Recent Advances in Near-Infrared Reflectance Spectroscopy

Martin, Kenneth L.

doi:10.1080/05704929208018109

Cited by 62 publications

(20 citation statements)

References 162 publications

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“…Initial results showed that, in most cases, the wavebands selected after the fifth step were highly correlated with wavebands selected at earlier steps. In addition, these wavebands were very likely modeling the error inherent in the data, rather than describing a connection between reflectance and nitrogen concentration, a common phenomenon when the number of cases is much smaller than the number of independent variables (Curran et al 1992;Martin 1992). Also, according to the initial results, the wavebands selected at the third through fifth step, showed a small reduction in the sum of deviation squares.…”

Section: Resultsmentioning

confidence: 91%

“…The first derivative is the difference between two successive reflectance measurements along the spectrum, divided by the wavelength distance between them (Hildebrand 1974) and the process removes the constant signal across the spectrum, and amplifies small changes in the reflectance of adjacent wavebands (Butler and Hopkins 1970;Demetriades-Shah et al 1990;Martin 1992;O'Haver 1982). Initial testing of the data showed that the smoothed reflectance values were less reliable at estimating foliar nitrogen concentration than the first derivative of reflectance (Kalaitzidis et al 2005).…”

Section: Spectral Data Collectionmentioning

confidence: 99%

See 1 more Smart Citation

Estimating Foliar Nitrogen Concentration of Heather (Calluna vulgaris) from Field and Laboratory Spectra

Kalaitzidis

Caporn

Cutler

2008

Water Air Soil Pollut

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Regional botanical surveys supported by field experiments suggest that atmospheric nitrogen deposition threatens the balance between species and causes loss of biodiversity within plant communities. Methods are required to monitor the nitrogen status of vegetation at a landscape scale and therefore the potential for ecological change. Remote sensing has the potential to monitor a number of plant biophysical and chemical variables, but its application to monitor the nitrogen status of native vegetation remains limited and untested. Using field spectroscopy, canopy reflectance measurements were taken from two heathland field sites and heather (Calluna vulgaris) plants grown in a greenhouse. The nitrogen concentration was determined through destructive sampling and chemical analysis. Stepwise multiple regression analysis was used to identify the wavebands most associated with nitrogen concentration and despite high variation in the selected wavebands between the three datasets, most of these wavebands were associated with nitrogen and protein absorption features within the spectral region 1,990-2,170 nm. Results highlight the potential of remote sensing as a bio-monitoring technique to estimate foliar nitrogen status in native plants.

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Section: Resultsmentioning

confidence: 91%

Section: Spectral Data Collectionmentioning

confidence: 99%

Estimating Foliar Nitrogen Concentration of Heather (Calluna vulgaris) from Field and Laboratory Spectra

Kalaitzidis

Caporn

Cutler

2008

Water Air Soil Pollut

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“…Detailed description of spectra preprocessing is provided in the literature [17,19,21,26,53]. The algorithms are frequently combined to improve the model (see table 1 for a partial list of the preprocessing methods tested in this study), and the quality of the fit can be evaluated through the statistics of the regression: correlation coefficient for the regression (R 2 ), the root mean square error of cross-validation (RMSECV), the root mean square error of prediction for independent sets (RMSEP) and number of required PLS factors to model the data.…”

Section: Development Of the Calibration Methodsmentioning

confidence: 99%

Non-destructive dating of fiber-based gelatin silver prints using near-infrared spectroscopy and multivariate analysis

et al. 2011

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An innovative approach to date fiber based gelatin silver prints using Near Infrared Spectroscopy and Multivariate Analysis (NIR/MVA) is presented. NIR spectra were acquired for 152 film stills printed in the US between 1914 and 1986 and Partial Least Square (PLS) analysis was used to correlate the spectra with the year the photographs were printed. Principal Component Analysis (PCA) and spectral interpretation helped clarify the underlying correlation between the print date and the composition and ageing of the photographic papers. The method was successfully validated with an independent set of 66 film stills printed in the US and a prediction error (RMSEP) of 6 years was achieved. The method was also tested on films stills printed in Germany and Russia, as well as amateur prints and photographs in the collection of the Museum of Modern Art (MoMA). The prediction error was significantly larger, with the exception of the amateur prints, due to differences in the composition and/or properties of the papers depending on their geographical origin and purpose as confirmed by Discriminant Analysis (PLS-DA) Published

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“…Hence, the discrimination and identification of herbal plants, their formulations (e.g. medicines made by extracts), and toxic heavy metal detection are essential for quality assurance (Martin, 1992;Woo et al, 1999;Cho et al, 2001;Garvey et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

Quality control of herbal medicines by using spectroscopic techniques and multivariate statistical analysis

Singh

Jha

Chaudhary

et al. 2009

Pharmaceutical Biology

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Recent Advances in Near-Infrared Reflectance Spectroscopy

Cited by 62 publications

References 162 publications

Estimating Foliar Nitrogen Concentration of Heather (Calluna vulgaris) from Field and Laboratory Spectra

Estimating Foliar Nitrogen Concentration of Heather (Calluna vulgaris) from Field and Laboratory Spectra

Non-destructive dating of fiber-based gelatin silver prints using near-infrared spectroscopy and multivariate analysis

Quality control of herbal medicines by using spectroscopic techniques and multivariate statistical analysis

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