Use Of Near-infrared Spectroscopy Research Articles

Accurate analysis of coal calorific value using NIRS-XRF: Utilizing RF classification and PLSR subtype modeling

Rapid and precise measurement of the calorific value of coal is crucial for coal chemical enterprises. However, due to the wide variety of coal sources and the diverse types of coal, the matrix effect significantly reduces the accuracy of spectroscopic rapid detection techniques for coal quality. To address this issue, this study conducts research on a coal calorific value detection method based on the combined use of near-infrared spectroscopy (NIRS) and X-ray fluorescence spectroscopy (XRF), exploring the feasibility of identifying coal types first and then predicting calorific value based on corresponding subtype models. In the aspect of spectral preprocessing, fusion of the dual spectra is achieved using techniques such as truncation, smoothing, Standard Normal Variate (SNV), and normalization. For coal type identification, the identification performance of five machine learning algorithms is compared, and the random forest (RF) algorithm is used to improve the identification accuracy to 98.43 %. In terms of prediction modeling, a comparison is made between traditional holistic models based on Partial Least Squares Regression (PLSR) and subtype models built according to coal types, revealing that the latter demonstrating stronger generalization ability and robustness. Accordingly, a precise prediction strategy for coal calorific value based on the combined use of NIRS and XRF in complex coal types is proposed: first, the RF algorithm is used to automatically identify coal types based on the fusion spectrum of NIRS and XRF, and then the calorific value of the corresponding coal type is accurately predicted using the PLSR subtype model selected according to the identification results. Industrial test results indicate that the average absolute error (AAE), root mean square error of prediction (RMSEP), average relative error (ARE), and standard deviation (SD) for coal calorific value prediction are 0.20 MJ/kg, 0.24 MJ/kg, 0.79 %, and 0.04 MJ/kg, respectively, meeting the requirements of enterprises. The research findings provide a practical technical method for timely and accurate acquisition of coal calorific value data, addressing the interference problem of matrix effects in complex coal type scenarios and holding broad application prospects in the coal-based energy industries.

Oil Quality Prediction in Olive Oil by Near-Infrared Spectroscopy: Applications in Olive Breeding

The oxidative stability index (OSI) and fatty acid (FA) composition of extra virgin olive oils (EVOOs) are key parameters in the characterization of new varieties in breeding programs. Their determination through traditional methods (Rancimat and gas chromatography, respectively) is expensive and time-consuming. Therefore, there is a need to develop rapid and cost-effective analytical procedures. This study aimed to evaluate the potential use of near-infrared spectroscopy (NIRS) for analyzing OSI and FA composition in EVOOs. A total of 318 samples sourced from different origins were evaluated using both FT-NIR MPA and MicroNIR instruments in transmittance mode, with wavelengths ranging from 1100 to 2500 nm and 908 to 1676 nm, respectively. Different accuracies were obtained in the models developed for the different evaluated traits, with simpler models (using a lower number of latent variables) for the MPA analyzer in all cases. Additionally, consistent results between instruments for the partitioning of the variance and heritability estimation, and the reliable ranking of genotypes were obtained from one of the sample sets tested. In summary, models derived from PLS regression using spectroscopic data of both instruments demonstrated promising results in determining these EVOO traits, facilitating their evaluation and selection of genotypes, particularly in breeding programs.

Near-Infrared Spectroscopy (NIRS) in the Assessment of Cerebral Tissue Oxygenation (rSO2): Methodological Issues and Dilemmas

