Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals

Objective. Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain–computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). Approach. We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. Main results. All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. Significance. The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.

The effect of arts speech therapy on cerebral oxygenation and low frequency hemodynamic oscillations measured using functional near-infrared spectroscopy

Introduction: As a previous study revealed, arts speech therapy (AST) affects cardiorespiratory interaction [1]. The aim of the present study was to investigate whether AST also has effects on brain oxygenation and hemodynamics measured non-invasively using near-infrared spectroscopy (NIRS). Material and methods: NIRS measurements were performed on 17 subjects (8 men and 9 women, mean age: 35.6 ± 12.7 y) during AST. Each measurement lasted 35 min, comprising 8 min pre-baseline, 10 min recitation and 20 min post-baseline. For each subject, measurements were performed for three different AST recitation tasks (recitation of alliterative, hexameter and prose verse). Relative concentration changes of oxyhemoglobin (Δ[O2Hb]) and deoxyhemoglobin (Δ[HHb]) as well as the tissue oxygenation index (TOI) were measured using a Hamamatsu NIRO300 NIRS device and a sensor placed on the subjects forehead. Movement artifacts were removed using a novel method [2]. Statistical analysis (Wilcoxon test) was applied to the data to investigate (i) if the recitation causes changes in the median values and/or in the Mayer wave power spectral density (MW-PSD, range: 0.07–0.13 Hz) of Δ[O2Hb], Δ[HHb] or TOI, and (ii) if these changes vary between the 3 recitation forms. Results: For all three recitation styles a significant (p < 0.05) decrease in Δ[O2Hb] and TOI was found, indicating a decrease in blood flow. These decreases did not vary significantly between the three styles. MW-PSD increased significantly for Δ[O2Hb] when reciting the hexameter and prose verse, and for Δ[HHb] and TOI when reciting alliterations and hexameter, representing an increase in Mayer waves. The MW-PSD increase for Δ[O2Hb] was significantly larger for the hexameter verse compared to alliterative and prose verse Conclusion: The study showed that AST affects brain hemodynamics (oxygenation, blood flow and Mayer waves). Recitation caused a significant decrease in cerebral blood flow for all recitation styles as well as an increase in Mayer waves, particularly for the hexameter, which may indicate a sympathetic activation. References 1. D. Cysarz, D. von Bonin, H. Lackner, P. Heusser, M. Moser, H. Bettermann. Am J Physiol Heart Circ Physiol, 287 (2) (2004), pp. H579–H587 2. F. Scholkmann, S. Spichtig, T. Muehlemann, M. Wolf. Physiol Meas, 31 (5) (2010), pp. 649–662

Rapid assessment of cerebral autoregulation by near-infrared spectroscopy and a single dose of phenylephrine

Rapid bedside determination of cerebral blood pressure autoregulation (AR) may improve clinical utility. We tested the hypothesis that cerebral Hb oxygenation (HbDiff) and cerebral Hb volume (HbTotal) measured by near-infrared spectroscopy (NIRS) would correlate with cerebral blood flow (CBF) after single dose phenylephrine (PE). Critically ill patients requiring artificial ventilation and arterial lines were eligible. During rapid blood pressure rise induced by i.v. PE bolus, ΔHbDiff and ΔHbTotal were calculated by subtracting values at baseline (normotension) from values at peak blood pressure elevation (hypertension). With the aid of NIRS and bolus injection of indocyanine green, relative measures of CBF, called blood flow index (BFI), were determined during normotension and during hypertension. BFI during hypertension was expressed as percentage from BFI during normotension (BFI%). Autoregulation indices (ARIs) were calculated by dividing BFI%, ΔHbDiff, and ΔHbTotal by the concomitant change in blood pressure. In 24 patients (11 newborns and 13 children), significant correlations between BFI% and ΔHbDiff (or ΔHbTotal) were found. In addition, the associations between Hb-based ARI and BFI%-based ARI were significant with correlation coefficients of 0.73 (or 0.72). Rapid determination of dynamic AR with the aid of cerebral Hb signals and PE bolus seems to be reliable.

Physiological effects of mechanical pain stimulation at the lower back measured by functional near-infrared spectroscopy and capnography

The aim was to investigate the effect of mechanical pain stimulation at the lower back on hemodynamic and oxygenation changes in the prefrontal cortex (PFC) assessed by functional near-infrared spectroscopy (fNIRS) and on the partial pressure of end-tidal carbon dioxide ( PetCO 2) measured by capnography. 13 healthy subjects underwent three measurements (M) during pain stimulation using pressure pain threshold (PPT) at three locations, i.e., the processus spinosus at the level of L4 (M1) and the lumbar paravertebral muscles at the level of L1 on the left (M2) and the right (M3) side. Results showed that only in the M2 condition the pain stimulation elicited characteristic patterns consisting of (1) a fNIRS-derived decrease in oxy- and total hemoglobin concentration and tissue oxygen saturation, an increase in deoxy-hemoglobin concentration, (2) a decrease in the PetCO 2 response and (3) a decrease in coherence between fNIRS parameters and PetCO 2 responses in the respiratory frequency band (0.2-0.5 Hz). We discuss the comparison between M2 vs. M1 and M3, suggesting that the non-significant findings in the two latter measurements were most likely subject to effects of the different stimulated tissues, the stimulated locations and the stimulation order. We highlight that PetCO 2 is a crucial parameter for proper interpretation of fNIRS data in experimental protocols involving pain stimulation. Together, our data suggest that the combined fNIRS-capnography approach has potential for further development as pain monitoring method, such as for evaluating clinical pain treatment.

