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Quantifying the onset, rate and duration of sugar accumulation in berries from commercial vineyards in contrasting climates of Australia
Author(s) -
SADRAS V.O.,
PETRIE P.R.
Publication year - 2011
Publication title -
australian journal of grape and wine research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.65
H-Index - 77
eISSN - 1755-0238
pISSN - 1322-7130
DOI - 10.1111/j.1755-0238.2011.00135.x
Subject(s) - percentile , ripening , sugar , statistics , vitis vinifera , environmental science , mathematics , horticulture , chemistry , biology , food science
Background and Aim: To predict the trajectory of sugar accumulation in berries for planning of harvest and post‐harvest operations, we derived a simple model that is consistent with the known biological and viticultural drivers of berry ripening and requires inputs that are readily available to industry. Methods and Results: We used data from three vintages in climatically contrasting regions of Australia to derive a relationship between total soluble solids (TSS) and thermal time. A linear‐plateau function was fitted to the 90th percentile data, hence providing a boundary function representing the potential for each variety‐environment combination. Biologically relevant parameters were derived including the rate of change in TSS, maximum TSS (TSS max ), the threshold thermal time when berries reached TSS max , the onset and the duration of the period of linear increase in TSS. Gaps, calculated as the difference between actual TSS and the boundary function, correlated positively with vapour pressure. A model with the observed onset of ripening as an input and a variety and site specific rate as parameter accounted for 81–92% of the variation in TSS for independent data sets. Conclusion: The trajectory of TSS in berries can be modelled ‘as if’ the main environmental and management sources of variation affect the onset rather than the rate of sugar accumulation. Significance of the Study: Our onset‐rate model can be coupled with: (i) short‐term temperature forecasts to predict the trajectory of TSS for management purposes; and (ii) long‐term records of temperature to produce probabilistic profiles of maturity date.