Annals of Botany

Some Like It Cold

In addition to crop management, understanding vernalization could be used to identify plant communities at risk from climate change.
Modelling temperature, photoperiod and vernalization to predict flowering
Modelling temperature, photoperiod and vernalization to predict flowering

Brunonia australis and Calandrinia sp. are Australian native herbs with commercial potential as flowering potted or bedding plants. Both species are best grown as annuals and flower naturally during spring and early summer. However, many ornamental plants are grown outside their natural flowering period to align flowering with peak market demand, which requires the capacity to predict flowering date under changing or different environments. Scheduling crop production using quantitative flowering time models can have considerable advantages as they can be tailored for individual requirements, unlike traditional scheduling methods that are typically based on calendar date and have no particular reference to the environment.

Most development rate models for ornamental species predict flowering time in relation to temperature, photoperiod and/or daily light integral as observed for the above models. However, there are few flowering time models for ornamental plants that include a vernalization function. Vernalization is important for early and complete flowering of many traditional herbaceous crops. Plant responses to vernalization have been incorporated into some models for field crops and arabidopsis, which reportedly improved accuracy. A new paper in Annals of Botany quantifies temperature and photoperiod or vernalization responses of B. australis and Calandrinia sp. and model development for the purpose of scheduling year-round flowering. The effects of temperature and photoperiod or vernalization on plant quality characteristics, including flower and branch number, were defined.

 

Modelling temperature, photoperiod and vernalization responses of Brunonia australis (Goodeniaceae) and Calandrinia sp. (Portulacaceae) to predict flowering time. Ann Bot (2013) 111 (4): 629-639.
doi: 10.1093/aob/mct028

Crop models for herbaceous ornamental species typically include functions for temperature and photoperiod responses, but very few incorporate vernalization, which is a requirement of many traditional crops. This study investigated the development of floriculture crop models, which describe temperature responses, plus photoperiod or vernalization requirements, using Australian native ephemerals Brunonia australis and Calandrinia sp.
A novel approach involved the use of a field crop modelling tool, DEVEL2. This optimization program estimates the parameters of selected functions within the development rate models using an iterative process that minimizes sum of squares residual between estimated and observed days for the phenological event. Parameter profiling and jack-knifing are included in DEVEL2 to remove bias from parameter estimates and introduce rigour into the parameter selection process.
Development rate of B. australis from planting to first visible floral bud (VFB) was predicted using a multiplicative approach with a curvilinear function to describe temperature responses and a broken linear function to explain photoperiod responses. A similar model was used to describe the development rate of Calandrinia sp., except the photoperiod function was replaced with an exponential vernalization function, which explained a facultative cold requirement and included a coefficient for determining the vernalization ceiling temperature. Temperature was the main environmental factor influencing development rate for VFB to anthesis of both species and was predicted using a linear model.
The phenology models for B. australis and Calandrinia sp. described development rate from planting to VFB and from VFB to anthesis in response to temperature and photoperiod or vernalization and may assist modelling efforts of other herbaceous ornamental plants. In addition to crop management, the vernalization function could be used to identify plant communities most at risk from predicted increases in temperature due to global warming.

 

%d bloggers like this: