Statistical And Biometrical Techniques In Plant Breeding By Jawahar R Sharmapdf New -
The largest section, detailing mating designs such as Diallel, Line x Tester, and North Carolina Designs (NCD I, II, III).
Unlike qualitative characteristics (such as flower color) controlled by one or two genes, economically vital agronomic traits (like crop yield, drought resistance, and biomass) are polygenic. They are regulated by many genes at once and heavily modified by the environment.
By providing structured data-management strategies and concrete biometrical blueprints, the text enables researchers to design high-yielding, climate-resilient crop varieties. Core Structure of Dr. J.R. Sharma’s Treatise
Modern mixed-model equations used in genomic selection directly evolved from the variance component estimations detailed in classical biometrical genetics. The largest section, detailing mating designs such as
The text is organized into across five distinct sections, providing a roadmap for managing breeding data from design to selection.
4. Nature of Gene Action and Variance Components (Chapters 11–23)
Advanced mating schemes used to estimate additive, dominance, and epistatic variances. Multivariate Statistical Tools The largest section
The text organizes 25 detailed chapters into , guiding the reader from basic field arrangements to specialized selection strategies.
Kempthorne, O. (1973). An introduction to genetic statistics. New York: John Wiley & Sons.
Vital layouts for testing massive germplasm collections with limited seed replication. detailing mating designs such as Diallel
Crosses a large group of female lines with a set of male testers. Screens general vs. specific combining ability. Initial screening of vast numbers of germplasm lines.
While the "PDF new" editions often circulate in academic circles, the enduring value of Sharma’s work lies in its structured approach to data interpretation. It transforms raw field observations into actionable genetic insights. For anyone serious about the science of plant breeding, this text is not just a reference but a fundamental guide to the quantitative methods that drive agricultural innovation.
2. Multivariate Analysis and Genetic Divergence (Chapters 6–7)