A Soil Temperature Control System for Sapling Study in Alpine Region

A soil temperature control system was designed for sapling study in alpine region and tested in summer, 2009. The system consisted of a power switch, voltage regulator, microcomputer timer, safety relays, temperature control device, temperature sensors, heating cables, fireproofing plastic pipes (PVC), 108 heavy-duty plastic containers and seedlings. The heating cables were held in six 2-layer PVC frames with 25 cm wide, 320 cm long and 25 cm high and three 1-layer frames with 25 cm wide and 320 cm long for 15°C soil temperature treatment, half of the 2-layer frames were used for 20°C and 25°C soil temperature treatments, respectively. Each of the frames was installed at each of ditches with 30 cm wide, 330 cm long and 30 cm deep in size. 12 seedling containers with 20 cm top diameter, 18cm bottom diameter and 25 cm high were homogenously placed at each of the ditches, and spaces between the containers were filled with natural soil. The system was economic, and could increase soil temperatures obviously and uniformly, the maximal and minimal standard errors of soil temperatures were ±0.28 and ±0.05°C at 10cm depth in the containers within each of all the ditches. In the system, aboveground environment was natural, diurnal and monthly soil temperatures varied with changing air temperature, the research results may be better to know the eco-physiological and growth responses of alpine saplings/seedlings to soil warming than that in greenhouse, laboratory, infrared heat lamp and open top chamber.

Design of greenhouse temperature and humidity wireless control system based on CC3200

Referring to the shortages that the process of traditional greenhouse measurement by using thermometer and hygrometer is complex,the measurement result is not accurate,and the control system operation is cumbersome,a greenhouse temperature and humidity(TH)control system based on CC3200 is designed.The system uses FPGA as the main controller,sends the TH signals to the wireless module CC3200 by controlling DHT22.The proposed system realizes the remote transmission of data and the automatic control of system.

Analysis of Variation Characters and Prediction Model of Soil Temperature in Solar Greenhouse

[Objective] The aim was to study the soil temperature changes and its forecast model in greenhouse by solar heat. [Method] Annual and daily variation characters of soil temperature were analyzed in this paper by using the observation data of air temperature out of solar greenhouse and different layers soil temperature in it. The soil temperature (daily maximum, daily minimum and daily mean) forecasting models were also studied. Simulation and test were conducted to the forecast model of soil temperature in the greenhouse. [Result] The annual changes and daily changes of soil temperature of each layer in the greenhouse were in single peak curve. The lower layer temperature changes were smaller than the upper layer. The soil temperature of each layer within the greenhouse was closely related to the relevance of same type temperature outside the greenhouse of the day. Taking the average daily temperature, daily maximum temperature and daily lowest temperature of the day and the day before as forecast factors, soil temperature forecast model of different layer of same type within greenhouse was constructed. The simulation outcome of average daily temperature of each layer within the greenhouse was better than the simulation outcome of highest temperature of corresponding layer, worse than the simulation of lowest temperature of corresponding layer. The highest temperature of lower soil and daily temperature of soil were better than the upper layer. The simulated soil temperature was much more close to the observation when the observation was during 15-30 ℃. In other interval, it was lower than the observation. [Conclusion] The study offered theoretical reference for the growth environment of sunlight greenhouse plantation.

Determining heating pipe temperature in greenhouse using proportional integral plus feedforward control and radial basic function neural-networks

Proportional integral plus feedforward (PI+FF) control was proposed for identifying the pipe temperature in hot water heating greenhouse. To get satisfying control result, ten coefficients must be adjusted properly. The data for training and testing the radial basic function (RBF) neural-networks model of greenhouse were collected in a 1028 m2 multi-span glasshouse. Based on this model, a method of coefficients adjustment is described in this article.

Temperature and Humidity Control in Greenhouses in Desert Areas

Water consumption can be reduced by using a greenhouse for agriculture in desert areas. We analyzed the effect of control of ventilation, sprinkler water, and solar radiation?shielding on changes of temperature and humidity in a greenhouse under various desert area conditions. We calculated the changes in temperature and humidity in a greenhouse for a whole day in four seasons, and the calculation results of water consumption with and without a greenhouse were compared. When ventilation, shielding, and sprinkler water were controlled under suitable conditions to grow orchids in a desert area, water consumption in July was only 7% of that without a greenhouse.

