Sensing Taste Attributes of Plums Using Near Infrared (NIR) Reflectance Spectroscopy

2002 ◽  
pp. 429-439
Author(s):  
Nawaf Abu-Khalaf ◽  
Bent S. Bennedsen
Keyword(s):  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Nir Reflectance Spectroscopy

Near Infrared Assessment of Vegetable Quality

1998 ◽  
Vol 6 (A) ◽  
pp. A107-A110 ◽  
Author(s):  
Christopher N.G. Scotter
Keyword(s):  
Product Quality ◽  
Industrial Application ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Quality Factors ◽  
Sensory Assessment ◽  
Research Consortium ◽  
The Uk ◽  
Nir Reflectance Spectroscopy ◽  
Vegetable Quality

NIR reflectance spectroscopy has been applied to the assessment of product quality factors for vining peas and sweetcorn. A CCFRA Industrial Research Club and an EU research consortium led by CCFRA, have been conducting the work since 1994. Sample sets of peas have been collected which are broadly representative of commercial material in the UK, Hungary, and Bulgaria All sweetcorn samples were from Hungary. The calibration results, at this stage, for alcohol insoluble solids (AIS) in peas and sweetcorn, and Tenderometer measurement and sensory assessment for both vegetables indicate that the work will find industrial application.

Authentication of Whole and Ground Coffee Beans by near Infrared Reflectance Spectroscopy

1994 ◽  
Vol 2 (2) ◽  
pp. 85-92 ◽  
Author(s):  
Gerard Downey ◽  
Jerôme Boussion ◽  
Dominique Beauchêne
Keyword(s):  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Correct Identification ◽  
Correct Classification Rate ◽  
Near Infrared Reflectance ◽  
Classification Rate ◽  
Identification Rate ◽  
Coffee Beans ◽  
Correct Identification Rate ◽  
Nir Reflectance Spectroscopy

The potential of NIR reflectance spectroscopy for discriminating between pure Arabica and pure Robusta coffees and blends of these two was investigated. Studies were performed on whole and ground beans using a factorial discriminant procedure. For whole beans, in the absence of blended samples, a correct classification rate of 96.2% was achieved. Inclusion of blended samples reduced this figure to between 82.9 and 87.6%. In the case of ground samples, including blends, a correct identification rate of 83.02% was achieved. The molecular basis for discrimination is discussed.

Studies to Measure Cotton Fibre Length, Strength, Micronaire and Colour by Vis/NIR Reflectance Spectroscopy. Part I: Descriptive Statistics of Fibre Properties and Reflectance Spectra

1993 ◽  
Vol 1 (3) ◽  
pp. 153-173 ◽  
Author(s):  
Joseph G. Montalvo ◽  
Sherman E. Faught ◽  
Harmon H. Ramey ◽  
Steven E. Buco
Keyword(s):  
Standard Error ◽  
Near Infrared ◽  
A Priori ◽  
Fibre Length ◽  
High Volume ◽  
Reflectance Spectroscopy ◽  
Reflectance Spectra ◽  
Fibre Property ◽  
Property Data ◽  
Nir Reflectance Spectroscopy

Fibre property data representing the 1989 and 1990 crop years and its reflectance spectra are analysed using standard error, regression and correlation analysis. The six properties of interest are upper-half mean length, uniformity index, strength and micronaire measured on two high volume instrument systems placed side-by-side, and colour (Rd and +b) measured by the traditional lab system. Visible (vis) and near infrared (NIR) reflectance spectra are observed on a scanning spectrophotometer, and span the 400–2500 nm range. Three findings highlight the research. One, a diagnostic test is presented to decide, a priori of reflectance spectroscopy, the degree to which the mean property values have reduced random error. Two, the standard error of replicate spectra provides a way to probe the fibre mass in the diffuse reflectance optical path. The spectral error is strongly influenced by both how the cotton is packed into the spectrophotometric cell and the non-homogeneity of the sample. And three, correlations between the spectra confirm that some visible and NIR wavelength regions contain mutually exclusive information about the properties of this natural staple.

