基于Gompertz模型营养面积对稻株性状的模拟分析

Simulation analysis of rice plant traits based on the nutrient area of Gompertz model

  • 摘要: 【目的】基于Gompertz模型系统性研究营养面积对水稻地上部干物质积累及产量的影响,为稻穴分布非均匀性的度量方法和实现水稻高产精准栽培提供理论依据。【方法】以常规晚稻农香42和杂交晚稻泰优398为材料开展水稻种植试验,水稻采用双苗抛秧移栽,设9个密度水平(140、120、100、60、40、28、20、12和8蔸/m2)营造局部密度迥异的稻株分布格局。于移栽后6~12 d的返青期利用无人机航拍稻株图像并利用拼接软件获取试验区正射图像,应用稻株识别算法、稻株位置标定算法和泰森图划分稻株营养区域并计算稻株营养面积,利用Gompertz模型模拟营养面积影响稻株穗重、有效穗数和地上部干物重等性状指标的趋势。【结果】稻株性状指标响应营养面积的趋势均较好符合Gompertz函数,拟合2个品种各性状指标的决定系数(R2)均大于0.8000(除农香42有效穗数的R2为0.7873外),稻株性状指标对营养面积的响应呈S形曲线变化规律;农香42最佳营养面积为429.88~445.47 cm2,有效营养面积应小于900 cm2;泰优398最佳营养面积为464.67~484.43 cm2,有效营养面积应小于1000 cm2。模型拟合优度分析结果表明,Gompertz模型对稻株产量性状响应营养面积的变化具有较好的解释力,泰优398稻株性状实测值与Gompertz曲线预测值的模型拟合精度相对高于农香42。【结论】利用Gompertz模型模拟稻株营养面积与性状指标的数量关系,得出了稻株最佳营养面积和有效营养面积,稻株性状指标随营养面积的增加呈S形曲线变化,各性状指标的单位面积产量呈先增后减最后趋于稳定的规律。

     

    Abstract: 【Objective】This study systematically investigates the influence of nutrient area on the aboveground dry matter accumulation and yield of rice plants using the Gompertz model, aiming to provide theoretical basis for the measurement method of the non-uniformity of rice pit distribution and the precise cultivation of high-yield rice. 【Method】Field experiments were conducted using 2 rice cultivars: the conventional late-season variety Nongxiang 42 and the hybrid late-season variety Taiyou 398. Rice was transplanted using a double-seedling casting method under 9 planting density levels(140, 120, 100, 60, 40, 28, 20, 12 and 8 hill/m2) to create locally heterogeneous plant distribution patterns. At the greening stage of 6-12 d after transplantion, orthophotos of the experimental plots were acquired using unmanned aerial vehicles(UAV) aerial rice plants image and stitching software. The rice plant identification algorithm, the rice plant position calibration algorithm and Voronoi diagram were applied to divide the nutrient area of the rice plants and calculate the area of the rice plants nutrient area. Then, the Gompertz model was used to simulate the trend of the nutrient area affecting trait indicators such as panicle weight, effective panicle number and aboveground dry matter. 【Result】The trends of rice trait responsed to nutrient area were well described by the Gompertz function. The coefficients of determination(R2) for the fitted models exceeded 0.8000 for all traits in both varieties, with the exception of effective panicle number in Nongxiang 42(R2=0.7873). The responses of rice traits to nutrient area followed an S-shaped curve. The optimal nutrient area for Nongxiang 42 ranged from 429.88 to 445.47 cm2, with an effective nutrient area below 900 cm2. For Taiyou 398, the optimal nutrient area ranged from 464.67 to 484.43 cm2, and the effective nutrient area below 1000 cm2. The analysis of model fit goodness indicated that the Gompertz model had a good explanatory power for the changes in the nutrient area in response to the yield traits of rice plants. The model fitting accuracy between the measured values of the traits of Taiyou 398 rice plants and the predicted values of the Gompertz curve was higher than that of Nongxiang 42. 【Conclusion】The Gompertz model is used to simulate the quantitative relationship between the nutrient area of rice plants and trait indicators, and the optimal nutrient area and effective nutrient area of rice plants are obtained. The trait indicators of rice plants change in an S-shaped curve with the increase of the nutrient area, and the yield per unit area of each trait indicator shows the law of first increasing, then decreasing, and finally tending to stabilize.

     

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