Introduction: Monitoring cerebral perfusion in patients with brain injury is a major clinical challenge. Monitoring cerebral oxygenation (rSO2) via NIRS was introduced in the early 1980s, and many clinicians believed it to be a valuable method for assessing cerebral perfusion and subsequent measures to optimize cerebral flow. The main problem with the use of NIRS is the presence of intermediate structures—the skin, skull, meninges, cerebrospinal fluid—and their influence on the test result. Therefore, it seems that NIRS assessment performed on a patient during brain death can give an idea of the magnitude of the influence of these intermediate structures on the monitoring result. Case presentation: We present a case study of cerebral oxygenation measurements in a patient undergoing a brain death diagnostic procedure. A clinical situation in which cerebral blood flow is stopped can give an idea of the specificity of this method, in particular of the influence of intermediate structures on the monitoring result. In this case, the result obtained using NIRS is increased by the patient’s oxygenation before the apnea test. The influence of chromophores in the tissues surrounding the CNS and reflections and scattering of the light wave spectrum have a very significant effect on the final result of cerebral saturation measurement. Discussion: The majority of observations in existing research describing changes in cerebral perfusion or its optimization may be burdened by the problem described here, i.e., by the significant influence of measured intermediate structure oxygenation. The specificity of NIRS in assessing cerebral perfusion requires careful analysis. The therapeutic implications of monitoring cerebral oxygenation with NIRS are of great importance, and based on the example presented and the literature provided, this method should be used with caution. It has been shown that in a patient with brain death, the result of NIRS oxygenation measurements depends on the structures surrounding the brain.

Mango quality prediction based on near-infrared spectroscopy using multi-predictor local polynomial regression modeling

Background pH and total soluble solids (TSS) are important quality parameters of mangoes; they represent the acidity and sweetness of the fruit, respectively. This study predicts the pH and TSS of intact mangoes based on near-infrared (NIR) spectroscopy using multi-predictor local polynomial regression (MLPR) modeling. Herein, the prediction performance of kernel partial least square regression (KPLSR), support vector machine regression (SVMR), and MLPR is compared. Methods For this purpose, 186 intact mango samples at three different maturity stages are used. Prediction models are built using MLPR, KPLSR, and SVMR based on untreated and treated spectra. The best regression model for predicting pH is MLPR based on Gaussian filter smoothing spectra. Moreover, the TSS value is more accurately predicted using MLPR based on Savitzky–Golay smoothing. Results The findings reveal that MLPR is highly accurate in estimating the pH and TSS of mangoes, with mean absolute percentage error (MAPE) values less than 10 %. In addition, the MLPR model has the best predictive performance with the lowest Mean Squared error (MSE) and root mean squared error (RMSE) values and the highest R2 value. Conclusions The use of NIR spectroscopy in combination with multi-predictor local polynomial regression could provide a quick and non-destructive technique for predicting mango quality. Thus, the results of this study help support sustainable production as a sustainable development goal.

Intraoperative Near-infrared Spectroscopy Can Predict Skin Flap Necrosis.

The study aimed to validate the previously identified capacity of near-infrared spectroscopy (NIRS) to detect clinically relevant differences in tissue perfusion intraoperatively. Consecutive patients undergoing oncologic resection requiring flap reconstruction were analyzed. Clinicians were blinded to tissue oxygen saturation (StO2) measurements taken intraoperatively. Measurements were taken at (1) control areas not affected by the procedure, (2) areas at risk of necrosis based on distal location, and (3) areas of skin flap necrosis (SFN) identified during the follow-up period. Mean StO2 values were compared using a single-sample t test and analysis of variance (ANOVA) to determine differences in oxygenation. There were 102 patients included from April 2018 to May 2019. Reconstruction was undertaken following resection for breast cancer (46), melanoma (35), sarcoma (9), and other cutaneous malignancies (12). Breast reconstruction involved 38 alloplastic reconstructions and eight autologous free flaps. Other skin flap reconstruction involved 42 local/regional skin flaps, 13 pedicled flaps, and one free flap. Eighteen patients (17.6%) developed SFN. Mean intraoperative StO2 measurements for control areas, areas at risk, and areas of SFN were 74.8%, 70.9%, and 54.3%, respectively. StO2 values equal to or less than 60% were highly specific (96%) for SFN, whereas StO2 values above 85% were highly sensitive (96%) to rule out SFN. These results further support the use of NIRS to objectively assess variations in skin flap oxygenation and tissue perfusion that are correlated with the development of postoperative SFN.

