Use Of Near-infrared Spectroscopy Research Articles

Characteristics of psychomotor retardation distinguishes patients with depression using multichannel near-infrared spectroscopy and finger tapping task

BackgroundPsychomotor retardation (PMR) is frequently noted as a characteristic feature of major depressive disorder (MDD). In patients with depression, it is characterized by retardation of speech, emotion, thinking, and cognition. This study explored the activation pattern of the prefrontal cortex (PFC) during the finger-tapping task (FTT) in subjects with MDD, aiming to provide additional understanding on the connection between PMR and PFC activation pattern in depression through the use of near-Infrared Spectroscopy (NIRS). We hypothesized that, through use of NIRS during the FTT, motor retardation in depression would generate a distinct PFC activation pattern, allowing for differentiation between patients with MDD and healthy controls (HCs). MethodsThirty-five patients with MDD and thirty-nine HCs underwent NIRS evaluation during performance of the FTT. The FTT included both left-finger tapping and right-finger tapping performed by a computer screen. Each participant was assessed using a 45-channel NIRS and various clinical scales. FindingsDuring the left-FTT, the left orbitofrontal cortex (OFC) showed higher oxy-hemoglobin (Oxy-Hb) activation in the MDD group when compared to the HCs. During the right-FTT, the right dorsolateral prefrontal cortex (DLPFC) demonstrated lower Oxy-Hb activation, and the dorsomedial prefrontal cortex (DMPFC) showed higher Oxy-Hb activation in the MDD group versus the HC group. ConclusionOur results demonstrated different activation patterns of the PFC between the MDD and HC groups, using FTT as a motor performance task. In particular, the OFC, the DLPFC and the DMPFC areas hold promise as new useful sites for such differentiation in future investigations.

Agronomic characterization of anaerobic digestates with near-infrared spectroscopy.

Anaerobic digestion is an increasingly widespread process for organic waste treatment and renewable energy production due to the methane content of the biogas. This biological process also produces a digestate (i.e., the remaining content of the waste after treatment) with a high fertilizing potential. The digestate composition is highly variable due to the various organic wastes used as feedstock, the different plant configurations, and the post-treatment processes used. In order to optimize digestate spreading on agricultural soils by optimizing the fertilizer dose and, thus, reducing environmental impacts associated to digestate application, the agronomic characterization of digestate is essential. This study investigates the use of near infrared spectroscopy for predicting the most important agronomic parameters from freeze-dried digestates. A data set of 193 digestates was created to calibrate partial least squares regression models predicting organic matter, total organic carbon, organic nitrogen, phosphorus, and potassium contents. The calibration range of the models were between 249.8 and 878.6 gOM.kgDM-1, 171.9 and 499.5 gC.kgDM-1, 5.3 and 74.1 gN.kgDM-1, 2.7 and 44.9 gP.kgDM-1 and between 0.5 and 171.8 gK.kgDM-1, respectively. The calibrated models reliably predicted organic matter, total organic carbon, and phosphorus contents for the whole diversity of digestates with root mean square errors of prediction of 70.51 gOM.kgDM-1, 34.84 gC.kgDM-1 and 4.08 gP.kgDM-1, respectively. On the other hand, the model prediction of the organic nitrogen content had a root mean square error of 7.55 gN.kgDM-1 and was considered as acceptable. Lastly, the results did not demonstrate the feasibility of predicting the potassium content in digestates with near infrared spectroscopy. These results show that near infrared spectroscopy is a very promising analytical method for the characterization of the fertilizing value of digestates, which could provide large benefits in terms of analysis time and cost.

