layout of experiment genetics and plant breeding

Experiment

1. CCS Haryana Agricultural University, Hisar Presented to: Dr. Bharat Taindu Jain (Asst. Prof. GPB) Presented by: Pankaj B2019A35BVI) GP 201 Experimental Design and Analysis of Variance

2. Meaning of the term “Experiment” Experiment: Planned research conducted for certain period to obtain new facts or to confirm or refuse the results of previous study

3. Experimental Design The term experimental design refers to a plan for assigning experimental units to treatment conditions in a systematic way so that the results can give meaningful output. It is not just describing the natural event through observation and measurement, but it is more of treating the observation and measurement in a planned way to illuminate the effect of any change in conditions. The importance of experimental design also stems from the quest for inference about effect of causes or relationships as opposed to simply description. Researchers are rarely satisfied to simply describe the events they observe. They want to make inferences about what produced, contributed to, or caused events.

4. Important terminology Treatment: A condition (or set conditions) that is imposed on a group of elements (subjects) by the experimenter is called treatment Variable: Any concept, or thing, or event that varies or can be made to vary, and is related to the research can be called a variable. Dependent variable: The variable that is changed by the change of another variable is called dependent variable Independent variable: The variable that is not changed due to change in another variable rather when it changes also causes change in another variable Randomisation: The procedure in which elements (subjects) are assigned to different groups at random (without any bias)

5. Replication: Repetition of experimental units in a treatment which is minimise the experimental error intended to is called replication. Null hypothesis: The assumption that there is no effect of independent variable on the dependent one. Factor: Factors can be classified as either controllable or uncontrollable variables. For example, in cake making the controllable factors are the ingredients for the cake and the oven that the cake is baked in. Levels: or settings of each factor. Examples include the oven temperature setting and the amounts of sugar, flour, and eggs. Response: or output of the experiment. In the case of cake baking, the taste, consistency, and appearance of the cake are measurable outcomes potentially influenced by the factors and their respective levels.

6. • The basic objective of plant breeding is the ultimate crop improvement. It results in development of high yielding varieties hybrids etc., over the existing cultivars and so on. The performance of the new varieties are confirmed from the results obtained from the field experiments. To be explained scientifically the field experiments are laid out following certain rules and the data thus collected are analyzed statistically. The steps involved in this process are explained here under. Laying out of Field Experiments

7. Any designing of experiments involves three major steps. Selection of experimental units 1. The objects on which the treatments are applied is known as experimental units. Eg. Plots in the field, plant, etc., Fixing of treatments 2. The comparison are known as treatments objects of Eg. Varieties, spacing etc.,

8. 3.Arrangement of treatments in the experimental Units. It comprises of three basic principles of design

9. Three principles of experimental designs repetition of treatments Replication: Randomization: unbiased allocation of treatments to the experimental units. 3. Local control: minimizing the effect of heterogeneity of the experimental units. The objective of replication, randomization and local control is to minimize the Experimental Error (EE). EE is nothing but differences in the responses from the experimental unit to experimental unit under similar environments. Apart from these, EE can be reduced further by proper selection of the experimental units and choosing of most appropriate experimental design for a given number of treatment.

10. (i) Randomization: The principle of randomization involves the allocation of treatment to experimental units at random to avoid any bias in the experiment resulting from the influence of some extraneous unknown factor that may affect the experiment. In the development of analysis of variance, we assume that the errors are random and independent. In turn, the observations also become random. The principle of randomization ensures this. The random assignment of experimental units to treatments results in the following outcomes. It eliminates systematic bias. It is needed to obtain a representative sample from the population. It helps in distributing the unknown variation due to confounded variables throughout the experiment and breaks the confounding influence

11. ( ii) Replication: In the replication principle, any treatment is repeated a number of times to obtain a valid and more reliable estimate than which is possible with one observation only. Replication provides an efficient way of increasing the precision of an experiment. The precision increases with the increase in the number of observations. Replication provides more observations when the same treatment is used, so it increases precision.

12. (iii) Local control (error control) The replication is used with local control to reduce the experimental error. For example, if the experimental units are divided into different groups such that they are homogeneous within the blocks, then the variation among the blocks is eliminated and ideally, the error component will contain the variation due to the treatments only. This will, in turn, increase the efficiency.

13. • Types of basic experimental designs Completely Randomized Design (CRD) Randomized Block Design (RBD) Latin Square Design (LSD) Among these, RBD is the widely used design

14. Completely Randomised Design What is CRD? • It is the simplest type of the basic designs, may be defined as a design in which the treatments are assigned to experimental units completely at random, that is the randomization is done without any restrictions. The design is completely flexible, i.e., any number of treatments and any number of units per treatment may be used. A completely randomized design is considered to be most useful in situations where (i) the experimental units are homogeneous , (ii) the experiments are relatively small and (iii) the number of treatments is relatively small.

15. Usage of CRD Simplest design to use. Design can be used when experimental units are essentially homogeneous. Because of the homogeneity requirement, it may be difficult to use this design for field experiments. The CRD is best suited for experiments with a small number of treatments. Randomization Procedure - Treatments are assigned to experimental units completely at random. - Every experimental unit has the same probability of receiving any treatment. - Randomization is performed using a random number table, computer, program, etc.

16. Advantages of a CRD Very flexible design (i.e. number of treatments and replicates is only limited by the available number of experimental units). Statistical analysis is simple compared to other designs. Loss of information due to missing data is small compared to other designs due to the larger number of degrees of freedom for the error source of variation. Disadvantages If experimental units are not homogeneous and you fail to minimize this variation using blocking, there may be a loss of precision. Usually the least efficient design unless experimental units are homogeneous. Not suited for a large number of treatments.

17. AOVA Table is essentially as follows:

18. If a large number of treatments are to be compared, then a large number of experimental units are required. This will increase the variation among the responses and CRD may not be appropriate to use. In such a case when the experimental material is not homogeneous and there are v treatments to be compared. A randomized block design is a restricted randomization design in which the experimental units are first sorted into homogeneous groups, called blocks , and the treatments are then assigned at random within the blocks . The randomized block design is an improvement over the completely randomized design. Both designs use randomization to guard against confounding effect or error. But only the randomized block design more accurately controls for gender. What is RBD

19. The experimental material (field) is divided first into blocks consisting of homogenous (uniform) experimental units. Each block is divided into number of treatments equal to the total number of treatments. Randomization should be taken within each block and the treatments are applied following the random number table. Collection and analysis of data: After the collection of data from the individual experimental unit (treatments) ANOVA (Analysis of Variance) table is formed. Laying Out of RBD

20. Example: Suppose there are 7 treatments denoted as 1 2 7 T ,T ,..,T corresponding to 7 levels of a factor to be included in 4 blocks. So one possible layout of the assignment of 7 treatments to 4 different blocks in an RBD is as follows

21. ANOVA

22. The significance of the ANOVA table is that it indicates the sources of variation exhibited by the treatments, the magnitude of variation derived from different sources and their worthiness (significant/ non significant).

23. Computation of Critical Difference (CD) Critical Difference is the difference between the treatment means, which places the treatments statistically as well as significantly apart. Otherwise if the difference of two treatments mean is less than CD it can be concluded both the treatments are on par.

24. SYMBOL OF TRUST