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.

scholarly journals Methods for predicting the energy value of pet foods

2009 ◽  
Vol 38 (spe) ◽  
pp. 1-14 ◽  
Author(s):  
Carlos Castrillo ◽  
Marta Hervera ◽  
Maria Dolores Baucells
Keyword(s):  
Near Infrared ◽  
Metabolizable Energy ◽  
Apparent Digestibility ◽  
Crude Fibre ◽  
Near Infrared Reflectance ◽  
Energy Value ◽  
Close Relationship ◽  
Accuracy Of Prediction

The energy value of foods as well as energy requirements of dogs and cats is currently expressed in terms of metabolizable energy (ME). The determination of ME content of foods requires experimental animals and is too expensive and time consuming to be used routinely. Consequently, different indirect methods have been proposed in order to estimate as reliably an accurately as possible the ME content of pet food. This work analyses the main approaches proposed to date to estimate the ME content of foods for cats and dogs. The former method proposed by the NRC estimates the ME content of pet foods from proximal chemical analysis using the modified Atwater factors, assuming constant apparent digestibility coefficients for each analytical fraction. Modified Atwater factors systematically underestimate the ME content of low-fibre foods whereas they overestimate those that are high in fibre. Recently, different equations have been proposed for dogs and cats based in the estimation of apparent digestibility of energy by the crude fibre content, which improve the accuracy of prediction. In any case, whatever the method of analysis used, differences in energy digestibility related with food processing and fibre digestibility are unlikely to be accounted for. A simple in vitro enzymatic method has been recently proposed based in the close relationship that exist between energy digestibility and organic matter disappearance after two consecutive enzymatic (pepsin-pancreatin) incubation of food sample. Nutrient composition and energy value of pet foods can be also accurately and simultaneously predicted using near infrared reflectance spectroscopy (NIRS).

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.

Sign in / Sign up

Export Citation Format

Share Document