基于生长模型的温室黄瓜氮素管理决策支持系统
摘要
氮素是影响作物生长、产量和品质形成的重要营养元素。我国温室作物生产中采用大肥大水的粗放管理方式,不仅导致温室作物生产氮肥利用率低下,而且因氮肥的大量淋洗而造成地下水污染等环境问题。温室作物生产中氮肥管理的优化是提高氮肥利用率、保证作物产量和品质、实现无公害生产的重要措施之一。生长模型可以预测不同氮素供应条件下作物的生长与产量,是作物生产中氮素优化管理决策的有力工具。黄瓜为世界也是我国温室主要栽培作物之一。本研究通过不同氮素处理的试验,对已有的温室黄瓜生长模拟模型进行检验。收集温室周年气象数据、作物信息、栽培管理等信息,建立了系统的数据库。在此基础上,将数据库、温室黄瓜生长模拟模型与氮素优化管理决策模型有机集成,建立了基于生长模型的温室黄瓜氮素管理决策支持系统。并用不同定植期、不同氮素营养液浓度下的温室黄瓜生产实验数据对系统的氮素管理决策进行了案例分析。具体研究结果如下：
(1)模型检验：通过2007年至2008年在上海农科院Venlo型温室里不同氮素处理(40、80、120、160mg·L-1)下的温室黄瓜‘戴多星’的生产实验研究,获取独立完整的试验数据,对现有的氮素对温室黄瓜生长影响的模拟模型进行检验,并分析模型的可靠性和实用性。结果表明,该模型对本试验对叶面积指数、植株总干物质量、果实干重和产量的预测结果与1：1直线之间的R2和RE分别为0.92、0.94、0.93、0.95、12.1%、13.1%、9.7%、9.1%。表明该模型具有较好的预测性和可靠性。
(2)决策模型：将温室黄瓜生长模拟模型与营养液氮素管理优化模型相结合,构建了黄瓜氮素管理决策模型。模型可以根据用户预设定的目标采收期和目标产量Y和温室环境信息计算出盛果期适宜叶片含氮量和对应的营养液浓度。目标产量Y与盛果期叶片含氮量以及对应的营养液浓度的关系如下：Y120=120×(Y/Tday) DW=Y120×DMC/HI/PIF HI=HImax×(1-exp(-c×(TEPab-13))) TEPab>13 b=0.0095+(0.042-0.0095)×exp(-0.044×NL) c=0.025+(0.059-0.025)×exp(-0.058×NL) N%=m×exp (-n/NC)×10
式中DW为黄瓜总干重；Y120为累积采果120天的黄瓜产量。Y为黄瓜目标产量(kg.m-2)；Tday为目标采果天数(day); NC为营养液浓度,mg·L-1；N%为盛果期叶片含氮量,mg·g-1；m为不同定植期黄瓜盛果期叶片含氮量的理论最大值,(mg·g-1)；参数n为负指数曲线的斜率。根据本研究数据,春夏差黄瓜参数m、n取值分别为38、9.4,秋冬茬黄瓜m、n取值为42、11.3。TEPab为一定生长阶段内的累积辐热积(MJ·m-2)；b为果实分配指数相对增加速率,c为采收指数相对增加速率；DMC为黄瓜的干物质含量,即黄瓜的干鲜比,(g·g-1)。
利用不同定植期(春夏茬、秋冬茬)、不同氮素处理浓度下的温室黄瓜生产数据对决策系统进行了案例分析,结果表明：随着目标产量的增大盛果期叶片氮浓度随着增大。春夏茬温室黄瓜120天累积产量稳定在7.2kg.m-2左右,要达到这一目标产量的最小叶片氮浓度为34 mg·g-1,对应的营养液浓度为113 mg·L-1。秋冬茬黄瓜120天累积产量最后稳定在6.5kg·m-2,要达到这一目标产量,盛果期叶片氮浓度最小要32mg·g-1,对应的营养液浓度为82 mg·L-1。
(3)系统的实现：系统以windowsXP为开发平台,利用Microsoft Acesses构建数据库,采用VB语言进行系统编程。系统数据库包括：温室环境数据、作物数据、栽培管理数据；系统模型库包括：氮素对温室黄瓜生长影响模拟模型、氮素管理决策模型。系统的输入信息主要包括温室类型、栽培管理数据和作物品种数据,系统的输出信息主要为盛果期叶片氮浓度、营养液浓度和配方。系统能够根据温室的环境信息、目标产量给出温室黄瓜生产的适宜的氮素管理方案,可以为温室黄瓜生产的氮素优化管理提供决策支持。
Nitrogen is an essential nutrient element which affects the crop growth and the yield and quality. The extensive management used in china greenhouse crop production leads not only to reduction of nitrogen utilization, but also to the environment problems such as the pollution of groundwater caused by the leaching of excessive nitrogen fertilizer. Optimizing the nitrogen management in greenhouse production is one of the most important measures to improve nitrogen utilization, ensure the yield and quality, and achieve the pollution-free production. As a powerful tool to optimize nitrogen management and decision-making in crop production, crop growth model is able to predict the crop growth and yield under various levels of nitrogen supply. Cucumber is one of the major cultivated crops in china. Combined with gathering annual meteorological data, crop information, cultivation management information, etc, the research validates the existed greenhouse cucumber growth simulation model through the experiment of various nitrogen treatments, sets up a systematic data-base, establishes nitrogen management and decision-making system of greenhouse cucumber based on the growth model by organic integration of date-base, greenhouse cucumber growth simulation model and optimized model of nutrient solution nitrogen management. Then experimental data obtained in different planting date and nitrogen concentration of nutrient solution are used to analysis the nitrogen management and decision-making system. The concrete results including:
