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FluorPen FP110手持式叶绿素荧光仪用于实验室、温室和野外快速测量植物叶绿素荧光参数,具有便携性强、精确度高、性价比高等特点;双键操作,具图形显示屏,内置锂电和数据存储,广泛应用于研究植物的光合作用、胁迫监测、除草剂检测或突变体筛选,还可用于生态毒理的生物检测,如通过不同植物对土壤或水质污染的叶绿素荧光响应,找出敏感植物作为生物传感器用于生物检测。FP110配备多种叶夹型号,用于不同的样品与研究。
应用领域
适用于光合作用研究和教学,植物及分子生物学研究,农业、林业,生物技术领域等。研究内容涉及光合活性、胁迫响应、农药药效测试、突变筛选等。
· 植物光合特性研究
· 光合突变体筛选与表型研究
· 生物和非生物胁迫的检测
· 植物抗胁迫能力或者易感性研究
· 农业和林业育种、病害检测、长势与产量评估
· 除草剂检测
· 教学
功能特点:
§ 结构紧凑、便携性强,LED光源、检测器、控制单元集成于仅手机大小的仪器内,重量仅188g
§ 功能强大,是叶绿素荧光技术的高端结晶产品,具备了大型荧光仪的所有功能,可以测量所有叶绿素荧光参数
§ 内置了所有通用叶绿素荧光分析实验程序,包括3套荧光淬灭分析程序、3套光响应曲线程序、OJIP快速荧光动力学曲线等
§ 高时间分辨率,可达10万次每秒,自动绘出OJIP曲线并给出26个OJIP–test参数
§ FluorPen专业软件功能强大,可下载、展示叶绿素荧光参数图表,也可以通过软件直接控制仪器进行测量
§ 具备无人值守自动监测功能
§ 内置蓝牙与USB双通讯模块,GPS模块,输出带时间戳和地理位置的叶绿素荧光参数图表
§ 配备多种叶夹型号:固定叶夹式(适于实验室内暗适应或夜间快速测量)、分离叶夹式(适用于野外暗适应测量)、探头式(透明光纤探头,具备叶片固定装置,用于非接触性测量监测或光适应条件下的叶绿素荧光监测)、用户定制式等
§ 可选配野外自动监测式荧光仪,防水防尘设计
测量程序与功能
· Ft:瞬时叶绿素荧光,暗适应完成后Ft=F0
· QY:量子产额,表示光系统II 的效率,等于Fv/Fm(暗适应状态)或ΦPSII (光适应状态)。
· OJIP:快速荧光动力学曲线,用于研究植物暗适应后的快速荧光动态变化
· NPQ:荧光淬灭动力学曲线,用于研究植物从暗适应到光适应状态的荧光淬灭变化过程。
· LC:光响应曲线,用于研究植物对不同光强的荧光淬灭反应。
· PAR:光合有效辐射,测量环境中植物生长可以利用的400-700nm实际光强(限PAR型号)。
技术参数
· 测量参数包括F0、Ft、Fm、Fm’、QY、QY_Ln、QY_Dn、NPQ、Qp、Rfd、PAR(限PAR型号)、Area、Mo、Sm、PI、ABS/RC等50多个叶绿素荧光参数,及3种给光程序的光响应曲线、3种荧光淬灭曲线、OJIP曲线等
· OJIP–test时间分辨率为10μs(每秒10万次),给出OJIP曲线和26个参数,包括F0、Fj、Fi、Fm、Fv、Vj、Vi、Fm/F0、Fv/F0、Fv/Fm、Mo、Area、Fix Area、Sm、Ss、N、Phi_Po、Psi_o、Phi_Eo、Phi–Do、Phi_Pav、PI_Abs、ABS/RC、TRo/RC、ETo/RC、DIo/RC等
· 测量程序:Ft、QY、OJIP、NPQ1、NPQ2、NPQ3、LC1、LC2、LC3、PAR(限PAR型号)、Multi无人值守自动监测
· 叶夹类型:FP110/S固定叶夹式、FP110/D分离叶夹式、FP110/P探头式、FP110/X用户定制式
· PAR传感器(限PAR型号):80o入射角余弦校正,读数单位μmol(photons)/m2.s,可显示读数,检测范围400-700 nm
· 测量光:每测量脉冲**0.09μmol(photons)/m2.s,10-100%可调
· 光化学光:10-1000μmol(photons)/m2.s可调
· 饱和光:**3000μmol(photons)/m2.s,10-100%可调
· 光源:标准配置蓝光470nm,可根据需求配备不同波长的LED光源
· 检测器:PIN光电二极管,667–750nm滤波器
· 尺寸大小:超便携,手机大小,134×65×33mm,重量仅188g
· 存贮:容量16Mb,可存储149000数据点
· 显示与操作:图形化显示,双键操作,待机8分钟自动关闭
· 供电:可充电锂电池,USB充电,连续工作48小时,低电报警
· 工作条件:0–55℃,0–95%相对湿度(无凝结水)
· 存贮条件:-10–60℃,0–95%相对湿度(无凝结水)
· 通讯方式:蓝牙+USB双通讯模式
· GPS模块:内置
· 软件:FluorPen1.1专用软件,用于数据下载、分析和图表显示,输出Excel数据文件及荧光动力学曲线图,适用于Windows 7及更高操作系统
操作软件与实验结果
产地:捷克
应用案例:
2017年4月,美国国家航空航天局(NASA)新一代先进植物培养器(Advanced Plant Habitat,APH)搭载联盟号MS-04货运飞船抵达国际空间站。宇航员使用FluorPen手持仪叶绿素荧光仪在其中开展植物生理学及太空食物种植(growth of fresh food in space)的研究。
参考文献
1. F Dang, et al. 2019. Discerning the Sources of Silver Nanoparticle in a Terrestrial Food Chain by Stable Isotope Tracer Technique. Environmental Science & Technology 53(7): 3802-3810
2. N Moghimi, et al. 2019. New candidate loci and marker genes on chromosome 7 for improved chilling tolerance in sorghum. Journal of Experimental Botany70(12): 3357–3371
3. M Rafique, et al. 2019. Potential impact of biochar types and microbial inoculants on growth of onion plant in differently textured and phosphorus limited soils. Journal of Environmental Management247: 672-680
4. P Soudek, et al. 2019. Thorium as an environment stressor for growth of Nicotiana glutinosa plants. Environmental and Experimental Botany164: 84-100
5. JA Pérez-Romero, et al. 2019. Investigating the physiological mechanisms underlying Salicornia ramosissima response to atmospheric CO2 enrichment under coexistence of prolonged soil flooding and saline excess. Plant Physiology and Biochemistry135: 149-159
