The time of flowering is key to understanding the development of grapevines. Flowering coincides with inflorescence initiation and fruit set, important determinants of yield. This research aimed to determine between and within-vine variability in 4-cane-pruned Sauvignon blanc inflorescence number per shoot, number of flowers per inflorescence and flowering progression using an objective method of assessing flowering via image capture and statistical analysis using a Bayesian modelling framework. The inflorescence number and number of flowers per inflorescence were measured by taking images over the flowering period. Flowering progression was assessed by counting open and closed flowers for each image over two seasons. An ordinal multinomial generalised linear mixed-effects model (GLMM) was fitted for inflorescence number, a Poisson GLMM for flower counts and a binomial GLMM for flowering progression. All the models were fitted and interpreted within a Bayesian modelling framework. Shoots arising from cane node one had lower numbers of inflorescences compared to those at nodes 3, 5 and 7, which were similar. The number of flowers per inflorescence was greater for basal inflorescences on a shoot than apical ones. Flowering was earlier, by two weeks, and faster in 2017/18 when compared to 2018/19 reflecting seasonal temperature differences. The time and duration of flowering varied at each inflorescence position along the cane. While basal inflorescences flowered later and apical earlier at lower insertion points on the shoot, the variability in flowering at each position on the vine dominated the date and duration of flowering. This is the first study using a Bayesian modelling framework to assess variability inflorescence presence and flower number, as well as flowering progression via objective quantification of open and closed flower counts rather than the more subjective method of visual estimation in the field or via cuttings. Although flower number differed for apical and basal bunches, little difference in timing and progression of flowering by these categories was observed. The node insertion point along a shoot was more important. Overall, the results indicate individual inflorescence variation and season are the key factors driving flowering variability and are most likely to impact fruit set and yield.
CITATION STYLE
Parker, A. K., Fourie, J., Trought, M. C. T., Phalawatta, K., Meenken, E., Eyharts, A., & Moltchanova, E. (2022). Evaluating sources of variability in inflorescence number, flower number and the progression of flowering in Sauvignon blanc using a Bayesian modelling framework. Oeno One, 56(1), 1–15. https://doi.org/10.20870/oeno-one.2022.56.1.4717
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