Quality evaluation of regional forage resources by means of near infrared reflectance spectroscopy
Quality parameters of grassland and pasture samples collected during a three-year period at two environmentally and<br />geographically different areas were analysed by Near Infrared Reflectance Spectroscopy (NIRS). Chemical analysis for<br />crude protein (CP), crude fibre (CF), neutral...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2010-01-01
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| Series: | Italian Journal of Animal Science |
| Subjects: | |
| Online Access: | http://www.aspajournal.it/index.php/ijas/article/view/212 |
| Summary: | Quality parameters of grassland and pasture samples collected during a three-year period at two environmentally and<br />geographically different areas were analysed by Near Infrared Reflectance Spectroscopy (NIRS). Chemical analysis for<br />crude protein (CP), crude fibre (CF), neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL)<br />and crude ash (ASH) carried out on two-thirds of the samples were used in calibration processes. The remaining onethird<br />of the data was used to validate the best calibrations obtained. Samples selection is discussed. Different math pretreatments<br />(derivative, gap, primary smoothing and secondary smoothing), light scattering correction methods and calibration<br />algorithms were tested to achieve the better predictive performances. We obtained the best results using different<br />regression algorithms to correlate spectral information to chemical data. For CP (R2 = 0.94, SEP=1.3), NDF (R2 =<br />0.95, SEP = 2.14) and ADF (R2 = 0.92, SEP=2.06) Multiple Linear Regression (MLR) models fit chemical data better than<br />Mean Partial Least Square (MPLS) regression. A molecular basis explanation of wavelengths selected was carried out.<br />MPLS models worked well for CF (R2 = 0.93, SEP=1.57), and ASH (R2 = 0.95, SEP=1.17) while poor calibrations were<br />obtained for ADL using both algorithms. To confirm the reliability of the models developed, uncertainties of predictions<br />were compared with findings on nutritional variations and animal performances. |
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| ISSN: | 1594-4077 1828-051X |