Influence of Temperature on the Predictive Ability of near Infrared Spectroscopy Models

2004 ◽  
Vol 12 (2) ◽  
pp. 121-126 ◽  
Author(s):  
Marcelo Blanco ◽  
Dámarih Valdés
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Predictive Ability ◽  
Influence Of Temperature ◽  
Influence Of Temperature On

Prediction of diet quality for sheep from faecal characteristics: comparison of near-infrared spectroscopy and conventional chemistry predictive models

2015 ◽  
Vol 55 (1) ◽  
pp. 1 ◽  
Author(s):  
D. G. Kneebone ◽  
G. McL. Dryden
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Predictive Ability ◽  
Validation Dataset ◽  
Least Squares Regression ◽  
Prediction Equations ◽  
Faecal Excretion ◽  
Excretion Rates

This study evaluated the ability of equations developed from the analysis of faecal material by conventional chemistry (F.CHEM), and by near-infrared spectroscopy (F.NIRS), to predict intake and digestibility of forages fed with or without supplements. In vivo datasets were obtained using 30 sheep and 25 diets to provide 124 diet–faecal pairs, with each sheep fed four or five of the diets. The diets were five forages fed alone or with urea, molasses, cottonseed meal or sorghum grain supplements. Ninety-nine diet–faecal pairs were selected at random, but ensuring that all diets were represented and both the F.CHEM and F.NIRS prediction equations were developed from this dataset. The remaining 25 diet–faecal pairs were used as a validation dataset. Regressions for F.CHEM were developed by stepwise regression, and F.NIRS prediction equations were developed by partial least-squares regression. Prediction equations based solely on faecal analyte concentrations (F.CHEMc) had poor predictive ability, and models incorporating faecal constituent excretion rates (F.CHEMe) were the best at predicting feed constituent intakes. These models had slightly lower standard errors of prediction (SEP) for organic matter (OM) intake and digestible OM intake compared with the F.NIRS models that did not include faecal excretion rates. However, F.NIRS models had lower SEP for protein intake and OM digestibility. Good agreement between the F.CHEMe and F.NIRS methods was evident (according to the 95% limits-of-agreement test), and both predicted the reference values precisely and with small bias. Equations derived from a dataset that included representatives of all diets used in the experiment gave much better prediction of diet characteristics than those developed from a dataset constructed entirely at random. Equations for F.NIRS developed in this way successfully predicted the characteristics of diets that included forages fed alone and with the type of supplements used in tropical Australia.

Estimation of Pinus radiata D. Don tracheid morphological characteristics by near infrared spectroscopy

Holzforschung ◽  
2004 ◽  
Vol 58 (1) ◽  
pp. 66-73 ◽  
Author(s):  
L. R. Schimleck ◽  
R. Evans
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Wall Thickness ◽  
Pinus Radiata ◽  
Near Infrared ◽  
Morphological Characteristics ◽  
Predictive Ability ◽  
Increment Core ◽  
Calibration Samples ◽  
Strong Agreement

Abstract Eight Pinus radiata D. Don increment core samples were selected from a total of 32 cores for the development of calibrations for several tracheid morphological characteristics: coarseness, perimeter, radial and tangential diameter and wall thickness. Near infrared (NIR) spectra, obtained from the radial-longitudinal face of each core in 10-mm sections from pith to bark, were used to develop the calibrations. Calibrations for coarseness and wall thickness were excellent, with coefficients of determination (R2) of 0.91 and 0.89, respectively. Calibrations for the remaining characteristics were weaker (R2 ranged from 0.65 to 0.69). To test the predictive ability of the calibrations, two intact P. radiata increment cores (core A and B) were selected from the same set as the calibration samples. NIR-predicted tracheid coarseness and wall thickness were in strong agreement with measured (SilviScan-determined) values. Radial patterns of variation (NIR-predicted, measured) closely followed each other for both cores, but coarseness and wall thickness were underestimated for core B. Tracheid tangential perimeter was well predicted with R2 of 0.69 (core A) and 0.79 (core B). Relationships for the remaining characteristics were weak. Collection of NIR spectra in smaller increments, to capture more of the variation, may improve calibration.

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