(1) Model validation:independent and complete experimental data acquired from the practice research of greenhouse cucumber'daiduoxing'under different nitrogen treatments (40,80,120,160mg·L-1) in Shanghai Academy of Agriculture Sciences Venlo-type greenhouse from the year 2007 to 2008 were used to validate the effects of existed nitrogen treatments on greenhouse cucumber growth simulation model and analysis the reliability and practicality. The results showed that the coefficient of determination (R2) and the relative error (RE) between the measured and simulated leaf area index (LAI), total dry weight, fruit dry weight and yield are 0.92,0.94,0.93,0.95 and 12.1%,13.1%,9.7%,9.1%, respectively, indicate preferable predictability and reliability of this model.
(2) Decision model:combining the greenhouse cucumber growth simulation model with optimized nutrient solution nitrogen management model, a decision-making model of cucumber nitrogen management has been established. According to the greenhouse environment information and the user's presetting target harvesting time and target yield Y, the model calculates the suitable leaf nitrogen concentration NL and the corresponded nutrient solution concentration NC. The relationships among Y, NL, and NC can be derived:
Y120=120×(Y/Tday)
DW=Y120*DMC/HI/PIF
N%=m*exp(-n/NC)*10
HI=HImax×(1-exp(-c*(TEPab-13))) TEPab>13
b=0.0095+(0.042-0.0095)×exp(-0.044×NL)
c=0.025+(0.059-0.025)×exp(-0.058×NL)
Where DW is total dry weight, Y120 is the accumulated yield in 120 days. Y, Tday, NC, N%, m, N,10 represent the target yield (kg·m-2), harvest days (day), nutrient solution concentration (mg·L-1), leaf nitrogen concentration (mg·g-1), theoretical maximum value of leaf nitrogen concentration in full fruit period under different planting date, the slope of negative exponential curve, and conversion factor, respectively. According to our research, the parameter m and n took value at 38,9.4 in spring-summer season respectively, and at 42, 11.3 in autumn-winter season respectively.; PIF is portioning index of fruit, HI is harvest index, and TEPab (MJ·m-2) is the accumulated product of thermal effectiveness and PAR during certain growth stage. NL, b, c, DMC represent leaf nitrogen concentration in full fruit period (mg·g-1), relative increasing rate of PIF, relative increasing rate of HI, and cucumber dry matter content (g·g-1).
The case analysis of decision-making model focused on greenhouse cucumber production data obtained from different planting date and various nitrogen concentration treatments, indicated that in full fruit period the leaf nitrogen concentration increases along with the increase of the accumulated yield in 120 days. To attain the target yield that 7.2kg·m-2 in the spring-summer season and 6.5kg·m-2 in the autumn-winter season, the minimum leaf nitrogen concentration at least reached at 34 mg·g-1 and 3.2 mg·g-1 in full fruit period which required the nutrient solution concentration at 113 mg·L-1 and 82 mg·L-1, respectively.