6. D Shao, et al. 2019. Physiological and biochemical responses of the salt-marsh plant Spartina alterniflora to long-term wave exposure. Annals of Botany, DOI: 10.1093/aob/mcz067
7. C Cirillo, et al. 2019. Biochemical, Physiological and Anatomical Mechanisms of Adaptation of Callistemon citrinus and Viburnum lucidum to NaCl and CaCl2 Salinization. Front. Plant Sci. 10:742
8. T Savchenko, et al. 2019. Waterlogging tolerance rendered by oxylipin-mediated metabolic reprogramming in Arabidopsis. Journal of Experimental Botany70(10): 2919–2932
9. M Liu, et al. 2019. Strong turbulence benefits toxic and colonial cyanobacteria in water: A potential way of climate change impact on the expansion of Harmful Algal Blooms. Science of The Total Environment670: 613-622
10. PK Tiwari, et al. 2019. Liquid assisted pulsed laser ablation synthesized copper oxide nanoparticles (CuO-NPs) and their differential impact on rice seedlings. Ecotoxicology and Environmental Safety176: 321-329
11. JA Pérez-Romero, et al. 2018. Atmospheric CO2 enrichment effect on the Cu-tolerance of the C4 cordgrass Spartina densiflora. Journal of Plant Physiology220: 155-166
12. SK Yadav, et al. 2018. Physiological and Biochemical Basis of Extended and Sudden Heat Stress Tolerance in Maize. Proceedings of the National Academy of Sciences 88(1): 249-263
13. D Balfagón, et al. 2018. Involvement of ascorbate peroxidase and heat shock proteins on citrus tolerance to combined conditions of drought and high temperatures. Plant Physiology and Biochemistry127: 194-199
14. JI Vílchez, et al. 2018. Protection of Pepper Plants from Drought by Microbacterium sp. 3J1 by Modulation of the Plant's Glutamine and α-ketoglutarate Content: A Comparative Metabolomics Approach. Front. Microbiol. 9:284
15. MC Sorrentino, et al. 2018. Performance of three cardoon cultivars in an industrial heavy metal-contaminated soil: Effects on morphology, cytology and photosynthesis. Journal of Hazardous Materials351: 131-137
16. E Niewiadomska, et al. 2018. Lack of tocopherols influences the PSII antenna and the functioning of photosystems under low light. Journal of Plant Physiology223: 57-64
17. S Singh, et al. 2018. Cadmium toxicity and its amelioration by kinetin in tomato seedlings vis-à-vis ascorbate-glutathione cycle. Journal of Photochemistry and Photobiology B: Biology178: 76-84
18. EL Fry, et al. 2018. Drought neutralises plant–soil feedback of two mesic grassland forbs. Oecologia186(4): 1113–-125
附:OJIP参数及计算公式
Bckg = background
Fo: = F50μs; fluorescence intensity at 50 μs
Fj: = fluorescence intensity at j-step (at 2 ms)
Fi: = fluorescence intensity at i-step (at 60 ms)
Fm: = maximal fluorescence intensity
Fv: = Fm - Fo (maximal variable fluorescence)
Vj = (Fj - Fo) / (Fm - Fo)
Fm / Fo = Fm / Fo
Fv / Fo = Fv / Fo
Fv / Fm = Fv / Fm
Mo = TRo / RC - ETo / RC
Area = area between fluorescence curve and Fm
Sm = area / Fm - Fo (multiple turn-over)
Ss = the smallest Sm turn-over (single turn-over)
N = Sm . Mo . (I / Vj) turn-over number QA
Phi_Po = (I - Fo) / Fm (or Fv / Fm)
Phi_o = I - Vj
Phi_Eo = (I - Fo / Fm) . Phi_o
Phi_Do = 1 - Phi_Po - (Fo / Fm)
Phi_Pav = Phi_Po - (Sm / tFM); tFM = time to reach Fm (in ms)
ABS / RC = Mo . (I / Vj) . (I / Phi_Po)
TRo / RC = Mo . (I / Vj)
ETo / RC = Mo . (I / Vj) . Phi_o)
DIo / RC = (ABS / RC) - (TRo / RC)
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