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• Inactive for Year: 2026/27

• Module Leader(s): Dr Ankush Prashar

• Owning School: Natural and Environmental Sciences
• Teaching Location: Â鶹´«Ã½ City Campus

Semesters

Your programme is made up of credits, the total differs on programme to programme.

Aims

This module introduces students to the concepts, tools, and data analytics that underpin modern precision breeding for crops. It aims to develop a foundation in quantitative genetics, genotype-phenotype-environment relationships, and the use of genomic, phenotypic, and environmental data to support selection decisions. Students will explore how high-throughput phenotyping, genomic prediction, and statistical genetics methods can be combined to accelerate breeding cycles and improve resilience under climate and multi-stress conditions. The module emphasises practical skills in handling breeding trial data, fitting genetic models, and interpreting prediction outputs for selection and advancement decisions. Students will work with real or realistic datasets (e.g. genotypes, phenotypes, environments) to learn how to design, analyse, and critique breeding schemes. Through hands-on computer practicals, they will gain experience in implementing genomic prediction, estimating heritability and genetic correlations, and exploring G×E and plasticity. The module fosters students’ ability to connect theory with application by asking them to translate model outputs into breeding recommendations and product profiles. As part of a data science degree, it demonstrates how statistical learning, modelling, and data integration directly support innovation in plant breeding and genetic improvement.

Outline Of Syllabus

• Foundations of Quantitative and Population Genetics
• Breeding Trial Design and Data Structures
• High-Throughput Phenotyping in Breeding
• Genomic Data and Markers
• Genomic Prediction and Selection
• G×E, Plasticity and Climate Resilience
• Practical Computing Sessions: Analysis of breeding datasets (Case Studies)

Teaching Methods

Teaching Activities

Teaching Rationale And Relationship

N/A

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment

Assessment Rationale And Relationship

The assessment pair (50-50) is designed to develop and test students’ ability to both critically appraise existing precision breeding work and to design their own data-informed breeding strategies.

The short methods critique (presentation, 50%) trains students to dissect and evaluate published precision breeding studies, focusing on data types, experimental design, statistical and genomic methods, and how well these support the stated breeding objectives. By requiring them to communicate this evaluation as a presentation, it strengthens skills in scientific argumentation, synthesis, and oral communication targeted at a professional breeding or research audience.

The breeding strategy design brief (50%) then asks students to move from critique to creation, using the concepts and methods encountered in the literature to design a realistic, coherent breeding programme for a defined target trait and context. It assesses their ability to specify appropriate crossing and testing schemes, choose relevant data streams (genomic, phenotypic, environmental), and justify the use of quantitative genetics and data science tools for selection and advancement. Together, the two assessments are tightly linked: insights from the critique inform better design choices, while the strategy brief demonstrates that students can apply what they have learned to real-world decision-making in precision breeding

Reading Lists

Timetable

• Timetable Website: