Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya, St.Petersburg, 195251, Russia.
National Taiwan University, Taipei, Taiwan.
BMC Plant Biol. 2020 Oct 14;20(Suppl 1):202. doi: 10.1186/s12870-020-02408-1.
Phenology data collected recently for about 300 accessions of Vigna radiata (mungbean) is an invaluable resource for investigation of impacts of climatic factors on plant development.
We developed a new mathematical model that describes the dynamic control of time to flowering by daily values of maximal and minimal temperature, precipitation, day length and solar radiation. We obtained model parameters by adaptation to the available experimental data. The models were validated by cross-validation and used to demonstrate that the phenology of adaptive traits, like flowering time, is strongly predicted not only by local environmental factors but also by plant geographic origin and genotype.
Of local environmental factors maximal temperature appeared to be the most critical factor determining how faithfully the model describes the data. The models were applied to forecast time to flowering of accessions grown in Taiwan in future years 2020-2030.
最近收集的约 300 份豇豆（绿豆）品种物候学数据是研究气候因素对植物发育影响的宝贵资源。
我们开发了一种新的数学模型，该模型通过每日最高和最低温度、降水、日照时间和太阳辐射值来描述开花时间的动态控制。我们通过适应现有实验数据来获得模型参数。通过交叉验证验证了模型，并使用模型证明了适应性状（如花开花时间）的物候不仅受当地环境因素强烈预测，还受植物的地理起源和基因型影响。
在当地环境因素中，最高温度似乎是决定模型描述数据的准确性的最关键因素。将这些模型应用于预测 2020-2030 年在台湾种植的品种的开花时间。