(3) System realization:based on windows XP as a platform, the system uses Microsoft Accesses to construct date-base and adopts VB to system programming. Its database includes greenhouse environment data, crop data, and cultivation management data, while its model base includes the model of simulating the effect of nitrogen on greenhouse cucumber growth, the model of nitrogen management decision-making model. The inputs of the system include the type of greenhouse, crop varieties data and cultivation management data. The outputs of the system contain leaf nitrogen concentration, the concentration and formula of nutrient solution. Base on the greenhouse environmental information and the suitable nitrogen scheme given by the target yield, the system can provide the decision support for the nitrogen optimal management of greenhouse cucumber production.
(1)模型检验：通过2007年至2008年在上海农科院Venlo型温室里不同氮素处理(40、80、120、160mg·L-1)下的温室黄瓜‘戴多星’的生产实验研究,获取独立完整的试验数据,对现有的氮素对温室黄瓜生长影响的模拟模型进行检验,并分析模型的可靠性和实用性。结果表明,该模型对本试验对叶面积指数、植株总干物质量、果实干重和产量的预测结果与1：1直线之间的R2和RE分别为0.92、0.94、0.93、0.95、12.1%、13.1%、9.7%、9.1%。表明该模型具有较好的预测性和可靠性。
(2)决策模型：将温室黄瓜生长模拟模型与营养液氮素管理优化模型相结合,构建了黄瓜氮素管理决策模型。模型可以根据用户预设定的目标采收期和目标产量Y和温室环境信息计算出盛果期适宜叶片含氮量和对应的营养液浓度。目标产量Y与盛果期叶片含氮量以及对应的营养液浓度的关系如下：Y120=120×(Y/Tday) DW=Y120×DMC/HI/PIF HI=HImax×(1-exp(-c×(TEPab-13))) TEPab>13 b=0.0095+(0.042-0.0095)×exp(-0.044×NL) c=0.025+(0.059-0.025)×exp(-0.058×NL) N%=m×exp (-n/NC)×10
式中DW为黄瓜总干重；Y120为累积采果120天的黄瓜产量。Y为黄瓜目标产量(kg.m-2)；Tday为目标采果天数(day); NC为营养液浓度,mg·L-1；N%为盛果期叶片含氮量,mg·g-1；m为不同定植期黄瓜盛果期叶片含氮量的理论最大值,(mg·g-1)；参数n为负指数曲线的斜率。根据本研究数据,春夏差黄瓜参数m、n取值分别为38、9.4,秋冬茬黄瓜m、n取值为42、11.3。TEPab为一定生长阶段内的累积辐热积(MJ·m-2)；b为果实分配指数相对增加速率,c为采收指数相对增加速率；DMC为黄瓜的干物质含量,即黄瓜的干鲜比,(g·g-1)。
利用不同定植期(春夏茬、秋冬茬)、不同氮素处理浓度下的温室黄瓜生产数据对决策系统进行了案例分析,结果表明：随着目标产量的增大盛果期叶片氮浓度随着增大。春夏茬温室黄瓜120天累积产量稳定在7.2kg.m-2左右,要达到这一目标产量的最小叶片氮浓度为34 mg·g-1,对应的营养液浓度为113 mg·L-1。秋冬茬黄瓜120天累积产量最后稳定在6.5kg·m-2,要达到这一目标产量,盛果期叶片氮浓度最小要32mg·g-1,对应的营养液浓度为82 mg·L-1。
(3)系统的实现：系统以windowsXP为开发平台,利用Microsoft Acesses构建数据库,采用VB语言进行系统编程。系统数据库包括：温室环境数据、作物数据、栽培管理数据；系统模型库包括：氮素对温室黄瓜生长影响模拟模型、氮素管理决策模型。系统的输入信息主要包括温室类型、栽培管理数据和作物品种数据,系统的输出信息主要为盛果期叶片氮浓度、营养液浓度和配方。系统能够根据温室的环境信息、目标产量给出温室黄瓜生产的适宜的氮素管理方案,可以为温室黄瓜生产的氮素优化管理提供决策支持。
Nitrogen is an essential nutrient element which affects the crop growth and the yield and quality. The extensive management used in china greenhouse crop production leads not only to reduction of nitrogen utilization, but also to the environment problems such as the pollution of groundwater caused by the leaching of excessive nitrogen fertilizer. Optimizing the nitrogen management in greenhouse production is one of the most important measures to improve nitrogen utilization, ensure the yield and quality, and achieve the pollution-free production. As a powerful tool to optimize nitrogen management and decision-making in crop production, crop growth model is able to predict the crop growth and yield under various levels of nitrogen supply. Cucumber is one of the major cultivated crops in china. Combined with gathering annual meteorological data, crop information, cultivation management information, etc, the research validates the existed greenhouse cucumber growth simulation model through the experiment of various nitrogen treatments, sets up a systematic data-base, establishes nitrogen management and decision-making system of greenhouse cucumber based on the growth model by organic integration of date-base, greenhouse cucumber growth simulation model and optimized model of nutrient solution nitrogen management. Then experimental data obtained in different planting date and nitrogen concentration of nutrient solution are used to analysis the nitrogen management and decision-making system. The concrete results including:
