Heineck, Garett2019-12-112019-12-112019-09https://hdl.handle.net/11299/209075University of Minnesota Ph.D. dissertation. September 2019. Major: Applied Plant Sciences. Advisors: Eric Watkins, Nancy Ehlke. 1 computer file (PDF); xx, 171 pages.This dissertation consists of five chapters, each was written as a stand-alone manuscript. The introduction of each chapter serves, in part, as the introductory literature review. Herein is described a brief summary of each chapter’s introduction, methods, and results. Chapter 1 Crown and stem rust are major diseases of perennial ryegrass (Lolium perenne L.). Plant breeders and pathologists often rate rust severity in the field using the modified Cobb scale, but this method is subjective and labor intensive. A novel, open-source system using ImageJ and R was developed to quantify pustule number and area using digital images collected from spaced plants in the field. The computer-processing pipeline included development of training data for prediction of pixel identity using random forest and noise reduction spatial processing. Raters and the computer scored rust severity on plant images of varying complexity including whole-plant (WP), five-leaf (FL), and single-leaf (SL) image series. Computer accuracy was determined using the SL, while the FL series gave insight into the true value of WP severity. Rater ability was assessed using a panel of nine scientists with varying levels of disease rating experience. Results showed rater perceptions of crown rust severity were very consistent across images, but agreement on severity values for a given image were low. Rater consistency for stem rust severity was low and FL scores were not strongly correlated with WP scores (r=0.36, P=0.03) indicating low rater accuracy. The computer-processing pipeline was able to accurately discriminate, count and quantify crown and stem rust pustules on leaf samples. Correlations between computer and the median rater score for crown rust were excellent (r>0.90, P< 0.001) for all image series. Similar to raters, there was lack of correlation between WP and FL series (r=0.20, NS) indicating this technique is limited to leaf or stem samples for stem rust and not applicable to WP. However, the computer-processing pipeline shows promise in replacing visual rating of WP for crown rust. Chapter 2 Perennial ryegrass is an important turf and forage species that often becomes infected with crown rust caused by Puccinia coronata f. sp. lolii. Disease control through Clavicipitaceous endophytes has been proposed as a potential biocontrol. Two field experiments were designed to determine the influence of native Epichloë endophyte infection on natural rust infection across a diverse panel of perennial ryegrass germplasm. Experiment 1 used an isogenic population design in which clonal plants infected (E+) or endophyte free (E-) were nested within 14 perennial ryegrass entries. Experiment 2 consisted of E+ and E- progeny from isogenic parents. Results showed the endophyte had no consistent marginal effect on crown rust severity across or within entries; however, several isogenic host pairs did show either favorable or antagonistic effects. Despite these sporadic effects, no differences were found between isofrequent family pairs indicating the presence of a host by endophyte interaction. These findings support the conclusion that endophyte infection does not play a substantial role in mediating crown rust severity on a population scale. Genotypic and phenotypic data revealed that endophyte isolates were similar within entry indicating that host genotype could be responsible for the highly specific endophyte effect on crown rust. The importance of host genotype was further supported by substantial heritability estimates for disease severity. Chapter 3 Understanding trade-offs between breeding for turfgrass performance and seed production capacity is beneficial for turfgrass breeders working on the improvement of perennial ryegrass. An experiment was designed to identify potential tradeoffs and their mechanistic causes by measuring turfgrass and seed production traits on 20 perennial ryegrass entries grown in two Minnesota environments. Average turfgrass quality scores were not correlated with seed yield at either location. However, several individual turf quality rating dates were moderately correlated with seed yield at both locations (P < 0.1). Within these dates, subsidiary turfgrass traits were exhaustively regressed against quality data to identify the optimum combination of variables explaining turfgrass quality. Turf quality was driven by lateral and vertical growth rate, crown rust severity, winter survival, and stemminess. Of these traits it was clear that breeding for increased lateral growth rate and winter survival would be positively correlated with increased yield. Crown rust severity was nearly perfectly correlated across environments (r > 0.95) indicating a favorable response. Vertical growth rate and fertile tiller production; however, were negatively associated with turf quality and were investigated to discover whether breeding for slower growth and steminess would negatively influence seed yield. Although fertile tillers were associated with higher seed yield, there was no relationship with steminess in turfgrass plots. Vertical growth rate was associated with earlier maturity, which is associated with increased seed yield indicating a slight tradeoff. Evidence from the environments and germplasm tested suggest that plant breeders should generally not be concerned with negative tradeoffs between perennial ryegrass turf quality and seed yield. Chapter 4 Producing adequate seed yield is essential for perennial ryegrass cultivar success in both the turf and forage industries. This study examined the importance of seed yield components across 20 perennial ryegrass entries in both spaced plantings and seed production swards at two locations in Minnesota. Competitive (23 plants m-2) and non-competitive (3 plants m-2) spaced plant nurseries were tested for predictive ability. Structural equation modeling (SEM) was used to determine the indirect and direct influences of yield components on total seed yield. The impetus of this approach was to discover new breeding targets and an ideotype for increasing seed yield. Results showed that when tiller survival was low winterkill was highly influential on seed yield both directly and indirectly through fertile tiller number. Fertile tiller number was more important in spaced plant environments than in swords, but very few differences were found between entries. Spike fertility directly influenced spike yield and was indirectly important for total seed yield. Although the relative importance of individual seed yield components was similar between nursery designs, the competitive design had a superior predictive ability for sward yield via total plant yield and spike fertility. Chapter 5 Turf-type perennial ryegrass success depends both on adequate turfgrass quality, but also economic seed yield. In most breeding programs, spaced plants are the initial unit of selection in which observations of related individuals dictate selections of superior germplasm for further testing. As such, spaced plants must be predictive of both seed production and turfgrass growing environments. This research investigated the effectiveness of both standard (3 plants m-2) and competitive (23 plants m-2) spaced plant nurseries as selection environments with respect to sward environments using the same 20 turf-type entries. Seed production, turfgrass and the two spaced plant growing environments were tested at two locations in Minnesota. Turfgrass quality traits were measured in 2017 and 2018 and seed production traits were measured in 2018. Rank correlations for fertility index between the competitive nursery and sward environments at both locations was substantial (rp = 0.52 and 0.81, P < 0.05). Genetic color and crown rust severity were the most prominent variables in models for predicting turfgrass quality. Competition between spaced plants made only a minor improvement of predictive ability for these traits. Overall, increased competition between spaced plants increased the predicative ability (rs) for both turfgrass and seed production traits. Furthermore, the competitive design takes up less space and often makes measurements and observations much easier for bunch-type grasses.enFungal endophytesImage analysisSeed productionTurfgrassThesis or Dissertation