Request a quote
Fill out the form below to help us pair you with the right expert. We’ll prepare the information you request, then contact you as soon as possible.
ACCUPAR LP-80
Canopy Interception and Leaf Area Index
The LP-80 is a highly accurate way to determine canopy growth and canopy light interception (PAR and LAI), along with calculating fractional interception and crop coefficient.
- Measures canopy PAR transmission
- Automatically calculates Leaf Area Index in real-time
- Above-canopy sensor enables simultaneous above- and below-canopy PAR measurements
-
Overview / Features
-
Measuring canopy density can be problematic
There are several methods to measure how much light is intercepted by a canopy in order to determine if water loss is from evaporation or transpiration. There’s the hard way. There’s the expensive way. And then there’s the smart way: the LP-80.
Rapid readings. Easy to use.
The optimal method for measuring fractional PAR (photosynthetically active radiation) is with the LP-80 Ceptometer. It’s a highly accurate way to determine canopy growth and canopy light interception, along with calculating fractional interception and crop coefficient. And because the methodology is automated, it spares you from intensive hand labor, saving you time. The LP-80’s low cost also saves your entire budget from evaporating.
Reliable results never get old
Backed by 35 years of research, the LP-80 is one of the most trusted and relied upon instruments among crop scientists, ecologists, and foresters for publishable data year after year. Why? It uses precise sun angle calculations to accurately and automatically calculate leaf area index (LAI) in real time, so you can be confident your data is right while in the field. And it includes external PAR sensor which can be used to make simultaneous above- and below-canopy PAR measurements as a reference for intercepted light in clear, partly cloudy, or even overcast sky conditions.
Accurate. Automated. Affordable.
Measure leaf area index (LAI) and fractional interception simply and accurately to estimate ET and canopy growth. A lightweight, portable, linear array of PAR sensors designed for real time, non-destructive LAI measurements, the LP-80 has you covered when it comes to reliable results, and time, labor, and cost savings.
Simplifies the measurement and the data
Rather than the painstaking 4- to 5-hour destructive method of running leaves through a conveyor belt, the LP-80 instead measures the photosynthetically active radiation that is impinging on the measurement wand. This is also a lot easier than the other time-consuming, multi-step alternative of placing a camera beneath a canopy, taking a picture with a fisheye lens and then using software for photo analysis.
LP-80 doesn’t just automate the measurement but also the data itself. Even in raw form, data are collected, stored, and can even be downloaded so you can analyze your data anywhere. This allows you to look at correlations to make sure what you saw in the field is consistent with your measurements. In addition, the attached controller can be used to take measurements manually or log data unattended for short periods of time.
The same measurements for less
The LP-80 costs less than competitor instruments that make the exact same measurements. It weighs less as well. At a little over one pound (0.5 kg), it’s not only lightweight, but smaller and self-contained, so it’s easier to carry around. And because the display is integrated with the measurement wand, you aren’t burdened by having to bring a separate instrument to read data. There aren’t any complex sets of buttons or screens to navigate either, allowing the LP-80 to provide the most value for less.
-
Feature summary
- Measures canopy PAR
- Automatically calculates Leaf Area Index in real-time
- Lightweight and self-contained
- Powered by four AAA batteries
- Can log data unattended for short periods of time
- Stores over 2,000 readings for later download and analysis
- Above-canopy sensor enables simultaneous above- and below-canopy PAR measurements
-
Specifications
-
TECHNICAL SPECIFICATIONS
Measurement Specifications
Probe PAR SensorsRange: 0.0 – 2500.0 μmol/(m2s)Resolution: 1.0 μmol/(m2s)External PAR SensorRange: 0 to 4,000 μmol/(m2s) (full sunlight ~2,000 μmol/[m2s])Resolution: 1.0 μmol/(m2s)Accuracy: ±5.0 %Unattended Logging IntervalBetween 1 and 60 min (user selectable)Physical Specifications
Computer InterfaceLocking 5-pin sealed circular connector to RS-232 cableControllerLength: 15.8 cm (6.20 in)Width: 9.5 cm (3.75 in)Height: 3.3 cm (1.30 in)Weight: 0.6 kg (1.21 lb) with batteriesExternal PAR SensorLocking 5-pin sealed circular connector on 5-m cableExternal Sensor DimensionsDiameter: 24.0 mm (0.94 in)Height: 27.0 mm (1.06 in)Probe DimensionsLength: 86.5 cm (34.06 in)Width: 19.0 mm (0.75 in)Height: 9.5 mm (0.38 in)Probe SensorsNumber: 80Type: Photosynthetically active radiation sensorExternal SensorNumber: 1Type: Apogee SQ110 photosynthetically active radiation sensorData Storage1 MB flash memoryOperating Temperature RangeMinimum: 0 °CMaximum: 50 °COperating Relative Humidity RangeMinimum: 0 %Maximum: 100 %Power4 AA batteries, includedOther
ComplianceEM ISO/IEC 17050:2010 (CE Mark)GSA
-
Support / FAQ
-
ACCUPAR LP-80 FAQs
- What leaf distribution χ value should I use for trees?
