Quantitative trait locus (QTL) analysis is a statistical method that links two types of information such as phenotypic data (trait measurements) and genotypic data (usually molecular markers). There a number of QTL tools have been developed for gene linkage mapping. Standard Interval Mapping (SIM) or Simple Interval Mapping or Interval Mapping (IM), Haley Knott, Extended Haley Knott and Multiple Imputation (IMP) method when the single-QTL is unlinked and Composite Interval Mapping (CIM) is designed to map the genetic linkage for both linked and unlinked genes in the chromosome. Performance of these methods is measured based on calculated LOD score. The QTLs are considered significant above the threshold LOD score 3.0. For backcross-simulated data, the CIM method performs significantly in detecting QTLs compare to other SIM mapping methods. CIM detected three QTLs in chromosome 1 and 4 whereas the other methods were unable to detect any significant marker positions for simulated data. For a real rice dataset, CIM also showed performance considerably in detecting marker positions compared to other four interval mapping methods. CIM finally detected 12 QTL positions while each of the other four SIM methods detected only six positions.

The field experiment was conducted with 15 Brassica rapa genotypes to estimate the genetic variability and correlation of yield contributing traits. The results indicated that the phenotypic variance for all the characters was considerably higher than the genotypic variance denoting little influence of environmental factors. Low genotypic and phenotypic coefficient of variation showed in plant height (6.36, 8.20) and thousand seed weight (4.58, 11.63). While moderate genotypic and phenotypic coefficient of variation was observed in seed yield (12.68, 18.09), number of branches per plant (13.71, 25.18), number of seeds per siliqua (20.20, 28.86). High genotypic (40.65) and phenotypic coefficient of variation (52.85) was observed for number of siliquae per plant. Low heritability with high genetic advance showed in plant height (0.60%, 8.85), number of branches per plant (0.29%, 0.54) and number of seeds per siliqua (0.48%, 6.75) indicating the possibility of non-additive gene action. High heritability with high genetic advance and high genetic advance in percentage of mean were observed in plant height (0.60%, 8.85, 10.16), number of siliquae per plant (0.59%, 31.93, 64.42), number of seeds per siliqua (0.48%, 6.75, 29.12) and seed yield (0.49%, 260.64, 18.32) which revealed the possibility of predominance of additive gene effects. Number of branches per plant had showed significant positive association with number of siliquae per plant (rg= 0.850**, rp= 0.795**) and number of seeds per siliqua (rg= 0.821**). On the other hand, it had significant negative association with thousand seed weight (rg= -0.912**) and non-significant positive and negative association showed with others characters. The results of the path analysis revealed that plant height (0.818) had the maximum direct effect and maximum negative direct effect was observed for number of seeds per siliqua (-2.558). However, the results suggested that some yield related traits such as plant height and thousand seed weight could be used in breeding program for the development of high yielding short duration B. rapa variety development in Bangladesh. Bangladesh J. Agri. 2022, 47(2): 161-170