Helland & Holland: Oat Cultivar Blending Ability, Response, and Stability

buffering capacity, that is, its ability to adapt to variable weather, insect, disease, weed, and soil conditions. Ways Genetic diversity in cropping systems can provide buffering against to improve a crop’s buffering capacity include intravarying environmental conditions. Therefore, cultivar blends may have greater and more stable yields than their pure-line components. population interplant buffering through mixing cultiOptimization of cultivar blend development requires knowledge of vars or genotypes, and individual intraplant buffering the relative importance of pure-line yield potential, blend response, through maintenance of heterozygosity (Allard and and cultivar interactions to blend yield. Grain yield and volume weight Bradshaw, 1964). A cultivar blend can capitalize on of oat (Avena sativa L.) pure-line cultivars and cultivar blends were the principle of intra-population buffering, because a measured in eight Iowa environments in order to compare their promixture of genetically different plants may have a ductivity and stability and to estimate genetic components of blend greater chance of successful adaptation across a range yields. In one experiment, five early-maturing cultivars were grown of environments than a genetically homogeneous popuas pure lines and as all possible twoand three-way cultivar blends. lation. In a second experiment, ten midseason-maturing cultivars were grown Smithson and Lenné (1996) reviewed the literature as pure lines and as all possible two-way blends. Grain yield was 3% greater (P 0.05) and volume weight was 1% greater (P 0.05) in on cultivar blends in many crops and concluded that blends than in pure lines in the early-maturity experiment; however, blends generally yield slightly more than pure lines, but pure line and blends did not differ in the midseason-maturity experitheir true benefits lie in disease control and stability. ment. Blends had more stable (P 0.05) yields than pure lines in Blending can have significant positive effects on disease the early-maturity experiment only. Modified diallel analysis was used control (Mundt et al., 1995; Finkh and Mundt, 1992; to partition the variation among two-way blends into general yielding Power, 1991), and can reduce yield losses caused by ability (GYA) and true general competitive ability (TGCA) of each variability in soil quality (Trimble and Fehr, 1983). The component genotype, and specific competing ability (SCA) interacusefulness of cultivar blends in oat, however, has not tion between blend components. General yielding ability variation been established definitively. Pfahler (1965) reported was significant, whereas variation for neither TGCA nor SCA was that a small sample of cultivar blends had greater yield significant. Oat genotype responses to blending were sufficiently consistent across blending partners that superior blends can be selected stability than the component pure lines. Frey and Malbased on pure-line evaluations of early-maturing cultivars. donado (1967) found that cultivar blends had significantly higher yields than their component pure-line cultivars only when in more stressful environments. Shorter and Frey (1979), by contrast, found no difference beO hectarage in the USA has declined dramatitween blend and pure-line performance. cally since 1950 (USDA-National Agricultural Comparisons of blends and pure lines can vary among Statistics Service, 1998). Inclusion of oat in crop rotasamples of cultivars because of genotypic variation for tions, however, can enhance species diversity on farms contributions to blend performance. Gizlice et al. (1989) and help to reduce weed and insect pests (Liebman used a modified diallel analysis to characterize specific and Dyck, 1993), increase soil quality and curb erosion genotypic contributions to blend response. In this analy(Gantzer et al., 1991), and stabilize farm incomes sis, variation among blends was partitioned into general (Brummer, 1998). Because oat has value as feed for blending ability (GBA) and SCA variances. These effects livestock, in human nutrition, and as a partial remedy are analogous to the general and specific combining for many production problems, methods to increase and abilities estimated from diallel analyses of single-cross stabilize oat grain yields are needed. hybrids in maize (Zea mays L.; Sprague and Tatum, To minimize the adverse effects of environmental 1942). Gizlice et al. (1989) demonstrated that if purestresses on yield, plant breeders have attempted to deline components are evaluated in the same experiment velop cultivars that will perform reliably well across as the blends, then GBA can be partitioned into two a range of years and sites (Evans, 1993; Allard and components, GYA and TGCA. The GYA represents Bradshaw, 1964). Yield stability is the result of a crop’s the innate yielding ability of a cultivar grown as a pure line, and the TGCA is the additional mean competitive S.J. Helland, Dep. of Plant Pathology, Iowa State Univ., Ames, IA 50011; response of a cultivar calculated as the difference beJ.B. Holland, USDA-ARS Plant Science Research Unit, Dep. of Crop Science, Box 7620, North Carolina State Univ., Raleigh, NC 276957620. Received 14 Aug. 2000. *Corresponding author (sarathom@ Abbreviations: GBA, general blending ability; GLM, general linear iastate.edu). models; GYA, general yielding ability; SCA, specific competing ability; TGCA, true general competitive ability. Published in Crop Sci. 41:1689–1696 (2001). 