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On the use of mean and extreme climate indices to predict sugar yield in western Fiji

journal contribution
posted on 2024-11-02, 13:55 authored by Simon McGree, Sergei Schreider, Yuriy KuleshovYuriy Kuleshov, Bipendra Prakash
Sugarcane is one of Fiji's largest commercial agricultural crops and greater than 80% of the raw sugar produced is exported. Few sugar-producing countries are as dependant on the contribution of sugar to the export market as Fiji. There has been a statistically significant decline in sugar yield since 1975. The proportion of sugar extracted from sugarcane has also declined as shown by the positive trend in the tonnes cane to tonnes sugar ratio (+0.07/year, p < 0.001). The role of climate in these changes was investigated by first using principal component analysis then stepwise regression to predict sugarcane and sugar yield. ‘Mild drought conditions’, an increase in the diurnal temperature range and cool conditions during the ripening and maturation period are favourable for sugar yield. The impact of future warmer, wetter and drier conditions on sugar yield was also examined, in the absence of adaptive measures. Results show declines in sugar yield with an increase in mean and extreme temperature. Results also show an increase in the number of rain days in March offsets the increase in temperature suggesting that an increase the number of rain days in the late growing season in a future climate may counter the influence of higher temperatures. As for Australia and other developed sugar producing countries, irrigation in the late growing season may be an option to increase yields and/or adapt to a warmer climate.

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Related Materials

  1. 1.
    DOI - Is published in 10.1016/j.wace.2020.100271
  2. 2.
    ISSN - Is published in 22120947

Journal

Weather and Climate Extremes

Volume

29

Number

100271

Start page

1

End page

11

Total pages

11

Publisher

Elsevier

Place published

Netherlands

Language

English

Copyright

Crown Copyright © 2020 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Former Identifier

2006101453

Esploro creation date

2020-10-03

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