The Use of near Infrared Reflectance Spectroscopy to Predict the Insoluble Dietary Fibre Fraction of Cereal Products

1998 ◽  
Vol 6 (1) ◽  
pp. 221-227 ◽  
Author(s):  
Sandra E. Kays ◽  
Franklin E. Barton
Keyword(s):  
Standard Error ◽  
Dietary Fibre ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Medical Community ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Cereal Products ◽  
Wide Range ◽  
Insoluble Dietary Fibre

The insoluble and soluble fractions of dietary fibre have different human physiological effects and their presence in foods is of interest to consumers, the medical community and the cereal product industry. The development of a model, using near infrared (NIR) reflectance spectroscopy, to predict insoluble dietary fibre in a wide range of dry-milled cereal products and grains is described. The products included breakfast cereals, crackers, brans, pastas and flours. Insoluble dietary fibre was measured by the AOAC enzymatic–gravimetric procedure (AOAC 991.43). The range in insoluble dietary fibre was 0–48%. Near infrared reflectance spectra were obtained with a scanning monochromator and data analysed with a commercial analysis program. A calibration ( n = 90) was developed for prediction of insoluble dietary fibre using preprocessed spectra and modified partial least squares regression. The standard error of cross validation and R2 were 1.34% and 0.99, respectively. The model was tested with independent validation samples ( n = 32) and the resulting standard error of performance and r2 were 1.13% insoluble dietary fibre and 0.99, respectively. The results show that NIR spectroscopy can be used to predict the insoluble dietary fibre content in a wide variety of processed and unprocessed cereal products.

Broad-based calibrations of in vitro gas production of forages by near-infrared reflectance spectroscopy

1998 ◽  
Vol 22 ◽  
pp. 234-237
Author(s):  
M. Herrero ◽  
N. S. Jessop
Keyword(s):  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Gas Production ◽  
Grass Species ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Wide Range

There is increasing demand to obtain fast and accurate dynamic nutritional information from forages. Near-infrared reflectance spectroscopy (NIRS) offers the possibility for obtaining such information for a range of nutritional constituents of foods. Herrero et al. (1996 and 1997) calibrated in vitro gas production measurements of a single grass species by NIRS. There would be greater practical benefit if the gas production predictions could be obtained using calibrations derived from a wide range of plant species, since a single equation could be used for all forages. The objective of this study was to investigate if in vitro gas production measurements of a broad based sample population could be calibrated by NIRS.

Near infrared reflectance spectroscopy as a potential surrogate method for the analysis of D13C in mature kernels of durum wheat

2001 ◽  
Vol 52 (8) ◽  
pp. 809 ◽  
Author(s):  
J. P. Ferrio ◽  
E. Bertran ◽  
M. Nachit ◽  
C. Royo ◽  
J. L. Araus
Keyword(s):  
Durum Wheat ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Local Models ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Δ13c Values ◽  
Infrared Reflectance Spectroscopy ◽  
Wide Range

Carbon isotope discrimination (Δ13C) in grain is a potentially useful trait in breeding programs that aim to increase the yield of wheat and other cereals. Near infrared reflectance spectroscopy (NIRS) is used in routine assays to determine grain and flour quality. This study assesses the ability of NIRS to predict Δ13C in mature kernels of durum wheat. Plants were grown in north-west Syria as this location provided 3 distinct Mediterranean trials that covered a wide range for Δ13C values in grains (from about 12.9‰ to 17.6‰). We measured the spectral reflectance signature between 1100 and 2500 nm in samples from the same flour used in the conventional (i.e. mass spectrometry) determinations of Δ13C. By using principal components regression and partial least squares regression (PLSR), a model of the association between conventional laboratory analysis and these spectra was produced. Global regressions, which included samples from all 3 trials, and local models, which used samples from only one trial, were built and then validated with sample sets not included in calibration procedures. In global models, strong significant correlations (P < 0.001) were found between NIRS-predicted Δ13C and measured Δ13C values. PLSR gave r 2 values of 0.86 and 0.82 for calibration and validation sets, respectively. Although less strongly correlated, all local models selected for a subset of samples with significantly higher Δ13C values. Local models also performed well when selecting samples from the other 2 trials. The advantages and possible limitations of NIRS are further discussed.