Greenhouse Environmental Control Using Optimized, Modeled and Simulated Fuzzy Logic Controller Technique in MATLAB SIMULINK

The main objective of this study is the control of the agricultural greenhouse in view of the economic interest generated by such an activity. A simulation model is developed, gathering all the external and internal climatic conditions that influence the microclimate of the greenhouse to predict the temporal evolution of the state variables characterizing this microclimate. The fuzzy control is an alternative to the approaches proposed by the automatic for the control of complex systems. The performance objectives of the looped systems and the corresponding actions are summarized in the form of rules of expertise, which are spelled out in plain language. This technique thus makes it possible to dispense with the use of mathematical models which are sometimes difficult to obtain. Our objective is the multivariable strategy synthesis and the fuzzy application to a multivariate system （MIMO ~ such as the agricultural greenhouse.） First, the principles of fuzzy logic and fuzzy control are recalled. The origins of non-Linearitys of the command are explained. One of the practical problems of this technique is the combinatorial explosion of the rule base when the number of variables involved becomes large. A solution to simplify the complexity of the system is presented together with an optimization algorithm to automatically adjust the parameters of the fuzzy controller. The last part is devoted to the synthesis of an optimal control of the greenhouse in order to compare it to the fuzzy control implemented.

Technology issues and prevention strategies on sunlight greenhouse vegetable

Energy-saving solar greenhouse vegetables cultivating is to create and improve microclimate environment with greenhouse in those seasons impossible for open cultivation production and in order to achieve the purpose of harvest in advance or in delay. Since a greenhouse needs huge construction expenses and high production costs, only though the improvement of facility utilization can we obtain better economic benefits. Vegetable germination and seedling stage need a long time for ground, so they need smaller standing area. So we concentrated in a small area of cultivation can not only create a suitable environment easily, nurture strong age seedling, but also can avoid greenhouse waste. Make transplanting to greenhouse after Seedlings breeding can effectively reduce the fertility cycle and substantially increase greenhouse utilization.

Improved root zone temperature buffer capacity enhancing sweet pepper yield via soil-ridged substrate-embedded cultivation in solar greenhouse

A novel soilless cultivation method,called as soil-ridged substrate-embedded cultivation(SSC)was invented,and an experiment was designed to investigate root zone temperature and production efficiency of sweet pepper cultivated by two SSC patterns,i.e.,SSC-P(polyethylene groove inserted)and SSC-W(wire-mesh groove inserted),and also other two cultivation methods,i.e.,soil ridge(SR)and naked polyethylene groove(PG).Results showed that PG,SSC-P and SSC-W increased the average minimal root zone temperature by 1.01℃,0.75℃,and 1.16℃ compared to SR(16.33℃)during March 16-20,2015.During June 1-5,SSC-P and SSC-W decreased the average maximal root zone temperature by 1.28℃ and 1.29℃ compared to SR(34.99℃),while PG increased it by 1.44℃.PG,SSC-P,and SSC-W decreased the differences of average daytime and night time temperatures by 1.34℃,2.13℃,and 2.88℃ compared to SR(4.56℃)during early stage.However,SSC-P and SSC-W decreased temperature differences of average daytime and night time by 0.9℃ and 1.07℃ compared to SR(0.95℃)during later stage,but PG improved by 2.85℃.Temperature difference of daytime and night time of SSC-W was minimal,and the temperature difference between the diurnal highest and the lowest temperature of SSC-W was also minimal.The buffer capacity of SSC-W was slightly better than that of SSC-P.SSC-W significantly improved the growth of sweet pepper compared to SR.Similarly,fruit yield per square meter of sweet pepper cultivated on SSC-P and SSC-W improved by 21.24%and 50.33%,respectively compared to SR(3.06 kg/m^(2)),while PG lowered the yield by 13.72%.SSC-W was a better SSC pattern compared with SSC-P in terms of production efficiency.

Robust model predictive control for greenhouse temperature based on particle swarm optimization

Application of model predictive control(MPC)in horticultural practice requires detailed models.However,even highly sophisticated greenhouse climate models are often known to have unknown dynamics affected by bounded uncertainties.To enforce robustness during the controller design stage,this paper proposes a particle swarm optimization(PSO)-based robust MPC strategy for greenhouse temperature systems.The strategy is based on a nonlinear physical temperature affine model.The robust MPC technique requires online solution of a minimax optimal control problem,which optimizes the tradeoff between set point tracking and cost requirements reduction.The minimax optimization problem is reformulated to a nonlinear programming problem with constraints.PSO is used to solve the reformulated problem and priority ranking of constraint fitness is proposed to guarantee that the constraints are satisfied.The results of simulations performed using the proposed control system show that the controller can effectively achieve the set point in the presence of disturbances and that it offers more suitable control variables,higher control precision,and stronger robustness than the conventional MPC.

