Predicting the effects of environment and management on cotton fibre growth and quality: a functional-structural plant modelling approach

文献类型： 外文期刊

第一作者： Xuejiao Wang

作者： Xuejiao Wang;Lizhen Zhang;Jochem B. Evers;Lili Mao;Shoujun Wei;Xuebiao Pan;Xinhua Zhao;Wopke van der Werf;Zhaohu Li

作者机构：

关键词： Cotton (Gossypium hirsutum);fibre length;fibre strength;functional-structural plant model (FSPM);growth and development;micronaire;simulation model

期刊名称：AOB PLANTS （ 影响因子：3.276； 五年影响因子：3.496 ）

ISSN： 2041-2851

年卷期： 2014 年 6 卷

页码：

收录情况： SCI

摘要： In general, the quality of fruits depends on local conditions experienced by the fruit during its development. In cotton, fruit quality, and more specifically the quality of the fibre in the fruit, depends on interactions between fruit position in the plant architecture, temperature and agronomic practices, such as sowing time, mulching with plastic film and topping of the plant's main stem and branches. To quantify this response of cotton fibre quality to environment and management, we developed a simulation model of cotton growth and development, CottonXL. Simulation of cotton fibre quality (strength, length and micronaire) was implemented at the level of each individual fruit, in relation to thermal time (represented by physiological age of the fruit) and prevailing temperature during development of each fruit. Field experiments were conducted in China in 2007 to determine model parameters, and independent data on cotton fibre quality in three cotton producing regions in China were used for model validation. Simulated values for fibre quality closely corresponded to experimental data. Scenario studies simulating a range of management practices predicted that delaying topping times can significantly decrease fibre quality, while sowing date and film mulching had no significant effect. We conclude that CottonXL may be used to explore options for optimizing cotton fibre quality by matching cotton management to the environment, taking into account responses at the level of individual fruits. The model may be used at plant, crop and regional levels to address climate and land-use change scenarios.

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