看了PlantPen叶夹式PRI&NDVI测量仪的用户又看亅/p>
虚拟号将 180 秒后失效
使用微信扫码拨号
PlantPen叶夹弎/span>PRI&NDVI测量仪是一种快速测量植物反射光谱指数的野外便携式仪器、/span>PlantPen的两种标准版配置分别测量NDVI咋/span>PRI这两种应?为广泛的植被指数。用户也可以定制其他参数、/span>
PlantPen PRI 2109/span>PRI (Photochemical Reflectance Index) 光化学反射指数是通过计算植物叶片寸/span>531nm咋/span>570nm两个波长光反射而得到的参数。该参数对类胡萝卜素极为敏感,反应植物的光合作用中的光能利用效率咋/span>CO2同化速率,并可作为植物水胁迫的可靠指数。因此广泛用于植物产量和胁迫研究、/span>
PlantPen NDVI 3109/span>NDVI (Normalized Difference Vegetation Index)归一化植被指数是通过计算植物叶片对红光和近红外两个波长光反射而得到的参数,是反映植物叶绿素含量的一个重要参数。叶绿素会强烈吸收红光用于光合作用,而叶片细胞结构会强烈反射近红外光。因此,NDVI与光合能力直接相关,从而反映植物冠层的能量吸收状况、/span>
应用领域
叶绿素含量快速检浊/span>
植物光合研究
早期胁迫检浊/span>
氮素利用效率研究
功能特点
携带方便、操作简单、/span>
直接无损测量得到NDVI咋/span>PRI值、/span>
内置蓝牙不/span>USB双通讯模块+/span>GPS模块,输出带时间戳的地理位置
软件可导出数据为Excel格式,具备实时控制和遥控功能
可用于农业、林业以及植物学中光合作用、逆境胁迫等的研究和教学、/span>
技术参?/span>
测量参数9/span>PlantPen PRI 210:光化学反射系数PRI = (R531 - R570)/(R531 + R570):/span>PlantPen NDVI 310:归一化植被指?/span>NDVI = (RNIR RRED) / (RNIR + RRED)
测量光:内置双波长光源,PlantPen PRI 2109/span>531nm咋/span>570nm:/span>PlantPen NDVI 3109/span>635nm咋/span>760nm
检测波长:PlantPen PRI 2109/span>500 600 nm:/span>PlantPen NDVI 3109/span>620-750 nm
通讯:蓝牘/span>1.1+/span>USB
存储9/span>16M
数据存储9/span>100?00?/span>
显示:图形显礹/span>
键盘:密封防水设讠/span>2?/span>
电源9/span>可充电锂电池+/span>USB充电,连续工佛/span>70小时,低电报?/span>
自动关机9/span>5分钟无操佛/span>
尺寸9/span>1356533 mm
重量9/span>188g
操作环境:温度: 0 55 oC; 相对湿度 0 }/span>95 % (无冷凜/span>)
存储条件:温度:-10 60 oC;相对湿度9/span>0 95 % (无冷凜/span>)
用户定制
描述植物结构和叶绿素含量的参数种类很多,应用测量光波长各异,计算方法也各不相同。为了满足不同客户的需求,可以定制适合各种类似参数的掌上植物测量仪。或购买PolyPen RP410光谱仪测量植物全反射光谱、/span>
应用案例
使用PlantPen NDVI咋/span>SpectroSense 2+植被指数测量仪分别测量水稻叶片和冠层皃/span>NDVI'/span>Y Fenghua et al. 2016(/span>
产地9/span>捷克
参考文?/span>
1. K Jabran et al. 2018. High carbon dioxide concentration and elevated temperature impact the growth of weeds but do not change the efficacy of glyphosate. Pest Management Science 74(3): 766-771
2. K Trnkov et al. 2017. Desiccation‐induced changes in photochemical processes of photosynthesis and spectral reflectance in Nostoc commune (Cyanobacteria Nostocales) colonies from polar regions. Phycological Research 65(1): 44-50
3. V Leemans et al. 2017. Estimation of leaf nitrogen concentration on winter wheat by multispectral imaging. SPIE Commercial + Scientific Sensing and Imaging
4. Y Fenghua et al. 2016. Models for estimating the leaf NDVI of japonica rice on a canopy scale by combining canopy NDVI and multisource environmental data in Northeast China. International Journal of Agricultural and Biological Engineering 9(5): 132-142
5. C Zhang et al. 2016. Affecting Factors and Recent Improvements of the Photochemical Reflectance Index (PRI) for Remotely Sensing Foliar Canopy and Ecosystemic Radiation-Use Efficiencies. Remote Sensing 8(9): 1-33
6. LLR Mendon?aa et al. 2016. Management of Meloidogyne javanica with biological pesticides and oils in a lettuce field. Nematoda 3: e152015
7. R Caldern et al. 2016. Soil temperature determines the reaction of olive cultivars to Verticillium dahliae pathotypes. PLOS ONE 9(10): e110664
8. M Bartk et al. 2015. Effect of dehydration on spectral reflectance and photosynthetic efficiency in Umbilicaria arctica and U. hyperborean. Biologia Plantarum 59(2): 357-365
暂无数据