Near Infrared Spectroscopy of Fuel Contaminated Sand and Soil. I. Preliminary Results and Calibration Study

1998 ◽  
Vol 6 (1) ◽  
pp. 189-197 ◽  
Author(s):  
Heinz W. Zwanziger ◽  
Heidrun Förster
Keyword(s):  
Near Infrared ◽  
Direct Detection ◽  
Scatter Correction ◽  
Reflectance Spectroscopy ◽  
Calibration Error ◽  
Particle Size Fractions ◽  
Cultivated Soil ◽  
Synthetic Hydrocarbon ◽  
Calibration Models ◽  
Nir Reflectance Spectroscopy

Regional areas may be contaminated by the past activities of the chemical and oil industries and of the military. Therefore, the present study was undertaken to test the possibilities of near infrared (NIR) reflectance spectroscopy for direct detection and determination of oil and fuel contaminations. If reliable results are obtained NIR reflectance spectroscopy could be a valuable part of land remediation processes. Preliminary investigations showed that it is possible to distinguish samples of stone chippings, sand, cultivated soil, humus and potting soil by multivariate data analysis. After spiking with gasoline, diesel, motor oil and synthetic hydrocarbon mixtures (BTEX) sand rather than cultivated soil shows obvious spectral absorptions due to contaminations higher than 1% (w/w). The influence of particle size fractions has been investigated in detail using dry sand sieved to < 500 μm (fine), 500–800 μm (medium) and >800 μm (coarse). Contaminations in fine and medium fractions often can be modelled with only one intensity at sufficiently low calibration error, SEC. With coarse fractions SEC is three times higher. Models based on derivative spectra have no significant advantage. In general, mean centring results in more pronounced error minima than multiplicative scatter correction (MSC). Partial least squares (PLS) models can be fitted to obtain any wanted SEC even by cross-validation. For comparable SEC, PLS models in general do not need more factors if samples become more inhomogeneous. Data pre-processing techniques such as Kubelka–Munk transformation, Saunderson correction, MSC and combinations thereof have been tested. Adequate sample variation of the diffuse reflectance fraction of detected light according to the Saunderson model could improve the performance of calibration models. The best values for standard error of prediction, SEP, are obtained if calibration models are derived from sets of spectra of sieved samples and used for contamination prediction of natural samples, and not vice versa. Spectra of contaminated soil and humus need cleverer spectral selection and pre-processing for better performance of calibration models.

Use of near Infrared Reflectance Spectroscopy to Analyse Bovine Faecal Samples

2002 ◽  
Vol 10 (4) ◽  
pp. 309-314 ◽  
Author(s):  
D. Cozzolino ◽  
A. La Manna ◽  
D. Vaz Martins
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Dry Weight ◽  
Reflectance Spectroscopy ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Faecal Samples ◽  
Acid Detergent Fibre ◽  
Nir Reflectance Spectroscopy ◽  
Calibration Equations

Near infrared (NIR) reflectance spectroscopy was used to predict nitrogen (N), acid detergent fibre (ADF), neutral detergent fibre (NDF) and chromium (Cr) in beef faecal samples. One hundred and twenty faecal samples were scanned in a NIRSystems 6500 monochromator instrument over the wavelength range of 400–2500 nm in reflectance. Calibration equations were developed using modified partial least squares (MPLS) with internal cross validation to avoid overfitting. The coefficient of determination in calibration ( R2cal) and the standard error in cross validation ( SECV) were 0.80 (0.74) for N, 0.92 (12.04) for ADF, 0.86 (13.5) for NDF and 0.56 (0.07) for Cr in g kg−1 dry weight, respectively. Results for validation were 0.78 ( SEP: 0.1) for N, 0.74 ( SEP: 7.5) for ADF, 0.85 ( SEP: 8.5) for NDF and 0.10 (0.09) for Cr in g kg−1 dry weight, respectively.

