多参数环境因子对黄瓜叶面湿度影响研究
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摘要
为研究在日光温室环境下多因子对黄瓜叶面湿度影响情况,采用人造叶片电阻模拟叶面湿度值,试验针对天津地区日光温室环境安装小气候检测设备,分别对温室内湿度群数据(空气湿度RH,叶片湿度RHL,土壤湿度RH_(10)、RH_(20)、RH_(30)、RH_(40))和温度群数据(空气温度T,土壤温度T_(10)、T_(20)、T_(30)、T_(40)),以及太阳辐射W进行数据采集,通过相关分析和主成分分析方法探讨各指标之间的关系。结果表明,除空气温度T和土壤温度T_(40)与土壤湿度RH_(30)以及土壤温度T_(20)与太阳辐射W间无显著相关性(P>0.05)外,其他指标间均存在极显著的相关性(P<0.01);经主成分可将12个指标分为3个主成分,主成分I为土壤温度指标(T_(10)、T_(20)、T_(30)、T_(40))和土壤湿度指标中的RH_(10)、RH_(20)、RH_(40),主成分Ⅱ为空气温湿度指标(T、RH)、太阳辐射指标(W)和叶片湿度指标(RHL),主成分Ⅲ为土壤湿度指标中的RH_(30)。综合而言,本试验所选11个环境因子指标中,叶面湿度受空气温湿度和太阳辐射的影响较大,主要表现为空气温度和太阳辐射高,空气湿度低,则叶面湿度亦低,其他环境因子指标对其影响相对较小。
In order to study the influence of multi-factors on cucumber leaf humidity in solar greenhouse environment, artificial leaf resistance was used to simulate leaf humidity. A microclimate detection device was installed in Tianjin solar greenhouse environment.The humidity group data(air humidity RH, leaf humidity RHL, soil humidity RH_(10), RH_(20), RH_(30), RH_(40)), temperature group data(air temperature, soil temperature T_(10), T_(20), T_(30), T_(40)), and solar radiation(W) were collected respectively, the relationship between the indicators were explored by correlation analysis and principal component analysis. The results showed that there was a significant correlation among all the 12 indices in this experiment(P<0.01), except soil moisture RH_(30) and air temperature(T)(P>0.05), soil moisture RH_(30) and soil temperature(T_(40))(P >0.05), soil temperature(T_(20)) and solar radiation(W)(P >0.05). According to the principal component analysis,the 12 indices were divided to three principal components,in which the principal component I included soil temperature index(T_(10), T_(20),T_(30), T_(40)) and three soil moisture index(RH_(10), RH_(20), RH_(40)), the principal component Ⅱ included air temperature(T), air humidity(RH),solar radiation(W) and leaf humidity(RHL), the principal component Ⅲ included only one soil moisture index(RH_(30)). Generally speaking,among the 11 enviroment factor indexes selected in this experiment, the leaf humidity(RHL) was greatly affected by air temperature, humidity and solar radiation, and the main manifestations were that higher the air temperature and solar radiation were, lower the air humidity was, the leaf humidity was also lower; the other 8 indicators had relatively small impacts on the leaf humidity(RHL).
In order to study the influence of multi-factors on cucumber leaf humidity in solar greenhouse environment, artificial leaf resistance was used to simulate leaf humidity. A microclimate detection device was installed in Tianjin solar greenhouse environment.The humidity group data(air humidity RH, leaf humidity RHL, soil humidity RH_(10), RH_(20), RH_(30), RH_(40)), temperature group data(air temperature, soil temperature T_(10), T_(20), T_(30), T_(40)), and solar radiation(W) were collected respectively, the relationship between the indicators were explored by correlation analysis and principal component analysis. The results showed that there was a significant correlation among all the 12 indices in this experiment(P<0.01), except soil moisture RH_(30) and air temperature(T)(P>0.05), soil moisture RH_(30) and soil temperature(T_(40))(P >0.05), soil temperature(T_(20)) and solar radiation(W)(P >0.05). According to the principal component analysis,the 12 indices were divided to three principal components,in which the principal component I included soil temperature index(T_(10), T_(20),T_(30), T_(40)) and three soil moisture index(RH_(10), RH_(20), RH_(40)), the principal component Ⅱ included air temperature(T), air humidity(RH),solar radiation(W) and leaf humidity(RHL), the principal component Ⅲ included only one soil moisture index(RH_(30)). Generally speaking,among the 11 enviroment factor indexes selected in this experiment, the leaf humidity(RHL) was greatly affected by air temperature, humidity and solar radiation, and the main manifestations were that higher the air temperature and solar radiation were, lower the air humidity was, the leaf humidity was also lower; the other 8 indicators had relatively small impacts on the leaf humidity(RHL).