Study of dissected lamb muscles by visible and near infrared reflectance spectroscopy for composition assessment

2000 ◽  
Vol 70 (3) ◽  
pp. 417-423 ◽  
Author(s):  
D. Cozzolino ◽  
I. Murray ◽  
J. R. Scaife ◽  
R. Paterson
Keyword(s):  
Standard Error ◽  
Near Infrared ◽  
Cross Validation ◽  
Rectus Femoris ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Fresh Weight Basis ◽  
Infrared Reflectance Spectroscopy

AbstractNear infrared reflectance spectroscopy (NIRS) was used to study the reflectance properties of intact and minced lamb muscles in two presentations to the instrument to predict their chemical composition. A total of 306 muscles were examined from 51 lambs, consisting of the following muscles: longissimus dorsi, supraspinatus, infraspinatus, semimembranosus, semitendinosus and rectus femoris. Modified partial least squares (MPLS) regression models of chemical variables yielded R2 and standard error of cross-validation (SECV) of 0·76 (SECV: 10·4), 0·83 (SECV: 5·5) and 0·73 (SECV: 4·7) for moisture, crude protein and intramuscular fat in the minced samples expressed as g/kg on a fresh-weight basis, respectively. Calibrations for intact samples had lower R2 and higher standard error of cross validation (SECV) compared with the minced samples.

QUALITY OF ALFALFA HERBAGE ESTIMATED BY A PREPARED CELLULASE SOLUTION AND NEAR INFRARED REFLECTANCE SPECTROSCOPY

1989 ◽  
Vol 69 (3) ◽  
pp. 833-839 ◽  
Author(s):  
S. S. BUGHRARA ◽  
D. A. SLEPER ◽  
R. L. BELYEA ◽  
G. C. MARTEN
Keyword(s):  
Dry Matter ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
In Vitro Digestibility ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Wide Range ◽  
Medicago Sativa L

Little information is available on estimating in vitro dry matter digestibility (IVDMD) of alfalfa (Medicago sativa L.) herbage by a prepared cellulase solution (PCS) and then using these IVDMD estimates to calibrate near infrared reflectance spectroscopy (NIRS) equations. Objectives were to compare PCS digestion to that by two rumen fermentation procedures, including true in vitro digestibility (TIVD), and develop NIRS equations to estimate TIVD, neutral detergent fiber, and acid detergent fiber of alfalfa hay. Seventy-eight alfalfa samples, having a wide range in herbage quality, were analyzed for IVDMD using five different PCS procedures and two rumen fermentation procedures (true and apparent in vitro digestibility). The best NIRS calibration equation for TIVD had R2 of 0.92 and a standard error of selection of 20.7 g kg−1. Correlations between IVDMD and TIVD obtained by the various PCS assays ranged from 0.91 to 0.96 (P < 0.01), with regression coefficients ranging from 0.94 to 0.98. We concluded that PCS gave rapid and accurate estimates of TIVD and that NIRS could accurately estimate TIVD of a wide range of alfalfa herbage quality.Key words: Acid detergent solubles, fungal cellulase solubles, in vitro digestible dry matter, Medicago sativa L., neutral detergent solubles, alfalfa

Opportunities for, and limitations of, near infrared reflectance spectroscopy applications in soil analysis: A review

2009 ◽  
Vol 89 (5) ◽  
pp. 531-541 ◽  
Author(s):  
C Nduwamungu ◽  
N Ziadi ◽  
L -É Parent ◽  
G F Tremblay ◽  
L Thuriès
Keyword(s):  
Sample Preparation ◽  
Standard Error ◽  
Near Infrared ◽  
Soil Analysis ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Reference Methods

