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为优化温室盆栽金鱼草光温调控精度,以‘红姬’品种为研究对象,通过不同定植期和密度试验,以辐热积(Product of thermal effectiveness and PAR,TEP)为尺度,建立了温室盆栽金鱼草生长发育的模型,并用独立试验数据检验了模型预测精度。结果表明,模型对萌芽期、展叶期、花蕾期和采收期的时间预测符合度较高,模拟值与实测值基于1:1直线间的决定系数R2为0.95,回归估计标准误差RMSE分别为1.3、1.7、2.3和1.8 d,预测精度明显高于以有效积温为尺度的发育模型(RMSE分别为2.6、2.5、3.9和3.2 d)。模型对株高、茎粗、叶片数、花苞数和干物质量的模拟值与实测值的决定系数R2分别为0.94、0.92、0.96、0.97和0.91,RMSE分别为6.9 cm、0.4 cm、5.8、2.2和1.27 g·株-1。该研究建立的模型能够较准确地预测温室盆栽金鱼草各生育期出现时间、植株形态和干物质生产的动态。建立的模型参数少且易获取,且预测精度较高,可为温室金鱼草生产中种植期、种植密度及环境的优化调控提供理论依据和决策支持。
In order to optimize the precision of light and temperature regulation in the greenhouse potted snapdragon, the varieties of ’Hongji’ were selected as the research object. Through the different planting and density tests, the pot of greenhouse was set up on the scale of TEP, Antirrhinum majus growth and development model, and independent test data to test the model prediction accuracy. The results showed that the model had a good coincidence degree with the time prediction of budding stage, leaf expanse stage, flower bud stage and harvesting stage. The coefficient of determination R2 was 0.95 based on the 1: 1 straight line between simulated and measured values, and RMSE of regression estimation standard 1.3, 1.7, 2.3 and 1.8 d, respectively. The prediction accuracy was significantly higher than that based on the effective accumulated temperature (RMSE 2.6, 2.5, 3.9 and 3.2 d respectively). The coefficients of determination R2 of simulated and measured values of plant height, stem diameter, number of leaves, number of flower buds and dry matter were 0.94, 0.92, 0.96, 0.97 and 0.91, respectively, and the RMSEs were 6.9 cm, 0.4 cm, 5.8 and 2.2 And 1.27 g · plant -1. The model established by this study can predict more accurately the appearance time, the plant morphology and the dry matter production dynamics in the greenhouse potted snapdragons. The established model parameters are few and easy to obtain, and the prediction accuracy is high, which can provide theoretical basis and decision-making support for the optimal regulation of planting period, plant density and environment in the production of snapdragon greenhouse.