study demonstrated the SOMA NIR device could predict lamb chemical IMF% with moderate precision and accuracy, however additional work is required to understand how loin preparation, blooming and surface hydration affect NIR measurement.

Controlling Interfacial Amidation Reaction Rate to Regulate Crystal Growth toward High-Performance FAPbBr3-Based Inverted Light-Emitting Diodes.

Controlling interfacial reactions is critical for zinc oxide (ZnO)-based inverted perovskite light-emitting diodes (PeLEDs), boosting the external quantum efficiency (EQE) of the near-infrared device to above 20%. However, violent interfacial reactions between the bromine-based perovskites and ZnO-based films severely limit the performance of inverted green PeLEDs, whose efficiency and stability lag far behind those of their near-infrared counterparts. Here, a controllable interfacial amidation between the bromine-based perovskites and magnesium-doped ZnO (ZnMgO) film utilizing caprylyl sulfobetaine (SFB) is realized. The SFB molecules strongly interact with formamidinium bromide, decelerating the amidation reaction between formamidinium and carboxylate groups on the ZnMgO film, thus regulating the crystallization of FAPbBr3. Combined with the passivation of benzylamine, a FAPbBr3 bulk film directly deposited on a ZnMgO substrate with single-crystal characteristics is obtained, exhibiting a high photoluminescence quantum yield of above 80%. The resultant PeLEDs demonstrate a peak EQE of exceeding 20% at a high luminance of 120,000 cd m-2 and a half lifetime of 26 min at 11,000 cd m-2, representing the state-of-the-art inverted green electroluminescence. This work resolves the crucial issues of violent interfacial reactions and provides a strategy toward inverted green PeLEDs with outstanding performance.

Non-Destructive Near-Infrared Technology for Efficient Cannabinoid Analysis in Cannabis Inflorescences.

In the evolving field of cannabis research, scholars are exploring innovative methods to quantify cannabinoids rapidly and non-destructively. This study evaluates the effectiveness of a hand-held near-infrared (NIR) device for quantifying total cannabidiol (total CBD), total delta-9-tetrahydrocannabinol (total THC), and total cannabigerol (total CBG) in whole cannabis inflorescences. Employing pre-processing techniques, including standard normal variate (SNV) and Savitzky-Golay (SG) smoothing, we aim to optimize the portable NIR technology for rapid and non-destructive cannabinoid analysis. A partial least-squares regression (PLSR) model was utilized to predict cannabinoid concentration based on NIR spectra. The results indicated that SNV pre-processing exhibited superior performance in predicting total CBD concentration, yielding the lowest root mean square error of prediction (RMSEP) of 2.228 and the highest coefficient of determination for prediction (R2P) of 0.792. The ratio of performance to deviation (RPD) for total CBD was highest (2.195) with SNV. In contrast, raw data exhibited the least accurate predictions for total THC, with an R2P of 0.812, an RPD of 2.306, and an RMSEP of 1.651. Notably, total CBG prediction showed unique characteristics, with raw data yielding the highest R2P of 0.806. SNV pre-processing emerges as a robust method for precise total CBD quantification, offering valuable insights into the optimization of a hand-held NIR device for the rapid and non-destructive analysis of cannabinoid in whole inflorescence samples. These findings contribute to ongoing efforts in developing portable and efficient technologies for cannabinoid analysis, addressing the increasing demand for quick and accurate assessment methods in cannabis cultivation, pharmaceuticals, and regulatory compliance.

Continuous monitoring of endotracheal tube position with near infrared light.

Endotracheal intubation is a common approach for airway management in critically ill patients. However, the position of the endotracheal tube (ETT) may be altered during the procedure due to head movements. Accidental displacement or dislodge of the ETT may reduce the airflow, leading to moderate to severe complications, and in some cases even fatality. Therefore, timely detection of changes in ETT position in the trachea is critical to ensure immediate and intermediate interventions to maintain the ETT in the proper position. Currently, there are no widely utilized tools for real-time monitoring of ETT positions. The goal of this study is to develop a cost-effective and easy-to-use near-infrared (NIR) device, named Opt-ETT, capable of continuously monitoring the ETT position in the trachea of a patient. A side-firing fiber is attached to the side of the ETT to illuminate the trachea tissue with NIR light, and a detector board containing five phototransistors is affixed to the chest skin to measure the intensity of diffusely transmitted light. Displacement of the ETT is estimated using second-order polynomial fitting to the ratios of the phototransistor readings. Monte Carlo simulations, ex vivo experiment on porcine tissue, and in vivo experiments using a swine model have been conducted to assess the feasibility of the device. The design of the Opt-ETT device has been verified by the Monte Carlo simulations and ex vivo experiment. The estimation of displacement from in vivo experiments using the Opt-ETT exhibited a high degree of agreement with that measured by a reference sensor, with a discrepancy between to within a displacement range from to . The Opt-ETT device provides a potentially cost-effective solution for real-time and continuous monitoring of ETT position in patient during an intubation procedure.