Near infrared reflectance spectroscopy (NIRS) is a cost- and time-effective and environmentally friendly technique that could be an alternative to conventional soil analysis methods. In this review, we focussed on factors that hamper the potential application of NIRS in soil analysis. The reported studies differed in many aspects, including sample preparation, reference methods, spectrum acquisition and pre-treatments, and regression methods. The most significant opportunities provided by NIRS in soil analysis include its potential use in situ, the determination of various biological, chemical, and physical properties using a single spectrum per sample, and an estimated reduction of analytical cost of at least 50%. Contradictory results among studies on NIRS utilisation in soil analysis are partly related to variations in sample preparation and reference methods. The following calibration statistics appear to be most appropriate for comparing NIRS performance across soil attributes: (i) coefficient of determination (r2), (ii) ratio of performance deviation (RPD), (iii) coefficient of regression (b), and (iv) ratio of the standard error of prediction (SEP) to the standard error of the reference method (SER), i.e., the ratio of standard errors (RSE). Further investigations on issues such as (i) RSE guidelines, (ii) correlation between NIRS spectrophotometers, (iii) correlation of different reference methods for a given attribute to soil spectra, (iv) identification of key factors affecting the accuracy of NIRS predictions, and (v) efficient use of spectral libraries are required to enhance the acceptability of NIRS as a soil analysis technique and to make it more user-friendly. Standardized guidelines are proposed for the assessment of the accuracy of NIRS predictions of soil attributes.Key words: Near infrared reflectance spectroscopy, soil analysis, calibration

Moisture Analysis of Forage by Near Infrared Reflectance Spectroscopy: Preliminary Collaborative Study and Comparison Between Karl Fischer and Oven Drying Reference Methods

1988 ◽  
Vol 71 (2) ◽  
pp. 256-262
Author(s):  
William R Windham ◽  
Franklin E Barton ◽  
James A Robertson
Keyword(s):  
Standard Error ◽  
Near Infrared ◽  
Collaborative Study ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Karl Fischer ◽  
Infrared Reflectance Spectroscopy ◽  
Moisture Analysis

Abstract A collaborative study of moisture analysis by neai infrared reflectance spectroscopy (NIRS) has been completed involving 5 laboratories and 20 forage samples. Near infrared reflectance spectroscopy calibrations for moisture were developed in the Associate Referee's laboratory from Karl Fischer (KF) and AOAC air oven (AO) (135°C for 2 h) moisture methods, respectively, and transferred to each collaborating laboratory's NIRS instrument. NIRS moisture data were validated with KF data from the Associate Referee's laboratory and AO data from each collaborating laboratory. The standard error of analysis of KF data by NIRS KF determination and AO data by NIRS AO determination ranged from 0.25 to 0.48% and from 0.74 to 1.88%, respectively. The standard errors between laboratories for NIRS KF and NIRS AO determinations were 0.2" and 0.39%, respectively. The standard error between moisture analyses by NIRS KF and NIRS AO calibrations, averaged across laboratories, was 0.42%. In addition, the standard error between laboratories for the AOAC AO method was 0.63%. The increase in standard error for the AOAC AO method was due to the random and systematic errors associated with the gravimetric techniques. The results indicate that NIRS analysis can accurately and precisely deterrr ine the moisture content of forages and forage crops because of th« very strong absorbance of water in the near infrared region.

Determination of macro elements in alfalfa and white clover by near-infrared reflectance spectroscopy

2002 ◽  
Vol 139 (4) ◽  
pp. 413-423 ◽  
Author(s):  
A. MORÓN ◽  
D. COZZOLINO
Keyword(s):  
White Clover ◽  
Near Infrared ◽  
Cross Validation ◽  
Dry Weight ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Wide Range

Near-infrared reflectance spectroscopy was used to assess the mineral composition of both alfalfa (Medicago sativa L.) and white clover (Trifolium repens L.). Alfalfa (n=230) and white clover (n=97) plant samples from different locations in Uruguay representing a wide range of soil types were analysed. The samples were scanned for reflectance in a NIRSystems 6500 monochromator (NIRSystems, Silver Spring, MD, USA). Predictive equations were developed using modified partial least squares (MPLS) with cross validation to avoid overfitting. The coefficients of determination in calibration (R_{\rm cal}^{2}) and the standard errors in cross validation (SECV) were 0·93 (SECV: 1·6), 0·95 (SECV: 1·3), 0·93 (SECV: 1·9), 0·88 (SECV: 2·7), 0·82 (SECV: 0·3) and 0·75 (SECV: 4·7) for alfalfa and 0·98 (SECV: 0·8), 0·52 (SECV: 0·8), 0·97 (SECV: 2·7), 0·83 (SECV: 3·1), 0·82 (SECV: 1·9) and 0·45 (SECV: 2·6) for white clover, for N, Ca, K, P, Mg and S in g/kg on a dry weight respectively. Calcium, nitrogen and potassium were well predicted by NIRS in both alfalfa and white clover samples.

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