LED supplementary strategy based on hourly light integral for improving the yield and quality of greenhouse strawberries

Supplemental lighting is critical to the growth of greenhouse crops under the environmental conditions of low temperatures combined with weak radiation during the winter and spring seasons.To achieve the essential daily light integral(DLI)for greenhouse crop growth,a supplemental light strategy was proposed based on hourly light integral(HLI).The target HLI was calculated by dividing the target DLI by the duration of light exposure,while the actual HLI was obtained by accumulating the Photosynthetic Photon Flux Density(PPFD)based on real-time monitoring.Subsequently,the supplemental lighting duration for the next hour was determined by the difference between the target HLI and the actual HLI from all previous periods.Furthermore,the supplementary lighting strategy incorporated maximum values for both PPFD and temperature,and the supplemental light was withheld whenever the actual PPFD or temperature exceeded these values.An experiment was conducted on strawberries in a commercial greenhouse,targeting a DLI of 12.6 mol/(m2∙d),with no supplemental lighting as the control.The results indicated that LED supplemental lighting based on HLI increased the DLI to approximately10 mol/(m2∙d)and raised the strawberry canopy temperature by 1°C-2°C.Compared to the control treatment,the LED supplemental lighting based on HLI significantly improved the net photosynthetic rate,stem thickness,number of leaves,leaf length,and leaf width of the strawberry plants.Additionally,the fruit yield per plant,soluble solids content,and sugar-acid ratio in the supplemental lighting treatment increased by 32%,21%,and 33%,respectively.Thus,LED supplemental lighting based on HLI is an effective strategy for improving the yield and quality of greenhouse crop production.

Fluxes of CH4 and N_2O from soil under a tropical seasonal rain forest in Xishuangbanna, Southwest China

CH4 and N2O fluxes from soil under a tropical seasonal rain forest in Xishuangbanna, Southwest China were measured for one year using closed static chamber technique and gas chromatography method. Three treatments were set in the studied field： （A） litter-free, （B） with litter, and （C） with litter and seedling. The results showed that the soil in our study was a sink of atmospheric CH4 and source of atmospheric N2O. The observed mean CH4 fluxes from treatments A, B, and C were -50.0 ± 4.0, -35.9 ± 2.8, -31.6 ± 2.8 μgC/（m^2·h）, respectively, and calculated annual fluxes in 2003 were -4.1, -3.1, and -2.9 kgC/hm^2, respectively. The observed mean N2O fluxes from treatments A, B, and C were 30.9 ± 3.1, 28.2 ± 3.5, 50.2±3.7 μgN/（m^2·h）, respectively, and calculated annual fluxes in 2003 were 2.8, 2.6, and 3.7 kgN/hm^2, respectively. Seasonal variations in CH4 and N2O fluxes were significant among all the three treatments. The presence of litter decreased CH4 uptake during wet season （P 〈 0.05）, but not during dry season. There was a similar increase in seedlings-mediated N2O emissions during wet and dry seasons, indicating that seedlings increased N2O emission in both seasons. A strong positive relationship existed between CH4 fluxes and soil moisture for all the three treatments, and weak relationship between CH4 fluxes and soil temperature for treatment B and treatment C. The N2O fluxes correlated with soil temperature for all the three treatments.

Responses of greenhouse gas fluxes to experimental warming in wheat season under conventional tillage and no-tillage fields

Understanding the effects of warming on greenhouse gas（GHG, such as N2O, CH4 and CO2 ）feedbacks to climate change represents the major environmental issue. However, little information is available on how warming effects on GHG fluxes in farmland of North China Plain（NCP）. An infrared warming simulation experiment was used to assess the responses of N2O, CH4 and CO2 to warming in wheat season of 2012–2014 from conventional tillage（CT） and no-tillage（NT） systems. The results showed that warming increased cumulative N2O emission by 7.7% in CT but decreased it by 9.7% in NT fields（p 〈 0.05）. Cumulative CH4 uptake and CO2 emission were increased by 28.7%–51.7% and 6.3%–15.9% in both two tillage systems,respectively（p 〈 0.05）. The stepwise regressions relationship between GHG fluxes and soil temperature and soil moisture indicated that the supply soil moisture due to irrigation and precipitation would enhance the positive warming effects on GHG fluxes in two wheat seasons.However, in 2013, the long-term drought stress due to infrared warming and less precipitation decreased N2O and CO2 emission in warmed treatments. In contrast, warming during this time increased CH4 emission from deep soil depth. Across two years wheat seasons, warming significantly decreased by 30.3% and 63.9% sustained-flux global warming potential（SGWP） of N2O and CH4 expressed as CO2 equivalent in CT and NT fields, respectively. However, increase in soil CO2 emission indicated that future warming projection might provide positive feedback between soil C release and global warming in NCP.

