Suitability of faecal near-infrared reflectance spectroscopy (NIRS) predictions for estimating gross calorific value

  1. De la Roza-Delgado, Begoña 1
  2. Modroño, Sagrario 1
  3. Vicente, Fernando 1
  4. Martínez-Fernández, Adela 1
  5. Soldado, Ana 1
  1. 1 SERIDA. Dept. Nutrition, Grasslands and Forages. PO Box 13, 33300 Villaviciosa (Asturias)
Revista:
Spanish journal of agricultural research

ISSN: 1695-971X,  2171-9292

Año de publicación: 2015

Volumen: 13

Número: 1

Tipo: Artículo

DOI: 10.5424/SJAR/2015131-6959 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: Spanish journal of agricultural research

Resumen

A total of 220 faecal pig and poultry samples, collected from different experimental trials were employed with the aim to demonstrate the suitability of Near Infrared Reflectance Spectroscopy (NIRS) technology for estimation of gross calorific value on faeces as output products in energy balances studies. NIR spectra from dried and grounded faeces samples were analyzed using a Foss NIRSystem 6500 instrument, scanning over the wavelength range 400-2500 nm. Validation studies for quantitative analytical models were carried out to estimate the relevance of method performance associated to reference values to obtain an appropriate, accuracy and precision. The results for prediction of gross calorific value (GCV) of NIRS calibrations obtained for individual species showed high correlation coefficients comparing chemical analysis and NIRS predictions, ranged from 0.92 to 0.97 for poultry and pig. For external validation, the ratio between the standard error of cross validation (SECV) and the standard error of prediction (SEP) varied between 0.73 and 0.86 for poultry and pig respectively, indicating a sufficiently precision of calibrations. In addition a global model to estimate GCV in both species was developed and externally validated. It showed correlation coefficients of 0.99 for calibration, 0.98 for cross-validation and 0.97 for external validation. Finally, relative uncertainty was calculated for NIRS developed prediction models with the final value when applying individual NIRS species model of 1.3% and 1.5% for NIRS global prediction. This study suggests that NIRS is a suitable and accurate method for the determination of GCV in faeces, decreasing cost, timeless and for convenient handling of unpleasant samples.

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