Unverified paper record
Integrating plant ontogeny and structure in Brassica napus L. I. Forward phenomics
Euphytica. · 1 Aug 2018 · 10.1007/s10681-018-2221-4
Abstract
Defining a minimum set of phenotypic traits that can integrate ontogeny and structure of Brassica napus L. is required for breeding and selection of high yielding and adapted genotypes to the short growing season of the upper Midwest, USA. Forward phenomics was instrumental in striking a balance between accuracy, timing and speed of capturing multi-level, spatiotemporal data at different scales of integration. Quantitative and categorical data digitally recorded, measured or scored on whole canopies, single plants, single leaves, and single siliques; and on random mature seed samples of entries in a phenotyping nursery of B. napus were used to identify plant traits that can integrate the effects of time (ontogeny) and space (architecture) on oil%, and to develop a multilevel-multitrait protocol based on field and laboratory characterization of phenotypic and agronomic data while accounting for fixed and random sources of variation when interpreting components of phenotypic variance. Traits conferring tolerance to low temperatures during germination and early seedling growth included fast emergence, early vigor, early flowering combined with short duration of bolting-to-flowering, and early maturity. To approximate rapeseed yield potential in the upper Midwest, USA, genotypes with biomass > 6.0 Mg ha⁻¹, seed > 3.5 Mg ha⁻¹, oil > 1.75 Mg ha⁻¹ and protein yield > 0.75 Mg ha⁻¹ are envisioned. A subset of adaptive traits has been identified that can be combined in a selection index to develop a plant ideotype for B. napus.
Plant phenotyping relevance
B. napusの複数器官・時空間形質を統合するフォワードフェノミクスと、マルチレベル・マルチ形質プロトコルの開発が研究の中心である。
abstractForward phenomics was instrumental in striking a balance between accuracy, timing and speed of capturing multi-level, spatiotemporal data at different scales of integration.
abstractto develop a multilevel-multitrait protocol based on field and laboratory characterization of phenotypic and agronomic data
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