Identifying climate variables having the greatest influence on sugarcane yields in the tully mill area
Skocaj, D.M., and Everingham, Y.L. (2014) Identifying climate variables having the greatest influence on sugarcane yields in the tully mill area. In: Proceedings of the Australian Society of Sugar Cane Technologists (36) pp. 53-61. From: ASSCT 2014: 36th Annual Conference of the Australian Society of Sugar Cane Technologists, 28 April - 1 May 2014, Broadbeach, QLD, Australia.
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Abstract
Large fluctuations in cane yield from one season to the next are problematic for all sectors of the sugar industry. The Wet Tropics region is characterised by high rainfall, excessive soil wetness, low solar radiation and vulnerability to extreme climatic variability. Although many different factors influence productivity, annual fluctuations in cane yield at the farm level in this region are believed to be strongly associated with changes in climatic conditions. To investigate this further, a stepwise linear regression model used atmospheric variables at different times of the growing season to explain Tully mill detrended cane yield data for eight different time blocks. These time blocks ranged from 10 to 80 years. The regression models explained between 32.2 and 94.1% of the variation in detrended cane yields for the Tully mill area. Rainfall, most commonly around spring and summer, was always the first variable entered into the models making it an important predictor. However, the other variables selected for late entry changed over time. Improved yield forecasts coupled with greater knowledge of the influence of climatic conditions on cane yields could be used for a range of management decisions across all sectors of the industry.
Item ID: | 38276 |
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Item Type: | Conference Item (Research - E1) |
ISSN: | 0726-0822 |
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Additional Information: | Page range is based on the electronic copy of the proceedings. |
Funders: | Sugar Research and Development Corporation (SRDC), Sugar Research Australia (SRA) |
Date Deposited: | 15 Apr 2015 04:51 |
FoR Codes: | 01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics @ 100% |
SEO Codes: | 82 PLANT PRODUCTION AND PLANT PRIMARY PRODUCTS > 8203 Industrial Crops > 820304 Sugar @ 100% |
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