Use of Near-Infrared Spectroscopy to Estimate Fiber and Crude Protein Content in Fodders

Objective: Demonstrate the need to use locally generated data in the calibration of a near-infrared spectrometer (NIRS) in order to predict the chemical characteristics of fodder; instead of using data bases from other geographic regions, as is commonly done in Mexico.
 Design/Methodology/Approach: Two groups of samples collected in prairies of the central highlands of Mexico, the first group was used to calibrate the equipment; the equations generated were validated with a second group, collected in prairies that were different from the ones of the calibration group, but in the same geographic zone.
 Results: The best regression coefficients of the NIRS predictions, compared to traditional laboratory analyses were for crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), dry matter (DM) and organic matter (OM) (0.93, 0.87, 0.87, 0.56, 0.72 y 0.68 respectively). The lowest predictive value was observed in ashes (0.27).
 Limitations of the study/implications: The results show the need to use local materials in the calibration process.
 Conclusions: NIRS will make predictions of their chemical composition, since this is influenced by geographic origin of the sample and its botanical composition

Near infrared spectroscopy (NIRS) coupled with chemometric methods to identify and estimate taxonomic relationships of flies with forensic potential (Diptera: Calliphoridae and Sarcophagidae)

Infrared spectroscopy has been gaining prominence in entomology, such as for solving taxonomic problems, sexing adult specimens, determining the age of immature specimens, detecting drugs of abuse in fly larvae, and can be an important technique in Forensic Entomology. In order to help identify the species of Calliphoridae and Sarcophagidae families, the present study aimed to evaluate the use of near infrared spectroscopy (NIRS) coupled with chemometric methods for separating fly specimens into taxonomic categories and understanding the taxonomic relationship between them. Spectra collected from nine species of flies were subjected to unsupervised principal component analysis (PCA) and hierarchical cluster analysis (HCA), in which we sought to visualize the relationship between the samples (segregation of genera and families) with subsequent identification. In PCA, the best model was achieved using five principal components (PCs), which explained 99.16% of total variance of the original data set. The first principal component (PC1) and the fourth principal component (PC4) provided the best segregation, the latter being more important in the segregation of the species Chrysomya albiceps, Lucilia eximia, and Ravinia belforti from the others. In the HCA dendrogram, there was a clear separation between the specimens by family (Calliphoridae and Sarcophagidae) and genera (Chrysomya, Lucilia, Oxysarcodexia, Peckia and Ravinia). This study shows that NIRS is efficient to identify flies’ taxonomic properties, such as family and genera, providing quick evidence for the tested species identity.

Near infrared spectroscopy in peripheral artery disease and the diabetic foot: A systematic review.

With the need for tools that assess microvascular status in diabetic foot disease (DFD) being clear, near infrared spectroscopy (NIRS) is a putative method for noninvasive testing of the diabetic foot. The use of NIRS in patients with peripheral arterial disease (PAD) has extended to its role in studying the pathophysiology of DFD. NIRS generates metrics such as recovery time, deoxygenation, oxygen consumption (VO2 ), tissue oxygen saturation (StO2 ), total haemoglobin (HbT), and oxyhaemoglobin area under the curve (O2 HbAUC ). NIRS may potentially help the multidisciplinary team stratify limbs as high-risk, especially in diabetic patients with symptoms masked by peripheral neuropathy. NIRS may be useful for assessing treatment effectiveness and preventing deterioration of patients with PAD.

Methods for quality evaluation of sweet cherry.

Sweet cherry (Prunus avium L.) is a highly valued fruit, whose quality can be evaluated using several objective methodologies, such as calibre, colour, texture, soluble solids content (SSC), titratable acidity (TA), as well as maturity indexes. Functional and nutritional compounds are also frequently determined, in response to consumer demand. The aim of the present review is to clarify and establish quality evaluation parameters and methodologies for the whole cherry supply chain, in order to promote easy and faithful communication among all stakeholders. The use of near-infrared spectroscopy (NIRS) as a non-destructive and expeditious method for assessing some quality parameters is discussed. In this review, the results of a wide survey to assess the most common methodologies for cherry quality evaluation, carried out among cherry researchers and producers within the framework of the COST Action FA1104 'Sustainable production of high-quality cherries for the European market', are also reported. The standardisation of quality evaluation parameters is expected to contribute to the preservation and shelf-life extension of sweet cherries, and the valorisation of the whole supply chain. For future studies on sweet cherry, we put forward a proposal regarding both sample size and the tests chosen to evaluate each parameter. © 2022 Society of Chemical Industry.

