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基于参考作物蒸散量的新区域棉花生长模型,用于预测生长过程。

A new regional cotton growth model based on reference crop evapotranspiration for predicting growth processes.

机构信息

State Key Laboratory of Eco-Hydraulics in Northwest Arid Region, Xi'an University of Technology, Xi'an, 710048, China.

Xinjiang Irtysh River Basin Development and Construction Administrative Bureau, Urumqi, The Xinjiang Uygur Autonomous Region, Ürümqi, 830000, China.

出版信息

Sci Rep. 2023 May 5;13(1):7368. doi: 10.1038/s41598-023-34552-7.

Abstract

Meteorological conditions and irrigation amounts are key factors that affect crop growth processes. Typically, crop growth and development are modeled as a function of time or growing degree days (GDD). Although the most important component of GDD is temperature, it can vary significantly year to year while also gradually shifting due to climate changes. However, cotton is highly sensitive to various meteorological factors, and reference crop evapotranspiration (ET) integrates the primary meteorological factors responsible for global dryland extension and aridity changes. This paper constructs a cotton growth model using ET, which improves the accuracy of crop growth simulation. Two cotton growth models based on the logistic model established using GDD or ET as independent factors are evaluated in this paper. Additionally, this paper examines mathematical models that relate irrigation amount and irrigation water utilization efficiency (IWUE) to the maximum leaf area index (LAI) and cotton yield, revealing some key findings. First, the model using cumulative reference crop evapotranspiration (CET) as the independent variable is more accurate than the one using cumulative growing degree days. To better reflect the effects of meteorological conditions on cotton growth, this paper recommends using CET as the independent variable to establish cotton growth models. Secondly, the maximum cotton yield is 7171.7 kg/ha when LAI is 6.043 cm/cm, the corresponding required irrigation amount is 518.793 mm, and IWUE is 21.153 kg/(ha·mm). Future studies should consider multiple associated meteorological factors and use ET crop growth models to simulate and predict crop growth and yield.

摘要

气象条件和灌溉量是影响作物生长过程的关键因素。通常,作物生长和发育被建模为时间或生长度日(GDD)的函数。尽管 GDD 的最重要组成部分是温度,但它会因年而异,而且由于气候变化,它也会逐渐发生变化。然而,棉花对各种气象因素非常敏感,参考作物蒸散量(ET)综合了导致全球旱地扩展和干旱变化的主要气象因素。本文使用 ET 构建了棉花生长模型,提高了作物生长模拟的准确性。本文评估了基于 GDD 或 ET 作为独立因素建立的 logistic 模型的两个棉花生长模型。此外,本文研究了与灌溉量和灌溉水利用效率(IWUE)与最大叶面积指数(LAI)和棉花产量相关的数学模型,揭示了一些关键发现。首先,使用累积参考作物蒸散量(CET)作为自变量的模型比使用累积生长度日的模型更准确。为了更好地反映气象条件对棉花生长的影响,本文建议使用 CET 作为自变量来建立棉花生长模型。其次,当 LAI 为 6.043 cm/cm 时,最大棉花产量为 7171.7 kg/ha,所需的灌溉量为 518.793 mm,IWUE 为 21.153 kg/(ha·mm)。未来的研究应考虑多个相关气象因素,并使用 ET 作物生长模型模拟和预测作物生长和产量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bb5/10163061/00bb4e73412e/41598_2023_34552_Fig1_HTML.jpg

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