引文
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[2]王慧,李梅兰,许建平,等.基于冠层温湿度模型的日光温室黄瓜霜霉病预警方法[J].应用生态学报,2015(10):3027-3034.
[3]王慧,陈梅香,李文勇,等.不同天气条件下黄瓜日光温室温湿度空间分布研究[J].北方园艺,2015(17):41 46.
[4]董志南,郑拴宁,赵会兵,等.基于空间插值的风场模拟方法比较分析[J].地球信息科学,2015,17(1):37-43.
[5]王虎,许哲,郭静,等.玉米品种多环境测试数据的空间插值分析[J].玉米科学,2012,20(6):143-148.
[6]凤舞剑.剖析温湿度与温室蔬菜病虫害的相关及应对措施[J].现代化农业,2009(10):7-8.
[7]齐志广.塑料温室生态环境调控技术的研究[J].生态农业研究,1997,5(2):57-60.
[8]王洪山.控制日光温室温湿度防控黄瓜霜霉病技术[J].中国农技推广,2013(8):45-46.
[9]杨卫中,王一鸣,董乔雪,等.大型联栋温室环境参数的线性时不变系统建模[J].农业工程学报,2010,26(14):285-289.
[10]徐立鸿,苏远平,梁毓明.面向控制的温室系统小气候环境模型要求与现状[J].农业工程学报,2013,29(19):1-15.
[11]王红君,史丽荣,赵辉,等.基于贝叶斯正则化BP神经网络的日光温室温度预测模型[J].湖北农业科学,2015,54(17):4300-4303.
[12]章文波,陈红艳.实用数据统计分析及SPSS12.0应用[M].北京:中国建筑工业出版社,2005.
[13]白青华,王惟晨.张掖日光温室最低温度预报模型的主成分回归法构建[J].中国农学通报,2015,31(32):223-228.
[14]李宁,申双和,黎贞发,等.基于主成分回归的日光温室内低温预测模型[J].中国农业气象,2013,34(3):306-311.
[15]柳芳,王铁,刘淑梅.天津市二代节能型日光温室内部温湿度预测模型:以西青为例[J].中国农业气象,2009,30(S1):86-89.
[16]符国槐,张波,杨再强,等.塑料大棚小气候特征及预报模型的研究[J].中国农学通报,2011,27(13):242-248.
[17]金志凤,符国槐,黄海静,等.基于BP神经网络的杨梅大棚内气温预测模型研究[J].中国农业气象,2011,32(3):362-367.
[18]石文学,王军,张志国,等.灌溉方式对春大棚黄瓜产量、经济效益和灌溉水分生产效率的影响[J].北方园艺,2016(5):56-59.
[19]王慧,许建华,陈梅香,等.基于温湿度模拟数据的日光温室黄瓜病害预警系统[C]//2014年中国植物保护学会年会,2014.
[20]刘婧,毕焕改,李清明,等.土壤湿度对低温下黄瓜幼苗光合作用及抗氧化酶活性的影响[J].植物生理学报,2015,51(12):2247-2254.
[21]陈春宏,向邦银.大棚温室黄瓜生长发育特征研究[J].农业工程学报,2005,12(S2):189-193.