Assessment of quality defects in macadamia kernels using NIR spectroscopy

Spectral data were collected of intact and ground kernels using 3 instruments (using Si-PbS, Si, and InGaAs detectors), operating over different areas of the spectrum (between 400 and 2500 nm) and employing transmittance, interactance, and reflectance sample presentation strategies. Kernels were assessed on the basis of oil and water content, and with respect to the defect categories of insect damage, rancidity, discoloration, mould growth, germination, and decomposition. Predictive model performance statistics for oil content models were acceptable on all instruments (R2 > 0.98; RMSECV < 2.5%, which is similar to reference analysis error), although that for the instrument employing reflectance optics was inferior to models developed for the instruments employing transmission optics. The spectral positions for calibration coefficients were consistent with absorbance due to the third overtones of CH2 stretching. Calibration models for moisture content in ground samples were acceptable on all instruments (R2 > 0.97; RMSECV < 0.2%), whereas calibration models for intact kernels were relatively poor. Calibration coefficients were more highly weighted around 1360, 740 and 840 nm, consistent with absorbance due to overtones of O-H stretching and combination. Intact kernels with brown centres or rancidity could be discriminated from each other and from sound kernels using principal component analysis. Part kernels affected by insect damage, discoloration, mould growth, germination, and decomposition could be discriminated from sound kernels. However, discrimination among these defect categories was not distinct and could not be validated on an independent set. It is concluded that there is good potential for a low cost Si photodiode array instrument to be employed to identify some quality defects of intact macadamia kernels and to quantify oil and moisture content of kernels in the process laboratory and for oil content in-line. Further work is required to examine the robustness of predictive models across different populations, including growing districts, cultivars and times of harvest.

Near infrared reflectance as a rapid and inexpensive surrogate measure for fatty acid composition and oil content in peanuts (Arachis hypogaea L.)

The fatty acid composition of ground nuts (Arachis hypogaea L.) commonly known as peanuts, is an important consideration when a new variety is being released. The composition impacts on nutrition and, importantly, self-life of peanut products. To select for suitable breeding material, it was necessary to develop a rapid, non-derstructive and cost-efficient method. Near infrared spectroscopy was chosen as that methodology. Calibrations were developed for two major fatty-acid components, oleic and linoleic acids and two minor components, palmitic and stearic acids, as well as total oil content. Partial least squares models indicated a high level of precision with a squared multiple correlation coefficient of greater than 0.90 for each constitutent. Standard errors for prediction for oleic, linoleic, palmitic, stearic acids and total oil content were 6.4%, 4.5%, 0.8%, 0.9% and 1.3% respectively. The results demonstrated that reasonable calibrations could be developed to predict oil composition and content of peanuts for a breeding programme.

Review: Near infrared spectroscopy of faeces to evaluate the nutrition and physiology of herbivores

Near infrared (NIR) spectroscopy, usually in reflectance mode, has been applied to the analysis of faeces to measure the concentrations of constituents such as total N, fibre, tannins and delta C-13. In addition, an unusual and exciting application of faecal NIR [F.NIR] analyses is to directly predict attributes of the diet of herbivores such as crude protein and fibre contents, proportions of plant species and morphological components, diet digestibility and voluntary DM intake. This is an unusual application of NIR spectroscopy insofar as the spectral measurements are made, not on the material of interest [i.e. the diet), but on a derived material (i.e. faeces). Predictions of diet attributes from faecal spectra clearly depend on there being sufficient NIR spectral information in the diet residues present in faeces to describe the diet, although endogenous components of faeces such as undigested debris of micro-organisms from the rumen and Large intestine and secretions into the gastrointestinal tract wilt also contribute spectral information. Spectra of forage and of faeces derived from the forage are generally similar and the observed differences are principally in the spectral regions associated with constituents of forages known to be of low, or of high, digestibility. Some diet components (for example, ureal which are likely to be entirely digested apparently cannot be predicted from faecal NIR spectra because they cannot contribute to faecal spectra except through modifying the microbial and endogenous components. The errors and robustness of F.NIR calibrations to predict the crude protein concentration and digestibility of the diet of herbivores are generally comparable with those to directly predict the same attributes in forage from NIR spectra of the forage. Some attributes of the animal, such as species, gender, pregnancy status and parasite burden have been successfully discriminated into classes based on their faecal NIR spectra. Such discrimination was likely associated with differences in the diet selected and/or differences in the metabolites excreted in the faeces. NIR spectroscopy of faeces has usually involved scanning dried and ground samples in monochromators in the 400-2500nm or 1100-2500nm ranges. Results satisfactory for the purpose have also been reported for dried and ground faeces scanned using a diode array instrument in the 800-1700nm range and for wet faeces and slurries of excreta scanned with monochromators. Chemometric analysis of faecal spectra has generally used the approaches established for forage analysis. The capacity to predict many attributes of the diet, and some aspects of animal physiology, from NIR spectra of faeces is particularly useful to study the quality and quantity of the diet selected by both domestic and feral grazing herbivores and to enhance production and management of both herbivores and their grazing environment.

