Identifying phenological phases in strawberry using multiple change-point models.

Abstract

Plant development studies often generate data in the form of multivariate time series, each variable corresponding to a count of newly emerged organs for a given development process. These phenological data often exhibit highly structured patterns, and the aim of this study was to identify such patterns in cultivated strawberry. Six strawberry genotypes were observed weekly for their course of emergence of flowers, leaves, and stolons during 7 months. We assumed that these phenological series take the form of successive phases, synchronous between individuals. We applied univariate multiple change-point models for the identification of flowering, vegetative development, and runnering phases, and multivariate multiple change-point models for the identification of consensus phases for these three development processes. We showed that the flowering and the runnering processes are the main determinants of the phenological pattern. On this basis, we propose a typology of the six genotypes in the form of a hierarchical classification. This study introduces a new longitudinal data modeling approach for the identification of phenological phases in plant development. The focus was on development variables but the approach can be directly extended to growth variables and to multivariate series combining growth and development variables.

Plant phenotyping relevance

イチゴの花・葉・ランナーの出現時系列から発育フェーズを同定する変化点モデルを開発・適用しており、植物表現型の抽出手法が研究の中心である。

Code and data availability

The supplied blocks describe strawberry phenological count data and multiple change-point analyses, but contain no data availability statement, no public phenotype dataset deposit, and no author code repository or URL. The only URLs present are Creative Commons license links, which are not paper-specific assets.

No evidence-backed public reproduction asset is currently recorded.