Early elimination of poor crosses based on an objective criterion allows increased allocation of resources only to a few promising crosses for identifying superior recombinant inbred lines (RILs) for use as pure-line cultivars in self-pollinated crops. Early generation (F2:3) prediction of frequency of superior RILs that could be derived from advanced generations of crosses is one such criterion. We predicted the frequency of transgressive RILs from two horse gram crosses (namely HPKM 320 × CRIDA18-R and IC 361290 × Palem 1) for primary branches per plant, pods per plant, pod weight per plant and grain weight per plant based on mid parental value, additive genetic effects and additive genetic variance estimated from trait means of parents, and their F2 and F2:3 generations. The predicted frequency of RILs that transgressed better parent/two checks varied with the cross and the trait within a cross. The frequencies of transgressive RILs predicted from IC 361290 × Palem 1 were higher than those predicted from HPKM 320 × CRIDA 18-R for three of the four traits. As expected, the minimum population size required to recover the transgressive RILs predicted from IC 361290 × Palem 1 was relatively smaller than that from IC 361290 × Palem 1. Increased allocation of resources for handling segregating populations derived from IC 361290 × Palem 1 is expected to result in superior RILs for use as cultivars. We believe that the objective criterion used in our study is handy in identifying superior RILs in early segregating populations derived from a few promising crosses.

The inheritance of total ridge count (TRC) was studied in 967 individuals from the families of 111 pairs of MZ twins. The sample included data on 47 male half-sibships with 227 offspring and 64 female half-sibships with 306 offspring. The males in this sample had a mean ridge count of 135 ± 2 and the females a mean ridge count of 124 ± 2. The distribution of scores for females showed evidence for significant skewness. For this reason, prior to the analysis, the data were corrected for sex and adjusted to normality using a power transformation. Nested analyses of variance were performed on the ridge counts from male and female half-sibships separately to derive estimates of among, between, and within-variance components. These estimates were then used in a nonlinear least squares program to estimate genetic and environmental parameters and to determine the goodness of fit of various models. A model which included additive genetic and dominance effects could not be rejected (P = 0.67) but did not fit the data as well as a simple additive genetic-random environmental model (P = 0.81). The addition of maternal effects to the latter model also provided a satisfactory fit (P = 0.68). However, there was no improvement in the goodness of fit over the simple model, and the estimated magnitude of the maternal effect was not significantly different from zero.