Use Of Near-infrared Spectroscopy Technology Research Articles

Near-infrared spectroscopy for analysing livestock diet quality: A systematic review

Near-infrared spectroscopy (NIRS) is a non-invasive and fast technology that has been increasingly used to analyse livestock diet quality. The objective of this study was to conduct a systematic review of the literature to examine the utilisation of NIRS technology for analysing livestock diet quality, with a focus on identifying trends, methodologies, and challenges in recent research. We conducted a systematic search of the literature on five electronic databases and retrieved 718 studies that have been published on the subject. Fifty-four studies were subsequently selected and investigated in depth. These studies were categorised into two groups, namely benchtop and portable, based on the types of NIRS devices utilised, with a majority employing the reflectance spectra mode. Our analysis found that standard normal variate (SNV), detrend (DT), and multiplicative scatter correction (MSC) are the most commonly used spectral data processing methods. The findings indicate that NIRS technology can provide accurate and reliable measurements of key livestock diet quality parameters such as crude protein, fibre, and moisture content. Additionally, we discuss the challenges associated with NIRS technology and provide recommendations for future research directions to further advance the use of NIRS technology in the livestock industry.

The Case for Measuring Long Bone Hemodynamics With Near-Infrared Spectroscopy.

Diseases and associated fragility of bone is an important medical issue. There is increasing evidence that bone health is related to blood flow and oxygen delivery. The development of non-invasive methods to evaluate bone blood flow and oxygen delivery promise to improve the detection and treatment of bone health in human. Near-infrared spectroscopy (NIRS) has been used to evaluate oxygen levels, blood flow, and metabolism in skeletal muscle and brain. While the limited penetration depth of NIRS restricts its application, NIRS studies have been performed on the medial aspect of the tibia and some other prominent bone sites. Two approaches using NIRS to evaluate bone health are discussed: (1) the rate of re-oxygenation of bone after a short bout of ischemia, and (2) the dynamics of oxygen levels during an intervention such as resistance exercise. Early studies have shown these approaches to have the potential to evaluate bone vascular health as well as the predicted efficacy of an intervention before changes in bone composition are detectable. Future studies are needed to fully develop and exploit the use of NIRS technology for the study of bone health.

Effect of Skin Pigmentation on Near Infrared Spectroscopy

The purpose of this study was to determine the effects of skin pigmentation regarding Near Infrared Spectroscopy (NIRS) tissue oxygen saturation values (StO2). The study examined NIRS values in individuals with varying skin pigmentation on the anterior compartment of the lower leg and volar forearm to determine if correlation exists among three NIRS devices, the EQUANOX, Casmed, and INVOS. Skin pigmentation was measured on the anterior lower leg (AL) and volar forearm (VF) of participants using a noninvasive colorimeter that employed reflective spectroscopy to produce a quantitative value for erythema (skin “redness”) and melanin (skin pigment). Muscle oxygenation was measured using three oximetry devices with sensors placed in the same areas. The EQUANOX device showed no significant correlation with skin pigmentation, while the Casmed and INVOS devices showed moderate and significant correlation with skin pigmentation, respectively. Different devices have different abilities to remove confounding variables, such as skin pigmentation and erythema, which may affect clinical decision-making, and affect the use of NIRS technology.

Chemical characteristics and mineral composition of quinoa by near‐infrared spectroscopy

