Using near infrared reflectance spectroscopy to estimate the nutritive value of senescing annual ryegrass (Lolium rigidum): a comparison of calibration methods

1998 ◽  
Vol 38 (1) ◽  
pp. 45 ◽  
Author(s):  
K. F. Smith ◽  
R. J. Simpson ◽  
R. D. Armstrong
Keyword(s):  
Leaf Blade ◽  
Nutritive Value ◽  
Near Infrared ◽  
Leaf Sheath ◽  
Plant Part ◽  
Annual Ryegrass ◽  
Lolium Rigidum ◽  
Near Infrared Reflectance ◽  
Calibration Methods ◽  
Calibration Equations

Summary. The suitability of near infrared reflectance (NIR) spectroscopy for predicting the concentration of several quality traits in samples of annual ryegrass (Lolium rigidum Gaud.) herbage was assessed in 2 separate experiments. In the first experiment, NIR calibration equations were developed for 6 traits (water-soluble carbohydrates, dry matter digestibility, neutral detergent solubles, neutral detergent solubles digestibility, neutral detergent fibre digestibility and nitrogen) using 4 calibration methods. No significant differences were found in the accuracy of NIR equations developed using either stepwise multiple linear regression (SMLR) or partial least squares regression (PLS) techniques when the equations were used to predict the concentration of constituents in those samples not used during the calibration process. The process of removing samples identified by the computer as spectral outliers was found to improve those statistics that related NIR data to the reference data of the samples used during calibration development (i.e. improved the goodness of fit of the regressions). However, when the resulting equations were used on all of the samples there was no improvement in the accuracy of the prediction of composition, and the estimates were less accurate for 2 of the equations. In the second experiment, plant part-specific equations (leaf blade, stem and leaf sheath) were developed. The specific equations were found to be no more accurate than those developed using a subset of all samples when used to analyse samples of the same plant part. However, using equations developed on either stem or leaf sheath samples to predict the composition of leaf blade samples led to inaccurate estimates of composition, illustrating the potential for error when NIR calibration equations are used on dissimilar samples. The similarity of the NIR estimates of decline in nutritive value and those obtained using reference analyses was illustrated by plotting the actual and predicted decline in nutritive value. The results of the experiments in this paper illustrate the need to monitor the accuracy of any NIR prediction of nutritive value. Striving for very low standard errors of calibration either by eliminating outliers or by limiting the plant tissues used during calibration did not lead to more accurate predictions of the composition of samples other than those used during the calibration process.

Losses of the digestible components of annual ryegrass (Lolium rigidum Gaudin) during senescence

1990 ◽  
Vol 41 (4) ◽  
pp. 719 ◽  
Author(s):  
RA Ballard ◽  
RJ Simpson ◽  
GR Pearce
Keyword(s):  
Chemical Composition ◽  
Leaf Blade ◽  
Leaf Sheath ◽  
Annual Ryegrass ◽  
Lolium Rigidum ◽  
Stem Internode ◽  
Whole Plants ◽  
Grass Sward ◽  
Stem Leaf

Changes in the digestibility and chemical composition of a L. rigidum cv. Wimmera sward sown in May, 1985 were measured from 21 d pre-anthesis (9 Oct.) until 69 d after anthesis (7 Jan.) when the plants were dead. Max. yield of 11.7 t DM/ha was reached 8 d pre-anthesis. The in vitro DM digestibility (IVDMD) of whole plants decreased from 58% at anthesis to 36% 69 d after anthesis. This was associated with a decrease in the IVDMD of stem, leaf blades and sheaths. In the 3rd stem internode, which was considered representative of the stem, the loss of digestible yield was due to loss of DM soluble in neutral detergent (NDS). The NDS consisted mainly of non-structural carbohydrates. Similar losses of NDS contributed to loss of digestibility in the uppermost leaf blade and leaf sheath. The digestibility of NDS was generally 80-95% but in the leaf blade this declined to 45% as NDS was mobilized during leaf senescence. NDF digestibility of the stem declined from 35% at anthesis to 19% when dead; corresponding values for the uppermost leaf blade were 83 and 54%, resp., and for the leaf sheath 46 and 37%, resp. These characteristics of a senescing grass sward are discussed in relation to options for improving digestibility of dead grass pastures.

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.

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.

