Tian Tian, Wu Lingtong, Henke Michael, Ali Basharat, Zhou Weijun, Buck-Sorlin Gerhard
Institute of Crop Science and Zhejiang Key Laboratory of Crop Germplasm, Zhejiang University Hangzhou, China.
Department of Ecoinformatics, Biometrics and Forest Growth, Georg-August University of Göttingen Göttingen, Germany.
Front Plant Sci. 2017 Mar 21;8:313. doi: 10.3389/fpls.2017.00313. eCollection 2017.
Functional-structural plant modeling (FSPM) is a fast and dynamic method to predict plant growth under varying environmental conditions. Temperature is a primary factor affecting the rate of plant development. In the present study, we used three different temperature treatments (10/14°C, 18/22°C, and 26/30°C) to test the effect of temperature on growth and development of rapeseed ( L.) seedlings. Plants were sampled at regular intervals (every 3 days) to obtain growth data during the length of the experiment (1 month in total). Total leaf dry mass, leaf area, leaf mass per area (LMA), width-length ratio, and the ratio of petiole length to leaf blade length (PBR), were determined and statistically analyzed, and contributed to a morphometric database. LMA under high temperature was significantly smaller than LMA under medium and low temperature, while leaves at high temperature were significantly broader. An FSPM of rapeseed seedlings featuring a growth function used for leaf extension and biomass accumulation was implemented by combining measurement with literature data. The model delivered new insights into growth and development dynamics of winter oilseed rape seedlings. The present version of the model mainly focuses on the growth of plant leaves. However, future extensions of the model could be used in practice to better predict plant growth in spring and potential cold damage of the crop.
功能结构植物建模（FSPM）是一种快速且动态的方法，用于预测不同环境条件下的植物生长。温度是影响植物发育速率的主要因素。在本研究中，我们采用了三种不同的温度处理（10/14°C、18/22°C和26/30°C）来测试温度对油菜（L.）幼苗生长和发育的影响。在实验期间（总共1个月），每隔一定时间（每3天）对植株进行采样以获取生长数据。测定并统计分析了总叶干质量、叶面积、单位面积叶质量（LMA）、宽长比以及叶柄长度与叶片长度之比（PBR），并建立了形态测量数据库。高温下的LMA显著小于中低温下的LMA，而高温下的叶片显著更宽。通过将测量数据与文献数据相结合，构建了一个具有用于叶片伸展和生物量积累的生长函数的油菜幼苗FSPM。该模型为冬油菜幼苗的生长和发育动态提供了新的见解。当前版本的模型主要关注植物叶片的生长。然而，该模型未来的扩展可在实际中用于更好地预测春季植物生长以及作物可能遭受的冷害。
