The Applicability of near Infrared Reflectance Spectroscopy for Determining Solubility and Digestibility of Heated Protein under High Pressure

1995 ◽  
Vol 3 (2) ◽  
pp. 73-79 ◽  
Author(s):  
R.K. Cho ◽  
J.H. Lee ◽  
J.J. Ahn ◽  
Y. Ozaki ◽  
M. Iwamoto
Keyword(s):  
High Temperature ◽  
Structural Changes ◽  
Near Infrared ◽  
Linear Regression Analysis ◽  
Nir Spectroscopy ◽  
Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Absorption Bands ◽  
Steel Cylinder ◽  
Temperature And Pressure

The potential of near infrared (NIR) reflectance spectroscopy for non-destructively probing structural changes in protein during the process of denaturation was investigated. Lysozyme as a model protein was adjusted to 15% moisture content, placed in a steel cylinder and then heated at 30, 90, 120 and 150°C under pressure conditions of 10, 15, 30 and 45 MPa. Significant changes were observed in absorption bands near 2144, 2168 and 2208 nm with increases in temperature and pressure. The spectral changes were, in general, much larger for samples subjected to both high temperature and pressure than for those subjected to high temperature only. It is likely that these changes are due to changes in the secondary structure of protein. Absorbance changes at the above wavelengths showed high correlations to variations in solubility and digestibility of protein treated under high heat and pressure conditions. The results of multiple linear regression analysis suggest that NIR spectroscopy may be used to predict the solubility and digestibility of protein.

Monitoring the performance of a broad-based calibration for measuring the nutritive value of two independent populations of pasture using near infrared reflectance (NIR) spectroscopy

1991 ◽  
Vol 31 (2) ◽  
pp. 205 ◽  
Author(s):  
KF Smith ◽  
PC Flinn
Keyword(s):  
Nutritive Value ◽  
Near Infrared ◽  
Linear Regression Analysis ◽  
Spectral Characteristics ◽  
Nir Spectroscopy ◽  
Cost Effective ◽  
Multiple Linear Regression Analysis ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance

Near infrared reflectance (NIR) spectroscopy is a rapid and cost-effective method for the measurement of organic constituents of agricultural products. NIR is widely used to measure feed quality around the world and is gaining acceptance in Australia. This study describes the development of an NIR calibration to measure crude protein (CP), predicted in vivo dry matter digestibility (IVDMD) and neutral detergent fibre (NDF) in temperate pasture species grown in south-western Victoria. A subset of 116 samples was selected on the basis of spectral characteristics from 461 pasture samples grown in 1987-89. Several grass and legume species were present in the population. Stepwise multiple linear regression analysis was used on the 116 samples to develop calibration equations with standard errors of 0.8,2.3 and 2.2% for CP, NDF and IVDMD, respectively. When these equations were tested on 2 independent pasture populations, a significant bias existed between NIR and reference values for 2 constituents in each population, indicating that the calibration samples did not adequately represent the new populations for these constituents. The results also showed that the H statistic alone was inadequate as an indicator of equation performance. It was confirmed that it was possible to develop a broad-based calibration to measure accurately the nutritive value of closed populations of temperate pasture species. For the resulting equations to be used for analysis of other populations, however, they must be monitored by comparing reference and NIR analyses on a small number of samples to check for the presence of bias or a significant increase in unexplained error.

On-line application of visible and near infrared reflectance spectroscopy to predict physical and sensory characteristics of beef quality

2009 ◽  
Vol 2009 ◽  
pp. 135-135
Author(s):  
N Prieto ◽  
D W Ross ◽  
E A Navajas ◽  
G Nute ◽  
R I Richardson ◽  
...  
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Reflectance Spectroscopy ◽  
Sensory Characteristics ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Beef Quality ◽  
Near Infrared Reflectance ◽  
On Line ◽  
Meat Samples

