Does the spectral format matter in diffuse reflection spectroscopy?

Near-infrared, and more recently, mid-infrared diffuse reflection spectroscopy (more commonly and erroneously called reflectance spectroscopy) have come to be extensively used to determine the composition of products ranging from forages and drugs to soils. In these methods, spectra are generally collected as reflectance or R and transformed to log (1/reflectance). However, some near-infrared researchers do not transform the data, but use the data directly as reflectance. As it is generally held that procedures such as partial least squares regression do not work well with nonlinear data and the log (1/reflectance) transformation is held to be a best effort at linearization for near-infrared diffuse reflection spectral data, the question arises as to why then does not everyone transform the data? The objective of this work was to investigate this question using near-infrared and mid-infrared spectra in various formats. Calibrations were developed using spectral data from forages in several formats: reflectance, log (1/reflectance), non-background corrected single beam spectra, interferograms, and Kubelka-Munk transformed data. Calibrations were developed using both non-pretreated spectra and using data pretreatments such as derivatives. Results showed that calibrations using partial least squares regression did not require any specific data format. Accurate calibrations were developed for fiber, digestibility, and protein measures in forages using any of the aforementioned spectral formats including non-background-corrected single beam spectra and even interferograms. While calibrations could be developed using any of the formats, results indicated that those using Kubelka-Munk and especially interferograms did not perform as well as the others, although they were still quite good. In conclusion, results using forage spectra indicated that accurate and equivalent calibrations can be developed using diffuse reflectance data, with (reflectance) or without background correction (single beam spectra), or log (1/reflectance) at least when using partial least squares regression for calibration development.

Mid-Infrared and near-infrared spectral properties of mycorrhizal and non-mycorrhizal root cultures.

We investigated the Fourier-transformed mid-infrared (MIR) and near-infrared (NIR) spectroscopic properties of mycorrhizal (M) and non-mycorrhizal (NM) carrot roots with the goal of finding infrared markers for colonization by arbuscular mycorrhizal (AM) fungi. The roots were cultured with or without the AM fungus Glomus intraradices under laboratory conditions. A total of 50 M and NM samples were produced after pooling subsamples. The roots were dried, ground, and scanned separately for the NIR and MIR analyses. The root samples were analyzed for fatty acid composition in order to confirm mycorrhizal infection and to determine the presence of fatty acid markers. Besides the roots, fatty acid standards, pure cultures of saprophytic fungi, and chitin were also scanned in order to identify spectral bands likely to be found in M samples. Principal components analysis (PCA) was used to illustrate spectral differences between the M and NM root samples. The NIR analysis achieved good resolution with the raw spectral data and no pretreatment was needed to obtain good resolution in the PCA analysis of the NIR data. Standard normal variate and detrending pretreatment improved the resolution between M and NM in the MIR range. The PCA loadings and/or the spectral subtraction of selected samples showed that M roots are characterized by absorbances at or close to 400 cm(-1), 1100-1170 cm(-1), 1690 cm(-1), 2928 cm(-1), and 5032 cm(-1). The NM samples had characteristic absorbances at or near 1734 cm(-1), 3500 cm(-1), 4000 cm(-1), 4389 cm(-1), and 4730 cm(-1). Some of the bands that differentiate M from NM roots are prominent in the spectra of pure fungal cultures, chitin, and fatty acids. Our results show that mycorrhizal and nonmycorrhizal root tissues can be differentiated via MIR and NIR spectra with the advantage that the same samples can then be used for other analyses.

Mid-infrared diffuse reflectance spectroscopic examination of charred pine wood, bark, cellulose, and lignin: implications for the quantitative determination of charcoal in soils.

