Predictive ability of perennial ryegrass spaced‐plant nurseries for turfgrass and seed production swards in Minnesota

Abstract

Turf‐type perennial ryegrass (Lolium perenne L.) success depends on adequate turfgrass quality and economical seed yield. In most breeding programs, spaced plants are the initial unit of selection in which observations of related individuals dictate the selection of superior germplasm for further testing. Therefore, spaced plants must be predictive of seed production and turfgrass growing environments. This study investigated the effectiveness of standard (three plants m⁻²) and competitive (23 plants m⁻²) spaced‐plant nurseries as selection environments with respect to two sward environments as well as applying a novel image analysis technique for several key traits. 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. Automated image analysis was able to predict the traditional visual scoring values at both locations for crown rust (Puccinia coronata f.sp. lolii) severity [Pearson's correlation (rₚ) > 0.79, P 0.89, P 0.88, P < .001). Increasing the competition among spaced plants altered the plant phenotype and improved accuracy for vegetative biomass, crown rust severity, seed yield, and, at one location, turfgrass quality. There was no benefit of increasing competition for several traits such as genetic color, fertile tillers, and spikelet number. Although the competitive design was not useful for all traits, pragmatically, the competitive design used less space and often made measurements and observations easier for bunch‐type grasses.

Plant phenotyping relevance

画像解析による植物形質推定が研究の明示的な技術的要素であり、従来の目視評価との予測性能も検証しているため、単なる農業試験の routine 測定ではない。

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