Alternative identification of wood from natural fallen trees of the Lecythidaceae family in the Central Amazonian using FT-NIR spectroscopy

The scientific identification of natural fallen trees in tropical forests is complex due to the lack of fertile material in field collection. The study evaluated the use of near-infrared spectroscopy with Fourier-transform (FT-NIR) in the discrimination of wood from fallen trees of the Lecythidaceae family. Seven trees were collected in the Central Amazonian region (Brazil), from which 63 specimens were prepared from the wood, and NIR spectra were obtained on different wood surfaces (total 756 spectra). Chemometric models were developed with a spectral data set, and the Mahalanobis algorithm was applied. The discriminant model with 2nd derivative spectra improved the identification capacity, resulting in errors < 5% in the identification of genus Couratari (3 ssp.), Eschweilera (2 ssp.), Holopyxidium (1 sp.) and Lecythis (1 sp.). The comparison of the spectral signatures of samples of fallen trees and wood library revealed that even when wood was exposed to environmental weathering, around 50% of the original bands were preserved, favouring discrimination at the genus level. The accuracy of the chemometric models developed indicates the applicability of FT-NIR spectroscopy integrative in identifying fallen trees from the Lecythidaceae family in the tropical forests.

Non-Destructive Assessment of Agarwood Resin Formation Status in Aquilaria crassna using Near-Infrared Spectroscopy

Agarwood is a unique and valuable resin synthesized within a few tree species of the tree family Thymelaeaceae primarily as a self-defence mechanism against stress causes such as fungal invasions. Instead, artificial inoculation leads to short-time harvesting practiced in intensive commercial-level cultivations. The extraction of this resin can be done only after the harvesting where accurate estimation of resin yield is crucial for avoiding immature or underdeveloped harvesting. However, the amount of resin accumulated in the trunk cannot be estimated by the outside inspection. As a result, trees are being cut down before they have reached their maximum harvest potential. Therefore, precise detection of fragrant resin formation status inside the tree has become one of the primary challenges in the agarwood production industry. Currently, the methods available are either destructive, inefficient, or inaccurate. As such, this study evaluates the possibility of the use of NIR spectroscopy as a non-destructive and quick detection method for agarwood formations status inside trees in the in-situ mode. Near-infrared (NIR) range (588–1,025 nm) spectra were acquired from resin-formed and non-formed areas from twenty tree trunks of agarwood with five different formation levels. The best agarwood formation areas of logs were assigned as class level 1 and the least was assigned as the class level 5. The spectra were acquired near the opening made for the artificial inoculation process of considered Aquilaria crassna tree trunks. The results of Soft Independent Modelling of Class Analogies showed consistent evidence of differences in the NIR spectral profiles of all levels of agarwood formations. The SIMCA discrimination between the resin developed versus not was achieved with 86% accuracy. The accuracy rates of the degree of the presence of agarwood were obtained as 80%, 100%, 85%, 90%, and 85% respectively, as assigned levels 1 to 5 in the SIMCA models. This research revealed the potential possibility of using NIR technology for the prediction of agarwood resin status inside the agarwood tree in A. crassna before harvesting the tree as a non-destructive and rapid method.
  
 Keywords: NIR spectroscopy, Agarwood, Aquilaria crassna, Non-destructive, Agarwood formation
  

Use of near-infrared spectroscopy for the online monitoring of natural gas composition (hydrocarbons, water and CO2 content) at high pressure

The natural gas production from Brazilian pre-salt fields imposed new challenges for petrochemical industry. Actual treatment facilities are not adequate for this new scenario and studies have been conducted to apply new adsorbents materials and membranes for water and CO2 removal from natural gas at high pressures. To better develop such investigations, sensors for on-line monitoring of natural gas properties like CO2 and water content are important, since their presence affects the quality of the final product. Near infrared (NIR) spectroscopy associated to chemometric models (partial least squares) were employed for on-line monitoring of representative natural gas systems (methane/CO2, methane/water and methane/CO2/water) and a real natural gas at temperature and pressure ranges from 20 to 60 °C and 10 to 200 bar, respectively, water content up to gas saturation and CO2 content up to 50 wt%. Water solubility values used as reference for NIR Spectrometer calibration in model systems were taken from the literature and for real natural gas calculated with Cubic Plus Association (CPA) Equation of State (EoS), while CO2 content was experimentally controlled aiming to calibrate the chemometric models in the full range of pressure and temperature. Several strategies were adopted for the chemometric model’s development to obtain the best correlation between NIR spectra and experimental data. Results indicate good correlation in both calibration and validation steps attaining linear correlation coefficients (R2) higher than 0.96 for all systems investigated. The proposed methodology is a potential tool for on-line monitoring of natural gas composition, including CO2 and water content, at high-pressures and can be applied at petrochemical industries or in laboratories, dispensing sampling or any sample preparation.