Visible and near infrared reflectance spectroscopy (Vis-NIR) has been widely used by the industry research-base for large-scale meat quality evaluation to predict the chemical composition of meat quickly and accurately. Meat tenderness is measured by means of slow and destructive methods (e.g. Warner-Bratzler shear force). Similarly, sensory analysis, using trained panellists, requires large meat samples and is a complex, expensive and time-consuming technique. Nevertheless, these characteristics are important criteria that affect consumers’ evaluation of beef quality. Vis-NIR technique provides information about the molecular bonds (chemical constituents) and tissue ultra-structure in a scanned sample and thus can indirectly predict physical or sensory parameters of meat samples. Applications of Vis-NIR spectroscopy in an abattoir for prediction of physical and sensory characteristics have been less developed than in other fields. Therefore, the aim of this study was to test the on-line Vis-NIR spectroscopy for the prediction of beef quality characteristics such as colour, instrumental texture, water holding capacity (WHC) and sensory traits, by direct application of a fibre-optic probe to the M. longissimus thoracis with no prior sample treatment.

Relation of the Acute Pulmonary Response to Cotton Dust and Dust Compositional Analysis by Near-Infrared Reflectance Spectroscopy. Part II: Unsieved Dust

1988 ◽  
Vol 42 (3) ◽  
pp. 433-442 ◽  
Author(s):  
Joseph G. Montalvo ◽  
Sherman E. Faught ◽  
Steven M. Buco
Keyword(s):  
Near Infrared ◽  
Compositional Analysis ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Cotton Dust ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Absorption Bands ◽  
Infrared Reflectance Spectroscopy ◽  
Pulmonary Response

The near-infrared reflectance spectroscopy (NIRS) method of analysis, as applied to cotton dust, offers an independent method for searching for byssinosis causatives. We report here a test of the hypothesis that the acute pulmonary response from subjects exposed to cotton dust is a linear function of the composition of unsieved dust as measured by near-infrared reflectance spectroscopy (NIRS). A linear relationship was found between delta FEV1 (the forced expiratory volume in 1 second) and unsieved cotton dust captured by the Hi-Vol dust sampler. Of the various agents proposed over the years as the byssinosis causative agent, at least three of them (gram-negative bacteria and their endotoxins, and tannins) were present in the unsieved dust at concentrations exceeding the NIRS sensitivity level and may account for the observed relationship. No association was found between the pulmonary effects and cotton compositional analysis by NIRS. NIR reflectance spectra of cotton and cotton dust, in air and in nonabsorbing carbon tetrachloride, reveal similar absorption bands of different intensity.

Determination of Soil Separates with near Infrared Reflectance Spectroscopy

1996 ◽  
Vol 4 (1) ◽  
pp. 201-212 ◽  
Author(s):  
A. Couillard ◽  
A.J. Turgeon ◽  
M.O. Westerhaus ◽  
J.S. Shenk
Keyword(s):  
Prediction Accuracy ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Reflectance Spectroscopy ◽  
Transformation Model ◽  
Natural State ◽  
Peat Moss ◽  
Particle Sizes ◽  
Near Infrared Reflectance ◽  
Laboratory Values

The use of near infrared (NIR) reflectance spectroscopy to evaluate soil properties has started to receive more attention in recent years. The technology is evolving and research on NIR spectroscopic analysis using natural state samples is increasing. There is no method available today, besides NIR spectroscopy, that could simultaneously evaluate physical and chemical properties of a soil sample without processing the sample and affecting the visual quality of the site. More samples can be scanned in their natural undisturbed form resulting in a variety of particle sizes. Research on the effect of scanning products with different particle sizes is essential. The differences in the particle size of the soil separates may lower the prediction accuracy of NIR spectroscopy. In this study, we evaluated the ability of NIR spectroscopy to predict soil separates from artificial soil samples. Feldspar and silica sands and silts, kaolinite and montmorillonite clays, and reed sedge and Canadian sphagnum peat moss organic matters were used as separates. They were scanned alone, and in different mixture percentages, from 400 to 2500 nm with a total of 116 samples. The absence of linearity in the binary mixtures, preventing accurate calibration, was noticed and required the development of a transformation model to generate new laboratory values from a laboratory weight scaling factor generated for each soil separate. The adjustment of the laboratory values improved the prediction accuracy of the mixtures. The coefficient of determination ranged from 0.95 to 0.99. The standard error of cross-validation ranged from 2.09 to 5.82%.