Determination of dry matter (DM) and nitrogen (N) degradability in forages by near infrared reflectance spectroscopy (NIRS)

2003 ◽  
Vol 2003 ◽  
pp. 154-154
Author(s):  
C. Cajarville ◽  
J. P Repetto ◽  
A. Curbelo ◽  
C. Soto ◽  
D. Cozzolino
Keyword(s):  
Nutritive Value ◽  
Near Infrared ◽  
Chemical Constituents ◽  
Climatic Conditions ◽  
Near Infrared Reflectance ◽  
Forage Crops ◽  
Optimum Planning ◽  
Plant Maturity ◽  
Animal Feeding

The nutritive value of forage crops is related mainly to climatic conditions and stage of plant maturity, and its determination for any given crop is essential for optimum planning and animal feeding (Berardo et al., 1993; Deaville and Flinn, 2000). Worldwide the nutritive value of forages is often estimated by chemical or physical methods and is expressed as the concentration of chemical constituents in the plant tissue. There is little information in the literature about the use of NIRS to determine degradability in pastures with different conditions, season, different places (Wilman et al., 2000). The aim of the work to explore the use of NIRS as rapid tool for estimate DM and N degradability in forages.

Measurement of the magnesium concentration in perennial ryegrass (Lolium perenne) using near infrared reflectance spectroscopy

1991 ◽  
Vol 42 (8) ◽  
pp. 1399 ◽  
Author(s):  
KF Smith ◽  
SE Willis ◽  
PC Flinn
Keyword(s):  
Lolium Perenne ◽  
Perennial Ryegrass ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Magnesium Concentration ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Calibration Equations

Near infrared reflectance spectroscopy (NIR) was used to develop calibration equations to measure the magnesium concentration in perennial ryegrass herbage (Lolium perenne). A subset of 72 samples was selected on the basis of spectral variation from 400 samples grown in 1988-1989. Three alternative equations were chosen using stepwise multiple linear regression, with standard errors ranging from 0.4 to 0.3 g/kg DM with corresponding squared multiple correlation coefficients ( R2) of 0.68 to 0.82. The equations had 2, 4 and 4 wavelength terms respectively. When these equations were tested on an independent population of perennial ryegrass samples, a significant bias existed when using the 4 term equations but there was no bias when the 2 term equation was used. We conclude that NIR can be used to screen large numbers of perennial ryegrass plants for magnesium concentration. However, for the calibration equations to be used for the analysis of other populations equation performance must be monitored by comparing reference and NIR analyses on a small number of samples.

Use of residual maximum likelihood to evaluate accuracy of two NIRS calibration procedures, relative to Kjeldahl, for determining nitrogen concentration of soybeans

1991 ◽  
Vol 71 (2) ◽  
pp. 385-392 ◽  
Author(s):  
G. B. Schaalje ◽  
H. -H. Mündel
Keyword(s):  
Maximum Likelihood ◽  
Near Infrared ◽  
Nitrogen Concentration ◽  
Principal Component Regression ◽  
Principal Component ◽  
Field Trials ◽  
Near Infrared Reflectance ◽  
Residual Maximum Likelihood ◽  
Maximum Likelihood Procedure ◽  
Calibration Methods

The accuracy of estimates of plant properties based on near-infrared reflectance spectroscopy (NIRS) varies with many factors including the biological material in question and the method used to calibrate the NIRS instrument. This study investigated the accuracy, relative to Kjeldahl analysis, of NIRS analysis based on two calibration methods in estimating nitrogen concentration of four stages and/or parts of soybean (Glycine max (L.) Merr.) plants. Samples of whole top growth at anthesis, whole top growth at maturity, whole top growth at maturity excluding seeds, and seeds were obtained from two field trials and one phytotron experiment. Two Kjeldahl determinations of nitrogen concentration were obtained for each sample, as well as reflectance values at each of 19 infrared wavelengths, using a Technicon InfraAlyser 400R. Different subsets of the sample data were used for calibration and assessment of accuracy. The instrument was calibrated using stepwise multiple linear regression (SMLR) and principal component regression (PCR). The residual maximum likelihood procedure was useful in showing that NIRS estimates based on either SMLR or PCR were at least as accurate as Kjeldahl estimates for all stages and/or parts except whole top growth at maturity excluding seeds. Key words: Calibration, principal component regression, stepwise regression

The use of near infrared reflectance spectroscopy (NIRS) to predict the nutritive value of standard commercial diets for post-weaned pigs

2009 ◽  
Vol 2009 ◽  
pp. 108-108
Author(s):  
M E E McCann ◽  
R Park ◽  
M J Hutchinson ◽  
B Owens ◽  
V E Beattie
Keyword(s):  
Nutritive Value ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Feed Ingredients ◽  
Infrared Reflectance Spectroscopy ◽  
Whole Wheat ◽  
Complete Diet

In order to assess the nutritive value of pig diets, performance and digestibility trials must be conducted as there is no accurate alternative to predict nutritive value. However, the use of near infrared reflectance spectroscopy (NIRS) to predict performance from feed ingredients has been shown to have potential. Owens et al (2007) investigated the use of NIRS to predict the performance of broilers offered wheat-based diets, through scanning of whole wheat, and observed that NIRS accurately predicted liveweight gain and gain:feed. The aim of this study was to investigate if NIRS could be used to predict the performance of pigs, through scanning of the complete diet.

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