Bifidobacterium breve M-16V regulates the autonomic nervous system via the intestinal environment: A double-blind, placebo-controlled study

We conducted a randomized controlled trial to investigate the potential of Bifidobacterium breve M-16 V to improve mood in humans. In this evaluation, we incorporated the use of near-infrared spectroscopy (NIRS), which has been used to evaluate mood states in studies with small sample sizes. Participants were given B. breve M-16 V (20 billion cells/day) for 6 weeks, and their mood state was assessed before and after ingestion. NIRS data were collected at rest and during a mental arithmetic task (under stress). Intake of B. breve M-16 V decreased the heart rate under stress and increased levels of the GABA-like substance pipecolic acid in stool samples. In addition, B. breve M-16 V improved mood and sleep scores in participants with high anxiety levels. These results suggest that B. breve M-16 V affects the metabolites of the gut microbiota and has the potential to modulate the autonomic nervous system and to improve mood and sleep.

A narrative review on the use of near-infrared spectroscopy to monitor bladder volume and in vitro validation approaches.

Current guidelines for patients with neurogenic bladder (NB) dysfunction suggest the use of self-intermittent catheterization with adherence to catheterization timers. Due to biorhythmic variability, unpredictable voiding times may occur. As a result, many patients abstain from extended social or work activities, turn to more secluded lifestyles, and generally experience a decrease in quality of life. Being able to know when to void is essential for patients with NB dysfunction. To solve the problem of variable void timings, wearable devices using near-infrared spectroscopy (NIRS) have been emergent and showed potential for bladder volume monitoring. Therefore, in this review, we provided a comprehensive overview of research which implemented NIRS for bladder volume monitoring, and discussed how the researchers validated their device by in-vitro methods and suggested a potential validation approach. A literature search using PubMed and Google Scholar was conducted on February 2023. Publications involving bladder volume monitoring incorporating NIRS technique with in-vitro validation was considered for review. Due to the novelty of NIRS being applied to bladder monitoring, there are a few possibilities to effectively validate this technique through in-vitro methods. Ballistics gel, which has been proven to be a versatile material for applications involving ultrasound, could be a suitable material when constructing a bladder phantom for in-vitro validation of NIRS technology. By outlining a more standardized in-vitro validation model based on ballistics gel, we hope to facilitate development in this field towards a more accurate and robust NIRS-based bladder monitoring device.

An overview of the use of near-infrared spectroscopy (NIRS) in assessing silage composition: review

 In this study, we confidently evaluated the effectiveness of using infrared spectroscopy for assessing silage, and observed the results obtained with portable equipment. Several factors alter this ensiled material's composition and quality, and monitoring is necessary to create an accurate diet formulation. Analysis using near-infrared spectroscopy (NIRS) this technique is the wavelength of the near-infrared region and measuring the difference in the amount of energy emitted by the equipment and the energy reflected by the sample to the detector, be measured by different bands create a spectrum of this sample. In the nutrition of ruminants, mainly confined animals, silage is the main source of fiber used in their diet and the NIRS technique has been widely used to evaluate its chemical composition the digestibility, within other parameters. Use with benchtop equipment in the laboratory or with portable equipment offers real-time results on the farm, allows diet variability to be monitored, and assists in decision maki. However, further research into the use of this equipment to assess its accuracy and which type of equipment is best to use is recommended.

Identification of individual goat animals by means of near infrared spectroscopy and chemometrics analysis of commercial meat cuts.

Although the identification of animal species and muscles have been reported previously, no studies have been found on the use of NIR spectroscopy to identify individual animals from the analysis of commercial meat cuts. The aim of this study was to evaluate the use of a portable near infrared (NIR) instrument combined with classical chemometrics methods [principal component analysis (PCA) and partial least squares discriminant analysis PLS-DA)] to identify the origin of individual goat animals using the spectral signature of their commercial cut. Samples were collected from several carcasses (6 commercial cuts x 24 animals) sourced from a commercial abattoir in Queensland (Australia). The NIR spectra of the samples were collected using a portable NIR instrument in the wavelength range between 950 and 1600nm. Overall, the PLS-DA models correctly classify 82% and 79% of the individual goat samples using either the goat rack or loin cut samples, respectively. The study demonstrated that NIR spectroscopy was able to identify individual goat animals based on the spectra properties of some of the commercial cut samples analysed (e.g. loin and rack). These results showed the potential of this technique to identify individual animals as an alternative to other laboratory methods and techniques commonly used in meat traceability.

