Vleeshouwers L M, Kropff M J
1 Wageningen University, Department of Plant Sciences, Group Crop and Weed Ecology, PO Box 430, 6700 AK, Wageningen, The Netherlands.
New Phytol. 2000 Dec;148(3):445-457. doi: 10.1046/j.1469-8137.2000.00773.x.
A model was developed to simulate weed emergence patterns after soil cultivation. In the model, the consecutive processes of dormancy release, germination and pre-emergence growth were modelled in separate modules. Input variables of the model were: date of soil cultivation, soil temperature and soil penetration resistance. Output variables of the model were: seedling density and timing of seedling emergence. The model was parameterized for Polygonum persicaria, Chenopodium album and Spergula arvensis with data from previous field and laboratory experiments. The model was evaluated with data from an experiment, in which emergence of P. persicaria, C. album and S. arvensis was monitored in field plots that were cultivated once only, at one of five dates in the spring. At the same time as the field observations on seedling emergence, seasonal changes in seed dormancy of the buried weed seeds were assessed by testing the germination of seed lots that were buried in envelopes. From a comparison between field observations and simulated data, it appeared that the model overestimated the rate of dormancy release in spring, whereas germination and pre-emergence growth were simulated well. In general, therefore, both the numbers of emerging seedlings and the timing of emergence could be predicted accurately, when dormancy was not simulated but introduced from experimental data. Improvement of predictions of field emergence of weeds should mainly focus on increasing the precision of the simulation of dormancy release. Close correlations were found between seedbed temperature and both the extent and rate of seedling emergence, but analysis with the simulation model revealed that they were only partly based on causal relationships, so that they have limited predictive value.
开发了一个模型来模拟土壤耕作后杂草的出苗模式。在该模型中，休眠解除、萌发和出土前生长的连续过程在单独的模块中进行建模。模型的输入变量为：土壤耕作日期、土壤温度和土壤穿透阻力。模型的输出变量为：幼苗密度和幼苗出苗时间。利用先前田间和实验室实验的数据对该模型进行了参数化，用于蓼、藜和田野菟丝子。该模型通过一项实验的数据进行评估，在该实验中，在春季五个日期中的某一天仅进行一次耕作的田间小区中监测了蓼、藜和田野菟丝子的出苗情况。在对幼苗出苗进行田间观察的同时，通过测试埋在信封中的种子批次的萌发情况，评估了埋藏杂草种子的种子休眠的季节性变化。通过田间观察与模拟数据的比较，发现该模型高估了春季休眠解除的速率，而出苗和出土前生长模拟得较好。因此，一般来说，当不模拟休眠而是从实验数据中引入休眠时，可以准确预测出苗幼苗的数量和出苗时间。杂草田间出苗预测的改进应主要集中在提高休眠解除模拟的精度上。发现苗床温度与幼苗出苗的程度和速率之间存在密切相关性，但用模拟模型分析表明，它们仅部分基于因果关系，因此其预测价值有限。