Non-destructive prediction of 'Hass' avocado dry matter via FT-NIR spectroscopy.

BACKGROUND: The inability to consistently guarantee internal quality of horticulture produce is of major importance to the primary producer, marketers and ultimately the consumer. Currently, commercial avocado maturity estimation is based on the destructive assessment of percentage dry matter (%DM), and sometimes percentage oil, both of which are highly correlated with maturity. In this study the utility of Fourier transform (FT) near-infrared spectroscopy (NIRS) was investigated for the first time as a non-invasive technique for estimating %DM of whole intact 'Hass' avocado fruit. Partial least squares regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. RESULTS: It was found that combining three harvests (early, mid and late) from a single farm in the major production district of central Queensland yielded a predictive model for %DM with a coefficient of determination for the validation set of 0.76 and a root mean square error of prediction of 1.53% for DM in the range 19.4-34.2%. CONCLUSION: The results of the study indicate the potential of FT-NIRS in diffuse reflectance mode to non-invasively predict %DM of whole 'Hass' avocado fruit. When the FT-NIRS system was assessed on whole avocados, the results compared favourably against data from other NIRS systems identified in the literature that have been used in research applications on avocados.

A novel method for the age estimation of Saddletail snapper (Lutjanus malabaricus) using Fourier Transform-near infrared (FT-NIR) spectroscopy

Near infrared (NIR) spectroscopy was investigated as a potential rapid method of estimating fish age from whole otoliths of Saddletail snapper (Lutjanus malabaricus). Whole otoliths from 209 Saddletail snapper were extracted and the NIR spectral characteristics were acquired over a spectral range of 800–2780 nm. Partial least-squares models (PLS) were developed from the diffuse reflectance spectra and reference-validated age estimates (based on traditional sectioned otolith increments) to predict age for independent otolith samples. Predictive models developed for a specific season and geographical location performed poorly against a different season and geographical location. However, overall PLS regression statistics for predicting a combined population incorporating both geographic location and season variables were: coefficient of determination (R2) = 0.94, root mean square error of prediction (RMSEP) = 1.54 for age estimation, indicating that Saddletail age could be predicted within 1.5 increment counts. This level of accuracy suggests the method warrants further development for Saddletail snapper and may have potential for other fish species. A rapid method of fish age estimation could have the potential to reduce greatly both costs of time and materials in the assessment and management of commercial fisheries.

Study on the thermal stability of InN by in-situ laser reflectance system

The thermal stability of InN in the growth environment in metalorganic chemical vapor deposition was systematically investigated in situ by laser reflectance system and ex situ by morphology characterization, X-ray diffraction and X-ray photoelectron spectroscopy. It was found that InN can withstand isothermal annealing at temperature as high as 600 degrees C in NH3 ambient. While in N-2 atmosphere, it will decompose quickly to form In-droplets at least at the temperature around 500 degrees C, and the activation energy of InN decomposition was estimated to be 2.1 +/- 0.1 eV. Thermal stability of InN when annealing in NH3 ambient during temperature altering would be very sensitive to ramping rate and NH3 flow rate, and InN would sustain annealing process at small ramping rate and sufficient supply of reactive nitrogen radicals. Whereas In-droplets formation was found to be the most frequently encountered phenomenon concerning InN decomposition, annealing window for conditions free of In-droplets was worked out and possible reasons related are discussed. In addition, InN will decompose in a uniform way in the annealing window, and the decomposition rate was found to be in the range of 50 and 100 nm/h. Hall measurement shows that annealing treatment in such window will improve the electrical properties of InN. (c) 2005 Elsevier B.V. All rights reserved.

