Flowering is a critical stage of fennel seed production, which strongly depends on climate factors. In crops such as fennel, the complexity of the umbellate structure and the lack of knowledge about its flowering dynamics make the prediction of the duration of this phenological stage uneasy. In the context of climate change, a reliable predictive tool for the duration of fennel flowering is needed. Our aim was to increase knowledge on fennel flowering dynamics and to propose a model to be used by seed producers. In 2018 and 2019, we studied the development of secondary and tertiary umbels during flowering stage which was determined from the Bundesanstalt Bundessortenamt und Chemische Industrie scale, in plants of four genotypes grown in tunnels. Multiple linear regression (MLR) models were used to select the more accurate equations which consisted of one or more variables as predictors of flowering duration and its dynamics across secondary and tertiary umbels. In all model subsets, the criterion-based procedure was used, followed by a criterion-based hybrid procedure to take advantage of the Mallows' Cp, adjusted R² and Bayesian information criterion, for equations and predictor selection. Two variables related to temperature, namely the temperature summation expressed in degree days and the number of days with temperature lower than 15°C, were identified as relevant parameters for predicting flowering duration expressed in days, in secondary as well as tertiary umbels. In addition, the equations and accurate predictors identified for modelling differences in time between flowering starts and ends of secondary and tertiary umbels also highlighted the importance of the number of days when the temperature amplitude is higher than 20°C, the number of days when the mean temperature is higher than 27°C, and the number of days when the relative humidity is higher than 80%.

中文翻译：

---

用于评估茴香复杂伞形花序在种子生产中的开花持续时间和动态的预测因子

开花是茴香种子生产的关键阶段，这在很大程度上取决于气候因素。在茴香等作物中，伞状结构的复杂性以及对其开花动态的了解的缺乏，使得对这一物候阶段持续时间的预测感到不安。在气候变化的背景下，需要一种可靠的茴香开花持续时间的预测工具。我们的目标是增加关于茴香开花动态的知识，并提出一个供种子生产者使用的模型。在 2018 年和 2019 年，我们研究了由Bundesanstalt Bundessortenamt und Chemische Industrie确定的开花期二级和三级伞形花序的发育规模，在隧道中生长的四种基因型的植物中。多元线性回归 (MLR) 模型用于选择更准确的方程，该方程由一个或多个变量组成，作为开花持续时间及其跨二级和三级伞形花序动态的预测因子。在所有模型子集中，使用基于标准的程序，然后是基于标准的混合程序，以利用 Mallows 的Cp，调整后的R ²和贝叶斯信息准则，用于方程和预测变量选择。与温度相关的两个变量，即以度数日表示的温度总和和温度低于 15°C 的天数，被确定为预测开花持续时间的相关参数，以天数表示，在二级和三级伞形花序中。此外，为模拟二级和三级伞形花序开花开始和结束之间的时间差异而确定的方程和准确预测因子也强调了温度幅度高于 20°C 的天数的重要性，平均气温高于27℃，相对湿度高于80%的天数。