Quinoa (Chenopodium quinoa Willd.) has been traditionally used as a foodstuff in the Andes and it has gained increasing interest in recent years owing to its high nutritional value. The potential of near-infrared spectroscopy (NIRS) for estimating chemical compounds in quinoa was studied because of the possibility of conducting direct measurement without prior sample treatment. The use of NIRS technology with a remote reflectance fiber-optic probe for the analysis of major compounds and mineral composition of 48 quinoa samples was studied. The calibration of the NIRS instrument was conducted using modified partial least squares (MPLS) analysis. This allowed the determination of protein (16.0-20.2 g 100g⁻¹), crude fiber (1.8-3.1 g 100g⁻¹), fat (4.4-7.5 g 100g⁻¹), calcium (298.8-1164.5 mg kg⁻¹), iron (0-948.5 mg kg⁻¹) and phosphorus (2735.0-4543.3 mg kg⁻¹). The correlation coefficients (RSQ) were 0.83 for protein, 0.73 for crude fiber, 0.93 for fat; 0.60 for calcium; 0.76 for iron and 0.75 for phosphorus. The robustness of the equations obtained was verified by external validation on unknown quinoa samples. NIRS with fiber-optic probe provides an alternative for the determination of chemical compounds of quinoa, faster and at lower cost, with results comparable with chemical methods.

Visible and NIR Spectroscopy to assess biodiesel quality: Determination of alcohol and glycerol traces

Biodiesel quality control is of relevant importance as biodiesel properties influence diesel engine performance. In the present work, the benefits of the use of visible and near-infrared Spectroscopy (NIRS) as a technique for screening undesirable contaminants, i.e. methanol and glycerol content in biodiesel are presented. Excess of methanol decreases heating value and flash point and increases carbon deposits, while the presence of glycerol may cause injector tip coking and deposits in the combustion chamber. Biodiesel samples contaminated with different amounts of methanol and glycerol were scanned by NIRS. Their NIR spectra were acquired at 2-nm intervals over a wavelength range from 400 to 2500nm (visible plus near-infrared regions). First derivative of the spectra were calculated and correlated to the raw optical data by means of modified partial least-squares (MPLS) regression. First derivative equation of the optical data, pretreated by standard normal variate (SNV) and De-trending (DT) transformations, showed a coefficient of determination r2 in the cross-validation step of 0.99 and 0.81, for the samples contaminated with methanol and glycerol, respectively. Also, the standard deviation to standard error of cross-validation ratio (RPD) was 10.0 and 2.5, respectively. These statistics are indicative of the high capacity of prediction of the equations for methanol content and acceptable for glycerol content. Visible spectra also showed differences related to the samples, thus indicating it could serve to determine the presence of these contaminants. The use of NIRS technology provides a trustworthy and low-cost method to determine the presence of undesirable amounts of methanol and glycerol. It also offers an important saving of time (each analysis requires less than two minutes).

Monitoring trauma and intensive care unit resuscitation with tissue hemoglobin oxygen saturation

IntroductionThe purpose of the present review is to review our experience with near-infrared spectroscopy (NIRS) monitoring in shock resuscitation and predicting clinical outcomes.MethodsThe management of critically ill patients with goal-oriented intensive care unit (ICU) resuscitation continues to evolve as our understanding of the appropriate physiologic targets improves. It is now recognized that resuscitation to achieve supranormal indices is not beneficial in all patients and may precipitate abdominal compartment syndrome.ResultsOver the years, ICU technology has provided physicians with specific physiologic parameters to guide shock resuscitation. Throughout this time, the tissue hemoglobin oxygen saturation (StO2) monitor has emerged as a non-invasive means to obtain reliable physiologic parameters to guide clinicians' resuscitative efforts. StO2 monitors have been shown to aid in early identification of nonresponders and to predict outcomes in hemorrhagic shock and ICU resuscitation. These data have also been used to better understand and refine existing resuscitation protocols. More recently, use of NIRS technology to guide resuscitation in septic shock has been shown to predict outcomes in high-risk patients.ConclusionsStO2 is an important tool in identifying high-risk patients in septic and hemorrhagic shock. It is a non-invasive means of obtaining vital information regarding outcome and adequacy of resuscitation.