1690 CROP SCIENCE, VOL. 41, NOVEMBER–DECEMBER 2001 a total of 25 entries. In the second trial, 10 midseason-maturing tween the GBA and the GYA. If either TGCA or SCA cultivars (Blaze, Burton, Chaps, Jerry, Jim, Newdak, Ogle, effects are significant, blend yields would be expected Prairie, Premier, and Rodeo) were evaluated as pure lines to be significantly different than the average of their and as all two-way cultivar blends. With the addition of one two component cultivars. Cultivars with positive TGCA experimental check line, IAR56-5, there were 56 entries in effects are those that capitalize on or contribute to the the midseason-maturity experiment. Blends were developed stabilizing and buffering effects of blending. by compositing equal numbers of seeds of each component Choosing the most efficient strategy for evaluating line and mixing thoroughly before planting. and selecting genotypes for use in blends requires Both experiments were grown during 1998 and 1999 at knowledge of the relative importance of GYA, TGCA, Ames (central Iowa), Nashua (northeastern Iowa), Crawfordsville (east central Iowa), and Lewis (west central Iowa). Soils and SCA effects in blends. If SCA effects are important, at each location were: Nicollet silty loam (fine-loamy, mixed, then superior blend combinations cannot be predicted superactive, mesic Aquic Hapludoll) at Ames, Readlyn loam on the basis of average blend responses of component (fine-loamy, mixed, mesic Aquic Hapludoll) at Nashua, Macultivars or cultivar pure-line performance. In this case, haska silty clay loam (fine, smectitic, mesic Aquic Argiudoll) at as many combinations of genotypes as possible should Crawfordsville, and Marshall silty clay loam (fine-silty, mixed, be evaluated in order to have a good probability of superactive, mesic Typic Hapludoll) at Lewis. The experimenidentifying the best blends. If SCA effects are not importal designs were a 5 5 square lattice for the early-maturity tant but variation for TGCA effects among cultivars experiment and a 7 8 rectangular lattice for the midseason exists, then superior blends can be developed by mixing experiment. There were three replications of each experiment genotypes with superior average blending responses. In within each environment. Plots were 3.72 m and consisted of four rows, each spaced 30 cm apart. Plots were sown at a rate this case, the most efficient breeding procedure would of 1000 seeds per plot. be to evaluate genotypes in blend combinations with a Flowering date was recorded at Ames as the number of subset of tester genotypes and to select those genotypes days after planting when 50% of the panicles in each plot with best average blending ability for use in blends. were fully emerged. Reactions to natural infections of crown Finally, if blends are superior to pure lines but SCA rust (Puccinia coronata Corda var. avenae W.P. Fraser and effects are unimportant and variation among genotypes Ledingham) were rated twice at 1-wk intervals within the 2 wk for TGCA effects is lacking, then superior blends can be following mean heading date of all entries at Ames and Nashua identified simply on the basis of pure-line evaluations. in both years. Ratings were based on a nine-point combined Whereas Shorter and Frey (1979) performed a diallel scale of incidence and severity (Holland et al., 1998). Plots analysis of oat blends and found that SCA effects were were machine-harvested and grain yield (kg ha 1 ) and volume weight (kg m 3 ) were measured on every plot. not important, they did not partition GBA into GYA and TGCA to identify optimal breeding procedures for Statistical Analysis blends. Furthermore, most of the genotypes in their study were selected from the same population, resulting Analyses of variance for each trait within and across enviin a limited sample of the genetic diversity available for ronments were obtained using the SAS procedure general use in oat cultivar blends. Estimation of the relative linear models (GLM; SAS Institute, 1985). Crossover genoimportance of GYA, TGCA, and SCA effects in a genettype-by-environment interactions were identified as instances in which the difference between two genotypes’ mean values ically broader sample of modern oat cultivars is needed was significantly (P 0.05) positive in at least one environto determine if blending current oat cultivars is warment and significantly negative in at least one other environranted to enhance productivity or stability and to idenment. A genotype’s stability for yield and volume weight was tify the most efficient method of identifying superior estimated using Shukla’s (1972) measure of genotype-by-enviblends. ronment interaction variance ( i), We investigated the effects of blending modern oat cultivars on grain yield and volume weight means and i p