Charge Injection and Auger Recombination Modulation for Efficient and Stable Quasi-2D Perovskite Light-Emitting Diodes.

The inefficient charge transport and large exciton binding energy of quasi-2D perovskites pose challenges to the emission efficiency and roll-off issues for perovskite light-emitting diodes (PeLEDs) despite excellent stability compared to 3D counterparts. Herein, alkyldiammonium cations with different molecular sizes, namely 1,4-butanediamine (BDA), 1,6-hexanediamine (HDA) and 1,8-octanediamine (ODA), are employed into quasi-2D perovskites, to simultaneously modulate the injection efficiency and recombination dynamics. The size increase of the bulky cation leads to increased excitonic recombination and also larger Auger recombination rate. Besides, the larger size assists the formation of randomly distributed 2D perovskite nanoplates, which results in less efficient injection and deteriorates the electroluminescent performance. Moderate exciton binding energy, suppressed 2D phases and balanced carrier injection of HDA-based PeLEDs contribute to a peak external quantum efficiency of 21.9%, among the highest in quasi-2D perovskite based near-infrared devices. Besides, the HDA-PeLED shows an ultralong operational half-lifetime T50 up to 479h at 20mA cm‒2, and sustains the initial performance after a record-level 30000 cycles of ON-OFF switching, attributed to the suppressed migration of iodide anions into adjacent layers and the electrochemical reaction in HDA-PeLEDs. This work provides a potential direction of cation design for efficient and stable quasi-2D-PeLEDs.

Highly efficient broadband near-infrared luminescence phosphors Ca3MgSn0.5Zr0.5Ge3O12:Pr3+,Cr3+ for multifunctional applications in pc-LEDs field

Exploring high-performance broadband near-infrared (NIR) emitting materials is crucial for the development of NIR devices. In this study, Ca3MgSn0.5Zr0.5Ge3O12:Cr3+ and rare earth ion Pr3+ co-doped Ca3MgSn0.5Zr0.5Ge3O12:Pr3+,Cr3+ phosphors were successfully synthesized. By utilizing time-resolved emission spectroscopy (TRES), photoluminescence (PL) spectra, and fluorescence decay curve, the Ca3MgSn0.5Zr0.5Ge3O12:Cr3+ phosphor is determined to exhibit a broadband emission (650–1150 nm) with a peak at 795 nm due to Cr3+ occupying multiple cationic sites. Ca3MgSn0.5Zr0.5Ge3O12:0.1Cr3+ has excellent thermal stability (86%@425 K), and co-doping Pr3+ ions into Ca3MgSn0.5Zr0.5Ge3O12:0.1Cr3+ obtains highly efficient NIR emission. The Ca3MgSn0.5Zr0.5Ge3O12:0.01Pr3+,0.1Cr3+ phosphor has quantum yield of 89.4% thanks to the energy transfer effect from Pr3+ to Cr3+. The fabricated NIR phosphor-converted light emitting diodes (pc-LEDs) by integrating the blue chip with Ca3MgSn0.5Zr0.5Ge3O12:0.01Pr3+,0.1Cr3+ has diverse applications including night vision, non-destructive testing, and medical imaging.

Crafting Near‐Infrared Photonics via the Programmable Assembly of Organic Heterostructures at Multiscale Level

AbstractOrganic single crystals with near‐infrared (NIR) emission demonstrate their excellent optical communications from well photonic confinement and low optical waveguide loss, which are considered as competitive candidates toward advanced optoelectronics. However, the increasingly diverse and sophisticated application demands result in the complicated design of NIR devices, which is hardly realized solely by the intrinsic properties of individual crystals. Herein, a programmable assembly strategy is presented to fabricate organic heterostructures. Triphenylene (TP), pyrene (Py) and 7,7,8,8‐tetracyanoquinodimethane (TCNQ) are primary selected to prepared organic cocrystals with narrow band gap and near‐infrared emission. Importantly, the charge‐transfer alloy with tunable emission from 700 nm to 850 nm and branched heterostructures with multichannel characteristics are prepared from these organic cocrystals by following the growth kinetics process at molecular level and lattice matching principle at structural level, respectively. Theses prepared heterostructures exhibit optical logic operation capabilities, which can serve as optical modulators. This work provides new insights into the manufacturing of organic NIR heterostructures applied in advanced optoelectronics.

