Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 478866
Title Predicting the effects of environment and management on cotton fibre growth and quality: a functional–structural plant modelling approach
Author(s) Wang, X.; Zhang, L.; Evers, J.B.; Mao, L.; Wei, S.; Pan, X.; Zhao, X.; Werf, W. van der; Li, Z.
Source AoB Plants 6 (2014). - ISSN 2041-2851 - 16 p.
DOI https://doi.org/10.1093/aobpla/plu040
Department(s) Centre for Crop Systems Analysis
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2014
Keyword(s) lint yield - gossypium-hirsutum - simulation-model - mepiquat chloride - temperature - date - boll - nitrogen - performance - elongation
Abstract 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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