Simultaneous Determination of Fecal Fat, Nitrogen and Water by Fourier Transform near Infrared Reflectance Spectroscopy through a Polyethylene/Polyaminde Film

1998 ◽  
Vol 6 (A) ◽  
pp. A265-A272 ◽  
Author(s):  
Volker Neumeister ◽  
Werner Jaross ◽  
Jobst Henker ◽  
Georg Kaltenborn
Keyword(s):  
Near Infrared ◽  
Fiber Optic ◽  
Reflectance Spectroscopy ◽  
Integrating Sphere ◽  
Standard Methods ◽  
Nitrogen Determination ◽  
Fecal Fat ◽  
Stool Samples ◽  
Nir Reflectance Spectroscopy

The determination of fecal fat, nitrogen and water is important to get evidence for malassimilation and for estimating the efficacy of treatment with pancreatic enzymes. Standard methods for the determination of these parameters (van-de-Kamer method for fat determination, Kjeldahl method for nitrogen determination) are expensive, time-consuming and cumbersome for laboratory assistants. Near infrared (NIR) reflectance spectroscopy was evaluated as a potentially attractive alternative method, especially because the simultaneous measurement of fat, nitrogen and water content is possible. After homogenisation parts of stool samples were packed and thermowelded in a bag of polyethylene/polyamide (PE/PA) film to optimize the handling in the laboratory. Two optical systems were tested: 1. Fiber optic, In-Ga-As-detector, weavelength range 1000–2500 nm, area of measurement diameter 4–mm; 2. Integrating sphere, Ge-detector, wavelength range 1000–1800 nm, area of measurement diameter 10 mm. Forty stool samples were used for calibration, another 20 for validation from both healthy children and patients with cystic fibrosis in an age range from 5 to 18 years. The concentrations of fecal compounds were calculated using the chemometric Partial Least Square (PLS) method with the NIR reflectance spectroscopy measurement data. The calibration were carried out based on results of chemical analysis with standard methods. The regression equations of the external NIR reflectance spectroscopy validations were as follows: 1. for the fiber optic system: fat determination y = 0.9737x + 5.7261r = 0.989, nitrogen determination y = 1.0092x+0.0731 r = 0.933, water determination y = 0.9699x+2.0703 r = 0.993; 2. for the integrating sphere system: fat determination y = 1.0308x–1.6797 r = 0.998, nitrogen determination y = 0.9529x+0.5302 r = 0.959, water y = 1.0301x–1.8193 r = 0.993. The NIR reflectance spectroscopy method is a precise and alternative method for the determination of fecal fat, nitrogen and water. Moreover, handling is simple, time of analysis is short (4 minutes on average) and all calibrated constituents can be analyzed simultaneously. Therefore, we conclude that NIR reflectance spectroscopy is a reliable and useful method for analysis of fecal components in laboratory medicine.

The use of visible (VIS) and near infrared (NIR) reflectance spectroscopy to predict fibre diameter in both clean and greasy wool samples

2005 ◽  
Vol 80 (3) ◽  
pp. 333-337 ◽  
Author(s):  
D. Cozzolino ◽  
F. Montossi ◽  
R. San Julian
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Model Development ◽  
Fibre Diameter ◽  
Reflectance Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Calibration Models ◽  
Nir Reflectance Spectroscopy

