基于有效积温的冬小麦返青后植株三维形态模拟

doi:10.3864/j.issn.0578-1752.2017.09.005

Abstract

Abstract: 【Objective】Based on effective accumulated temperature, the aim of this study is to realize combination of wheat growth model and shape model using 3D modeling technology, express environmental factors influence on wheat growth and morphological structure, finally realize the 3D visualization in the process of wheat growth, provide important reference for wheat crop growth dynamic prediction, cultivation management control and crop plant type design.【Method】As the main commercial wheat varieties in Tianjin region, Hengguan35, Jimai22 and Heng4399 were used as the experimental materials in this study, the field experiments of different varieties and nitrogen levels were carried out in 2015-2016 growth reasons of winter wheat, winter wheat shape data were collected under different nitrogen levels. After analysis of quantitative relationship among various varieties of winter wheat morphology data and effective accumulated temperature, simulation models of winter wheat leaf length and maximum leaf width were constructed using Logistic equation. Based on simulation models, every day shape data of various varieties of winter wheat were calculated. With the help of OpenGL and NURBS surface modeling technology, winter wheat geometry model was built. Finally, combination of winter wheat growth model and shape model was realized, and growth process visualization of winter wheat after turning green stage was realized.【Result】Under the different varieties and different nitrogen levels, R2 of leaf length regression equation was between 0.772-0.983, F was between 10.153-340.191, and Sig was less than 0.05, R2 of maximum leaf width regression equation was between 0.853-0.999, F was between 17.371-4 359.236, and Sig was less than 0.05, the results showed that the model fitting degree and significance were better. After data validation, absolute error of leaf length model was between 0-3.88 cm, root mean squared error (RMSE) was between 0.24-1.95 cm, absolute error of maximum leaf width model was between 0-0.28 cm, and RMSE was between 0.02-0.15 cm. It is indicated that the simulation models had high precision, and the models had a good predictive ability for different varieties of winter wheat leaf growth. Based on simulation models, every day shape data of winter wheat was calculated, plant morphology of different varieties under different nitrogen levels was constructed, and growth process after turning green stage was realistically simulated. 【Conclusion】The winter wheat leaf length and maximum leaf width simulation model after turning green stage was built based on the effective accumulated temperature, which could predict winter wheat leaf growth state after turning green stage, could realize combination of wheat growth model and shape model, and could implement leaf growth visualization of different varieties of winter wheat under different nitrogen levels.

Key words: winter wheat, effective accumulated temperature, growth model, shape model, 3D visualization

LI ShuQin, ZHU YePing, LIU HaiLong, LI ShiJuan, LIU ShengPing, ZHANG HongYing, GAO Wei. 3D Shape Simulation of Winter Wheat after Turning Green Stage Based on Effective Accumulated Temperature[J].Scientia Agricultura Sinica, 2017, 50(9): 1594-1605.

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3D Shape Simulation of Winter Wheat after Turning Green Stage Based on Effective Accumulated Temperature

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