[O/Fe] ESTIMATES FOR CARBON-ENHANCED METAL-POOR STARS FROM NEAR-INFRARED SPECTROSCOPY

We report on oxygen abundances determined from medium-resolution near-infrared spectroscopy for a sample of 57 carbon-enhanced metal-poor (CEMP) stars selected from the Hamburg/ESO Survey. The majority of our program stars exhibit oxygen-to-iron ratios in the range +0.5 < [O/Fe]< + 2.0. The [O/Fe] values for this sample are statistically compared to available high-resolution estimates for known CEMP stars as well as to high-resolution estimates for a set of carbon-normal metal-poor stars. Carbon, nitrogen, and oxygen abundance patterns for a sub-sample of these stars are compared to yield predictions for very metal-poor asymptotic giant branch (AGB) abundances in the recent literature. We find that the majority of our sample exhibit patterns that are consistent with previously studied CEMP stars having s-process-element enhancements and thus have very likely been polluted by carbon- and oxygen-enhanced material transferred from a metal-poor AGB companion.

Near infrared spectroscopy for soil bulk density assessment

P>Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic ""core cylinders"". The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (-0.002 g cm-3) and the lowest prediction error (0.13 g cm-3) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.

Can near infrared spectroscopy of the liver monitor tissue oxygenation?

Measurement of the hepatic oxygenation index by near infrared spectroscopy is a suitable method to estimate the oxygenation and can be a non-invasive means to continuously monitor tissue perfusion and to detect early haemodynamic disturbances in critically ill children.

Developments in near infrared spectroscopy

Vibrational spectroscopy at high excitation is an important research frontier for two reasons. Firstly, the near infrared is proving to be an important area for the analytical applications of spectroscopy, and we would therefore like to understand how the spectra we observe relate to the molecular structure of the absorbing species. Secondly, there is a fundamental interest in understanding molecular dynamics and energy flow within a polyatomic molecule at high excitation, because this is the boundary between spectroscopy and chemistry through which we try to understand the details of a chemical reaction. In this presentation I shall survey recent progress in this field.

Visible-near infrared spectroscopy sensor for predicting curd and whey composition during cheese processing

The potential of visible-near infrared spectra, obtained using a light backscatter sensor, in conjunction with chemometrics, to predict curd moisture and whey fat content in a cheese vat was examined. A three-factor (renneting temperature, calcium chloride, cutting time), central composite design was carried out in triplicate. Spectra (300–1,100 nm) of the product in the cheese vat were captured during syneresis using a prototype light backscatter sensor. Stirring followed upon cutting the gel, and samples of curd and whey were removed at 10 min intervals and analyzed for curd moisture and whey fat content. Spectral data were used to develop models for predicting curd moisture and whey fat contents using partial least squares regression. Subjecting the spectral data set to Jack-knifing improved the accuracy of the models. The whey fat models (R = 0.91, 0.95) and curd moisture model (R = 0.86, 0.89) provided good and approximate predictions, respectively. Visible-near infrared spectroscopy was found to have potential for the prediction of important syneresis indices in stirred cheese vats.

Prediction of moisture, calorific value, ash and carbon content of two dedicated bioenergy crops using near-infrared spectroscopy

The potential of near infrared spectroscopy in conjunction with partial least squares regression to predict Miscanthus xgiganteus and short rotation coppice willow quality indices was examined. Moisture, calorific value, ash and carbon content were predicted with a root mean square error of cross validation of 0.90% (R2 = 0.99), 0.13 MJ/kg (R2 = 0.99), 0.42% (R2 = 0.58), and 0.57% (R2 = 0.88), respectively. The moisture and calorific value prediction models had excellent accuracy while the carbon and ash models were fair and poor, respectively. The results indicate that near infrared spectroscopy has the potential to predict quality indices of dedicated energy crops, however the models must be further validated on a wider range of samples prior to implementation. The utilization of such models would assist in the optimal use of the feedstock based on its biomass properties.

Nuclear and extended spectra of NGC 1068-I. Hints from near-infrared spectroscopy

We report the first simultaneous zJHK spectroscopy on the archetypical Seyfert 2 galaxy NGC 1068 covering the wavelength region 0.9-2.4 mu m. The slit, aligned in the north-south direction and centred in the optical nucleus, maps a region 300 pc in radius at subarcsec resolution, with a spectral resolving power of 360 km s-1. This configuration allows us to study the physical properties of the nuclear gas including that of the north side of the ionization cone, map the strong excess of continuum emission in the K band and attributed to dust and study the variations, both in flux and profile, in the emission lines. Our results show the following. (1) Mid- to low-ionization emission lines are split into two components, whose relative strengths vary with the position along the slit and seem to be correlated with the jet. (2) The coronal lines are single-peaked and are detected only in the central few hundred of pc from the nucleus. (3) The absorption lines indicate the presence of intermediate age stellar population, which might be a significant contributor to the continuum in the near-IR spectra. (4) Through some simple photoionization models we find photoionization as the main mechanism powering the emitting gas. (5) Calculations using stellar features point to a mass concentration inside the 100-200 pc of about 1010 M(circle dot).