A gas chro
matography鈥搈ass spectro
metry approach was e
mployed to evaluate the use of
metabolite patterns to differentiate fruit fro
m six co
mmercially grown apple cultivars harvested in 2008. Principal co
mponent analysis (PCA) of apple fruit peel and flesh data indicated that individual cultivar replicates clustered together and were separated fro
m all other cultivar sa
mples. An independent
metabolo
mics investigation with fruit harvested in 2003 confir
med the separate clustering of fruit fro
m different cultivars. Further evidence for cultivar separation was obtained using a hierarchical clustering analysis. An evaluation of PCA co
mponent loadings revealed specific
metabolite classes that contributed the
most to each principal co
mponent, whereas a correlation analysis de
monstrated that specific
metabolites correlate directly with quality traits such as antioxidant activity, total phenolics, and total anthocyanins, which are i
mportant para
meters in the selection of breeding ger
mplas
m. These data sets lay the foundation for elucidating the
metabolic basis of co
mmercially i
mportant fruit quality traits.
Keywords:
apple; correlation analysis; hierarchical clustering analysis; metabolomics&qsSearchArea=searchText">metabolomics; mponent+analysis&qsSearchArea=searchText">principal component analysis; quality trait