Effect of Sample Presentation and Animal Muscle Species on the Analysis of Meat by near Infrared Reflectance Spectroscopy

2002 ◽  
Vol 10 (1) ◽  
pp. 37-44 ◽  
Author(s):  
D. Cozzolino ◽  
I. Murray
Keyword(s):  
Crude Protein ◽  
Near Infrared ◽  
Cross Validation ◽  
Infrared Region ◽  
Coefficient Of Determination ◽  
Meat Industry ◽  
Near Infrared Reflectance ◽  
Silver Spring ◽  
Meat Samples ◽  
Beef Muscle

The useful wavelengths in both the visible and the near infrared region as well as two sample presentations (intact and minced) were evaluated to assess moisture (M), crude protein (CP) and intra muscular fat (IMF) in lamb ( n = 300), beef ( n = 100) and chicken ( n = 48) muscle samples. Samples were scanned in reflectance in a NIRSystems 6500 (NIRSystems, Silver Spring, MD, USA). Predictive equations were performed using modified partial least squares (MPLS) with internal cross-validation. The coefficient of determination in calibration ( R2CAL) and the standard error in cross-validation ( SECV) were calculated for each chemical parameter. For moisture, crude protein and fat (each expressed as g kg−1), R2CAL and SECV for beef muscle were 0.98, 0.81 and 0.96, respectively, and SECV was 33.1, 21.8 and 44.8 for beef muscle; for chicken muscle the comparable statistics were 0.99, 0.97 and 0.95 and SECV was 6.9, 2.4 and 33.1; while for lamb muscle R2CAL was 0.76, 0.83 and 0.73 and SECV 10.3, 5.5 and 4.7. It was concluded that the minced presentation is the best way to analyse muscle samples. On the other hand, intact presentation could have a great potential for use in the meat industry, although more research will be needed in order to determine quality attributes on meat samples.

Application of near Infrared Reflectance Spectroscopy for the Analysis of Organic C, Total N and pH in Soils of Uruguay

2002 ◽  
Vol 10 (3) ◽  
pp. 215-221 ◽  
Author(s):  
A. Morón ◽  
D. Cozzolino
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Reflectance Spectroscopy ◽  
Calibration Coefficient ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Total N ◽  
Organic C ◽  
Silver Spring ◽  
Validation Set

Near infrared (NIR) reflectance spectroscopy was used to analyse samples ( n = 332) from different soils from Uruguay (South America) for organic carbon (OC), total nitrogen (N) and pH. One set ( n = 200) of samples randomly selected was used to develop the NIR calibrations while the remaining ( n = 132) samples were used as the validation set. The samples were scanned in a small circular cup in reflectance mode (400–2500 nm), using a Foss NIRSystems 6500 (Silver Spring, MD, USA). Modified partial least squares (MPLS) was used to produce the calibration models and cross-validation was used to avoid collinearity effects among variables. Three mathematical treatments and four scatter corrections were also applied. The calibration coefficient of determination ( R2CAL) and the standard error in cross-validation ( SECV) were 0.94 ( SECV: 1.9) for OC; 0.91 ( SECV: 0.19) for total N in g kg−1 and 0.93 ( SECV: 0.18) for pH, respectively. The simple correlation coefficient of validation ( rVAL) and the standard errors of prediction ( SEP) were 0.74 and 5; 0.73 and 0.4; 0.84 and 0.28 for OC, total N and pH, respectively.

The potential of near-infrared reflectance spectroscopy to analyse soil chemical and physical characteristics

2003 ◽  
Vol 140 (1) ◽  
pp. 65-71 ◽  
Author(s):  
D. COZZOLINO ◽  
A. MORÓN
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Reflectance Spectroscopy ◽  
Coefficient Of Determination ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Silver Spring

Near-infrared reflectance spectroscopy (NIRS) was used for the analysis of soil samples for silt, sand, clay, calcium (Ca), potassium (K), sodium (Na), magnesium (Mg), copper (Cu) and iron (Fe). A total of 332 samples of different soils from Uruguay (South America) were used. The samples were scanned in a NIRS 6500 (NIRSystems, Silver Spring, MD, USA) in reflectance. Cross validation was applied to avoid overfitting of the models. The coefficient of determination in calibration (R^2_{\rm cal}) and the standard errors in cross validation (SECV) were 0·80 (SECV: 6·8), 0·84 (SECV: 6·0), 0·90 (SECV: 3·6) in per cent for sand, silt and clay respectively. For both macro and microelements the R^2_{\rm cal} and SECV were 0·80 (SECV: 0·1), 0·95 (SECV: 2·9), 0·90 (SECV 0·8), for K, Ca, Mg in g/kg respectively, and 0·86 (SECV: 0·82) and 0·92 (SECV: 25·5) for Cu and Fe in mg/kg. It was concluded that NIRS has a great potential as an analytical method for soil routine analysis due to the speed and low cost of analysis.