Abstract 14998: Assessment of Microcirculatory Dysfunction by Measuring Subcutaneous Tissue Oxygen Saturation Using Near-Infrared Spectroscopy in Patients With Circulatory Failure

Background: Patients with circulatory failure have been treated with the goal of normalizing systemic hemodynamic parameters such as blood pressure, central venous pressure, urine output, and central venous oxygen saturation. However, microcirculatory dysfunction remains even after improvement of these indices, suggesting a loss of hemodynamic coherence between the macrocirculation and the microcirculation. Recently, the usefulness of near-infrared spectroscopy (NIRS) in assessing the microcirculation has been reported. Aim: We measure regional tissue oxygenation saturation (rSO 2 ) at 3 - 5 mm subcutaneously in patients with circulatory failure using a finger-mounted tissue oximeter with the NIRS technique (Toccare: Astem Co., Ltd., Kawasaki, Japan) to investigate its relationship with microcirculation. Methods: This is a single-center prospective observational cohort study of patients with circulatory failure (systolic blood pressure ≤ 90 mmHg or lactate ≥ 2 mmol/L at presentation) transported to the emergency department of Nihon University Hospital from 15 June 2020 to 31 March 2022. We measured rSO 2 in the forehead, thenar eminence, thumb and knee using Toccare and assessed the relationship between rSO 2 and blood pressure, acute physiology and chronic health evaluation (APACHE) II score, sequential organ failure assessment (SOFA) score and mottling score. Result: In patients with circulatory failure (n = 38), rSO 2 at each site showed no correlation with blood pressure, a negative correlation with SOFA score and APACHE II score and a positive correlation with mottling score. These significant correlations were also best observed in the knee. Conclusion: In patients with circulatory failure, rSO 2 measured with Toccare showed no correlation with blood pressure but a significant negative correlation with the severity of organ damage. The knee is possibly the optimal measurement site for monitoring microcirculatory dysfunction and determining the effectiveness of treatment.

Use of near infrared spectroscopy for the prediction of perioperative complications in patients undergoing elective microsurgical resection of cerebral arteriovenous malformations- a prospective observational trial (NIRSCAM trial).

Cerebral arteriovenous malformations (AVM) represent focal abnormal areas of low resistance circulation which render the peri-nidal neuronal tissue susceptible to ischemia. The post-excision cerebral perfusion surge can result in hyperaemic complications.We hypothesised that Near Infrared Spectroscopy (NIRS)-guided perioperative management can aid in the prediction and prevention of perioperative complications in patients presenting for surgical excision of cerebral AVMs. We also intended to identify a threshold value of regional cerebral oxygen saturation (rScO2) to predict the incidence of perioperative complications. This was a prospective observational study involving patients undergoing elective supratentorial AVM resection surgeries. Intraoperative rScO2 and hemodynamic monitoring were done and continued for postoperatively for 12h. Any drift in rScO2 by > 12% from baseline was managed as per study protocol and perioperative adverse events were recorded and analyzed. Post surgery,for analytical purpose patients were categorized into two groups, Group A - patients without complications and Group B - patients who had complications postoperatively. Twenty-five patients presenting for surgical excision of cerebral AVM were recruited for this study of which 9 patients had postoperative adverse events and were allocated to group B. The ipsilateral mean rScO2 at the time of complication (Pc) was significantly lower in Group B than in group A [62.08 ± 9.33 vs.70.52 ± 7.17; p = 0.04]. The mean ipsilateral rScO2 drift from N2- N5 (i.e., post excision) was significantly higher in Group B than in Group A [12.01 ± 2.63% vs. 4.98 ± 5.7%;p = 0.02]. Mean ipsilateral rScO2 Drift ratio (N5 :N2) was significantly higher in group B as compared to group A [1.32 ± 0.01 vs. 1.01 ± 0.06;p < 0.001]. In the immediate post excision phase, the ipsilateral mean rScO2 was significantly higher in Group B at the post excision time point compared to Group A [ 83.03 ± 6.08 vs. 73.52 ± 7.07;p < 0.01)]. The mean ipsilateral rScO2 drift from N1-N6 (i.e., postoperatively) was significantly higher in Group B as compared to Group A [14.96 ± 0.080% vs. 6.88 ± 4.5% ; p < 0.01]. Similarly, the Mean Ipsilateral rScO2 Drift ratio (N6:N1) was significantly lower in group B as compared to group A [2.17 ± 0.02 vs. 1.05 ± 0.03 ;p < 0.0001]. In patients undergoing cerebral AVM resection, a post-resection ipsilateral rScO2 increase by > 12% with a drift ratio of > 1.3 could signify cerebral hyperemia. A postoperative ipsilateral rScO2 drift > 14.5% with a drift ratio of 2.1 from the baseline is associated with postoperative complications in our study. Further multi-centric randomized control trials are needed to support our research findings.