-
If you set χ to 1, then that covers almost all of the real vegetation cases.
One of our scientists prepared an application note that describes the reasoning for this. Read it here.
- How can LP-80 data be used?
-
- Computing crop coefficients => irrigation management
- Modeling biomass production
- Leaf area index (LAI), a measure of the foliage in a canopy
- How can crop coefficients be computed from data collected with the LP-80?
-
Crop coefficients are used to estimate crop water needs. The procedure for computing a crop coefficient for a vineyard using the AccuPAR LP-80 and Williams (2001) correlation is as follows:
- Make measurements on a clear day within a couple of hours of noon.
- Make one PAR measurement above the canopy and several equally spaced measurements below the canopy from row center to row center following the instructions in the AccuPAR manual.
- Don’t sample preferentially in sun or shade areas, and take enough samples to give a good average for the area.
- The AccuPAR automatically computes t*. Subtract this value from 1.0 to get the interception. Williams’ (2001) correlation multiplies this value by 1.7 to get Kc (crop coefficient). For example, if t were 0.60, interception would be 1 – 0.60 = 0.40, and then Kc would be 1.7 x 0.40 = 0.68.
- Is there a lower limit of "above PAR" to collect reliable data with the LP-80?
- There isn’t a lower limit of “above PAR” to collect reliable LAI data; however, very large zenith angles around dawn and dusk can cause more variability. As long as sampling does not occur within an hour of dawn and dusk, the data collected are reliable (even 300 µmol m−2 s −1 on a diffuse day). Most peer-reviewed research would prefer sampling with the LP-80 between 10 am and 2 pm.
- How often should the LP-80 be calibrated?
- METER recommends performing the user calibration routinely on a weekly basis. It is a fast and easy routine and only takes a couple of minutes. Refer to Is it time to recalibrate your ACCUPAR LP-80 external quantum sensor?
- I took my readings, but I'm still getting LAI values of 0.0. What's going on?
-
1. Make sure that the location (latitude and longitude), date, and time are entered correctly in the AccuPAR LP-80 handheld.
2. Perform the user calibration on a clear and sunny day with the light bar level and green cap removed from the external PAR sensor. Ensure that the external PAR sensor is connected and level. The user calibration should be performed in an open area, where there are no shadows on the sensors.
3. Read the measurement tips in the LP-80 user manual.
4. Contact METER if you have additional problems.
- Can we add more locations (cities) to the hand-held options for setting the latitude/longitude?
- The cities are there to at least provide an approximate location to start from, and then you make adjustments from there. Select the closest city, then just use the up and down arrows to move to the Latitude and Longitude lines. Press “ENTER” to make adjustments to these values to better reflect the actual location. Once it is set correctly, they just press the MENU button again to get out of this menu and the setting will be saved.
-
Resources / Publications
-
Resource links
- The researcher’s complete guide to leaf area index
- Webinar: Leaf Area Index—Theory, Measurement, and Application
- Why measure PAR?
- How to use PAR for more efficient irrigation
- How to find crop coefficients for irrigated grapevine production
- Simplified models for carbon assimilation by plants
Support
Case studies
-
Selected Publications
Listed below are a few examples of cited publications for the LP-80 ceptometer. This list is not exhaustive.
2020
- Anapalli, Saseendran S., Daniel K. Fisher, Srinivasa Rao Pinnamaneni, and Krishna N. Reddy. “Quantifying evapotranspiration and crop coefficients for cotton (Gossypium hirsutum L.) using an eddy covariance approach.” Agricultural Water Management 233 (2020): 106091. (Article link).
