Linseed Essay

Selection strategy and estimation of interrelationships for improvement of seed yield and other related traits in Linseed (Linum usitatissimum L.)

Satish Paul and Nimit Kumar* Department of Crop Improvement, CSK Himachal Pradesh Krishi Vishvavidyalaya, Palampur-176062, India

*Corresponding Author Email - [e-mail]

ABSTRACT

Thirty five genotypes of linseed (Linum usitatissimum L.) were evaluated to determine the selection strategy and interrelationships of seed yield and yield related traits, during rabi 2013-14. Analysis of variance revealed that the differences among all the genotypes were significant for all the traits under study. Sufficient genetic variability was observed in the present material selected for the study, through

The yield of flax is related to its components as number of plant per unit area, number of capsules per plant and weight of seeds per capsule and so on. The main target of improvement programmes is achieving varieties having high yield and quality. Obtaining high yielding and high quality linseed varieties depend upon selection strategy. Genetic variability is a measure of the tendency of individual genotypes in a population to vary from one another. The measurement of genetic variation and mode of inheritance of quantitative and qualitative traits are of prime importance in planning the breeding programme efficiently and effectively (Shah et al., 2015). Selection for yield has many complexities because it is end product of various yield components, which are naturally polygenic inherited and maximally influenced by environment. So due to less impression of direct selection for yield, more efforts should be over indirect selection for yield components (changing yield through yield components). Proper understanding of association of different traits, provide more reliable selection criterion to achieve a high seed yield (Akbar et al., 2001). This selection criterion takes into account the information on interrelationships among agronomic characters, their relationship with seed yield as well as their direct influence on seed yield. However, simple correlation coefficients and ANOVA tables (even in multiple-year trials) may not evolve satisfactory results in uncovering the real interrelationships among the traits. Nevertheless, selection for yield via highly correlated characters becomes easy if the contribution of different characters to yield is quantified using path coefficient analysis (Dewey and Lu, 1959). In fact, practically selection criteria will contribute to selection based on direct effects (Yucel, 2004; Copur and Oglakci,