Adjusting the growth curve of sugarcane varieties using nonlinear models

ABSTRACT: Assessing sugarcane (Saccharum spp.) stalk growth helps to adequately manage the phenological stages of the crop. The aim of this study was to describe the height-growth curve of four sugarcane varieties (RB92579, RB93509, RB931530 and SP79-1011), in irrigated plant-cane and ratoon cane plantations, using the Logistic and Gompertz nonlinear models, while considering all deviations from assumptions. The model parameters were estimated based on the least squares method using the Gauss-Newton algorithm. To select the most suitable model, nonlinear measures, adjusted coefficient of determination (R2 adj), residual standard deviation (RSD), and corrected Akaike information criterion (AICc) were used. Based on the best models, stalk height growth rates and crop phenological stages were determined using critical points. All tests were performed in the free software environment for statistical computing and graphics, R. In general, the Logistic and Gompertz models without AR(1) better described the plant-cane and ratoon cane stalk height, respectively. All varieties showed early growth, and the RB92579 variety presented higher rates in both cycles.

摘要：评估甘蔗（Saccharum spp.）茎秆生长情况，可为作物物候期的合理调控提供依据。本研究针对RB92579、RB93509、RB931530及SP79-1011共4个甘蔗品种，在灌溉新植蔗与宿根蔗种植模式下，采用Logistic与Gompertz非线性模型拟合其株高生长曲线，并充分考量模型假设的各类偏离情况。模型参数基于最小二乘法，通过高斯-牛顿算法进行估计。为筛选最优拟合模型，本研究采用非线性检验、调整决定系数（R²adj）、残差标准差（RSD）以及校正赤池信息准则（AICc）作为评价指标。基于最优模型，通过临界点确定茎秆株高生长速率与作物物候期。所有数据分析均在用于统计计算与绘图的自由软件环境R中完成。总体而言，未引入一阶自回归（AR(1)）结构的Logistic模型与Gompertz模型，分别更适配新植蔗与宿根蔗的茎秆株高生长数据。供试的所有甘蔗品种均表现出前期快速生长的特征，其中RB92579品种在两个种植周期中均展现出更高的生长速率。