李 明, 赵春江, 乔 淑, 钱建平, 杨信廷. 基于冠层相对湿度的日光温室黄瓜叶片湿润时间估计模型[J]. 农业工程学报, 2010, 26(9): 286-291.
    引用本文: 李 明, 赵春江, 乔 淑, 钱建平, 杨信廷. 基于冠层相对湿度的日光温室黄瓜叶片湿润时间估计模型[J]. 农业工程学报, 2010, 26(9): 286-291.
    Li Ming, Zhao Chunjiang, Qiao Shu, Qian Jianping, Yang Xinting. Estimation model of leaf wetness duration based on canopy relative humidity for cucumbers in solar greenhouse[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(9): 286-291.
    Citation: Li Ming, Zhao Chunjiang, Qiao Shu, Qian Jianping, Yang Xinting. Estimation model of leaf wetness duration based on canopy relative humidity for cucumbers in solar greenhouse[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010, 26(9): 286-291.

    基于冠层相对湿度的日光温室黄瓜叶片湿润时间估计模型

    Estimation model of leaf wetness duration based on canopy relative humidity for cucumbers in solar greenhouse

    • 摘要: 叶片湿润时间是日光温室作物病害预警系统的关键输入,基于相对湿度的叶片湿润时间估计模型(简称RH阈值模型)是最简便的估计模型之一。为了在日光温室实际环境中对模型参数进行校准和检验,以夏末秋初的日光温室盛果期迷你黄瓜为试材,以5 min为间隔自动采集冠层相对湿度数据,采用试错法、平均值法和叶湿频率法3种校准方法对RH阈值进行校准,分别获得相对湿度RH=90%、89%和93% 3个阈值,并采用均方根误差法、回归分析法以及一系列误差分析指标对校准结果进行检验。结果表明:试错法和平均值法的预测效果要显著好于叶湿频率法,误差一般在1~2 h左右;与本试验中普遍超过3 h的叶片湿润时间相比,RH阈值模型监测效果仍然可接受;验证结果中,平均值法的效果反而好于试错法,这说明在实际应用中不能仅局限于一种校准方法。该文总结的模型校准和检验方法,以及构建的基于冠层相对湿度的叶片湿润时间估计模型,可以用于日光温室黄瓜叶片湿润时间监测,符合日光温室黄瓜病害预警系统的要求。

       

      Abstract: The leaf wetness duration (LWD) is a key input factor of disease warning systems for crops in solar greenhouses. The LWD estimation model based on canopy relative humidity (RH threshold model) is one of the easiest models. To calibrate and validate the model in real greenhouse conditions, the experiment was conducted in the solar greenhouse during late summer and early autumn with mini cucumber at fruit harvesting stage. The relative humidity (RH) data were obtained automatically at every five-minute interval. The trial-and-error method, average value method and the method based on frequency of leaf wetness were used to calibrate the RH threshold, and then RH thresholds were obtained including 90%, 89% and 93%, respectively. In addition, the calibration results were validated by root mean square error (RMSE), regression analysis and a series of error analysis indicators. The results showed that the estimation effects of trial-and-error approach and average value approach were better than the method based on frequency of leaf wetness, and the errors were around 1–2 h. Compared with the leaf wetness duration that was over 3 h, the monitoring effects of RH threshold model were acceptable. However, from the validation results, the estimation effects of average value approach were better than trial-and-error approach, which indicated that it was impossible to apply only one calibration method in practice. The calibration and validation methods and the estimation model of leaf wetness duration based on canopy relative humidity can be used for monitoring leaf wetness duration of cucumbers and meet the requirement of cucumber disease early warning systems in solar greenhouses.

       

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