To be useful to breeders, classification of genotypes based on cluster
analysis must provide meaningful groupings of the genotypes clustered
. We evaluated a classification of 148 U.S. maize [Zea mays L.] inbred
s resulting from cluster analysis based on restriction fragment length
polymorphisms (RFLPs) to determine if it represented the true associa
tions among the lines. Testing was aimed at the products of the two st
eps in cluster analysis: the proximity matrix containing estimates of
relationship computed from the data and the phenogram displaying group
s in the form of a tree diagram. The proximity matrix and a matrix of
pedigree relationships were compared by the Hubert Gamma statistic. Di
ssimilarities indicated in the phenogram were correlated with those de
fined in the proximity matrix. The grouping displayed in the phenogram
was compared to that exhibited in phenograms resulting from three add
itional cluster analyses generated by different methods for computing
proximities. These groupings were then compared to the expected groupi
ng based on pedigree information. The patterns present in the proximit
y matrix were substantiated by pedigree information. Based on agreemen
t between the phenogram and the proximity matrix, the phenogram depict
ed estimates of genetic relationship accurately. Inbreds were grouped
similarly in the four classifications and the level of correspondence
of inbred group assignments to the expected grouping based on availabl
e pedigree information was similar across classifications, suggesting
that a natural grouping of the Lines exists and was generally reflecte
d in each classification. Therefore, the classification was judged to
reasonably represent the true associations among the 148 maize inbreds
. In addition, the advantages of a method to compute proximities by a
formula proposed by Nei and Li were noted.