Linear or non-linear multivariate calibration models? That is the question

Concepts from data science, machine learning, deep learning and artificial neural networks are spreading in many disciplines. The general idea is to exploit the power of statistical tools to interpret complex and, in many cases, non-linear data. Specifically in analytical chemistry, many chemometrics tools are being developed. However, they tend to get more complex without necessarily improving the prediction ability, which conspires against parsimony. In this report, we show how non-linear analytical data sets can be solved with equal or better efficiency by easily interpretable modified linear models, based on the concept of local sample selection before model building. The latter activity is conducted by choosing a sub-set of samples located in the neighborhood of each unknown sample in the space spanned by the latent variables. Two experimental examples related to the use of near infrared spectroscopy for the analysis of target properties in food samples are examined. The comparison with seemingly more complex chemometric models reveals that local regression is able to achieve similar analytical performance, with considerably less computational burden.

Predicting single kernel and bulk milled rice alkali spreading value and gelatinization temperature class using NIR spectroscopy

AbstractBackground and ObjectivesThe alkali spreading value (ASV) of rice is a widely measured quality parameter and accepted indicator of gelatinization temperature (GT) class. However, the alkali test, developed in 1958, is labor intensive and subjective. Better methods to measure ASV and GT, for single kernel and bulk rice would provide an important tool to determine the effects of individual kernels on end‐use quality and rice with desired cooking qualities. An instrument developed by the USDA‐ARS and a commercially available near infrared (NIR) instrument were evaluated for determining ASV and classification of intermediate and low GT levels for single kernel and bulk milled rice, respectively.FindingsQuantitative prediction of ASV scores (2–7) demonstrated the potential of NIR spectroscopy for screening with a standard error of prediction for validation samples ranging from 0.91 to 1.39 for the single kernel NIR instrument, and from 0.97 to 1.19 for the commercial instrument. GT categorization into intermediate and low values, using ASV scores, showed 82.4% and 85.0% correct classification using 1 and 30‐single kernel average calibration models, respectively. GT was correctly classified (93.6%–84.4%) using a commercial NIR instrument.ConclusionNIR spectroscopy has potential for rough screening of ASV and for two‐category GT rice classification.Significance and NoveltyConsidering that NIR spectroscopy has been proven to be applicable for other quality parameters, such as rice starch content and quality, protein content, and milling degree, the addition of calibrations for ASV as a predictor of GT class will be highly beneficial while not requiring additional resources. The rapid and nondestructive classification of individual kernels may also enable physical segregation of individual kernels for use by rice researchers and/or industry for additional studies on kernels with specific quality parameters and for determining the extent of variant kernels in a milled rice lot that could affect end use quality. Future studies on the use of NIR spectroscopy for brown rice should be evaluated so that quality could be assessed, while maintaining seed viability, and then used in field studies.

Non-Invasive Spectroscopy for Measuring Cerebral Tissue Oxygenation and Metabolism as a Function of Cerebral Perfusion Pressure.

Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) measure cerebral hemodynamics, which in turn can be used to assess the cerebral metabolic rate of oxygen (CMRO2) and cerebral autoregulation (CA). However, current mathematical models for CMRO2 estimation make assumptions that break down for cerebral perfusion pressure (CPP)-induced changes in CA. Here, we performed preclinical experiments with controlled changes in CPP while simultaneously measuring NIRS and DCS at rest. We observed changes in arterial oxygen saturation (~10%) and arterial blood volume (~50%) with CPP, two variables often assumed to be constant in CMRO2 estimations. Hence, we propose a general mathematical model that accounts for these variations when estimating CMRO2 and validate its use for CA monitoring on our experimental data. We observed significant changes in the various oxygenation parameters, including the coupling ratio (CMRO2/blood flow) between regions of autoregulation and dysregulation. Our work provides an appropriate model and preliminary experimental evidence for the use of NIRS- and DCS-based tissue oxygenation and metabolism metrics for non-invasive diagnosis of CA health in CPP-altering neuropathologies.

Association of early cerebral oxygen saturation and brain injury in extremely preterm infants.

