Analysis of Feed Barley by near Infrared Reflectance Technology

1994 ◽  
Vol 2 (1) ◽  
pp. 33-41 ◽  
Author(s):  
M.J. Edney ◽  
J.E. Morgan ◽  
P.C. Williams ◽  
L.D. Campbell
Keyword(s):  
Near Infrared ◽  
In Vitro Digestibility ◽  
Mathematical Treatment ◽  
Data Sets ◽  
Calibration Data ◽  
Least Squares Regression ◽  
Near Infrared Reflectance ◽  
Canadian Prairies ◽  
Nir Reflectance Spectroscopy

Rapid methods for predicting feed barley quality with near infrared (NIR) reflectance spectroscopy were investigated. Reference tests for true metabolisable energy (TME), in vitro digestibility, neutral-detergent fibre, protein and kernel plumpness in feed barley is time-consuming. Near infrared technology can save considerable time by testing all of the above simultaneously, but accurate calibration of the equipment is essential. Calibration requires accurate results from chemical or physical tests and wide variance in reference data. Our calibration data sets were selected from over 800 feed barley (hulless, two- and six-rowed) samples that were grown at various locations across the Canadian Prairies in 1990 or 1991. Calibrations for a NIRSystems 6500 scanning spectrophotometer, using both whole and ground kernels, were calculated using one of three basic mathematical treatments: log (1/ R) or the first or second derivative thereof. Partial Least Squares regression was applied to the best mathematical treatment and further calibrations were generated where applicable. We found correlations of 0.95 (TME), 0.98 ( in vitro digestibility), 0.90 (NDF), 0.97 (protein) and 0.91 (kernel plumpness). Standard errors of prediction were 0.21, 0.97, 0.65, 0.31 and 11.5, respectively.

scholarly journals COMPARISON OF NEAR INFRARED CALIBRATIONS FOR ESTIMATING IN VITRO DIGESTIBILITY IN WHOLE-PLANT CORN HYBRIDS

1987 ◽  
Vol 67 (2) ◽  
pp. 557-562 ◽  
Author(s):  
E. V. VALDES ◽  
R. B. HUNTER ◽  
G. E. JONES
Keyword(s):  
Dry Matter ◽  
Near Infrared ◽  
Mature Stage ◽  
In Vitro Digestibility ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Corn Hybrids ◽  
Dry Matter Digestibility ◽  
Whole Plant

A comparison of two near infrared (NIRA) calibrations (C1 and C2) for the prediction of in vitro dry matter digestibility (IVDM) in whole-plant corn (WPC) was conducted. C1 consisted of 40 WPC samples collected from four locations across Ontario (Brucefield, London, Guelph and Elora). C2 consisted of 90 samples and included the above locations plus Pakenham and Winchester. Nine wavelengths were used in both equations but only three were common in C1 and C2 equations. These wavelengths were 2139 nm, 2100 nm, and 1445 nm, respectively. The predictions of IVDM utilizing both C1 and C2 were good. Coefficients of determination (r2) and standard error of the estimate (SEE) for calibration and prediction sets were 0.91, 1.7; 0.85, 1.7 for C1 and 0.88, 1.6; 0.77, 1.6 for C2 respectively. Regression analysis within location, however, showed low r2 values for the prediction of IVDM for Pakenham and Winchester in both calibrations. The more mature stage of harvest at these locations might be the cause of the poorer predictions. Key words: In vitro digestibility, whole-plant corn, near infrared reflectance

scholarly journals The Relative Performance of a Benchtop Scanning Monochromator and Handheld Fourier Transform Near-Infrared Reflectance Spectrometer in Predicting Forage Nutritive Value

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 658
Author(s):  
Matthew F. Digman ◽  
Jerry H. Cherney ◽  
Debbie J. R. Cherney
Keyword(s):  
Nutritive Value ◽  
Near Infrared ◽  
Prediction Models ◽  
Low Cost ◽  
Neutral Detergent Fiber ◽  
In Vitro Digestibility ◽  
Near Infrared Reflectance ◽  
Average Decrease ◽  
Manufacturing Techniques

