Semester4

Brief description of aims and content

 The module gives deep insights into quantitative and population genetics, reproductive systems of crops, principles and tools of plant breeding, breeding self, cross and vegetatively propagated crops and development of new crop varieties as well as molecular markers. It is designed to provide learners with knowledge in gene frequencies, population dynamics mating designs, selection methods, molecular markers and quantitative trait loci. The module focuses on lectures, self-studies, problem sets, field and laboratory exercises, and presentations. The module focuses on lectures, self-studies, problem sets, field and laboratory exercises, and presentations.

Learning Outcomes

A.     Knowledge and understanding

Having successfully completed the module, learners will demonstrate:

1. Understanding of the theories and core principles of quantitative and population genetics, and molecular markers;
2. Deep understanding of major principles of quantitative genetics such as selection theory, mating designs and Quantitative Trait Loci (QTL);  
3. Understanding of  Hardy-Weinberg principles, gene frequencies and population dynamics
4. Deep understanding of molecular markers and their use.

1. Reproductive systems of major crops;
2. Major principles and tools of plant breeding;
3. Differences in breeding self, cross and vegetatively propagated crops;
4. Crop variety development procedures

1. B.     Cognitive/Intellectual skills/Application of Knowledge

Having successfully completed the module, learners will apply:

1. The principles of quantitative, population and molecular markers to solve problems related to population structures and changes;
2. Acquired knowledge in predicting genetic outcomes and performing analysis of genetic data.
3. Plan and carry out a project of research, investigation and development
4. Demonstrate originality in the application of knowledge
5. Optimize different strategies to a specific crop in order to breed for superior genotypes with specified characteristics
6. Plan and carry out a project of research, investigation or development
7. Demonstrate originality in the application of knowledge

1. C.     Communication/ICT/Numeracy/Analytic Techniques/Practical Skills

Having successfully completed the module, learners should be able to:

1. To present and discuss the core principles of quantitative, population and molecular markers;
2. Use appropriate methods to track allele frequencies through generations;
3. Use correct techniques to predict and produce new genotypes; construct genetic maps.
4. Evaluate a wide range of numerical and graphical information
5. Identify genetically variable source of germplasm
6. Design crossings following the reproduction system of crops
7. Use of appropriate methods to conduct selection procedures to identify superior genotypes
8. Use correct techniques to stabilize superior genotypes and develop them into commercial cultivars

1. D.    Generic cognitive skills

Having successfully completed the module, students must be able to demonstrate the following skills:

1. Deal with complex issues and make informed judgement in the absence of complete data,

2. Analyse, evaluate and synthesise issues, in complex which are at the forefront of knowledge,

3. Demonstrate original responses to problems and issues

E. Autonomy, responsibility and working with others

1. Exercise initiative and personal responsibility

2. Demonstrate self-direction and originality in tackling and solving problems,

3. Act autonomously in planning and implementing decisions at a professional level,

4. Demonstrate the skills of life-long learning in his/her own discipline,

5. Demonstrate the skills of leadership and the management of resources

Indicative Content

• Quantitative traits
• Hardy-Weinberg      Equilibrium;
• Covariance      between relatives;
• Mating      designs and hereditary variances;
• Selection      theory;
• Quantitative      traits loci;
• DNA isolation
• Restriction enzymes
• Polymerase Chain Reaction
• Molecular markers

• Molecular assisted selection
• Plant reproductive systems
• Tools in plant breeding
• Genetic resources and Centers of origin
• Plant breeding methods for self pollinated crops
• Plant breeding methods for cross pollinated crops
• Plant breeding methods for asexually propagated crops
• Double haploid techniques of plant breeding
• Development of hybrid varieties
• Evaluation of new varieties, variety description, release, maintenance and commercialization
• Genetic engineering in crops and genetically modified crops
• Defining goals in plant breeding
• Breeding plans

Brief description of aims and content

This module presents an in depth knowledge of statistics, biometry and research methodology The module is designed to introduce learners to the fields of statistical research in Agricultural Sciences. Concepts on ethics and philosophy of science, and scientific writing skills will be introduced. Advanced statistical methods, experimental design, data collection, data exploration and analyses will form part of the modules.

Learning Outcomes

1. A.     Knowledge and Understanding
2. Having successfully completed the module, learners should be able to demonstrate a thorough understanding of: 

• Ethical considerations in research
• Philosophy of science
• How to choose and develop proper research projects

1. Learners should demonstrate a comprehensive understanding of relevant techniques and approaches applicable to the research
2. Learners should demonstrate a clear understanding of how established techniques of research and enquiry are used in the discipline
3. How to formulate hypotheses and to design tests of hypotheses
4. Experimental design
5. Data collection
6. Data exploration and handling of data
7. Interpretation and reporting of results

1. B.     Cognitive/Intellectual skills/Application of Knowledge

Having successfully completed the module, learners should be able to:

• Use a significant range of the principle skills, techniques, practices appropriate for the research in their discipline
• Apply a range of standards and specialised research techniques to execute their research project
• Demonstrate originality in the application of knowledge
• Use a significant range of the principle skills, techniques, practices and/or materials, including some at the forefront of developments, associated with their discipline
• Apply a range of standard and specialised research techniques of enquiry
• Plan and carry out a research or development project.
• Demonstrate originality in the application of knowledge

1. C.     Generic cognitive skills

Having successfully completed the module, students must be able to demonstrate the following skills:

1. Deal with complex issues and make informed judgement in the absence of complete data,

2. Analyse, evaluate and synthesise issues, in complex which are at the forefront of knowledge,

3. Demonstrate original responses to problems and issues

1. D.    Communication/ICT/Numeracy/Analytic Techniques/Practical Skills

Having successfully completed the course, learners should be able to:

• Communicate their research to wide range of audience with some levels of expertise
• Communicate with peers, more senior colleagues and specialists
• Use a wide range of appropriate software for presentation/communication to the audience
• Evaluate a wide range of numerical and graphical information
• Synthesise and critically analysing the content of a scientific paper
• Use an appropriate experimental design and sampling schedule.
• Use an appropriate statistical method to analyse data, evaluate and report the results.
• Communicate research findings to a range of audience using appropriate statistical methods
• Correctly interpret and numerical and graphical information

1. E.     Autonomy, responsibility and working with others

1. Exercise initiative and personal responsibility

2. Demonstrate self-direction and originality in tackling and solving problems,

3. Act autonomously in planning and implementing decisions at a professional level,

4. Demonstrate the skills of life-long learning in his/her own discipline,

5. Demonstrate the skills of leadership and the management of resources

Indicative Content

• Ethics in research
• Philosophy of science
• Research methods
• The scientific writing process
• Preparation of scientific presentations
• Presentation and communication of scientific research results
• Principles of experimental design and census techniques
• Design of field experiments – characteristics, merits and limitations
• Statistical tools – tests and report of results.
• Data exploration
• Distributions - (Normal vs. other and data transformation)
• Regression analysis and analysis of variance
• Analysis of categorical data
• Missing data
• Principles of experimentation
• Generalized Linear Models
•  Mixed Linear Models
• Restricted Maximum Livelihood (REML)
• Multivariate analysis

- Principal Components Analysis (PCA)

- Discriminant analysis

- Cluster analysis

• Genotype × environment Interaction Analysis