(1) Model validation:independent and complete experimental data acquired from the practice research of greenhouse cucumber'daiduoxing'under different nitrogen treatments (40,80,120,160mg·L-1) in Shanghai Academy of Agriculture Sciences Venlo-type greenhouse from the year 2007 to 2008 were used to validate the effects of existed nitrogen treatments on greenhouse cucumber growth simulation model and analysis the reliability and practicality. The results showed that the coefficient of determination (R2) and the relative error (RE) between the measured and simulated leaf area index (LAI), total dry weight, fruit dry weight and yield are 0.92,0.94,0.93,0.95 and 12.1%,13.1%,9.7%,9.1%, respectively, indicate preferable predictability and reliability of this model.
(2) Decision model:combining the greenhouse cucumber growth simulation model with optimized nutrient solution nitrogen management model, a decision-making model of cucumber nitrogen management has been established. According to the greenhouse environment information and the user's presetting target harvesting time and target yield Y, the model calculates the suitable leaf nitrogen concentration NL and the corresponded nutrient solution concentration NC. The relationships among Y, NL, and NC can be derived:
Y120=120×(Y/Tday)
DW=Y120*DMC/HI/PIF
N%=m*exp(-n/NC)*10
HI=HImax×(1-exp(-c*(TEPab-13))) TEPab>13
b=0.0095+(0.042-0.0095)×exp(-0.044×NL)
c=0.025+(0.059-0.025)×exp(-0.058×NL)
Where DW is total dry weight, Y120 is the accumulated yield in 120 days. Y, Tday, NC, N%, m, N,10 represent the target yield (kg·m-2), harvest days (day), nutrient solution concentration (mg·L-1), leaf nitrogen concentration (mg·g-1), theoretical maximum value of leaf nitrogen concentration in full fruit period under different planting date, the slope of negative exponential curve, and conversion factor, respectively. According to our research, the parameter m and n took value at 38,9.4 in spring-summer season respectively, and at 42, 11.3 in autumn-winter season respectively.; PIF is portioning index of fruit, HI is harvest index, and TEPab (MJ·m-2) is the accumulated product of thermal effectiveness and PAR during certain growth stage. NL, b, c, DMC represent leaf nitrogen concentration in full fruit period (mg·g-1), relative increasing rate of PIF, relative increasing rate of HI, and cucumber dry matter content (g·g-1).
The case analysis of decision-making model focused on greenhouse cucumber production data obtained from different planting date and various nitrogen concentration treatments, indicated that in full fruit period the leaf nitrogen concentration increases along with the increase of the accumulated yield in 120 days. To attain the target yield that 7.2kg·m-2 in the spring-summer season and 6.5kg·m-2 in the autumn-winter season, the minimum leaf nitrogen concentration at least reached at 34 mg·g-1 and 3.2 mg·g-1 in full fruit period which required the nutrient solution concentration at 113 mg·L-1 and 82 mg·L-1, respectively.
(3) System realization:based on windows XP as a platform, the system uses Microsoft Accesses to construct date-base and adopts VB to system programming. Its database includes greenhouse environment data, crop data, and cultivation management data, while its model base includes the model of simulating the effect of nitrogen on greenhouse cucumber growth, the model of nitrogen management decision-making model. The inputs of the system include the type of greenhouse, crop varieties data and cultivation management data. The outputs of the system contain leaf nitrogen concentration, the concentration and formula of nutrient solution. Base on the greenhouse environmental information and the suitable nitrogen scheme given by the target yield, the system can provide the decision support for the nitrogen optimal management of greenhouse cucumber production.
引文
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