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.）茎秆生长状况，有助于对作物物候期进行精准管理。本研究旨在采用逻辑斯蒂（Logistic）与龚珀兹（Gompertz）两种非线性模型，拟合灌溉条件下新植蔗与宿根蔗4个甘蔗品种（RB92579、RB93509、RB931530、SP79-1011）的株高生长曲线，并考量所有与模型假设相悖的偏差。模型参数通过最小二乘法结合高斯-牛顿（Gauss-Newton）算法进行估计。为筛选最优模型，本研究采用非线性检验指标、调整决定系数（R² adj）、残差标准差（RSD）以及修正赤池信息准则（AICc）进行模型遴选。基于最优模型，通过临界点计算茎秆生长速率与作物物候期。所有统计与绘图检验均在开源统计计算与绘图软件R环境中完成。总体而言，不含一阶自回归（AR(1)）的逻辑斯蒂模型与龚珀兹模型分别更适配新植蔗与宿根蔗的茎秆株高生长数据。所有供试品种均表现出前期快速生长的特性，其中RB92579品种在两个种植周期内的生长速率均更高。