- Chang, Christine Y., Luis Guanter, Christian Frankenberg, Philipp Köhler, Lianhong Gu, Troy S. Magney, Katja Grossmann, and Ying Sun. “Systematic assessment of retrieval methods for canopy far‐red solar‐induced chlorophyll fluorescence (SIF) using high‐frequency automated field spectroscopy.” Journal of Geophysical Research: Biogeosciences (2020): e2019JG005533. (Article link).
- Shao, Liping, Gang Li, Qiannan Zhao, Yabing Li, Yutong Sun, Weinan Wang, Chuang Cai et al. “The fertilization effect of global dimming on crop yields is not attributed to an improved light interception.” Global Change Biology 26, no. 3 (2020): 1697-1713. (Article link).
2019
- Alam, Muhammad Shahinur, David W. Lamb, and Muhammad Moshiur Rahman. “In-situ partitioning of evaporation and transpiration components using a portable evapotranspiration dome—A case study in Tall Fescue (Festuca arundinacea).” Agricultural Water Management 213 (2019): 352-357. (Article link).
- Bogie, N. A., R. Bayala, I. Diedhiou, R. P. Dick, and T. A. Ghezzehei. “Intercropping with two native woody shrubs improves water status and development of interplanted groundnut and pearl millet in the Sahel.” Plant and Soil 435, no. 1-2 (2019): 143-159. (Article link).
- Carter, David R., Robert A. Slesak, Timothy B. Harrington, and Anthony W. D’Amato. “Effects of irrigation and phosphorus fertilization on physiology, growth, and nitrogen-accumulation of Scotch broom (Cytisus scoparius).” Plant Physiology Reports 24, no. 3 (2019): 410-421. (Article link).
- Carter, David R., Robert A. Slesak, Timothy B. Harrington, and Anthony W. D’Amato. “Comparative effects of soil resource availability on physiology and growth of Scotch broom (Cytisus scoparius) and Douglas-fir (Pseudotsuga menziesii) seedlings.” Forest Ecology and Management 453 (2019): 117580. (Article link).
- Comas, Louise H., Thomas J. Trout, Kendall C. DeJonge, Huihui Zhang, and Sean M. Gleason. “Water productivity under strategic growth stage-based deficit irrigation in maize.” Agricultural Water Management 212 (2019): 433-440. (Article link).
- Nogueira, Carla, Christiane Werner, Ana Rodrigues, and Maria C. Caldeira. “A prolonged dry season and nitrogen deposition interactively affect CO2 fluxes in an annual Mediterranean grassland.” Science of The Total Environment 654 (2019): 978-986. (Article link).
- Sonkar, Ickkshaanshu, Hari Prasad Kotnoor, and Sumit Sen. “Estimation of root water uptake and soil hydraulic parameters from root zone soil moisture and deep percolation.” Agricultural Water Management 222 (2019): 38-47. (Article link).
2018
- Anapalli, Saseendran S., Timothy R. Green, Krishna N. Reddy, Prasanna H. Gowda, Ruixiu Sui, Daniel K. Fisher, Jerry E. Moorhead, and Gary W. Marek. “Application of an energy balance method for estimating evapotranspiration in cropping systems.” Agricultural Water Management 204 (2018): 107-117. (Article link).
- Fahey, Catherine, Christine Angelini, and S. Luke Flory. “Grass invasion and drought interact to alter the diversity and structure of native plant communities.” Ecology 99, no. 12 (2018): 2692-2702. (Article link).
- Guo, Yanjun, Terri Starman, and Charles Hall. “Reducing Substrate Moisture Content during Greenhouse Production of Poinsettia Improves Postproduction Quality and Economic Value.” HortScience 53, no. 11 (2018): 1618-1628. (Article link).
- Hassan, Muhammad Adeel, Mengjiao Yang, Awais Rasheed, Xiuliang Jin, Xianchun Xia, Yonggui Xiao, and Zhonghu He. “Time-series multispectral indices from unmanned aerial vehicle imagery reveal senescence rate in bread wheat.” Remote Sensing 10, no. 6 (2018): 809. (Article link).
- Kim, Su Min, Jaehak Jeong, Dan Keesee, and James R. Kiniry. “Development, growth, and biomass simulations of two common wetland tree species in Texas.” Environmental Monitoring and Assessment 190, no. 9 (2018): 521. (Article link).