AbstractAbstract Visible (VIS) and near infrared (NIR) reflectance spectroscopy combined with multivariate data analysis were explored to predict fibre diameter in both clean and greasy Merino wool samples. Fifty clean and 400 greasy wool samples were analysed. Samples were scanned in a large cuvette using a NIRSystems 6500 monochromator instrument by reflectance in the VIS and NIR regions (400 to 2500 nm). Partial least square (PLS) regression was used to develop a number of calibration models between the spectral and reference data. Different mathematical treatments were used during model development. Cross validation was used to assess the performance and avoid overfitting of the models. The NIR calibration models gave a coefficient of determination in calibration (R2) > 0·90 for clean wool samples and a R2 < 0·50 for greasy wool samples. The values for the residual predictive value, RPD (ratio of standard deviation (s. d.) to the root mean square of the standard error of cross validation (RMSECV)) were 3 for clean and 0·6 for greasy wool samples, respectively. The results indicated that fibre diameter in greasy wool samples was poorly predicted with NIR, while clean wool showed good relationships.More research is required to improve the calibration on greasy wool samples if the technology is to be used for rapid analysis to assist in the selection of animals in breeding programmes.

Predicting Elements in White Pine and Red Oak Foliage with Visible-Near Infrared Reflectance Spectroscopy

1997 ◽  
Vol 5 (2) ◽  
pp. 77-82 ◽  
Author(s):  
R.A. Hallett ◽  
J.W. Hornbeck ◽  
M.E. Martin
Keyword(s):  
Forest Canopy ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Red Oak ◽  
Acid Digestion ◽  
White Pine ◽  
Near Infrared Reflectance ◽  
Nir Reflectance Spectroscopy ◽  
Calibration Equations ◽  
Mn Concentrations

Near infrared (NIR) reflectance spectroscopy was evaluated for its effectiveness at predicting Al, Ca, Fe, K, Mg and Mn concentrations in white pine ( Pinus strobus L.) and red oak ( Quercus rubra L.) foliage. A NIR spectrophotometer was used to scan 470 dried, ground foliage samples. These samples were used to develop calibration equations using a modified partial least squares (MPLS) regression technique. For the calibration equations, concentrations of Al, Ca, Fe, K, Mg and Mn as determined by acid digestion and laboratory analysis were regressed against second-difference absorbance values measured from 400 to 2498 nm. The regression models developed by NIR reflectance spectroscopy were unable to predict Fe. Predictions were satisfactory for Al, Ca, K, Mn and Mg. It still is uncertain which mineral/organic associations are being detected by NIR reflectance spectroscopy. Future applications may include prediction of element concentrations in the forest canopy via remote sensing.

The Potential of near Infrared Reflectance Spectroscopy as a Tool for the Chemical Characterisation of Agricultural Soils

2001 ◽  
Vol 9 (2) ◽  
pp. 123-131 ◽  
Author(s):  
M. Confalonieri ◽  
F. Fornasier ◽  
A. Ursino ◽  
F. Boccardi ◽  
B. Pintus ◽  
...  
Keyword(s):  
Total Nitrogen ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Soil Samples ◽  
Available Phosphorus ◽  
Exchangeable Potassium ◽  
Near Infrared Reflectance ◽  
Nir Reflectance Spectroscopy ◽  
Soil Constituents

The feasibility of near infrared (NIR) reflectance spectroscopy in determining various soil constituents such as total organic carbon, total nitrogen, exchangeable potassium and available phosphorus has been investigated, to monitor their concentration during a long-term agronomic trial. Soil samples previously analysed by conventional chemical methods were scanned using a NIRSystems 5000 monochromator and spectra were treated using several algorithms. The first derivative of each NIR spectrum was used for all statistical analyses. Step-up, stepwise and modified partial least squares (MPLS) regression methods were applied to develop reliable calibration models between the NIR spectral data and the results of wet analyses. MPLS almost always gave the most successful calibrations. The results demonstrated that NIR reflectance spectroscopy can be used to determine accurately two important soil constituents, namely total nitrogen and carbon content. This technique could be employed as a routine testing method in estimating, rapidly and non-destructively, these constituents in soil samples, demonstrating soil variations within a long-term field experiment. For other determinations, such as exchangeable potassium and available phosphorus content, our results were less successful but may be useful for separation of samples into groups.

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