Predicting intramuscular fat, moisture and Warner-Bratzler shear force in pork muscle using near infrared reflectance spectroscopy

2006 ◽  
Vol 82 (1) ◽  
pp. 111-116 ◽  
Author(s):  
N. Barlocco ◽  
A. Vadell ◽  
F. Ballesteros ◽  
G. Galietta ◽  
D. Cozzolino
Keyword(s):  
Shear Force ◽  
Near Infrared ◽  
Cross Validation ◽  
Nir Spectroscopy ◽  
Intramuscular Fat ◽  
Coefficient Of Determination ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Calibration Models ◽  
Intact Muscle

AbstractPartial least-squares (PLS) models based on visible (Vis) and near infrared reflectance (NIR) spectroscopy data were explored to predict intramuscular fat (IMF), moisture and Warner Bratzler shear force (WBSF) in pork muscles (m. longissimus thoracis) using two sample presentations, namely intact and homogenized. Samples were scanned using a NIR monochromator instrument (NIRSystems 6500, 400 to 2500 nm). Due to the limited number of samples available, calibration models were developed and evaluated using full cross validation. The PLS calibration models developed using homogenized samples and raw spectra yielded a coefficient of determination in calibration (R2) and standard error of cross validation (SECV) for IMF (R2=0·87; SECV=1·8 g/kg), for moisture (R2=0·90; SECV=1·1 g/kg) and for WBSF (R2=0·38; SECV=9·0 N/cm). Intact muscle presentation gave poorer PLS calibration models for IMF and moisture (R2<0·70), however moderate good correlation was found for WBSF (R2=0·64; SECV=8·5 N/cm). Although few samples were used, the results showed the potential of Vis-NIR to predict moisture and IMF using homogenized pork muscles and WBSF in intact samples.

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.

Prediction of Fatty Acid Content in Beef Neck Lean by near Infrared Reflectance Analysis

1998 ◽  
Vol 6 (1) ◽  
pp. 229-234 ◽  
Author(s):  
William R. Windham ◽  
W.H. Morrison
Keyword(s):  
Fatty Acids ◽  
Fatty Acid ◽  
Near Infrared ◽  
Fatty Acid Content ◽  
Reference Method ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Longissimus Dorsi ◽  
Near Infrared Reflectance ◽  
Total Fatty Acids

Near infrared (NIR) spectroscopy in the prediction of individual and total fatty acids of bovine M. Longissimus dorsi neck muscles has been studied. Beef neck lean was collected from meat processing establishments using advanced meat recovery systems and hand-deboning. Samples ( n = 302) were analysed to determine fatty acid (FA) composition and scanned from 400 to 2498 nm. Total saturated and unsaturated FA values ranged from 43.2 to 62.0% and 38.3 to 56.2%, respectively. Results of partial least squares (PLS) modeling shown reasonably accurate models were attained for total saturate content [standard error of performance ( SEP = 1.10%); coefficient of determination on the validation set ( r2 = 0.77)], palmitic ( SEP = 0.94%; r2 = 0.69), unsaturate ( SEP = 1.13%; r2 = 0.77), and oleic ( SEP = 0.97; r2 = 0.78). Prediction of other individual saturated and unsaturated FAs was less accurate with an r2 range of 0.10 to 0.53. However, the sum of individual predicted saturated and unsaturated FA was acceptable compared with the reference method ( SEP = 1.10 and 1.12%, respectively). This study shows that NIR can be used to predict accurately total fatty acids in M. Longissimus dorsi muscle.

