Developing grapevine phenological models in response to environmental and management factors

Yield estimation is a key consideration for the successful management of grape production in New Zealand. Understanding the timing of key phenological stages which are important for yield development is critical to improving yield estimation in the future. Phenological models have been developed for the grapevine based on the role of temperature in driving key stages such as budburst, flowering and veraison. Few studies have addressed the confounding influence of other environment or management practices by phenological model predictions. Models have not been adapted to predict more intermediary phenological stages, some of which are central for understanding the formation of yield components.

This project will develop an in-depth modelling approach to predict phenology for the grapevine, focussing in particular on key stages necessary for grapevine yield prediction. In addition the phenological stages will be investigated in a modelling framework in terms of i) spatial and temporal variability and ii) investigating the influence of environmental and management factors on the phenological model predicted outputs. There will be an opportunity to develop experimental and modelling approaches within the project.

The project is based at Lincoln, New Zealand, approximately 30 minutes from central Christchurch. The project will involve travel to field experimentation sites in the South Island.

Profile

Applicant must have a B.Sc. (Hons) or Master degree in Biology or related field and a keen interest in combining modelling approaches to investigate grapevine physiology. Candidates will have experience in crop or plant physiology and an interest in or experience in computational science is preferred. Experience in statistical analysis is required (Genstat or R) and candidates should demonstrate a willingness to learn new statistical procedures and to use various software for model development. The student must be willing and able to independently travel to various field experimentation sites.