PTM-50植物生理生态监测系�?参数-价格-中国粉体罐�/title>

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$(this).css({"color":"#1479d7","border-bottom-color":"#1479d7"}); }); }); </script>  <div class="cpjj"> <h1>前言</h1>PTM-50植物生理生态监测系统在原有PTM-48A基础上升级而来，可长期、自动监测植物的光合速率、蒸腾速率，植物生理生长状态，环境因子，从而得到植物的全面的信息、�/span><h1>主要功能特点</h1>l 系统具备4个自动开合的叶室，可�?/span>20秒内获得叶片皃�/span>CO2�?/span>H2O交换速率、�/span>l 系统标配1个数字通道连接RTH-50多功能传感器（可测定总辐射、光合有效辐射、空气温�?/span>&湿度、露点温度等）、�/span>l 分析单元升级为双通道测量，新款的PTM-50由之前的1个分析器分时测量，升级为2个独立分析器，实时测量参比气和样品气的浓度差，增强了对环墂�/span>CO2�?/span>H2O波动的耐受能力，数据更加稳定可靠、�/span>l 可选的植物生理指标监测传感器以无线方式传送数据，传感器可不�/span>PC独立连接，布设更为灵活、�/span>l 可同时配备叶绿素荧光自动监测模块进行叶绿素荧光实时监测、�/span>l 系统通过2.4GHz RF咋�/span>3G实现无线通讯和网络化、�/span>上图丹�/span>PTM-50系统结构国�/span><h1>应用领域</h1>2 应用于植物生理学、生态学、农学、园艺学、作物学、设施农业、节水农业等研究领域2 比较不同物种、不同品种的差异2 比较不同处理、不同栽培条件对植物的影哌�/span>2 研究植物光合、蒸腾、生长的限制因子2 研究生长环境对植物的影响及植物对环境变化的响库�/span>上图为主机与圆形叶室照片<h1>基本配置组成</h1>1��PTM-50系统控制�?/span>1��电源适配�?/span>1��蓄电池连接线1��RTH-50多功能传感器4��LC-10R叶室，测量面�?/span>10 cm24��4米气体连接管2��1.5米不锈钢支架选配无线传感�?/span>英文软件英文说明�?/span><h1>技术指栆�/span></h1>l 工作方式：自动持续测野�/span>l 叶室取样时间９�/span>20sl CO2测量原理９�/span>双這�/span>道非色散红外气体分析�?/span>l CO2浓度测量范围９�/span>0-1000 ppml CO2交换速率的额定测量范围：-70-70��molCO2m-2s-1l H2O测量原理：集成型空气温度和湿度传感器l 叶室空气流速：0.25L/minl RTH-50 多功能传感器：温�?/span>-10�?/span>60ℂ�/span>；相对湿度：3-100%RH；光合有效辐射：0-2500��molm-2s-1l 测量间隔９�/span>5-120分钟用户自定么�/span>l 存储容量９�/span>1200条数�?/span>，采样频率为30分钟时可存储25�?/span>l 连接管的标准长度９�/span>4m��l 电源９�/span>9 � 24 Vdcl 通讯方式９�/span>2.4GHz RF咋�/span>3G网络通讯l 环境防护级别９�/span>IP55l 可逈�/span>配叶室和传感�?/span>1. LC-10R透明叶室：圆形叶室，面积10cm2，空气流逞�/span>0.23��0.05L/min2. LC-10S透明叶室：矩形叶室，13��77mm＋�/span>10cm2，空气流逞�/span>0.23��0.05L/min3. MP110叶绿素荧光自动监测模块，可自动监测Ft、QY等叶绿素荧光参数4. LT-1 叶面温度传感器：测量范围0-50ℂ�/span>5. LT-4 叶面温度传感器：4个LT-1传感器集成，用以估算叶面平均温度6. LT-IRz 红外温度传感器：范围0-60℃，视野范围5�?7. SF-4 植物茎流传感器：**10ml/h，适用于直�?-5mm茎杆8. SF-5植物茎流传感器：**10ml/h，适用于直徃�/span>4-10mm茎杆9. SD-5 茎杆微变化传感器９�/span>行程0�?mm，适用于直�?-25mm茎杆10. SD-6 茎杆微变化传感器９�/span>行程0�?mm，适用于直�?-7cm茎杆11. SD-10茎杆微变化传感器９�/span>行程0�?0mm，适用于直�?-7cm茎杆12. DE-1 树干生长传感器：行程0�?0mm，适用亍�/span>直径6cm以上树干13. FI-L 大型果实生长传感器：范围30�?60mm，适用于圆形果宝�/span>14. FI-M 中型果实生长传感器：范围15�?/span>90mm，适用于圆形果宝�/span>15. FI-S 小型果实生长传感器：范围7�?/span>45mm，适用于圆形果宝�/span>16. FI-XS 微型果实生长传感器：行程0�?0mm，适用于直徃�/span>4�?0mm的圆形果宝�/span>17. SA-20 株高传感器：范围0�?00cm�?5 dS/m18. SMTE 土壤水分、温度、电导率三参数传感器９�/span>0 � 100 % vol.% WC ; -40 � 50 ��C ; 19. PIR-1 光合有效辐射传感器：波长400�?00nm，光弹�/span>0�?500��molm-1s-120. TIR-4 总辐射传感器：波镾�/span>300�?000nm，辐尃�/span>0�?200W/m221. ST-21 土壤温度传感器：范围0�?0 ��C22. LWS-2 叶片湿度传感器：产生与传感器表面湿度成比例的指示信号<h1>软件界面与数�?/span></h1>上图右展示的�?