Prediction of crude protein content in field peas using near infrared reflectance spectroscopy

2006 ◽  
Vol 86 (1) ◽  
pp. 157-159 ◽  
Author(s):  
G. C. Arganosa ◽  
T. D. Warkentin ◽  
V. J. Racz ◽  
S. Blade ◽  
C. Phillips ◽  
...  
Keyword(s):  
Crude Protein ◽  
Near Infrared ◽  
Spectroscopic Method ◽  
Correlation Coefficients ◽  
Reflectance Spectroscopy ◽  
Field Pea ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy

A rapid, near-infrared spectroscopic method to predict the crude protein contents of 72 field pea lines grown in Saskatchewan, both whole seeds and ground samples, was established. Correlation coefficients between the laboratory and predicted values were 0.938 and 0.952 for whole seed and ground seed, respectively. Both methods developed are adequate to support our field pea breeding programme. Key words: Field pea, near-infrared reflectance spectroscopy, crude protein

EVALUATION OF NEAR INFRARED REFLECTANCE SPECTROSCOPY FOR PREDICTING FORAGE QUALITY IN TIMOTHY

1988 ◽  
Vol 68 (2) ◽  
pp. 471-480 ◽  
Author(s):  
J. SURPRENANT ◽  
R. MICHAUD
Keyword(s):  
Crude Protein ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Phleum Pratense ◽  
Standard Errors ◽  
Wavelength Selection ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Laboratory Procedures ◽  
Phleum Pratense L

Near infrared reflectance spectroscopy (NIRS) is a newly attractive technology introduced for the analysis of agricultural products and for which new instruments have been developed. The objective of this experiment was to evaluate the capabilities of the Technicon InfraAlyzer 500 (I/A-500), a scanner monochromator type instrument, with regard to its potential utilization in the breeding of timothy (Phleum pratense L.) for higher nutritional qualities. Special features of this instrument were also used to further assess its capacities once the wavelengths were deliberately reduced and set to make the I/A-500 comparable to a 19 wavelength filter instrument such as typically found in a Technicon I/A-400R model. The investigation was performed using a total of 120 timothy samples collected from spaced plant nurseries in 1982 and 1984 and analyzed for acid detergent fiber (ADF), neutral detergent fiber (NDF), crude protein (CP), digestibility (DMM), water solubility (WS), water retention (WR) and packed volume (PV) in the laboratory. The equations developed with the I/A-500 had R2 and r2 larger than 0.85 for ADF, NDF, CP, DDM and WS in both 1982, and 1984, and combined 1982–1984 with the exception of DDM and WS in 1982 that had r2 of 0.76. The lower R2 and r2 obtained for WR and PV were attributed to poor laboratory procedures. The standard errors of calibration of ADF, NDF, CP and DDM were all as good or better than those previously reported, with other cool season grasses. The equations developed by using only the 19 wavelengths typically found in an I/A-400R provided R2 standard errors of calibration, r2 and standard error of analysis which were quite similar to those obtained with the I/A-500. Thus, we concluded that both the unrestricted wavelength selection of the I/A-500 and the restricted wavelength selection available in an I/A-400R would be adequate to evaluate forage quality in timothy. In this experiment, the main limitations appeared to have been related to the precision of the laboratory procedures and to the lack of variation in the populations under evaluation. As a general guideline to evaluate these two factors, it is proposed to use the ratio of the standard deviation of the population over the standard deviation of the laboratory procedure. In our experimentation a ratio larger than 5.0 appeared suitable to obtain adequate calibrations.Key words: Fiber, crude protein, digestibility, forage physical properties, Phleum pratense L.

scholarly journals BIDIRECTIONAL REFLECTANCE MODELING OF THE GEOSTATIONARY SENSOR HIMAWARI-8/AHI USING A KERNEL-DRIVEN BRDF MODEL

2016 ◽  
Vol III-7 ◽  
pp. 3-8 ◽  
Author(s):  
M. Matsuoka ◽  
M. Takagi ◽  
S. Akatsuka ◽  
R. Honda ◽  
A. Nonomura ◽  
...  
Keyword(s):  
Surface Properties ◽  
Land Surface ◽  
Goodness Of Fit ◽  
Near Infrared ◽  
Temporal Frequency ◽  
Atmospheric Correction ◽  
Time Of Day ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Bidirectional Reflectance