Determination of Moisture in Cheddar Cheese by Near Infrared Reflectance Spectroscopy

1988 ◽  
Vol 71 (3) ◽  
pp. 571-574 ◽  
Author(s):  
Randy L Wehling ◽  
Michelle M Pierce
Keyword(s):  
Near Infrared ◽  
Spectral Response ◽  
Linear Regression Analysis ◽  
Nir Spectroscopy ◽  
Cheddar Cheese ◽  
Multiple Linear Regression Analysis ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Wide Range ◽  
Validation Set

Abstract Near infrared reflectance (NIR) spectroscopy was used to determine the moisture content of Cheddar cheese. Through multiple linear regression analysis, a 3-wavelength calibration was developed for use with a commercial filter monochromator instrument. For a validation set of 47 samples, the correlation coefficient squared (r2) between the NIR and oven moisture methods was 0.92, with a standard error of performance (SEP) of 0.38%. Sample temperature was found to significantly affect the spectral response; therefore, it was necessary to equilibrate all samples to a uniform temperature prior to NIR analysis. Aging may also affect the NIR characteristics of cheese, although it was possible to develop a successful calibration that encompassed a wide range of aging times

Development of a Sample Set for Soya Bean Calibration of near Infrared Reflectance Spectroscopy

1994 ◽  
Vol 2 (4) ◽  
pp. 223-227 ◽  
Author(s):  
T.L. Hong ◽  
S.-J. Tsai ◽  
S.C.S. Tsou
Keyword(s):  
Near Infrared ◽  
Analytical Data ◽  
Storage Period ◽  
Nir Spectroscopy ◽  
Reflectance Spectroscopy ◽  
Soya Bean ◽  
Chemical Compositions ◽  
Near Infrared Reflectance ◽  
Sample Set ◽  
Calibration Equations

The potential application of near infrared (NIR) spectroscopy is limited since its calibration equations are not always transferable from one instrument to another. Hence, an attempt was made to develop a selected sample set of soya beans with analytical data, which could be distributed to collaborators to calibrate their instruments. Sixty soya bean samples, (1 kg each) were selected and packed (200 g each) in laminated film bags after thorough mixing. During their storage at 4°C, the soya bean samples were periodically evaluated by chemical analysis as well as by NIR spectroscopy. Chemical compositions (i.e. moisture, protein and fat) were determined using conventional methods. Experimental results showed that no significant differences were found in the compositions of interest as well as in the reflectance spectra over a storage period of up to three years, and that the NIR spectroscopy method is independent of the location and model of the instruments. The experiment demonstrated that it is possible practically to use a pre-packed sample set with chemical data for calibration purposes.

Identification of Breast Carcinomatous Tissue by Near-Infrared Reflectance Spectroscopy

1994 ◽  
Vol 48 (2) ◽  
pp. 190-193 ◽  
Author(s):  
Joëlle Wallon ◽  
Shou He Yan ◽  
Jiashu Tong ◽  
Marc Meurens ◽  
Jules Haot
Keyword(s):  
Breast Cancer ◽  
Normal Tissue ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Tissue Sections ◽  
Derivative Spectra ◽  
Second Derivative Spectra ◽  
Cryostat Sections