Advanced manufacturing techniques have enabled low-cost, on-chip spectrometers. Little research exists, however, on their performance relative to the state of technology systems. The present study compares the utility of a benchtop FOSS NIRSystems 6500 (FOSS) to a handheld NeoSpectra-Scanner (NEO) to develop models that predict the composition of dried and ground grass, and alfalfa forages. Mixed-species prediction models were developed for several forage constituents, and performance was assessed using an independent dataset. Prediction models developed with spectra from the FOSS instrument had a standard error of prediction (SEP, % DM) of 1.4, 1.8, 3.3, 1.0, 0.42, and 1.3, for neutral detergent fiber (NDF), true in vitro digestibility (IVTD), neutral detergent fiber digestibility (NDFD), acid detergent fiber (ADF), acid detergent lignin (ADL), and crude protein (CP), respectively. The R2P for these models ranged from 0.90 to 0.97. Models developed with the NEO resulted in an average increase in SEP of 0.14 and an average decrease in R2P of 0.002.

Prediction of Chemical Composition in Sunflower Whole Plant and Silage (Helianthus Annus L.) by near Infrared Reflectance Spectroscopy

2007 ◽  
Vol 15 (3) ◽  
pp. 201-207 ◽  
Author(s):  
A. Fassio ◽  
A. Gimenez ◽  
E. Fernandez ◽  
D. Vaz Martins ◽  
D. Cozzolino
Keyword(s):  
Chemical Composition ◽  
Near Infrared ◽  
Cross Validation ◽  
Reference Method ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Near Infrared Reflectance ◽  
Whole Plant ◽  
Calibration Models

The aim of this study was to investigate the potential use of near infrared (NIR) reflectance spectroscopy to predict chemical composition in both sunflower whole plant (WPSun) and sunflower silage (SunS). Samples of both WPSun ( n = 73) and SunS ( n = 50) were analysed by reference method and scanned in reflectance using a NIR monochromator instrument (400–2500 nm). Calibration models were developed between NIR data and reference values for dry matter (DM), crude protein (CP), ash, acid detergent fibre (ADFom), neutral detergent fibre (aNDFom), in vitro organic matter digestibility (OMD), ether extract (EE) and pH using partial least squares regression (PLS). Due to the limited number of samples full cross-validation was used to test the calibration models. The best correlations (R 2cal) and lowest standard errors in cross-validation (SECV) were obtained for DM (R 2cal > 0.82, SECV: 27.0 and 35.8 g kg−1), CP (R 2cal> 0.85, SECV: 9.9 and 10.1 g kg−1) and ash (R2cal> 0.85, SECV 11.2 and 8.2 g kg−1) in both WPSun and SunS samples, respectively. For ADFom, aNDFom and OMD the calibrations were considered to be poor (R 2cal < 0.85). In SunS samples a good correlation was found for EE (R 2cal = 0.94, SECV: 15.3 g kg−1).

Determination of carbon fraction and nitrogen concentration in tree foliage by near infrared reflectances: a comparison of statistical methods

1996 ◽  
Vol 26 (4) ◽  
pp. 590-600 ◽  
Author(s):  
Katherine L. Bolster ◽  
Mary E. Martin ◽  
John D. Aber
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Near Infrared ◽  
Data Sets ◽  
Independent Data ◽  
Least Squares Regression ◽  
Near Infrared Reflectance ◽  
Regression Methods

Further evaluation of near infrared reflectance spectroscopy as a method for the determination of nitrogen, lignin, and cellulose concentrations in dry, ground, temperate forest woody foliage is presented. A comparison is made between two regression methods, stepwise multiple linear regression and partial least squares regression. The partial least squares method showed consistently lower standard error of calibration and higher R2 values with first and second difference equations. The first difference partial least squares regression equation resulted in standard errors of calibration of 0.106%, with an R2 of 0.97 for nitrogen, 1.613% with an R2 of 0.88 for lignin, and 2.103% with an R2 of 0.89 for cellulose. The four most highly correlated wavelengths in the near infrared region, and the chemical bonds represented, are shown for each constituent and both regression methods. Generalizability of both methods for prediction of protein, lignin, and cellulose concentrations on independent data sets is discussed. Prediction accuracy for independent data sets and species from other sites was increased using partial least squares regression, but was poor for sample sets containing tissue types or laboratory-measured concentration ranges beyond those of the calibration set.