坡地面栽培对日光温室土壤温度环境的影响

以平地面温室为对照,对坡地面温室土壤白天蓄热期间的温度变化和蓄热量变化进行研究,以期为老旧日光温室的改造提供参考。结果表明:坡地面温室明显改善了日光温室土壤温度环境,与平地面温室相比,坡地面温室日提高土壤温度0.1~1.7℃,日最高土壤温度提高1.0~1.9℃,日降低冠层上部空气温度1.9~4.0℃,日增大土壤蓄热量8.44%~44.57%。晴天土壤温度和蓄热量的增加幅度大于阴天。

Review on the Impact of Climate Change on Great Lakes Region’s Agriculture and Water Resources

This study investigates the multifaceted impacts of climate change on the Midwest region of the United States, particularly the rising temperatures and precipitation brought about by hot weather activities and technological advances since the 19th century. From 1900 to 2010, temperatures in the Midwest rose by an average of 1.5 degrees Fahrenheit, which would also lead to an increase in greenhouse gas emissions. Precipitation is also expected to increase due to increased storm activity and changes in regional weather patterns. This paper explores the impact of these changes on urban and agricultural areas. In urban areas such as the city of Chicago, runoff from the increasing impervious surface areas poses challenges to the drainage system, and agriculture areas are challenged by soil erosion, nutrient loss, and fewer planting days due to excessive rainfall. Sustainable solutions such as no-till agriculture and the creation of grassland zones are discussed. Using historical data, recent climate studies and projections, the paper Outlines ways to enhance the Midwest’s ecology and resilience to climate change.

炭基肥对老茶园土壤有机碳矿化温度敏感性的影响

采取室内恒温培养法,以施用炭基肥(BF)、不施炭基肥(CK)的40a茶园土壤为研究对象,设定15℃、25℃和35℃共3种不同温度场景,连续监测土壤有机碳(soil organic carbon,SOC)矿化特征并分析有机碳矿化温度敏感性,为评估老茶园固碳减排及障碍消减提供参考。结果表明:(1)炭基肥提升了温变场景下茶园土壤pH值和SOC含量。15℃、25℃和35℃培养温度下,BF处理的土壤pH值较CK处理分别增加0.45、0.07和0.28个单位;BF处理的SOC含量较CK处理分别提高22.19%、16.65%和25.50%。(2)炭基肥增加了温变场景下茶园SOC累计矿化量、潜在矿化势(C_(S))及土壤呼吸强度,对SOC矿化呈现正激发效应。15℃、25℃和35℃培养温度下,BF处理的SOC累计矿化量较CK处理分别提高15.61%、46.51%和36.89%。BF处理的C_(S)值随温度升高呈现先增加后减少的变化趋势,25℃培养温度下BF处理的C_(S)值较15℃和35℃培养温度下分别提高147.11%和29.21%。(3)炭基肥降低温度升高处理下茶园SOC矿化温度敏感性。25~35℃温度范围内,BF处理的Q_(10)(土壤有机碳矿化温度敏感性)值较CK处理降低6.25%;BF处理在25~35℃温度范围内Q_(10)值较15~25℃温度范围内的Q_(10)值降低25%。说明施用炭基肥可有效改良40a茶园土壤理化性质,增加土壤固碳,并提升茶园土壤碳库应对温度变化的稳定性,炭基肥利于优化低产老龄茶园可持续生产管理。

基于窄带物联网的茶叶灭虫控制系统研究

为克服当前物联网在丘陵地区农业生产过程中存在通信距离短、消耗功率大、终端数量易饱和等问题,以茶叶虫害防治为研究对象,将窄带物联网技术与农业生产相结合,实时精准监测土壤温湿度,并根据土壤温湿度数据变化远程控制茶叶灭虫电磁阀启闭状态,设计了智能茶叶灭虫控制系统,并优化了超级电容太阳能电源管理、无线传感网络监测、远程监测控制等核心技术及关键模块。试验结果表明:系统运行稳定,能通过窄带物联网技术实时监测、传输土壤温湿度信息,终端可实时远程控制茶叶灭虫电磁阀,实时启闭茶叶灭虫系统,达到了实时精准监测和远程控制的目的。研究弥补了当前物联网在农业生产中应用的不足,提高了太阳能电源使用效率,延长了蓄电池使用寿命,可为我国智慧农业发展提供参考。

