Modeling sugarcane ripening as a function of accumulated rainfall in Southern Brazil

被引:20
作者
Cardozo, Nilceu P. [1 ]
Sentelhas, Paulo C. [2 ]
Panosso, Alan R. [3 ]
Palhares, Antonio L. [4 ]
Ide, Bernardo Y. [4 ]
机构
[1] Sugarcane Res Ctr, Piracicaba, SP, Brazil
[2] Univ Sao Paulo, ESALQ, Dept Biosyst Engn, Piracicaba, SP, Brazil
[3] FEIS UNESP, Dept Math, Ilha Solteira, SP, Brazil
[4] Raizen Co, Piracicaba, Brazil
关键词
Saccharum spp; Empirical models; Rainfall; Total recoverable sugar; CROP; MATURITY; GROWTH; YIELD;
D O I
10.1007/s00484-015-0998-6
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
The effect of weather variables on sugarcane ripening is a process still not completely understood, despite its huge impact on the quality of raw material for the sugar energy industry. The aim of the present study was to evaluate the influence of weather variables on sugarcane ripening in southern Brazil, propose empirical models for estimating total recoverable sugar (TRS) content, and evaluate the performance of these models with experimental and commercial independent data from different regions. A field experiment was carried out in Piracicaba, in the state of So Paulo, Brazil, considering eight sugarcane cultivars planted monthly, from March to October 2002. In 2003, at the harvest, 12 months later, samples were collected to evaluate TRS (kg t(-1)). TRS and weather variables (air temperature, solar radiation, relative humidity, and rainfall) were analyzed using descriptive and multivariate statistical analysis to understand their interactions. From these correlations, variables were selected to generate empirical models for estimating TRS, according to the cultivar groups and their ripening characteristics (early, mid, and late). These models were evaluated by residual analysis and regression analysis with independent experimental data from two other locations in the same years and with independent commercial data from six different locations from 2005 to 2010. The best performances were found with exponential models which considered cumulative rainfall during the 120 days before harvest as an independent variable (R (2) (adj) ranging from 0.92 to 0.95). Independent evaluations revealed that our models were capable of estimating TRS with reasonable to high precision (R (2) (adj) ranging from 0.66 to 0.99) and accuracy (D index ranging from 0.90 to 0.99), and with low mean absolute percentage errors (MAPE a parts per thousand currency signaEuro parts per thousand 5 %), even in regions with different climatic conditions.
引用
收藏
页码:1913 / 1925
页数:13
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