- Soderquist, B. S., K. L. Kavanagh, T. E. Link, M. S. Seyfried, and A. H. Winstral. “Simulating the dependence of aspen (Populus tremuloides) on redistributed snow in a semi‐arid watershed.” Ecosphere 9, no. 1 (2018): e02068. (Article link).
2017
- Balbontín, Claudio, Isidro Campos, Magali Odi-Lara, Antonio Ibacache, and Alfonso Calera. “Irrigation Performance Assessment in Table Grape Using the Reflectance-Based Crop Coefficient.” Remote Sensing 9, no. 12 (2017): 1276. (Article link).
- Schuster, Michael J., and Jeffrey S. Dukes. “Rainfall variability counteracts N addition by promoting invasive Lonicera maackii and extending phenology in prairie.” Ecological Applications 27, no. 5 (2017): 1555-1563. (Article link).
2016
- Candeias, Matthew, and R. J. Warren. “Rareness starts early for disturbance-dependent grassland plant species.” Biodiversity and Conservation 25, no. 13 (2016): 2771-2785. (Article link).
- Devnarain, Natrisha, Bridget Genevieve Crampton, R. Chikwamba, John VW Becker, and Martha M. O’Kennedy. “Physiological responses of selected African sorghum landraces to progressive water stress and re-watering.” South African Journal of Botany 103 (2016): 61-69. (Article link).
- Huang, Jun, Juan Wang, Xining Zhao, Hongbin Li, Zilong Jing, Xiaodong Gao, Xiaoli Chen, and Pute Wu. “Simulation study of the impact of permanent groundcover on soil and water changes in jujube orchards on sloping ground.” Land Degradation & Development 27, no. 4 (2016): 946-954. (Article link).
2015
- Feng, Gary, Haile Tewolde, Liwang Ma, Ardeshir Adeli, Karamat R. Sistani, and Johnie N. Jenkins. “Simulating the fate of fall-and spring-applied poultry litter nitrogen in corn production.” Soil Science Society of America Journal 79, no. 6 (2015): 1804-1814. (Article link).
- Huff, L. M., D. L. Potts, and E. P. Hamerlynck. “Ecosystem CO2 exchange in response to nitrogen and phosphorus addition in a restored, temperate grassland.” The American Midland Naturalist 173, no. 1 (2015): 73-87. (Article link).
- Rahman, M. A., D. Armson, and A. R. Ennos. “A comparison of the growth and cooling effectiveness of five commonly planted urban tree species.” Urban Ecosystems 18, no. 2 (2015): 371-389. (Article link).
2014
- Huang, Jun, Juan Wang, Xining Zhao, Pute Wu, Zhiming Qi, and Hongbing Li. “Effects of permanent ground cover on soil moisture in jujube orchards under sloping ground: A simulation study.” Agricultural Water Management 138 (2014): 68-77. (Article link).
2011
- Rahman, M. A., J. G. Smith, P. Stringer, and A. R. Ennos. “Effect of rooting conditions on the growth and cooling ability of Pyrus calleryana.” Urban Forestry & Urban Greening 10, no. 3 (2011): 185-192. (Article link).
2010
- Booth, Eric G., and Steven P. Loheide. “Effects of evapotranspiration partitioning, plant water stress response and topsoil removal on the soil moisture regime of a floodplain wetland: implications for restoration.” Hydrological Processes 24, no. 20 (2010): 2934-2946. (Article link).
- Davitt, Andrew J., Marcus Stansberry, and Jennifer A. Rudgers. “Do the costs and benefits of fungal endophyte symbiosis vary with light availability?.” New Phytologist 188, no. 3 (2010): 824-834. (Article link).
- Parker, John D., Lauren J. Richie, Eric M. Lind, and Kelly O. Maloney. “Land use history alters the relationship between native and exotic plants: the rich don’t always get richer.” Biological Invasions 12, no. 6 (2010): 1557-1571. (Article link).
2008
- Bertheloot, Jessica, Pierre Martre, and Bruno Andrieu. “Dynamics of light and nitrogen distribution during grain filling within wheat canopy.” Plant Physiology 148, no. 3 (2008): 1707-1720. (Article link).
-
Accessories
Request a quote
Fill out the form below to help us pair you with the right expert. We’ll prepare the information you request, then contact you as soon as possible.