压砂地西瓜光合作用干物质及产量水氮耦合模型及验证

为探明压砂地西瓜光合作用机理以及水氮条件对压砂地西瓜干物质积累和产量的影响,于2009年进行了桶栽对比试验,用高斯积分法计算冠层每日总光合同化量的方法建立压砂地西瓜光合作用干物质累积模型,并用试验实测值对模型进行验证。同时建立水氮耦合回归模型并进行验证。结果表明:1)光合作用干物质模型均方根误差(root mean square of error,RMSE)为22.5 kg/hm~2,相对均方根误差(normalized RMSE,n RMSE)为14.5%,相关系数(correlation coefficient,r)为0.89;2)当蒸发蒸腾量ET≥213~513.8 mm、可利用氮量N≥...

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Published in农业工程学报 Vol. 32; no. 20; pp. 129 - 136
Main Author 马波 田军仓 沈晖 李王成
Format Journal Article
LanguageChinese
Published 宁夏大学土木与水利工程学院,银川 750021 2016
宁夏节水灌溉与水资源调控工程技术研究中心,银川 750021
教育部旱区现代农业水资源高效利用工程研究中心,银川 750021
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Summary:为探明压砂地西瓜光合作用机理以及水氮条件对压砂地西瓜干物质积累和产量的影响,于2009年进行了桶栽对比试验,用高斯积分法计算冠层每日总光合同化量的方法建立压砂地西瓜光合作用干物质累积模型,并用试验实测值对模型进行验证。同时建立水氮耦合回归模型并进行验证。结果表明:1)光合作用干物质模型均方根误差(root mean square of error,RMSE)为22.5 kg/hm~2,相对均方根误差(normalized RMSE,n RMSE)为14.5%,相关系数(correlation coefficient,r)为0.89;2)当蒸发蒸腾量ET≥213~513.8 mm、可利用氮量N≥172.1~226.9 kg/hm~2时,水氮耦合压砂地西瓜干物质积累模型和产量模型的n RMSE均〈20%,R2约0.8,说明水氮耦合干物质和产量模型的可靠性。所建立的光合作用干物质累积模型和水氮耦合模型在一定条件下能够准确的预测压砂地西瓜干物质累积和经济产量,但光合作用模型更具有广泛的适用性。
Bibliography:11-2047/S
Ma Bo, Tian Juncang, Shen Hui, Li Wangcheng (1. College of Civil and Hydraulic Engineering, Ningxia University, Yinchuan 750021, China; 2.Ningxia Research Center of Technology on Water-saving Irrigation and Water Resource Regulation, Yinchuan 750021, China; 3. Efficient Use of Water Resources in Arid Modern Agriculture Ministry of Educational Engineering Research Center, Yinchuan 750021, China)
Gravel-mulched field is typical in Northwest of China for watermelon production. Few studies are on dry matter and yield models establishment of watermelon in gravel-mulched field, which is good for prediction of watermelon growth and yield. This study aimed to establish the dry matter and yield models for watermelon in gravel-mulched field based on photosynthesis and water-N coupling. Two experiments were designed in 2009. One was for photosynthesis-based dry matter model validation(Exp. 1) and the other was for water-N coupling model validation(Exp. 2). The experiments were conducted under a rain shelter in o
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2016.20.017