To assess the association between cerebral saturation (crSO2) using Near-Infrared Spectroscopy (NIRS) and brain injury in extremely preterm infants. This retrospective study includes 62 infants (<28 weeks gestation) who underwent continuous NIRS monitoring in the first 5 days after birth. Median crSO2 were compared in 12 h increments between infants with and without germinal matrix/intraventricular hemorrhage (GM/IVH). crSO2 was also compared by IVH severity, onset, and by grade of injury on term equivalent MRI. After 48 h of life (HOL), infants with GM/IVH had significantly lower crSO2 than those without GM/IVH in analysis adjusted for potential confounding e.g., at 49-60 HOL (69.5 (66.2, 72.8) vs. 74.7 (71.8, 77.6), p = 0.023). There were no significant differences in crSO2 by IVH subcategory or injury severity on MRI. Clinical use of NIRS has the potential to identify crSO2 patterns associated with development of GM/IVH.

The Conservation of Cloud Pattern-painted Boots (1800–1600 BP) Excavated in Yingpan, Xinjiang

ABSTRACT Yingpan, Xinjiang, was an important site on the Silk Road of China. A large number of precious objects with exquisite patterns have been excavated from this site, and they provide valuable physical evidence for the study of the cultural exchanges between China and the rest of the world. The conservation methods applied to a pair of cloud pattern-painted boots excavated in Yingpan, Xinjiang, are introduced in this paper, and the various factors influencing the repair process are explained. The results show that an oil-in-water emulsifier with contaminant removal and antibacterial functions effectively softened the hardened and deformed ancient leather. The use of near infrared spectroscopy (NIR) to evaluate the dosage of the softening agent can prevent excessive use of softening agents on historical leathers. A silk crepeline method was used to influence the physical reinforcement of the boots without affecting their appearance. It improved the fiber strength of the ancient textiles. This article is a good reference for conservators seeking to repair ancient leather products with textiles.

NIR spectroscopy for rapid measurement of moisture and cannabinoid contents of industrial hemp (Cannabis sativa)

With the legalization of industrial hemp in the United States, defined based on tetrahydrocannabinol (THC) dry weight content of ≤ 0.3%, the market for various cannabinoids including cannabidiol (CBD), cannabinol (CBN), cannabigerol (CBG), and cannabichromene (CBC) have flourished. The current measurement methods such as ultra-high performance liquid chromatography and gas chromatography (GC) require sophisticated instruments and trained personnel and are time-consuming. Therefore, there is a critical need for a rapid and reliable method to measure cannabinoids for regulatory compliance, determination of usage, and for quality control. Here, we report the use of near-infrared spectroscopy (NIRS) for rapid measurement of moisture content (MC) and cannabinoid contents of ground and whole hemp and rapid identification of legal from illegal industrial hemp. Good NIRS quantitative predictions were obtained for MC of ground and whole hemp, THC of ground hemp, CBD of ground and whole hemp, and CBC of whole hemp. Binary classification of industrial hemp as legal (≤0.3% THC) or illegal was performed using discriminant analysis and thresholding models. Discriminant calibration models developed showed correct classifications (CC) ranging from 93.0% to 94.0% with CC for independent validation at 83.9–87.5%. The concurrent multi-constituent predictions of MC and THC using NIRS allows for real-time adjustments of cannabinoid contents and rapid identification of legal or illegal hemp. These are important tools that will benefit the hemp industry, regulators, farmers, and consumers.

Regional Splanchnic Oxygenation during Continuous versus Bolus Feeding among Stable Preterm Infants.

Introduction: There is no agreement regarding the best method for tube-feeding preterm infants. Few studies, to date, have evaluated the influence of different methods of enteral feeding on intestinal oxygenation. The use of near-infrared spectroscopy (NIRS) has permitted the noninvasive measurement of splanchnic regional oxygenation (rSO2S) in different clinical conditions. The aim of this prospective, single-center study was to compare rSO2S during continuous versus bolus feeding among stable preterm infants. Methods: Twenty-one preterm infants, less than 32 weeks gestation and appropriate for gestational age, were enrolled. All infants were clinically stable and on full tube feedings. Each infant received a bolus feeding initially (20 min duration), and after 3 h, a continuous feeding (5 h duration). Infants were evaluated 30 min before and 30 min after the bolus and continuous feedings. The regional splanchnic saturation (rSO2S) was measured using near-infrared spectroscopy (NIRS) technology and systemic saturation was measured with pulse oximetry. From these measurements, we calculated the splanchnic fractional oxygen extraction ratio (FOES) for each of the four intervals. Results: rSO2S decreased after continuous vs. bolus feeding (p = 0.025), while there was a trend toward decreased SaO2 after bolus feeding (p = 0.055). The FOES, which reflects intestinal oxygen extraction, was not affected by the feeding mode (p = 0.129). Discussion/Conclusion: Continuous vs. bolus feeding decreases rSO2S but does not affect oxygen extraction by intestinal tissue; after bolus feeding there was a trend towards decreased systemic saturation.