Near-infrared spectroscopy with a provocative maneuver to detect the presence of severe peripheral arterial disease

Current assessment standards for peripheral arterial disease (PAD), such as the ankle brachial index, are limited in their utility and portability. Near-infrared spectroscopy (NIRS) has shown some promise in diagnosing PAD when used in conjunction with a provocative maneuver. The purpose of this study was to assess the viability of NIRS in conjunction with a transient leg elevation provocative maneuver for detecting severe PAD. This retrospective observational cross-sectional study assessed 57 limbs in 34 patients receiving routine vascular screening for PAD at Madigan Army Medical Center. The patient limbs were stratified into normal (n = 17), mild (n = 9), moderate (n = 16), and severe (n = 15) PAD groups based on the clinician assessments. Additionally, the patients were assessed with NIRS measurements taken with the patient in the supine position at rest and using a provocative leg raise maneuver of transient leg elevation of 45° for 60 seconds. The resting tissue oxygen saturation (StO2) and the change in StO2 (ΔStO2) from rest to elevation were recorded and compared between the PAD severity groups via independent measures analysis of variance with the Tukey honest significant difference post hoc test. The supine resting StO2 was not different between the normal (77.5% ± 7.7%), mild (72.5% ± 7.4%), moderate (72.0% ± 10.3%), and severe (74.2% ± 5.4%) PAD groups (P = .23). However, the ΔStO2 with transient leg elevation was significantly greater in the severe PAD group (−17.2% ± 6.0%) compared with the normal (−3.9% ± 4.8%), mild (−6.9% ± 4.7%), and moderate (−9.7% ± 5.2%) PAD groups (P < .002 for all). Similar results were observed in the changes in oxyhemoglobin and deoxyhemoglobin. The leg elevation protocol was also used for two patients before and after lower limb revascularization, which demonstrated that the ΔStO2 corresponded with the clinical assessment of PAD severity. Resting supine NIRS images were unable to detect any differences among normal and limbs with different PAD severity. However, NIRS imaging with 45° leg elevation for 60 seconds showed a significant difference between severe PAD compared healthy patients and those with mild to moderate PAD in a fast, precise, and accurate manner. These preliminary data support the use of NIRS and transient leg elevation as a tool to diagnose severe PAD but do not support the use of NIRS alone as a screening test for PAD. NIRS measurements with leg elevation might be a viable noninvasive, noncontact, and portable method of assessing severe PAD for home monitoring, in rural communities, and/or in standard clinical practice.