/span>24小时冄�/span>CO2＇�/span>CO2 EXCHANGE）、茎流（SAP FLOW）、蒸腾速率＇�/span>VPD）、光合有效辐射（PAR）的连续变化，这是便携式光合仪无法做到的<h1>应用案例</h1>Net CO2 uptake rates for Hylocereus undatus and Selenicereus megalanthus under field conditions: Drought influence and a novel method for analyzing temperature dependence� Ben –Asher. J. et al. 2006� Photosynthetica� 44(2): 181-186本研究测量量天尺＇�/span>Hylocereus undatus，果实为火龙果）和蛇鞭柱＇�/span>Selenicereus megalanthus）在高温上�/span>CO2吸收率的变化，并分析了其生理生化变化、�/span><h1>产地</h1>欧洲<h1>选配技术方桇�/span></h1>1) 与叶绿素荧光仪组成光合作用与叶绿素荧光测量系绞�/span>2) 不�/span>FluorCam联用组成光合作用与叶绿素荧光成像测量系统3) 可选配高光谱成像实现从单叶片到复合冠层的光合作用时空变化研穵�/span>4) 可选配O2测量单元5) 可选配红外热成像单元以分析气孔导度动�?/span>6) 可选配PSI智能LED光源7) 可选配FluorPen�?/span>SpectraPen�?/span>PlantPen等手持式植物（叶片）测量仪器，全面分析植物叶片生理生�?/span>8) 可选配ECODRONE?无人机平台搭载高光谱和红外热成像传感器进行时空格局调查研究<h1>部分参考文�?/span></h1>1. 宋宗沲�/span>� 郑文� & 张学昅�/span>. 甘蓝型油菜耐旱相关性状的主成分分析及综合评件�/span>. 中国农业科学 44� 1775‒�/span>1787 (2011).2. 李婷婶�/span>� 江朝晕�/span>� 闵文芲�/span>� 姜贯� & 饶元. 基于基因表达式编程的番茄叶片CO2交换率建模与预测. 浙江农业学报 28� 1616‒�/span>1623 (2016).3. Ton� Y. ADVANTAGES OF THE CONTINUOUS AROUND-THE-CLOCK MONITORING OF THE LEAF CO2 EXCHANGE IN PLANT RESEARCH AND IN CROP GROWING. 54. Jiang� Z. H.� Zhang� J.� Yang� C. H.� Rao� Y. & Li� S. W. Comparison and Verification of Methods for Multivariate Statistical Analysis and Regression in Crop Modelling. in Proceedings of the 2015 International Conference on Electrical� Automation and Mechanical Engineering (Atlantis Press� 2015). doi:10.2991/eame-15.2015.1635. Ben-Asher� J.� Garcia y Garcia� A. & Hoogenboom� G. Effect of high temperature on photosynthesis and transpiration of sweet corn (Zea mays L. var. rugosa). Photosynthetica 46� 595‒�/span>603 (2008).6. Schmidt� U.� Huber� C. & Rocksch� T. EVALUATION OF COMBINED APPLICATION OF FOG SYSTEM AND CO2 ENRICHMENT IN GREENHOUSES BY USING PHYTOMONITORING DATA. Acta Horticulturae 1301‒�/span>1308 (2008).7. Qian� T. et al. Influence of temperature and light gradient on leaf arrangement and geometry in cucumber canopies: Structural phenotyping analysis and modelling. Information Processing in Agriculture (2018). doi:10.1016/j.inpa.2018.11.0028. Uwe Schmidt� Ingo Schuch� Dennis Dannehl� Thorsten Rocksch & Sonja Javernik. Micro climate control in greenhouses based on phytomonitoring data.pdf.9. Turgeman� T. et al. Mycorrhizal association between the desert truffle Terfezia boudieri and Helianthemum sessiliflorum alters plant physiology and fitness to arid conditions. Mycorrhiza 21� 623‒�/span>630 (2011).10. Ben-Asher� J.� Nobel� P. S.� Yossov� E. & Mizrahi� Y. Net CO2 uptake rates for Hylocereus undatus and Selenicereus megalanthus under field conditions: Drought influence and a novel method for analyzing temperature dependence. Photosynthetica 44� 181‒�/span>186 (2006).11. Zhaohui� J.� Jing� Z.� Chunhe� Y.� Yuan� R. & Shaowen� L. Performance of classic multiple factor analysis and model fitting in crop modeling. Biol Eng 9� 812. Ojha� T.� Misra� S. & Raghuwanshi� N. S. Wireless sensor networks for agriculture: The state-of-the-art in practice and future challenges. 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