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M. Joseph Stephens, Peter A. Alspach, Ron A. Beatson, Chris Winefield and Emily J. Buck

The Pacific northwestern (PNW) region of the United States is well known for production of machine-harvested red raspberries (Rubus idaeus) for process markets. The cultivar Meeker, developed in the 1960s, is well suited to this area and for machine-harvesting, but it is susceptible to raspberry bushy dwarf virus and root rot caused by Phytophthora rubi. Despite the efforts of several breeding programs, ‘Meeker’ is still the predominant cultivar for commercial production in the PNW. One of the major difficulties with breeding new berry fruit cultivars is the time-consuming nature of collecting fruit yield and quality data on large seedling populations. For fruit yield, visual scoring assessment methods are commonly used for seedling populations, but these may be poor predictors of yield. Consequently, visual scores for yield can result in less genetic improvement and thus can adversely affect successful cultivar development. Total yield measured by hand-harvesting is labor-intensive and does not assess machine-harvestability, but machine-harvesting is not practical to measure on individual plants. In this study we set out to see if we could bulk machine-harvest full-sib family plots for among-family selection and use yield component data on individuals within the plots for within-family selection. Using best linear unbiased predictors, we estimated machine-harvest yield breeding values for our individual seedlings and found higher genetic gain per generation using estimated individual machine-harvest breeding values (7.6%) than using hand-harvested breeding values (6.5%). Implications for breeding machine-harvest red raspberries are discussed.

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M. Joseph Stephens, Peter A. Alspach, Ron A. Beatson, Chris Winefield and Emily J. Buck

For most small fruit-breeding programs, high yield is a key objective and breeders face a number of challenges breeding for high yield, including interaction of environmental influences and the high cost of yield measurements. Red raspberry (Rubus idaeus) yield is determined by a number of yield components (YC), including cane number, cane length, number of fruiting laterals, fruit numbers, and fruit size. The ultimate goal for breeders would be to be able to select for high-yield genotypes using key YC as early in the life of the plant as possible. In this study we set out to determine how individual components of yield are inherited, determine which components contribute the most to total yield, and investigate whether it is possible using key components to make selections for high-yielding genotypes on 1- and 2-year-old plants. We estimated variance components, heritabilities, phenotypic and genotypic correlations, and breeding values for yield and YC from 1008 genotypes based on 85 families derived from 45 parents harvested over three seasons in Washington state. Narrow-sense heritability estimates varied from moderately low [0.2 for number of canes (NCAN)] to moderately high [0.69 for berry weight (BWT)]. In general, all YCs were positively correlated with total yield (TYLD). The highest genetic correlation with TYLD was found for BWT (0.8), followed by cane length (CLEN) (0.54) and number of fruit per lateral (NFRT) (0.5). NCAN had the lowest genetic correlation with TYLD (–0.03). Genotype × year (G×Y) interaction was higher for some YCs than others. Berry weight, lateral length (LLEN), and NFRT were found to be the most stable overall seasons and the interaction was higher between the first and second years than between the second and third years of the study. To determine the most important YC, we calculated the correlations between the product of all combinations of subsets of the YC breeding values and TYLD. Berry weight, CLEN, and cane diameter (CDIA) were found to be the most important for 2009, 2010, and 2011, respectively. The two most important YCs were LLEN and BWT and this was consistent overall seasons. We demonstrate that it is possible to select high-yielding genotypes by measuring key components such as LLEN, CLEN, and BWT in the first and second fruiting seasons.

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M. Joseph Stephens, Peter A. Alspach, Ron A. Beatson, Chris Winefield and Emily J. Buck

New commercial red raspberry (Rubus idaeus) cultivars suited to machine-harvesting and processing markets need to be high-yielding and have good fruit quality attributes, including fruit firmness, sugar content, acidity, flavor, and health properties. Combining many traits in one genotype is a challenge for breeders, especially for traits negatively correlated with yield. Despite its potential, the use of multiple-trait selection through selection indices has had limited application in fruit breeding. In this study, we estimated variance components, heritabilities, phenotypic and genetic correlations and breeding values for total yield (TYLD), harvest span, mid-harvest day and fruit quality traits, firmness (FIRM), soluble solids (SS), acidity (ACID), total anthocyanins (TACY), and total ellagitannins (TELG) from 1008 seedling genotypes based on 85 families derived from 45 parents harvested over three seasons in Washington state. Narrow-sense heritability estimates ranged from moderately low (0.22 for TYLD) to moderately high (0.73 for SS). All traits measured had positive genetic correlations with TYLD except for ACID (–0.35) and TACY (–0.28). Genotype × year (G×Y) interaction was high for TYLD and low for fruit quality attributes FIRM, SS, ACID, TACY, and TELG, and interactions were higher between the first (2009) and second (2010) seasons than between the second (2010) and third (2011) seasons. Using economic weights and breeding values derived from multivariate analysis for TYLD, FIRM, SS, and TACY, we constructed a selection index designed to assist with multiple-trait selection for population improvement and the development of commercial raspberry cultivars.

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M. Joseph Stephens, Jessica Scalzo, Peter A. Alspach, Ron A. Beatson and Ann Marie Connor

Breeding for high yield is a major objective of most small fruit breeding programs worldwide. In recent years, research associated with health benefits of berry fruit has resulted in some breeding programs looking for material with improved health properties with the goal of incorporating these into genotypes with high yield and other favorable agronomic characters. In this study, we estimated variance components, heritabilities, and phenotypic and genotypic correlations for yield components and phytochemicals [total phenolics (TPH), antioxidant activity (FRAP), and total anthocyanins (TACY)] from 828 genotypes in a red raspberry (Rubus idaeus) factorial mating design based on 42 full-sib families derived from seven female and six male parents harvested in one season in New Zealand. Narrow sense heritability estimates varied from moderately low [0.23 for percent budburst (PCBB)] to high [0.82 for mean berry weight (BWT)]. Highest genotypic correlations with total yield (TYLD) were found for mean cane length (0.60) followed by moderate correlations for PCBB (0.38), BWT (0.34) and fruit number per unit lateral (0.31). For these four components, the correlation between the product of the empirical breeding values (eBV) and TYLD was as good (0.67) as the correlation between the product of the seven yield components measured (0.68). Moderately high negative genotypic correlations were found between TYLD and TPH (–0.67), FRAP (–0.68), and TACY (–0.64), suggesting that breeding for high-yielding genotypes may result in reduced phytochemical levels. A pigment-deficient R. parvifolius × R. idaeus hybrid derivative parent (R. parv deriv) had the most influence on berry weight as a yield component. Removal of the R. parv deriv progeny from the analysis increased the contribution of berry weight to total yield. Heritability estimates were generally lower when the R. parv deriv crosses were omitted, particularly for number of canes BWT, TYLD, and the phytochemicals. Implications of R. parv deriv crosses on these results are discussed. Of the 828 genotypes, only five had an eBV for total yield greater than that of the best yielding parent, whereas 49 had larger berries than the best parent. None of the 828 genotypes had an eBV for yield components or phytochemicals less than that of the lowest parent, whereas 13 had a higher eBV associated with phytochemicals than that of the highest parent.