Use of levosimendan in hemodynamic management of heart failure in two neonates with intracranial arteriovenous shunts: a case series

BackgroundThe hemodynamic status of newborns with intracranial arteriovenous shunts (AVSs) may be extremely complex. Mini-invasive hemodynamic monitoring through innovative techniques such as Near-Infrared Spectroscopy (NIRS) and Pressure Recording Analytical Method (PRAM) may help in understanding hemodynamics in newborns with AVSs. Levosimendan is a calcium sensitizer and inodilator, and it is known to improve ventricular function, but its use in newborns is limited. In our cases, we evaluated the effect of levosimendan on hemodynamics through NIRS and PRAM.Case presentationHerein, we report the cases of two neonates with intracranial arteriovenous shunts, in whom we used levosimendan to manage cardiac failure refractory to conventional treatment. Levosimendan was used at a dosage of 0.1 mcg/kg/min for 72 h. Combined use of NIRS and PRAM helped in real-time monitoring of hemodynamic effects; in particular, levosimendan determined significant improvement in myocardium contractility as well as a reduction of heart rate.ConclusionIn two neonatal cases of AVSs, levosimendan led to an overall hemodynamic stabilization, documented by the combination of NIRS and PRAM. Our results suggest introducing levosimendan as a second-line treatment in cases of severe cardiac dysfunction due to AVSs without improvement using standard treatment strategies. Future prospective and larger studies are highly warranted.

Use of Near-InfraRed Spectroscopy (NIRS) during Vascular Occlusion Test (VOT) for predicting an increase in oxygen consumption after fluid challenge in circulatory shock patients

Background: The goal of fluid challenge (FC) is to increase cardiac output (CO) and oxygen delivery (DO2) (known as fluid responders) to correct tissue hypoxia. To optimize fluid administration, fluid challenge (FC) during dependence of oxygen consumption on oxygen delivery (VO2/DO2 dependency) would correct tissue hypoxia confirmed by an increase of oxygen consumption (VO2) and oxygen delivery (DO2) after FC (known as VO2 responders) and get more benefit from a reduction in tissue hypoxia. Markers of anaerobic metabolisms, such as blood lactate concentration or the ratio of venous-arterial CO2 tension difference (P(cv-a)CO2) over arterial-to-venous oxygen content difference (C(a-cv)O2), can predict VO2 responders but still have several limitations. Therefore, near-infrared spectroscopy (NIRS) has been developed to evaluate tissue perfusion, presented as tissue oxygen saturation (StO2), at the bedside. Combining StO2 with the vascular occlusive test (VOT) and introducing a short period of forearm ischemia is a non-invasive technique to examine microvascular alterations at the bedside. However, a study validating the ability of these variables to predict VO2 response has not been conducted. Methods: We plan to conduct a single-center prospective study on circulatory failure patients. The cardiac index (CI), oxygen delivery (DO2), oxygen consumption (VO2), arterial lactate, central venous oxygen saturation (ScvO2), ratio of venous-arterial carbon dioxide tension to arterial-to-central venous oxygen content difference (P(cv-a)CO2/ C(a-cv)O2), and tissue oxygen saturation measured by near-infrared spectroscopy (NIRS) probe during vascular occlusion test variables (NIRS-VOT variables) will be collected before and after the fluid challenge. Hypothesis: We hypothesize that markers of reactive hyperemia by NIRs will predict an increase in VO2 after FC in patients with circulatory shock. Ethics: The study protocol has been approved by the ethics committee of the faculty of medicine, Ramathibodi Hospital, Mahidol University (COA. MURA2022/80).

Optimized variable selection and machine learning models for olive oil quality assessment using portable near infrared spectroscopy

Olive oil is a key component of the Mediterranean diet, rich in antioxidants and beneficial monounsaturated fatty acids. As a result, high-quality olive oil is in great demand, with its price varying depending on its quality. Traditional chemical tests for assessing olive oil quality are expensive and time-consuming. To address these limitations, this study explores the use of near infrared spectroscopy (NIRS) in predicting key quality parameters of olive oil, including acidity, K232, and K270. To this end, a set of 200 olive oil samples was collected from various agricultural regions of Morocco, covering all three quality categories (extra virgin, virgin, and ordinary virgin). The findings of this study have implications for reducing analysis time and costs associated with olive oil quality assessment. To predict olive oil quality parameters, chemical analysis was conducted in accordance with international standards, while the spectra were obtained using a portable NIR spectrometer. Partial least squares regression (PLSR) was employed along with various variable selection algorithms to establish the relationship between wavelengths and chemical data in order to accurately predict the quality parameters. Through this approach, the study aimed to enhance the efficiency and accuracy of olive oil quality assessment. The obtained results show that NIRS combined with machine learning accurately predicted the acidity using iPLS methods for variable selection, it generates a PLSR with coefficients of determination R2 = 0.94, root mean square error RMSE = 0.32 and ratios of standard error of performance to standard deviation RPD = 4.2 for the validation set. Also, the use of variable selection methods improves the quality of the prediction. For K232 and K270 the NIRS shows moderate prediction performance, it gave an R2 between 0.60 and 0.75. Generally, the results showed that it was possible to predict acidity K232, and K270 parameters with excellent to moderate accuracy for the two last parameters. Moreover, it was also possible to distinguish between different quality groups of olive oil using the principal component analysis PCA, and the use of variable selection helps to use the useful wavelength for the prediction olive oil using a portable NIR spectrometer.