Fires in terrestrial ecosystems produce large amounts of charcoal that persist in the environment and represent a substantial pool of sequestered carbon in soil. The objective of this research was to investigate the effect of charring on mid-infrared spectra of materials likely to be present in forest fires in order to determine the feasibility of determining charred organic matter in soils. Four materials (cellulose, lignin, pine bark, and pine wood) and char from these materials, created by charring for various durations (1 to 168 h) and at various temperatures (200 to 450 degrees C), were studied. Mid-infrared spectra and measures of acidity (total acids, carboxylic acids, lactones, and phenols as determined by titration) were determined for 56 different samples (not all samples were charred at all temperatures/durations). Results showed spectral changes that varied with the material, temperature, and duration of charring. Despite the wide range of spectral changes seen with the differing materials and length/temperature of charring, partial least squares calibrations for total acids, carboxylic acids, lactones, and phenols were successfully created (coefficient of determination and root mean squared deviation of 0.970 and 0.380; 0.933 and 0.227; 0.976 and 0.120; and 0.982 and 0.101 meq/g, respectively), indicating that there is a sufficient commonality in the changes to develop calibrations without the need for unique calibrations for each specific material or condition of char formation.

Comparison of diffuse reflectance fourier transform mid-infrared and near-infrared spectroscopy with grating-based near-infrared for the determination of fatty acids in forages.

Diffuse reflectance Fourier transform mid infrared (FTMIR) and near-infrared spectroscopy (FTNIR) were compared to scanning monochromator-grating-based near-infrared spectroscopy (SMNIR), for their ability to quantify fatty acids (FA) in forages. A total of 182 samples from thirteen different forage cultivars and three different harvest times were analyzed. Three calibration analyses were conducted for lauric (C12:0), myristic (C14:0), palmitic (C16:0), stearic (C18:0), palmitoleic (C16:1), oleic (C18:1), linoleic (C18:2), and alpha-linolenic (C18:3) acids. When all samples were used in a one-out partial least squares (PLS) calibration, the average R (2) were FTNIR (0.95) > SMNIR (0.94) > FTMIR (0.91). Constituents C18:2 and C16:0 had among the highest R (2) regardless of the spectroscopic method used. The FTNIR did better for C12:0, C14:0, and C18:3. The SMNIR did better for C16:0, C16:1, C18:0, C18:1, and C18:2. A second set of calibrations developed with half of the samples as the calibration set and the rest as the validation set showed that all the methods produce acceptable calibrations, with calibration R (2) above 0.9 for most constituents. However, the SMNIR had a better average calibration relative error than the FTNIR, which was slightly better than the FTMIR. A third set of calibration equations developed using 100 random PLS runs with the 182 samples split randomly also shows that the three spectral methods are satisfactory for predicting FA. It is not clear whether any of the spectral methods is distinctly better than another. Calibration R (2) and validation R (2) were higher for most FA with the SMNIR than the FTMIR and FTNIR.

Stearic acid solubility and cubic phase volume.

Stearic acid (SA) is highly soluble in structurally diverse solvents. SA/solvent packing within a (24.8 A)3 cubic volume explains the stoichiometry of SA solubility at multiple temperatures in multiple solvents. In the absence of solvent, the cubic volume contains 25 molecules at van der Waals distances from each other. At 55 degrees C, SA occupied half the cubic volume in saturated solution of four structurally diverse solvents. Below 4% SA/volume (e.g. in acetonitrile), the head and foot of each SA molecules on average is more than one solvent molecule away from the head and foot of a neighboring SA molecule. At 50% SA/cubic volume, -CH2- groups on SA molecules are separated from neighboring -CH2- groups on SA molecules by a monolayer of solvent molecules. Lowering the temperature from 55 to 25 degrees C, the volume fraction of SA decreased by a factor of 2 (or more) for every 6 degrees C. Lowering temperature increased the relative number of column of solvent molecules in the cubic phase, and correspondingly, the distance between SA molecules within the cubic volume increased. In three of five solvents, molecular mechanics calculations demonstrated the van der Waals stabilization that occurs from SA/SA affinity in the absence of solvent is similar in magnitude to the van der Waals stabilization from SA/solvent affinity. Methyl-t-butyl ether was less stabilized than hexane, acetone or methanol because the more bulky molecules packed less efficiently within the cubic volume. The most efficient/most stable packing however was still as columns of solvent between columns of SA. The efficiency and stability of SA and solvent packing optimal within the (24.8 A)3 cubic volume. Between 100 and 8% SA, multiple SA molecules present within the cubic volume function as SA aggregates. Both inter- and intra-cubic (phase) volume properties of SA aggregates coexist. Although acetonitrile and SA at the molecular level are both rod shaped, acetonitrile disrupted the packing of SA molecules within the cubic phase. The disrupted packing explains the much lower solubility of SA in acetonitrile than in the other solvents. The same molecular structures (e.g. methanol) can either stabilize or disrupt the packing of aggregated SA molecules, depending upon temperature. The mechanisms of aggregation within cubic volumes could also occur with structurally more complicated lipids. Aggregation and dispersion from such cubic phases could also be present in more complex chemical and/or macromolecular environments.

