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Quality evaluation of regional forage resources by means of near infrared reflectance spectroscopy

Author(s): Pier Paolo Danieli | Paolo Carlini | Umberto Bernabucci | Bruno Ronchi

Journal: Italian Journal of Animal Science
ISSN 1594-4077

Volume: 3;
Issue: 4;
Start page: 363;
Date: 2010;
Original page

Keywords: NIRS | Grasslands | Pastures | Forages quality

Quality parameters of grassland and pasture samples collected during a three-year period at two environmentally andgeographically different areas were analysed by Near Infrared Reflectance Spectroscopy (NIRS). Chemical analysis forcrude protein (CP), crude fibre (CF), neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL)and crude ash (ASH) carried out on two-thirds of the samples were used in calibration processes. The remaining onethirdof the data was used to validate the best calibrations obtained. Samples selection is discussed. Different math pretreatments(derivative, gap, primary smoothing and secondary smoothing), light scattering correction methods and calibrationalgorithms were tested to achieve the better predictive performances. We obtained the best results using differentregression algorithms to correlate spectral information to chemical data. For CP (R2 = 0.94, SEP=1.3), NDF (R2 =0.95, SEP = 2.14) and ADF (R2 = 0.92, SEP=2.06) Multiple Linear Regression (MLR) models fit chemical data better thanMean Partial Least Square (MPLS) regression. A molecular basis explanation of wavelengths selected was carried out.MPLS models worked well for CF (R2 = 0.93, SEP=1.57), and ASH (R2 = 0.95, SEP=1.17) while poor calibrations wereobtained for ADL using both algorithms. To confirm the reliability of the models developed, uncertainties of predictionswere compared with findings on nutritional variations and animal performances.
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