基于模糊PID算法的食用菌大棚温度控制系统研究

食用菌大棚温度控制系统是一个具有时滞性的复杂系统,传统的开关量或常规PID控制很难满足设计要求。该研究设计一种基于STM32F103CRT6单片机为控制核心,加入模糊自适应PID控制算法,利用DHT11温湿度传感器进行温度实时采集,单片机运算处理,光耦固态继电器驱动电路对热风机进行控制,从而达到温度调节的目的。并在MATLAB/simulink环境下建立常规PID控制和模糊自适应PID控制的仿真模型,通过仿真结果,对比验证了该方法比常规PID控制方法具有低超调量和调节时间短等较好的控制效果。

基于主元分析的温室物联网空气温湿度传感器故障诊断

针对温室物联网测控系统中空气温湿度传感器受恶劣环境影响易发生故障的问题,研究温室物联网测控系统中空气温湿度传感器的故障诊断,保障温室物联网测控系统整体工作的稳定可靠性,提出一种基于主元分析的空气温湿度传感器故障诊断方法。首先对空气温湿度传感器数据进行主元分析,通过监控平方预测误差统计量的变化实现传感器的故障检测;再针对检测出的空气温湿度传感器故障数据,利用加权后的平方预测误差统计量来计算传感器的累积贡献率,并将其作为传感器故障识别的指标,识别出现故障的空气温湿度传感器。利用空气温湿度传感器数据在不同故障条件下进行传感器故障诊断方法验证,验证结果表明:所提方法可用于温室物联网测控系统中空气温湿度传感器偏差故障和漂移故障的检测,偏差故障的检测效果要好于漂移故障,偏差故障综合检测率为100%,漂移故障综合检测率为51.25%;同时所提方法能够正确识别出故障传感器,有效提高温室物联网测控系统中空气温湿度传感器故障诊断结果的准确性。

信息物理系统(cyber-physical system)时空建模方法及在温室控制中的应用

传统农业采用人工方式对温室进行控制,但是随着现代农业的快速发展,这种人工投入大、精度低的控制方式已不能满足现代农业需要。该文基于分层有限状态机和事件晶格的概念,建立3层的信息物理系统模型,并提出一种基于分层有限状态机的信息物理系统时空建模方法,同时利用该建模方法开发了新的温室控制系统。该系统能够将物理层传感器感知到的温室物理环境数据通过物理-信息层汇聚节点融合后上报信息层决策节点得到决策信息,物理-信息层控制节点分析决策信息得到控制信息后下传物理层执行器进行控制。由于该系统模型考虑了各层状态机中事件的时空属性,能够将温室控制的正确率由传统基于物联网的温室控制方法的80.20%提高到87.20%,错误肯定率和错误否定率由7.50%和12.30%下降到3.60%和9.20%,保障温室环境满足作物生长对温度、湿度和光照的要求。

基于模糊自适应控制的温室温度调控

为了实现温室在冬季时温度控制精度高、能耗小的目标,该研究提出了一种将热量平衡原理与模糊控制相结合的模糊自适应控制方法,在模糊控制器中加入基于热量平衡方程的输出隶属度函数修正模块,通过监测温室内外温度数据,在上位机中对模糊控制器中的输出隶属度函数进行自适应调整,最终使温室温度稳定在目标温度。结果表明,基于热量平衡方程的温室温度模糊自适应控制系统具有较好的稳定性和准确性,在设置20℃为目标温度值的情况下,基于热量平衡方程的模糊自适应控制最终使温室温度稳定在(19.8±0.11)℃,一般模糊控制方法最终使温室温度稳定在(13.5±0.5)℃,无法达到目标环境温度值,而阈值控制最终使温室温度稳定在(20.0±0.85)℃;同时,基于热量平衡方程的温室温度模糊自适应控制能耗较低,且能量利用率更高,模糊自适应控制能量利用率为45.97%,而阈值能量利用率仅为20.21%。研究提出的基于热量平衡方程的模糊自适应控制方法不仅满足温室温度调控需求,而且能够提高能量利用率,降低能耗。