Detection of indium segregation effects in InGaAs/GaAs quantum wells using reflectance-difference spectrometry

The influence of the Indium segregation on the interface asymmetry in InGaAs/GaAs quantum wells have been studied by reflectance-difference spectroscopy (RDS). It is found that the anisotropy of the 2H1E (2HH --> 1E) transition is very sensitive to the degree of the interface asymmetry. Calculations taking into account indium segregation yield good agreement with the observed anisotropy structures. It demonstrates that the anisotropy intensity ratio of the 1L1E (1LH --> 1E) and 2H1E transitions measured by RDS can be used to characterize the interface asymmetry. (C) 2002 Elsevier Science B.V. All rights reserved.

Interference effects in differential reflectance spectra of the GaAs epilayers grown on Si substrate

We report the observation of oscillating features in differential reflectance spectra from the GaAs epilayer grown on Si substrate in the energy range both below and above the fundamental band gap. It is demonstrated that the oscillating features are due to the difference in the interference between two neighboring areas of the sample. The interference arises from two light beams reflected from different interfaces of the sample. The calculated spectra in the nonabsorption region are in good agreement with measured data. It is shown that the interference effect can be used as a sensitive method to characterize the inhomogeneity of the semiconductor heterostructures. (C) 1998 American Institute of Physics. [S0021-8979(98)08723-4].

A New Discrimination Method of Maize Seed Varieties Based on Near-Infrared Spectroscopy

A new discrimination method for the maize seed varieties based on the near-infrared spectroscopy was proposed. The reflectance spectra of maize seeds were obtained by a FT-NIR spectrometer (12 000-4 000 cm(-1)). The original spectra data were preprocessed by first derivative method. Then the principal component analysis (PCA) was used to compress the spectra data. The principal components with the cumulate reliabilities more than 80% were used to build the discrimination models. The model was established by Psi-3 neuron based on biomimetic pattern recognition (BPR). Especially, the parameter of the covering index was proposed to assist to discriminating the variety of a seed sample. The authors tested the discrimination capability of the model through four groups of experiments. There were 10, 18, 26 and 34 varieties training the discrimination models in these experiments, respectively. Additionally, another seven maize varieties and nine wheat varieties were used to test the capability of the models to reject the varieties not participating in training the models. Each group of the experiment was repeated three times by selecting different training samples at random. The correct classification rates of the models in the four-group experiments were above 91. 8%. The correct rejection rates for the varieties not participating in training the models all attained above 95%. Furthermore, the performance of the discrimination models did not change obviously when using the different training samples. The results showed that this discrimination method can not only effectively recognize the maize seed varieties, but also reject the varieties not participating in training the model. It may be practical in the discrimination of maize seed varieties.

Detection of indium segregation effects in InGaAs/GaAs quantum wells using reflectance-difference spectrometry

The influence of the Indium segregation on the interface asymmetry in InGaAs/GaAs quantum wells have been studied by reflectance-difference spectroscopy (RDS). It is found that the anisotropy of the 2H1E (2HH --> 1E) transition is very sensitive to the degree of the interface asymmetry. Calculations taking into account indium segregation yield good agreement with the observed anisotropy structures. It demonstrates that the anisotropy intensity ratio of the 1L1E (1LH --> 1E) and 2H1E transitions measured by RDS can be used to characterize the interface asymmetry. (C) 2002 Elsevier Science B.V. All rights reserved.

Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning

Ellis, D. I., Broadhurst, D., Kell, D. B., Rowland, J. J., Goodacre, R. (2002). Rapid and quantitative detection of the microbial spoilage of meat by Fourier Transform Infrared Spectroscopy and machine learning. ? Applied and Environmental Microbiology, 68, (6), 2822-2828 Sponsorship: BBSRC

Portable, Fiber-Based, Diffuse Reflection Spectroscopy (DRS) Systems for Estimating Tissue Optical Properties.

Steady-state diffuse reflection spectroscopy is a well-studied optical technique that can provide a noninvasive and quantitative method for characterizing the absorption and scattering properties of biological tissues. Here, we compare three fiber-based diffuse reflection spectroscopy systems that were assembled to create a light-weight, portable, and robust optical spectrometer that could be easily translated for repeated and reliable use in mobile settings. The three systems were built using a broadband light source and a compact, commercially available spectrograph. We tested two different light sources and two spectrographs (manufactured by two different vendors). The assembled systems were characterized by their signal-to-noise ratios, the source-intensity drifts, and detector linearity. We quantified the performance of these instruments in extracting optical properties from diffuse reflectance spectra in tissue-mimicking liquid phantoms with well-controlled optical absorption and scattering coefficients. We show that all assembled systems were able to extract the optical absorption and scattering properties with errors less than 10%, while providing greater than ten-fold decrease in footprint and cost (relative to a previously well-characterized and widely used commercial system). Finally, we demonstrate the use of these small systems to measure optical biomarkers in vivo in a small-animal model cancer therapy study. We show that optical measurements from the simple portable system provide estimates of tumor oxygen saturation similar to those detected using the commercial system in murine tumor models of head and neck cancer.