Near Infrared Spectroscopy for Poor Grade Aneurysmal Subarachnoid Hemorrhage-A Concise Review.

Delayed cerebral ischemia (DCI) disproportionately affects poor grade aneurysmal subarachnoid hemorrhage (aSAH) patients. An unreliable neurological exam and the lack of appropriate monitoring leads to unrecognized DCI, which in turn is associated with severe long-term deficits and higher mortality. Near Infrared Spectroscopy (NIRS) offers simple, continuous, real time, non-invasive cerebral monitoring. It provides regional cerebral oxygen saturation (c-rSO2), which reflects the balance between cerebral oxygen consumption and supply. Reports have demonstrated a good correlation with other cerebral oxygen and blood flow monitoring, and credible cerebrovascular reactivity indices were also derived from NIRS signals. Multiple critical c-rSO2 values have been reported in aSAH patients, based on various thresholds, duration, variation from baseline or cerebrovascular reactivity indices. Some were associated with vasospasm, some with DCI and others with clinical outcomes. However, the poor grade aSAH population has not been specifically studied and no randomized clinical trial has been published. The available literature does not support a specific NIRS-based intervention threshold to guide diagnostic or treatment in aSAH patients. We review herein the fundamental basic concepts behind NIRS technology, relationship of c-rSO2 to other brain monitoring values and their potential clinical interpretation. We follow with a critical evaluation of the use of NIRS in the aSAH population, more specifically its ability to diagnose vasospasm, to predict DCI and its association to outcome. In summary, NIRS might offer significant potential for poor grade aSAH in the future. However, current evidence does not support its use in clinical decision-making, and proper technology evaluation is required.

Measurement of water-holding capacity in fermented milk using near-infrared spectroscopy combined with chemometric methods.

We investigated the use of near-infrared spectroscopy (NIR) for measuring water-holding capacity (WHC) in fermented milk. Increased WHC ensures improved texture and decreased syneresis in fermented dairy products and also improves cheese yield. NIR combined with partial least-squares-discriminant analysis (PLS-DA) was found to be a promising rapid and non-invasive method with no pretreatment of the samples for prediction of WHC in fermented milk samples. Analysis of the chemical bonds in the region 10 700-4500 cm-1 (935-2200 nm) of the electromagnetic spectrum was able to distinguish between samples with high vs. low WHC. This technique was successfully used to screen different strains of lactic acid bacteria for their ability to provide fermented milk with increased WHC, which is of great importance for use in various dairy products.

Potential of Near-Infrared Spectroscopy for the Determination of Olive Oil Quality.

The analysis of the physico-chemical parameters of quality of olive oil is still carried out in laboratories using chemicals and generating waste, which is relatively costly and time-consuming. Among the various alternatives for the online or on-site measurement of these parameters, the available literature highlights the use of near-infrared spectroscopy (NIRS). This article intends to comprehensively review the state-of-the-art research and the actual potential of NIRS for the analysis of olive oil. A description of the features of the infrared spectrum of olive oil and a quick explanation of the fundamentals of NIRS and chemometrics are also included. From the results available in the literature, it can be concluded that the four most usual physico-chemical parameters that define the quality of olive oils, namely free acidity, peroxide value, K232, and K270, can be measured by NIRS with high precision. In addition, NIRS is suitable for the nutritional labeling of olive oil because of its great performance in predicting the contents in total fat, total saturated fatty acids, monounsaturated fatty acids, and polyunsaturated fatty acids in olive oils. Other parameters of interest have the potential to be analyzed by NIRS, but the improvement of the mathematical models for their determination is required, since the errors of prediction reported so far are a bit high for practical application.