Specular reflection and diffuse reflectance spectroscopy of soils.

Studies on the occurrence and effects of specular reflection in midinfrared spectra of soils have shown that distortions due to specular reflection occur for both organic (humic acid) and non-organic fractions (carbonates, silica, ashed fraction of soil). The results explain why the spectra of CaCO(3) in limed soils do not match published spectra and offer an explanation as to why the presence of inorganic C interferes with the development of calibrations for organic C. These results may also have implications for the use of mid-infrared spectra for quantitative and qualitative analysis of soils. For example, libraries of spectra collected by means other than diffuse reflectance would be largely useless for comparing mineral spectra to soil spectra. To obtain the best results with forages and grains, it is necessary to develop separate calibrations for different products, but this has not seemed to be a problem for diverse sets of soil samples with C contents of 0 to 5%. Mid-infrared calibrations have also appeared to be more robust than the corresponding near-infrared calibrations in that fewer outliers are found. However, the results discussed here indicate that at least for some soil types (e. g., large differences in mineralogy or C contents), separate calibrations may be necessary.

Influence of ash on the fiber composition of dried dairy manures.

The objective of this work was to examine the role of ash in the compositional analysis of dried dairy manures. Ninety-nine dairy manures obtained from Connecticut, Maryland, New York, Pennsylvania and Virginia were dried at 60 degrees C, and ground to 20 mesh. Samples were analyzed for neutral and acid detergent fiber, acid detergent lignin, total carbon, total nitrogen, and ash. In addition, cellulose and hemicellulose were computed by difference. Results indicated that high ash contents (8-52% of dry matter) can dramatically and unpredictably alter various measures of fiber composition and are a significant source of error in the determination of manure composition and how it relates to mineralization or other compositional influenced factors. Also, while the ash content of the dried intact manure can easily be determined, it is difficult to estimate the ash contribution to the individual fiber determinations, especially if sequential assays are performed.

Near- and mid-infrared diffuse reflectance spectroscopy for measuring soil metal content.

Rapid and nondestructive methods such as diffuse reflectance infrared spectroscopy provide potentially useful alternatives to time-consuming chemical methods of soil metal analysis. To assess the utility of near-infrared reflectance spectroscopy (NIRS) and diffuse mid-infrared reflectance spectroscopy (DRIFTS) for soil metal determination, 70 soil samples from the metal mining region of Tarnowskie Gory (Upper Silesia, Poland) were analyzed by both chemical and spectroscopic methods. Soils represented a wide range of pH (4.0-8.0), total carbon (5.1-73.2 g kg(-1)), and textural classes (from sand to silty clay loam). Soils had various contents of metals (14-4500 mg kg(-1) for Zn, 18-6530 mg kg(-1) for Pb, and 0.17-34 mg kg(-1) for Cd), ranging from natural background levels to high contents indicative of industrial contamination in the region. Soil samples were scanned at the wavelengths from 400 to 2498 nm (near-infrared region) and from 2500 to 25000 nm (mid-infrared region). Calibrations were developed using the one-out validation procedure under partial least squares (PLS) regression. Mid-infrared spectroscopy markedly outperformed NIRS. Iron, Cd, Cu, Ni, and Zn were successfully predicted using DRIFTS. The coefficients of determination (R(2)) between actual and predicted contents were 0.97, 0.94, 0.80, 0.99, and 0.96 for those metals, respectively. Only Pb content was predicted poorly. Calibrations using NIRS were less accurate. Root mean squared deviation (RMSD) values were from 1.27 (Pb) to 3.3 (Ni) times higher for NIRS than for DRIFTS. Results indicate that DRIFTS may be useful for accurate predictions of metals if samples originate from one region.

