Case Study: Directed mass selection for leafhopper, alfalfa aphid and diseases in alfalfa (Hanson et al., 1972)
5.4.8 Breeding trials design
The basics of trials design for field experi- ments have been dealt with in Chapter 3.
Additional trial designs that are particu- larly relevant to plant breeding trials are included here. They are collectively referred to as incomplete block designs.
In plant breeding trials large numbers of breeding lines need to be screened and
compared for yield, quality and resistance.
Such large numbers of treatments with complete replication can extend over very large areas. One option in trials design would be to have controls randomly scat- tered throughout the experiment so that each of the treatments could be compared with the controls and hence with one another. With such a design the accuracy of comparison with the control is increased at the expense of other comparisons, hence use of random controls is usually consid- ered inefficient (John and Quenoulille, 1977). An alternative is the type of design in which comparisons between pairs of treatments are all made equally accurate.
These designs are the incomplete block designs. This subject is dealt with only briefly here and readers requiring more information should consult Cochran and Cox (1957), John (1971) and John and Quenoulille (1977).
Incomplete block designs may require more planning than randomized blocks but are no more difficult as far as experimental
Fig. 5.13.The response to recurring selection for resistance to leafhopper yellowing (expressed as a percentage of yellowing on a check cultivar (Cherokee)), for germplasm pools A (d) and B (s) (after Hanson et al., 1972).
operations are concerned. Most of the incomplete block designs cover the range from 6 to 200 treatments and work has indicated that an average gain in accuracy of about 25% over randomized blocks can be obtained (Cochran and Cox, 1957).
However, the number of treatments for which a substantial increase in accuracy is obtained needs to be determined by experi- ence. It should be noted though that incomplete block designs are most useful when there are few or no missing data.
Three of the more simple incomplete block designs are depicted in Fig 5.15: the balanced, the incomplete, Latin Square and a partially balanced incomplete block design arranged in a Latin Square forma- tion (Cochran and Cox, 1957). The bal- anced design shows seven treatments arranged in blocks of three units with every pair of treatments occurring once within some block. The incomplete Latin Square was designed for use in greenhouse experi- ments and is named after the man who developed it, Fouden, and hence the name Fouden squares. The example shown is a balanced design for seven treatments, so
that every treatment appears in each of the three rows and every pair of treatments appear together once in the same column.
The example in Fig. 5.15b is of a partially balanced incomplete block design with six treatments in blocks of four. Each row forms a complete replication but some treatments occur less often than others in the same block, e.g. treatments 1 and 2 occur twice in the same block (1) and (4) whereas treatments 1 and 4 occur four times in the same block (1), (3), (4) and (6).
This design permits greater flexibility over choice of replicates for particular treat- ments but their statistical analysis is more complicated and some pairs are more pre- cisely compared than others. Visual assess- ment of plants using scales or indices are the commonest form of resistance evalua- tion. Bellotti and Kawano (1980) recom- mended the use of two selection scales, the first to evaluate a large number of varieties when the major objective is to reject sus- ceptible material and the second allows a more accurate definition of the reaction of the selected plants (Table 5.4). The second scale (Scale B) in Table 5.4 uses three dis- Fig. 5.14.Mean changes in alfalfa yield over 14 generations of selection in the field and the laboratory, for germplasm pools A (d) and B (s) (after Hanson et al., 1972).
tinct damage symptoms, leaf speckling, leaf deformation and bud reduction, which combined define the damage symptoms of Mononychellus tanajoa on cassava and permit small differences in damage to be detected. The development and use of scales that permit a comprehensive evalua- tion of damage or resistance should be used where possible. Although the need for subjective assessment in large scale screen- ing is not denied, there is a need to ensure that the evaluation is based on actual dis- cernible differences and scales that incor- porate a number of important indicator characters that will provide a safety net during the selection process.
The value of the subjective assessment made by an assessor will depend on the
person’s perception of the crop and the pest infestation which, to a large extent, will be determined by an assessor’s experi- ence. The ability of assessors to discrimi- nate between plant characters can also be improved through various physical means including the use of keys and regular inclu- sion of check plant material. Breeders must then be aware of two things in relation to the screening and selection techniques:
firstly, the efficiency of the visual assess- ments for particular crop characters; and secondly, the variation in this efficiency between individual assessors. The easiest method of assessing these efficiencies is to compare a visual score assigned to crop characters with the actual quantitative esti- mate of the same characters. Alternatively, (a)
Block
Rows
1 1 2 4 3 3 4 6 5 1 5 6 7 1 3 7 2 2 3 5 4 4 5 7 6 2 6 7
1 2 3 4 5 6 1 1 2 3 4 5 6 2 4 5 6 1 2 3 3 2 3 1 5 6 4 4 5 6 4 2 3 1 (b)
Columns (Blocks)
Rows
(c)
Columns (Blocks) 1 2 3 4 5 6 7 1 1 2 3 4 5 6 7 2 2 3 4 5 6 7 1 3 4 5 6 7 1 2 3
Fig. 5.15. Examples of three simple incomplete block designs: (a) balanced design for seven treatments in blocks of three units; (b) a partially balanced incomplete block design arranged in a Latin Square; (c) balanced design for seven treatments in an incomplete Latin Square (after Cochran and Cox, 1957).
visual scores can be compared with actual estimates between plants selected by an assessor and those randomly selected over the same area. Work with barley comparing scores of yield with actual yield has resulted in conflicting opinions. McKenzie and Lambert (1961) concluded that the use of visual scores for yield was unsatisfactory for evaluations, while Ismail and Valentine (1983) concluded that in the early genera- tions visual selection using scores should be recognized as a basic tool of breeding.
Briggs and Shebeski (1970) working with
spring wheat and testing the visual selec- tion efficiency of 14 assessors, using com- parisons between random and assessor selections, found that assessors had a gen- eral ability to improve yield by selection, but that individual selectors demonstrated a rather limited ability to identify the actual highest yielding plots in the experi- ment. The variation between assessors in their ability to select visually for a specific character such as yield (the same applies equally to characters for resistance) is only a major concern if they are unaware of Table 5.4.Plant damage scales that have been used to screen cassava plants for resistance to the cassava mite Mononychellus tanajoa (after Bellotti and Kawana, 1980).
Score Description
A. Initial screening scale used to discard susceptible plants (up to 85%)