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Agriculture, Vol. 21 No. 1 SUPPLEMENT, 2015.

Original scientific paper

https://doi.org/10.18047/poljo.21.1.sup.30

USE OF FOURIER TRANSFORM INFRARED (FTIR) SPECTROSCOPY TO PREDICT VFA AND AMMONIA FROM IN VITRO RUMEN FERMENTATION

Franco Tagliapietra ; University of Padova, DAFNAE department, Viale Dell'Università 16, 35020, Legnaro (PD), Italy
Giulia Rossi ; University of Padova, DAFNAE department, Viale Dell'Università 16, 35020, Legnaro (PD), Italy
Stefano Schiavon ; University of Padova, DAFNAE department, Viale Dell'Università 16, 35020, Legnaro (PD), Italy
Alessandro Ferragina ; University of Padova, DAFNAE department, Viale Dell'Università 16, 35020, Legnaro (PD), Italy
Claudio Cipolat-Gotet ; University of Padova, DAFNAE department, Viale Dell'Università 16, 35020, Legnaro (PD), Italy
Giovanni Bittante ; University of Padova, DAFNAE department, Viale Dell'Università 16, 35020, Legnaro (PD), Italy

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Abstract

The aim of the present study was to develop a FTIR method to quantify amounts and proportions of volatile fatty acids (VFA) and ammonia nitrogen (N-NH3) in fermentation fluids collected in vitro using innovative Bayesian models as chemometric technique. A set of 170 fluids, collected before and after 4 in vitro incubations of 8 diets in 5 replication plus 5 blanks, were analysed for VFA, N-NH3 and scanned using the MilcoScan FT2 (Foss Electric, Hillerød, Denmark) in the spectral range between 5000 and 900 cm-1. A Bayes B model was used to calibrate equations for each fermentative trait. The calibration equation predicts well VFA and N-NH3 amounts in calibration and also in validation (R2 VAL ranged from 0.93 to 0.83 for isovaleric and n-butyric acid, respectively). However, the prediction of VFA expressed as proportions of total amount was much less accurate (R2 VAL ranged from 0.81 to 0.52 for iso-valeric and n-butyric acid, respectively). In conclusion, FTIR and Bayesian models can be used as tools to accurately predict VFA amounts in vitro.

Keywords

mid infrared spectroscopy; in vitro rumen fermentation; Bayesian regression model

Hrčak ID:

150662

URI

https://hrcak.srce.hr/150662

Publication date:

2.9.2015.

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