Simultaneous monitoring of drug and solvent diffusion across a model membrane using ATR-FTIR spectroscopy

Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been used to simultaneously follow the diffusion of model drugs and solvent across polydimethylsiloxane (silicone) membrane. Three model drugs, cyanophenol (CNP), methyl nicotinate (MN) and butyl paraben (BP) were selected to cover a range of lipophilicities. Isostearyl isostearate (ISIS) was chosen as the solvent because its large molecular weight should facilitate observation of whether the drug molecules are able to diffuse through the membrane independently of the solvent. The diffusion of the three drugs and the solvent was successfully described by a Fickian model. The effects of parameters such as the absorption wavelength used to follow diffusion on the calculated diffusion coefficient were investigated. Absorption wavelength which affects the depth of penetration of the infrared radiation into the membrane did not significantly affect the calculated diffusion coefficient over the wavelength range tested. Each of the model drugs was observed to diffuse independently of the solvent across the membrane. The diffusion of a CNP-ISIS hydrogen bonded complex across the membrane was also monitored. The relative diffusion rates of the solute and solvent across the membrane can largely be accounted for by the molecular size of the permeant.

ATR-FTIR spectroscopy and spectroscopic imaging of solvent and permeant diffusion across model membranes

The uptake and diffusion of solvents across polymer membranes is important in controlled drug delivery, effects on drug uptake into, for example, infusion bags and containers, as well as transport across protective clothing. Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR) spectroscopy has been used to monitor the effects of different solvents on the diffusion of a model compound, 4-cyanophenol (CNP) across silicone membrane and on the equilibrium concentration of CNP obtained in the membrane following diffusion. ATR-FTIR spectroscopic imaging of membrane diffusion was used to gain an understanding of when the boundary conditions applied to Fick's second law, used to model the diffusion of permeants across the silicone membrane do not hold. The imaging experiments indicated that when the solvent was not taken up appreciably into the membrane, the presence of discrete solvent pools between the ATR crystal and the silicone membrane can affect the diffusion profile of the permeant. This effect is more significant if the permeant has a high solubility in the solvent. In contrast, solvents that are taken up into the membrane to a greater extent, or those where the solubility of the permeant in the vehicle is relatively low, were found to show a good fit to the diffusion model. As such these systems allow the ATR-FTIR spectroscopic approach to give mechanistic insight into how the particular solvents enhance permeation. The solubility of CNP in the solvent and the uptake of the solvent into the membrane were found to be important influences on the equilibrium concentration of the permeant obtained in the membrane following diffusion. In general, solvents which were taken up to a significant extent into the membrane and which caused the membrane to swell increased the diffusion coefficient of the permeant in the membrane though other factors such as solvent viscosity may also be important.

Quantitative Analysis of Adsorbate Concentrations by Diffuse Reflectance FT-IR

Fully quantitative analyses of DRIFTS data are required when the surface concentrations and the specific rate constants of reaction (or desorption) of adsorbates are needed to validate microkinetic models. The relationship between the surface coverage of adsorbates and various functions derived from the signal collected by DRIFTS is discussed here. The Kubelka-Munk and pseudoabsorbance (noted here as absorbance, for the sake of brevity) transformations were considered, since those are the most commonly used functions when data collected by DRIFTS are reported. Theoretical calculations and experimental evidence based on the study of CO adsorption on Pt/SiO2 and formate species adsorbed on Pt/CeO2 showed that the absorbance (i.e., ) log 1/R������¢, with R������¢ ) relative reflectance) is the most appropriate, yet imperfect, function to give a linear representation of the adsorbate surface concentration in the examples treated here, for which the relative reflectance R������¢ is typically > 60%. When the adsorbates lead to a strong signal absorption (e.g., R������¢ < 60%), the Kubelka-Munk function is actually more appropriate. The absorbance allows a simple correction of baseline drifts, which often occur during time-resolved data collection over catalytic materials. Baseline corrections are markedly more complex in the case of the other mathematical transforms, including the function proposed by Matyshak and Krylov (Catal. Today 1995, 25, 1-87), which has been proposed as an appropriate representation of surface concentrations in DRIFTS spectroscopy.