Review: Prediction of variation in energetic value of wheat for poultry

2012 ◽  
Vol 92 (3) ◽  
pp. 261-273 ◽  
Author(s):  
M. Yegani ◽  
D. R. Korver
Keyword(s):  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
In Vitro Digestibility ◽  
Chemical Characteristics ◽  
Energy Availability ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Physico Chemical

Yegani, M. and Korver, D. R. 2012. Review: Prediction of variation in energetic value of wheat for poultry. Can. J. Anim. Sci. 92: 261–273. Variations in physical and chemical characteristics of wheat can significantly influence the energy availability of this feed ingredient for poultry. These variations can result in inefficiencies in the form of over- or under-formulation of the diets at commercial feed mills or on poultry farms. Therefore, having a clear understanding of the variations is of paramount importance in the formulation of poultry diets as they can have negative consequences for production performance of birds. There are a large number of factors that can contribute to variations in energy availability of wheat for poultry. This review is intended to briefly discuss these factors and also practical approaches that can be used to predict these variations. These approaches include measuring physico-chemical characteristics, in vivo digestibility trials, in vitro digestibility techniques, and near infrared reflectance spectroscopy (NIRS). There are limitations associated with physico-chemical and in vivo measurements. However, in vitro digestibility techniques are simple and fast and can provide data for database development and ongoing calibrations of NIRS systems. Near infrared reflectance spectroscopy has enormous potential to predict variations in wheat apparent metabolizable energy, leading to more accurate diet formulation.

scholarly journals Prediction of aspects of neutral detergent fibre digestion of forages by chemical composition and near infrared reflectance spectroscopy

2005 ◽  
Vol 56 (2) ◽  
pp. 187 ◽  
Author(s):  
S. Andrés ◽  
F. J. Giráldez ◽  
J. S. González ◽  
R. Peláez ◽  
N. Prieto ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Near Infrared ◽  
Chemical Data ◽  
In Vitro Digestibility ◽  
Near Infrared Reflectance ◽  
Independent Variables ◽  
Neutral Detergent Fibre ◽  
In Sacco Degradability ◽  
In Sacco

Sixty-two herbage samples, harvested in natural meadows located in the mountains of León (north-west Spain), and characterised by a diverse botanical composition and different stages of maturity of the plants, were used to evaluate the ability of chemical composition and near infrared (NIR) spectroscopy to predict in vitro digestibility and in sacco degradability of the neutral detergent fibre (NDF) fraction. In vitro digestibility was performed as described by the Goering and Van Soest procedure. Three dry Holstein-Friesian cows fitted with a rumen cannula were used to incubate the herbage samples. A Bran+Luebbe InfraAlyzer 500 spectrophotometer was used to obtain the NIR spectra corresponding to the 62 original herbage samples. Prediction equations for the estimation of in vitro digestibility and in sacco degradability parameters of the NDF fraction were generated using NIR spectra or chemical data as independent variables. The results showed that the in vitro digestibility and kinetic parameters of degradation of the NDF fraction could not be predicted accurately, probably as a consequence of the errors corresponding to the reference methods. In contrast, these errors did not greatly affect the extent of disappearance of the NDF fraction at later times, so the accuracy of prediction of these parameters was higher, especially when NIR spectra were used as independent variables. This is probably due to the close relationship that the parameters showed with the chemical data, since this kind of information, together with some physical characteristics of the samples, is included in the NIR spectra.

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

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