NIR reflectance spectra of 110 cryostat sections of carcinomatous tissue and 114 cryostat sections of normal surrounding fibro-glandular tissue from 10 cases of breast cancer, identified by a classical pathology method, were scanned between 1100 and 2500 nm by a grating spectrometer in reflectance mode. Four wavelength intervals (1208–1242, 1746–1788, 2012–2048 and 2326–2368 nm) were found to be different for normal and carcinomatous tissues. In each interval, the second-derivative spectra of normal tissue showed a similar pattern with several characteristic peaks. In order to test the capacity of NIR spectroscopy in discriminating between normal and carcinomatous breast samples, 104 tissue sections from five additional cases were scanned prior to microscopic examination. The diagnostic prediction of NIR spectroscopy coincided exactly with the histology diagnosis for all the samples. Moreover, the presence of even a minute quantity of cancer infiltration can be detected by NIR spectroscopy, in total accordance with the microscopical observation. Therefore, the results of our experiments allow us to consider that NIR spectroscopy might become, with feasible improvements, an accurate, rapid, and reliable method for detecting breast cancer.

Application of Near Infrared Reflectance Spectroscopy to Determination of Fat in Cheddar Cheese

1989 ◽  
Vol 72 (1) ◽  
pp. 56-58 ◽  
Author(s):  
Randy L Wehling ◽  
Michelle M Pierce
Keyword(s):  
Near Infrared ◽  
Nir Spectroscopy ◽  
Cheddar Cheese ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Validation Set ◽  
Duplicate Sample

Abstract Near infrared reflectance (NIR) "spectroscopy was used to determine the fat content of Cheddar cheese. Through multiple linear regression, calibrations were developed for use with a commercial filter monochromator instrument. A 6-wavelength calibration, using 1734 nm as the primary indicator wavelength, was found to perform satisfactorily. Averaging readings from duplicate sample repacks reduced the standard error of performance (SEP) compared with the use of single readings. For a validation set of 23 samples, the correlation coefficient squared (r2) between the NIR and Roese-Gottlieb methods was 0.92, with an SEP of 0.44%. Both sample temperature and age of the cheese influenced the NIR response.

Nondestructive Analysis for Nitrogens of Soils by near Infrared Reflectance Spectroscopy

1998 ◽  
Vol 6 (A) ◽  
pp. A87-A91 ◽  
Author(s):  
R. K. Cho ◽  
G. Lin ◽  
Y. K. Kwon
Keyword(s):  
Near Infrared ◽  
Linear Regression Analysis ◽  
Nir Spectroscopy ◽  
Multiple Linear Regression Analysis ◽  
Soil Samples ◽  
Near Infrared Reflectance ◽  
Available Nitrogen ◽  
Destructive Analysis ◽  
Filter Type ◽  
Non Destructive

Traditional wet analytical method such as the gravimetric, Kjeldahl or Walkley-Black method are still the most widely used for determining the organic matter (OM), moisture and notal nitrogen (T–N) content of soils. However, these are time-consuming, high in cost and labour intensive as well producing harmfull pollutants making the method undesirable for field measurement. Over three years we have been working on the development of a non-destructive on-site analyser for measuring OM, moisture and T–N. In this research we investigated the possibility of using near infrared (NIR) spectroscopy for the non-destructive analysis of T–N, inorganic and available nitrogen in domestic soil samples.85 soil samples of upland over the Kyungpook prefecture were colledted to make a calibration and validation. Dried soil samples were packed in the closed-cup and the NIR spectra data was measured from 1100–2500 nm using a scanning type NIR instrum, InfraAlyzer 500 and filter type NIR instrument, InfraAlyzer 400, which has a modified sample compartment. Multiple linear regression analysis between the content of soil properties determined by the traditional method and the NIR spectral data were conducted to develop an non-destructive analysing equation for T–N, inorganic and available nitrogen. In the case of the scanning type, the standard error or prediction were 0.028%. 1.7 mg−1 and 1.1 mg−1 for T–N, inorganic and available nitrogen respectively. The prediction results in the filter type appeared to have the same accuracy as the scanning type. It is concluded that NIR spectroscopy could be used to predict soil nitrogen compounds such as total nitrogen, inorganic and available nitrogen non-destructively.

Sign in / Sign up

Export Citation Format

Share Document