Evaluation of three field-based methods for quantifying soil carbon.

Three advanced technologies to measure soil carbon (C) density (g C m(-2)) are deployed in the field and the results compared against those obtained by the dry combustion (DC) method. The advanced methods are: a) Laser Induced Breakdown Spectroscopy (LIBS), b) Diffuse Reflectance Fourier Transform Infrared Spectroscopy (DRIFTS), and c) Inelastic Neutron Scattering (INS). The measurements and soil samples were acquired at Beltsville, MD, USA and at Centro International para el Mejoramiento del Maíz y el Trigo (CIMMYT) at El Batán, Mexico. At Beltsville, soil samples were extracted at three depth intervals (0-5, 5-15, and 15-30 cm) and processed for analysis in the field with the LIBS and DRIFTS instruments. The INS instrument determined soil C density to a depth of 30 cm via scanning and stationary measurements. Subsequently, soil core samples were analyzed in the laboratory for soil bulk density (kg m(-3)), C concentration (g kg(-1)) by DC, and results reported as soil C density (kg m(-2)). Results from each technique were derived independently and contributed to a blind test against results from the reference (DC) method. A similar procedure was employed at CIMMYT in Mexico employing but only with the LIBS and DRIFTS instruments. Following conversion to common units, we found that the LIBS, DRIFTS, and INS results can be compared directly with those obtained by the DC method. The first two methods and the standard DC require soil sampling and need soil bulk density information to convert soil C concentrations to soil C densities while the INS method does not require soil sampling. We conclude that, in comparison with the DC method, the three instruments (a) showed acceptable performances although further work is needed to improve calibration techniques and (b) demonstrated their portability and their capacity to perform under field conditions.

Mid-infrared spectroscopy of biochars and spectral similarities to coal and kerogens: what are the implications?

Biochar is the solid residue produced by the pyrolysis of any bio-organic material under low, or no, oxygen conditions and has generated considerable interest as a means to sequester carbon in, and improve the quality of, soils. However, the exact properties of biochar depend on its composition, which in turn depends on the composition of the starting material and the temperature and conditions under which the biochar is produced. Mid-infrared spectroscopy offers an excellent and rapid method for characterizing both the starting materials and the resulting biochar. Results using diffuse reflection infrared Fourier transform spectroscopy (DRIFTS) have shown that spectral changes can be easily correlated with the production temperature and that DRIFTS offers a rapid method for biochar characterization. It was demonstrated that as the temperature increases biochars become increasingly more aromatic and carbonaceous in nature. We also showed that biochars are spectrally very similar to kerogens and coals; therefore, the methods and knowledge developed from decades of studies on these materials should greatly improve our understanding of biochar composition and effects in soil. This work indicates that rapid characterization using DRIFTS can be used to predict the nature of biochar and to determine the production conditions needed to produce a so-called "Designer Biochar" which will have properties of benefit to soil quality as well as sequestering carbon.

Use of mid- and near-infrared spectroscopy to track degradation of bio-based eating utensils during composting.

Near-infrared spectroscopy (NIRS) and mid-infrared spectroscopy (MIRS) have been used for quantitative and/or qualitative analysis of a wide range of materials. The objective of this study was to investigate the potential of MIRS and NIRS for following the degradation of bio-based food utensils during composting. Polylactide (PLA)-based forks lost 34% of their initial mass and were reduced to small friable fragments after 7 weeks of composting. NIRS and MIRS spectra of forks that were incubated for 7 weeks were nearly identical to spectra of untreated forks. NIRS and MIRS were more useful in following the degradation of a starch/polypropylene (PP) polymer. Spectral results demonstrated that the starch component degraded during composting and that the PP component was recalcitrant. These results confirm that MIRS and NIRS are useful in determining the composition of biobased materials. However, the spectra did not provide useful information about the extent of PLA polymer degradation.