Application of a short-wave pocket-sized near-infrared spectrophotometer to predict milk quality traits

Portable-hand-held devices based on near-infrared (NIR) technology have improved and are gaining popularity, even if their implementation in milk has been barely evaluated. Thus, the aim of the present study was to assess short-wave pocket-sized NIR devices' feasibility to predict milk quality. A total of 331 individual milk samples from different cow breeds and herds were collected in 2 consecutive days for chemical determination and spectral collection by using 2 pocket-sized NIR spectrophotometers working in the range of 740-1070 nm. The reference data was matched with the corresponding spectrum and modified-partial least-squares regression models were developed. A 5-fold cross-validation was applied to evaluate individual devices' performance and an external-validation with 25% of the data set as the validation set was applied for the final models. Results revealed that both devices' absorbance was highly correlated but greater for instrument A than B. Thus, the final models were built by averaging the spectra from both devices for each sample. The fat content prediction model was adequate for quality control with a coefficient of determination (R2ExV) and a residual predictive deviation (RPDExV) in external validation of 0.93 and 3.73, respectively. Protein and casein content as well as fat-to-protein ratio prediction models might be used for a rough screening (R2ExV > 0.70; RPDExV > 1.73). However, poor prediction models were obtained for all the other traits with an R2ExV between 0.43 (urea) and 0.03 (somatic cell count), and a RPDExV between 1.18 (urea) and 0.22 (somatic cell count). In conclusion, short-wave portable-hand-held NIR devices accurately predicted milk fat content, and protein, casein, and fat-to-protein ratio might be applied for rough screening. It seems that there is not enough information in this NIR region to develop adequate prediction models for lactose, somatic cell count, urea, and freezing point.

Phase transition and Nd3+/Pr3+ co-doping induced enhancement of NIR emission in ScP3O9: Cr3+ phosphor

Near-infrared (NIR) phosphors play an important role in NIR pc-LEDs. However, NIR phosphor with long wavelength are still suffered from low efficiency and poor thermal stability. Herein, a blue light excitable ScP3O9: Cr3+ NIR phosphor with an emission peak > 880 nm is reported. Significantly, the PL intensity of ScP3O9: Cr3+ increased to 241 % when the monoclinic phase changes to cubic. Moreover, by co-doping the cubic ScP3O9: Cr3+ with Nd3+, Pr3+ ions, the PL internal quantum efficiency (IQE) of the phosphors increased from 62 % to 74 %, and the thermal quenching of the phosphor is suppressed effectively (86 % at 423 K). The energy transfer processes between Cr3+ and Nd3+, Pr3+ ions are proposed to be responsible for the enhancement. Furthermore, an efficient NIR pc-LED was fabricated, and gives a high photoelectric efficiency of 16.5 % (26.8 mW at 60 mA). Finally, multifunctional applications of the NIR device in night-vision and nondestructive analysis were demonstrated.

Performance of benchtop and portable spectroscopy equipment for discriminating Iberian ham according to breed

Iberian ham is a highly appreciated product and according to Spanish legislation different labels identify different products depending on the genetic purity. Consequently, “100% Iberian” ham from purebred Iberian animals is more expensive than “Iberian” ham from Iberian x Duroc crosses. The hypothesis of this study was that to avoid labelling fraud it is possible to distinguish the breed (Iberian or Iberian x Duroc) of acorn-fed pigs of Iberian ham without any prior preparation of the sample by using spectroscopy that is a rapid and reliable technology. Moreover, portable devices which can be used in situ could provide similar results to those of benchtop equipment. Therefore, the spectra of the 60 samples (24 samples of 100% Iberian ham and 36 samples of Iberian x Duroc crossbreed ham) were recorded only for the fat, only for the muscle, or for the whole slice with two benchtop near-infrared (NIR) spectrometers (Büchi NIRFlex N-500 and Foss NIRSystem 5000) and five portable spectrometers including four portable NIR devices (VIAVI MicroNIR 1700 ES, TellSpec Enterprise Sensor, Thermo Fischer Scientific microPHAZIR, and Consumer Physics SCiO Sensor), and one RAMAN device (BRAVO handheld). The results showed that, in general, the whole slice recording produced the best results for classification purposes. The SCiO device showed the highest percentages of correctly classified samples (97% in calibration and 92% in validation) followed by TellSpec (100% and 81%). The SCiO sensor also showed the highest percentages of success when the analyses were performed only on lean meat (97% in calibration and 83% in validation) followed by microPHAZIR (84% and 81%), while in the case of the fat tissue. Raman technology showed the best discrimination capacity (96% and 78%) followed by microPHAZIR (89% and 81%). Therefore, spectroscopy has proved to be a suitable technology for discriminating ham samples according to breed purity; portable devices have been shown to give even better results than benchtop spectrometers.