Factors affecting cane yield and commercial cane sugar in the Tully district

被引:15
|
作者
Lawes, RA [1 ]
McDonald, LM
Wegener, MK
Basford, KE
Lawn, RJ
机构
[1] CRC Sustainable Sugar Prod, Townsville, Qld 4811, Australia
[2] James Cook Univ, Sch Trop Biol, Townsville, Qld 4811, Australia
[3] Univ Queensland, Dept Nat & Rural Syst Management, Brisbane, Qld 4072, Australia
[4] Univ Queensland, Sch Land & Food Sci, Brisbane, Qld 4072, Australia
来源
AUSTRALIAN JOURNAL OF EXPERIMENTAL AGRICULTURE | 2002年 / 42卷 / 04期
关键词
D O I
10.1071/EA01020
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
The Tully Sugar Mill has collected information about sugarcane supplied for crushing from every block in the mill district from 1970 to 1999. Data from 1988 to 1999 were analysed to understand the extent of the variation in cane yield per hectare and commercial cane sugar in the Tully mill area. The key factors influencing the variation in cane yield and commercial cane sugar in this commercial environment were identified and the variance components computed using a restricted maximum likelihood methodology. Cane yield was predominantly influenced by the year in which it was harvested, the month when the crop was ratooned (month of harvest in the previous year) and the farm of origin. These variables were relatively more important than variety, age of crop or crop class (plant crop, first ratoon through to fourth or older ratoons) and fallowing practice (fallow or ploughout-replant). The month-of-ratooning effect was relatively stable from year-to-year. Commercial cane sugar was influenced by the year of harvest, the month of harvest and their interaction, in that the influence of the month of harvest varied from year to year. Variety and farm differences were also significant but accounted for a much lower portion of the variation in commercial cane sugar. An empirical model was constructed from the key factors that influenced commercial cane sugar and cane yield to quantify their combined influence on sugar yield (t/ha). This may be used to assist mill personnel to predict their activities more accurately, for example to calculate the impact of a late finish to the current harvest season on the following year's crop.
引用
收藏
页码:473 / 480
页数:8
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