THE USE OF PRIN IPAL COMPONENT ANALYSIS IN IDENTIFYING AND INTEGRATING VARIABLES RELATED TO FORAGE QUALITY AND METHANE PRODU TION

Abstract

This research was aimed to explore the use of multivariate statistics i.e.principal component analysis (PCA)in identifying and integrating variables related to forage quality and ruminal methane production,and in classifying forage species into both characteristics.Seventeen plants were used as a database for the above mentioned purposes.Plant samples were determined for their chemical composition cumulative gas production (represents the nutrient degradation)and methane production after 24 hours of fermentation period using the Hohenheim gas test.The results showed that the PCA could clearly identify factors related to forage quality and methane production and separated them into different principal components (PC).The obtained PC1 was related to methane production and substantially 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 to cumulative gas production (forage quality)and substantially influenced by crude protein (positive) NDF ADF and condensed tannins (negative).Classification and screening of forages that have high quality and low methane production are possible using the PCA technique.Rhenum undulatum Peltiphyllum peltatum and Rhus typhina were found to have such desired characteristics. Key words:PCA,multivariate,gas,quality,methane,forage