Quantitatively Determine the Iron Content in the Fruit of ‘Huangguan’ Pear Using Near-Infrared Spectroscopy

‘Huangguan’ pear has excellent quality, strong adaptability, and good socioeconomic value. Iron is one of the important trace elements in plants, and iron imbalance seriously affects the growth and development of pear trees and reduces their economic benefits. If the iron content in pear fruit can be easily and non-destructively detected using modern technology during the critical period of fruit development, it will undoubtedly help guide actual production. In this study, ‘Huangguan’ pear fruit was used as the research object, and the possibility of using the more convenient near-infrared spectroscopy (900~1700 nm) technology for nondestructive detection of the iron content in the peel and pulp of ‘Huangguan’ pear was explored. First, 12 algorithms were used to preprocess the original spectral data, and based on the original and the preprocessed spectral data, partial least squares regression and gradient boosting regression tree algorithms were used. A full-band prediction model of the iron content in the peel and pulp of ‘Huangguan’ pear was established, and the genetic algorithm was used to extract characteristic wavelengths, establish a characteristic wavelength prediction model, and evaluate the prediction effect of each model according to the coefficient of determination R² and the relative analysis error RPD. After comparison, we found that the prediction model with the best prediction of the iron content in the peel and pulp of ‘Huangguan’ pear reaches class A, and the prediction effect is good and meets expectations. This experiment shows that the use of near-infrared spectroscopy can achieve better prediction of the iron content in the peel and pulp of ‘Huangguan’ pear.

Performance of Near-Infrared Spectroscopy in Detecting Acute Tourniquet-Induced Upper-Extremity Ischemia Across Different Skin Phenotypes

Diagnosing acute tissue ischemia is challenging, particularly in patients with higher skin melanin content. We investigated whether near-infrared spectroscopy (NIRS) is effective and consistent in detecting upper extremity ischemia across various skin phenotypes. Volunteers underwent tourniquet-induced upper extremity ischemia. Skin color was evaluated by the Fitzpatrick scale (FP, range: I-VI) and the Von Luschan scale (vL, range: 1-36). A NIRS probe was placed on one finger. The tourniquet was inflated to 250 mmHg and perfusion was restricted for 7 minutes, followed by a 10-minute monitored reperfusion period. The percent tissue oxygenation (StO2) was recorded. A total of 55 volunteers were enrolled (22 self-identified as Caucasian, 21 African American, 7 Asian, 2 Latinx, and 2 Biracial). Average starting and ending StO2 for the cohort was 72.2% and 45.9%, respectively. However, there was variability based on skin melanin content. Increasing vL correlated with lower starting StO2, smaller StO2 decrease, and shorter time to reach ischemic steady state. High skin melanin (FP scale IV-VI) was associated with significantly lower starting StO2 (-7.1%) and shorter time to reach ischemic steady state (-0.3 mins). African Americans had lower starting StO2 (-8.6%) and 7.8% lesser total StO2 decrease than other groups. NIRS can rapidly detect acute onset tissue ischemia in the upper extremity. However, given the lower starting StO2 and smaller total StO2 decrease after tourniquet-induced ischemia for patients with higher skin melanin, using NIRS for clinical detection of acute ischemia may be more challenging in these patients. These inconsistencies may limit use of NIRS clinically for spot identification of ischemia. Although NIRS has utility in tracking tissue oxygenation, variable performance with different skin melanin content raises concerns as to whether different cutoff/threshold levels are needed for different groups, and whether NIRS is reliable for spot checks in acute events.