THE USE OF PRINCIPAL COMPONENT ANALYSIS IN IDENTIFYING AND INTEGRATING VARIABLES RELATED TO FORAGE QUALITY AND METHANE PRODUCTION
Abstract:This research was
aimed to explore the use of multivariate statistics i.e. principal
componentanalysis (PCA) in identifying and integrating variables related to
forage quality and ruminal methaneproduction, and in classifying forage species
into both characteristics. Seventeen plants were used as adatabase for the
above mentioned purposes. Plant samples were determined for their
chemicalcomposition, cumulative gas production (represents the nutrient
degradation) and methane productionafter 24 hours of fermentation period using
the Hohenheim gas test. The results showed that the PCAcould clearly identify
factors related to forage quality and methane production and separated them
intodifferent principal components (PC). The obtained PC1 was related to methane
production andsubstantially influenced positively by crude protein, NDF, ADF
(positive), total phenols, total tannins,condensed tannins and tannin activity
(negative). On the other hand, the obtained PC2 was related tocumulative gas
production (forage quality) and substantially influenced by crude protein
(positive),NDF, ADF and condensed tannins (negative). Classification and
screening of forages that have highquality and low methane production are
possible using the PCA technique. Rhenum undulatum,Peltiphyllum peltatum and
Rhus typhina were found to have such desired characteristics.
Author: A. Jayanegara, H.P.S.
Makkar, K. Becker
Journal Code: jppeternakangg090011