A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression.

In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly smoothing operations or derivatives. While such operations are often useful in reducing the number of latent variables of the actual decomposition and lowering residual error, they also run the risk of misleading the practitioner into accepting calibration equations that are poorly adapted to samples outside of the calibration. The current study developed a graphical method to examine this effect on partial least squares (PLS) regression calibrations of near-infrared (NIR) reflection spectra of ground wheat meal with two analytes, protein content and sodium dodecyl sulfate sedimentation (SDS) volume (an indicator of the quantity of the gluten proteins that contribute to strong doughs). These two properties were chosen because of their differing abilities to be modeled by NIR spectroscopy: excellent for protein content, fair for SDS sedimentation volume. To further demonstrate the potential pitfalls of preprocessing, an artificial component, a randomly generated value, was included in PLS regression trials. Savitzky-Golay (digital filter) smoothing, first-derivative, and second-derivative preprocess functions (5 to 25 centrally symmetric convolution points, derived from quadratic polynomials) were applied to PLS calibrations of 1 to 15 factors. The results demonstrated the danger of an over reliance on preprocessing when (1) the number of samples used in a multivariate calibration is low (<50), (2) the spectral response of the analyte is weak, and (3) the goodness of the calibration is based on the coefficient of determination (R(2)) rather than a term based on residual error. The graphical method has application to the evaluation of other preprocess functions and various types of spectroscopy data.

Mid-infrared and near-infrared calibrations for nutritional parameters of Triticale (Triticosecale) and pea (Pisum sativum).

The objective of this study was to develop Fourier transformed mid-infrared (MidIR) and near-infrared (NIR) calibrations for acid detergent fiber (ADF), neutral detergent fiber (NDF), and total nitrogen in triticale, peas, and triticale/pea mixtures. Heterogeneous calibration-validation combinations were also tested for calibration quality. The forage samples were collected from forage plots grown following millet or wheat. Other factors included population density, forage mixtures, and nitrogen fertilizer rate. Total N always achieved a better validation R(2) than ADF and NDF, regardless of the sample set or spectral range. The ADF and NDF could not be predicted well with heterogeneous calibration/validation sets, with the exception of ADF predicted by the pea/triticale mixture in the MidIR. Using whole sample sets resulted in better predictive calibrations for the fiber analytes for both the MidIR and the NIR. This study shows that MidIR compares well with NIR for the development of ADF and total N calibrations in forages. The NIR and MidIR are both useful as quick methods for measuring total N, and they show promise for measuring ADF and total N in forage samples, but performance with NDF was less satisfactory.

Pyrolysis of foundry sand resins: a determination of organic products by mass spectrometry.

Pyrolysis-gas chromatography-mass spectrometry (MS) was used to identify the major organic products produced by pyrolysis of three foundry sand resins: (i) Novolac and (ii) phenolic urethane (PU) (both phenol-formaldehyde based resins) and (iii) furan (furfuryl alcohol based resin). These resins are used in the metal casting industry as a "sand binder" for making cores (used to produce cavities in molds) and molds for nonferrous castings. During the casting process, the cores and molds are subjected to intense heat from the molten metal. As a result, the organic resins undergo thermal decomposition and produce a number of complex organic compounds. In this study, the organics were tentatively identified by MS after pyrolysis of the resins at 750 degrees C. The major thermal decomposition products from the Novolac, PU, and furan resins were derivatives of phenol, benzene, and furan, respectively. Compounds identified that are of potential environmental concern were benzene, toluene, phenol, o- and p-xylene, o- and m-cresol, and polycyclic aromatic hydrocarbons. Pyrolysis of the Novolac resin resulted in the generation of the most compounds of environmental concern. Because there is interest in beneficially using foundry molding sands in manufactured soils and other agricultural products, it is necessary that organic thermal decomposition products be identified to ensure environmental protection.