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
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
Publication date:
2.9.2015.
Visits: 1.829 *