Use of NIRS technology with a remote reflectance fibre-optic probe for predicting major components in bee pollen

In the present work, we study the use of near infra-red spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe for determination of the major components in bee pollen. The method allows immediate control of the bee pollen without prior sample treatment or destruction through direct application of the fibre-optic probe to the sample. The regression method employed was modified partial least squares (MPLS). The calibration results obtained using 45 samples of bee pollen allowed the measurement of protein, moisture, ash, reducing sugars, and pH with multiple correlation coefficients (RSQ) and prediction corrected standard errors (SEPC) of 0.91, 0.56% for protein, of 0.78 and 0.49% for moisture; 0.92 and 0.049% for ash; 0.81 and 1.32 g of glucose/100 g of bee pollen; 0.84 and 0.15 for pH, respectively. The prediction capacity of the pattern was checked by applying it to samples of unknown pollen in external validation.

Use of NIRS technology with a remote reflectance fibre-optic probe for predicting mineral composition (Ca, K, P, Fe, Mn, Na, Zn), protein and moisture in alfalfa

In the present work we study the use of near-infrared spectroscopy (NIRS) technology together with a remote reflectance fibre-optic probe for the analysis of major (Ca, K, P) and minor (Fe, Mn, Na, Zn) elements, protein and moisture in alfalfa. The method allows immediate analysis of the alfalfa without prior sample treatment or destruction through direct application of the fibre-optic probe on ground samples in the case of the mineral composition and on-ground and compacted (baled) samples in the case of protein and humidity. The regression method employed was modified partial least-squares (MPLS). The calibration results obtained using samples of alfalfa allowed the determination of Ca, K, P, Fe, Mn, Na and Zn, with a standard error of prediction (SEP(C)) and a correlation coefficient (RSQ) expressed in mg/kg of alfalfa of 1.37x10(3) and 0.878 for Ca, 1.10x10(3) and 0.899 for K, 227 and 0.909 for P, 103 and 0.948 for Fe, 5.1 and 0.843 for Mn, 86.2 and 0.979 for Na, and of 1.9 and 0.853 for Zn, respectively. The SEP(C) and RSQ values (in %) for protein and moisture in ground samples were 0.548 and 0.871 and 0.150 and 0.981, respectively; while in the compacted samples they were 0.564 and 0.826 and 0.262 and 0.935, respectively. The prediction capacity of the model and the robustness of the method were checked in the external validation in alfalfa samples of unknown composition, and the results confirmed the suitability of the method.

Near-infrared evaluation of wet mink diets

Near-infrared spectroscopy (NIRS) is a relatively new technology in the determination of chemical constituents in compound (complete) feeds. The current paper reports on the application of NIRS to the measurement of dry matter (DM), crude protein (CP) and crude fat (CF) in wet diets for mink and the development of a calibration to predict these chemical constituents. In total, 287 typical wet mink feeds were collected from commercial mink ranches located on the south shore of Nova Scotia, Canada, to provide a large representative sample population. After population structuring, using CENTER and SELECT software (ISI) during calibration development, there were 73 samples remaining in the calibration. All feeds were analyzed by standard reference methods (primary) and then scanned (secondary) with a scanning monochromator NIR, model 5000 (NIRSystems Inc.), to develop a global calibration to predict DM, CP and CF. The “best fit” treatment for the calibration was a modified partial least squares analysis with a standard normal variate (SNV) correction for scatter, a derivative math treatment of 1, 4, 4, 1 to remove particle size interference while scanning segments 1108–2492 skipping every 8 nm for prediction of DM, CP and CF. Standard error of calibration (SEC, g kg −1), proportion of explained variance (RSQ), and standard error of cross-validation (SECV, g kg −1) for DM, CP, and CF were; 11.9, 0.92 and 14.3; 11.3, 0.96 and 17.5; and 20.0, 0.92 and 22.5. Two external validation sets were used to evaluate the accuracy of the calibration with standard error of prediction (SEP), ranging from 12.7 to 19.5 g kg −1. Based on the results of the data reported the use of NIRS technology in the nutritional evaluation of complete wet diets for mink is feasible. The most promising future use for this NIRS application is as on-line quality control in a central feed kitchen.