The Queensland strawberry breeding program aims to sustainably increase profitability for the producer by selecting superior genotypes. To be effective and efficient, selection must account for several traits simultaneously and focus on: 1) the most economically important traits; and 2) the ease with which the levels of traits can be changed by selection. Thus, the breeder must account for and connect the relative economic importance of traits and the genetic architecture of the traits underlying the population to achieve maximum genetic progress toward a nominated economic goal.
The relative economic values can take a number of approaches; e.g., profit, return on investment, cost per unit of production, etc. Apiolaza and Garrick (2001) used incremental change in profit with change in the level of each trait to develop weights. However, this profit formulation is claimed to include scaling components such that improvements could be made by changing the size of the farming operation rather than the need to change the genetic base (Ponzoni, 1988). Ratio forms of economic value are claimed to avoid this scaling effect (Ponzoni, 1988). However, Smith et al. (1986) claimed there would be only small differences among the forms. Additionally, the profit and ratio forms were shown to be equivalent when profit [i.e., when net earnings in an accountant’s sense minus the farm’s (firm’s) opportunity cost of capital] was set at zero in an economic sense (Brascamp et al., 1985; Ponzoni, 1988). Profit is zero in an economic sense when the farm (firm) earns the normal economy-wide rate of profit in an accounting sense. By contrast, Melton and Colette (1993) argue that the most important criteria is that the weighting values reflect the contributions to economic improvement of the enterprise and so advocate a more detailed approach than input output ratios for complex evaluations (e.g., commercial beef herd). Doupe and Lymbery (2003) support this view and also indicate that using a ratio alone as a selection criterion does not allow an accurate prediction of response to selection. Hardner et al. (2006) combined both profit and ratio forms to efficiently use ratios based on profit through a PI to develop relative economic weights for traits in a horticultural production system for macadamia (Macadamia integrifolia and M. tetraphylla). This combination of profit and ratio is also likely to be appropriate for use in strawberry.
The advantages claimed from using a breeding objective in livestock and plantation trees, and calculating the economic weights for various traits, should also apply to strawberry improvement. The use of an aggregate economic genotype (breeding objective) should enable breeders to direct their activities to combine traits with the highest estimated breeding values and make the most rapid (total) genetic progress for their particular situation.
Development of an aggregate economic genotype (breeding objective) can be described in the following phases: specification of the breeding, production, and marketing system; identification of sources of income and expense; determination of biological traits influencing income and expense; estimation of phenotypic and genetic parameters (i.e., breeding values) and choice of selection criteria; and derivation of the economic weights (values) of each trait (Ponzoni and Newman, 1989). The ideal aggregate economic genotype (breeding objective) should be composed of all traits that influence returns and costs, regardless of whether they can be changed by selection or measured (Ponzoni and Newman, 1989).
The formal definition of a breeding objective and identification of selection criteria based on this objective should be the first step in developing a structured breeding program (Apiolaza and Garrick, 2001). Despite this, although general combining abilities or breeding values associated with traits have been reported for horticultural crops (Souza et al., 2000; Tancred et al., 1995), there is only one published example of the formal definition of a breeding objective (aggregate economic genotype) in horticultural crops (Hardner et al., 2006). Additionally, although selection indices based on economic criteria have been developed (Wenzel, 1980), there is no report of an aggregate economic genotype (breeding objective) involving multiple traits in strawberry.
Herrington et al. (2012) described the contribution of 12 individual plant and fruit traits to farm cost and income under subtropical Queensland conditions with the overall goal of improving the profitability of the industry through the release of new strawberry cultivars. The study involved specifying the production and marketing system in southeast Queensland, developing a spreadsheet to assess the economic impact of changes to the system, and identifying plant traits that influenced outcomes from the system. The traits included total yield, early yield, fruit size, fruit size variation, and plant size, display of fruit, truss branching, ease of detaching fruit, resistance of fruit to rain damage, abrasion, and bruising. These traits and the levels of expression of the traits were related to the amount of marketable fruit available for sale and the cost (based on time) to gather and consolidate fruit into a marketable unit. Additionally, the analysis related total volume of farm production to market prices received. Genetic parameters associated with the traits have also been estimated (M.E. Herrington, unpublished data). Because of the importance of defining the breeding objective (Apiolaza and Garrick, 2001), but its lack of formal use in strawberry, our study used this information to produce a linear combination of economic and genetic parameters to estimate the aggregate economic genotype (i.e., breeding objective) for over 3000 genotypes that are represented in the breeding program or the pedigree of individuals in the breeding program relevant to strawberry production in southeast Queensland. Associations with gross margin and the effect of reducing the number of traits in the model were also investigated.
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