Glossary Plant Breeding

data. The core collection is then assessed for various qualitative and quantitative
characters, and ultimately, a subset of 10% accessions from the core subset (that is,
1% of the entire collection) that captures most of the useful variation in the crop is
formed. At both stages, standard clustering procedures are used to separate groups of
similar accessions, and various statistical tests are used to assess representatives of the
core and mini core collections. Mini-core collections of chickpea, groundnut, and a
few other crops are available at ICRISAT.
Correlated Response. The change in mean value of a trait brought about through direct
selection for an otherwise associated character. For example, if x and y are associated
with each other, one can predict correlated response in y while selection is directly
practiced for x. Thus CRy =i x .h x .h y .r g .σp y , where, i x is a constant value depending
upon selection intensity for x, h x &h y are square-roots of the heritability of concerned
traits, r g is the genetic correlation between the two traits, and σp y is the phenotypic
standard deviation of y.
Correlation Coefficient. A statistic that measures the precision of relationship between
two variables. It is also called simple correlation coefficient, simple linear correlation
coefficient or product moment correlation coefficient. It is usually designated by r,
which is a ratio of the covariance between the two variables and product of their
standard deviations [r = σxy / σxσy]. It is alternatively defined as geometric mean of
the two regression coefficients. The value of r lies between +1 to –1. The extreme
value indicates the perfect association between the two variables. If the two variables
change in the same direction, the correlation is positive. However, when a + change in
one character is accompanied by a – change in the other, there is negative association.
An r value of zero indicates either (a) absence of association whatsoever between the
two variables, or (b) presence of non-linear association. Sometimes, the numerical
value of genetic correlation coefficient may exceed the extreme limit (± 1). As it is
not directly measured, larger experimental error could inflate the numerical estimate.
The r is a pure number, and is thus independent of units of measurement of the two
variables and a change of origin and scale. The calculated value of r is compared with
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