Use of near infrared spectroscopy for hemodynamic monitoring in pediatrics.

Near infrared spectroscopy (NIRS) is a non-invasive optical technique for the evaluation of regional tissue oxygenation using transcutaneous detectors. In recent years, publications about this topic have increased exponentially; this reflects the growing interest among investigators and clinicians about this new technology and its potential benefits for pediatric patients. The objective of this review is to know the functioning and potential uses of regional saturation measured by NIRS and establish future challenges.

Use of near-infrared spectroscopy and chemometrics for fast discrimination of Sargassum fusiforme

Edible marine algae, often referred to as seaweeds, have health benefits and nutritional value. Origin discrimination of seaweeds is essential for quality assurance and traceability. As a rapid, easy, and economical method, near-infrared spectroscopy (NIR) was used in this study to investigate its ability to identify Sargassum fusiforme according to geographical origin, cultivar, and production method. A potential particle swarm optimization-support vector machine (PSO-SVM) identification model was constructed and exhibited its superiority in the origin determination of S. fusiforme. Results showed that the correct recognition rates were 90.00% for geographical origin, 100.00% for cultivar, and 100.00% for production method, when the PSO-SVM models were validated using the test sets. Overall, the results proved the potential of NIR spectroscopy combined with PSO-SVM models as a fast analytical method to trace the origin of S. fusiforme in terms of geographical origin, cultivar, and production method.

Determination of Second Lactate Threshold Using Near-infrared Spectroscopy in Elite Cyclists.

The use of near-infrared spectroscopy could be an interesting alternative to other invasive or expensive methods to estimate the second lactate threshold. Our objective was to compare the intensities of the muscle oxygen saturation breakpoint obtained with the Humon Hex and the second lactate threshold in elite cyclists. Ninety cyclists performed a maximal graded exercise test. Blood capillary lactate was obtained at the end of steps and muscle oxygenation was continuously monitored. There were no differences (p>0.05) between muscle oxygen oxygenation breakpoint and second lactate threshold neither in power nor in heart rate, nor when these values were relativized as a percentage of maximal aerobic power or maximum heart rate. There were also no differences when men and women were studied separately. Both methods showed a highly correlation in power (r=0.914), percentage of maximal aerobic power (r=0.752), heart rate (r=0.955), and percentage of maximum heart rate (r=0.903). Bland-Altman resulted in a mean difference of 0.05±0.27 W·kg-1, 0.91±4.93%, 0.63±3.25 bpm, and 0.32±1.69% for power, percentage of maximal aerobic power, heart rate and percentage of maximum heart rate respectively. These findings suggest that Humon may be a non-invasive and low-cost alternative to estimate the second lactate threshold intensity in elite cyclists.

Near-infrared spectroscopy for the inline classification and characterization of fruit juices for a product-customized flash pasteurization.

The feasibility of inline classification and characterization of seven fruit juice varieties was investigated by the application of near‐infrared spectroscopy (NIRS) combined with chemometrics. The findings are intended to be used to optimize the flash pasteurization of liquid foods. More precise information of the kind of product in real time had to be achieved to enable a more product‐specific process. Using the method of partial least squares discriminant analysis, the fruit juice varieties were classified, showing a classification rate of 100% regarding an internal and 69% regarding an external test sets. A characterization by the extract content, pH value, turbidity, and viscosity was made by fitting a partial least squares regression model. The percentage prediction error of the pH value was <3% for internal and external test sets, and for the Brix value prediction errors were about 4% (internal) and 20% (external). The parameters viscosity and turbidity were found to be unsuitable. Despite this, the strategy applied to gain more product‐specific information in real time showed to be feasible. By linking the results to a database containing potentially harmful microorganisms for various types of fruit juices, a more product‐specific calculation of the necessary heat input can be performed. To demonstrate the practical relevance, a comparison between conventional and product‐adapted process control was performed using two fruit varieties as examples in case of Alicyclobacillus acidoterrestris. Thus, with more accurate product information, achieved through the use of NIRS with chemometrics, a more precise calculation of the heat input can be achieved.