Himawari-8/AHI is a new geostationary sensor that can observe the land surface with high temporal frequency. Bidirectional reflectance derived by the Advanced Himawari Imager (AHI) includes information regarding land surface properties such as albedo, vegetation condition, and forest structure. This information can be extracted by modeling bidirectional reflectance using a bidirectional reflectance distribution function (BRDF). In this study, a kernel-driven BRDF model was applied to the red and near infrared reflectance observed over 8 hours during daytime to express intraday changes in reflectance. We compared the goodness of fit for six combinations of model kernels. The Ross-Thin and Ross-Thick kernels were selected as the best volume kernels for the red and near infrared bands, respectively. For the geometric kernel, the Li-sparse-Reciprocal and Li-Dense kernels displayed similar goodness of fit. The coefficient of determination and regression residuals showed a strong dependency on the azimuth angle of land surface slopes and the time of day that observations were made. Atmospheric correction and model adjustment of the terrain were the main issues encountered. These results will help to improve the BRDF model and to extract surface properties from bidirectional reflectance.

scholarly journals Research on Crude Protein Contents in Medicago Sativa Hay Harvest During 2008-2009 Using FT-NIR Spectrometry

2011 ◽  
Vol 68 (1) ◽  
Author(s):  
Laura DALE ◽  
Ioan ROTAR ◽  
Vasile FLORIAN ◽  
Roxana VIDICAN ◽  
André THEWIS ◽  
...  
Keyword(s):  
Medicago Sativa ◽  
Protein Content ◽  
Crude Protein ◽  
Nutritive Value ◽  
Cross Validation ◽  
External Validation ◽  
Flowering Plant ◽  
Coefficient Of Determination ◽  
Research Station ◽  
Crude Protein Content

Medicago sativa or alfalfa is a flowering plant that belongs to Pea Family that is widely grown throughout the world as forage for cattle, and is most often harvested as hay. Usually, alfalfa has the highest nutritive value of all common hay crops. This work aims to highlight a way for direct, non-destructive analysis of crude protein content in alfalfa hays. The primary objective was to build a model for crude protein calibration for alfalfa based on FT-NIR spectroscopy. The samples for analysis were collected over two experimental years (2008-2009) from field trials from the research station– Agricultural Development, Cojocna. In order to construct the model, reference values are needed; for this reason, the crude protein content was determined using the classical Kjeldahl method (Kjeltec Auto Analyser, Tecator). The values for crude protein ranged from 12.63% to 19.12% on the dry matter basis. The regression model’s construction was based on Partial Least Squares (PLS) calculated with the SIMPLS algorithm, using different pre-processing techniques and leave-one-out cross validation. Calibration of the two years together drove to a coefficient of determination for cross validation, R2 of 0.965. The robustness of the model was confirmed by applying it to independent samples (external validation) where the coefficient of determination was R2 = 0.977, RMSEP = 0.8. The results obtained indicated that NIRS can be used to determine crude protein, which could be used as criteria for quality control of alfalfa hays.

CHLOROPHYLL ANALYSIS OF WHOLE RAPESEED KERNELS BY NEAR INFRARED REFLECTANCE

1982 ◽  
Vol 62 (4) ◽  
pp. 875-884 ◽  
Author(s):  
RUSSELL TKACHUK ◽  
F. D. KUZINA
Keyword(s):  
Chlorophyll Content ◽  
Near Infrared ◽  
Good Accuracy ◽  
Visible Region ◽  
Infrared Region ◽  
Multiple Correlation Coefficient ◽  
Multiple Correlation ◽  
Near Infrared Reflectance ◽  
Laboratory Results ◽  
Near Infrared Region

Chlorophyll content was determined in whole rapeseed samples, from Regent and Candle cultivars, by using a reflectance technique in the visible and near infrared region. Chlorophyll content was estimated with good accuracy when predicted results for 42 samples of Regent, 37 samples of Candle and 79 samples for both cultivars combined were compared with standard laboratory results. For Regent, a multiple correlation coefficient (R) of 0.944 and a standard error of estimate (Sy) of 4.7 were obtained when reflectance was measured at six wavelengths. For Candle, R = 0.963 and Sy = 4.4, using another six wavelengths. For both cultivars combined, R = 0.939 and Sy = 4.8, again using a different set of six wavelengths. Wavelengths for predicting chlorophyll were selected from the 630-to 754-nm visible region, and from the 1640- to 2176-nm near infrared region. This reflectance method described for whole rapeseed is rapid, involves no sample preparation, and leaves the seed intact and available for other uses.

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