Quantum sensors for accurate and stable long-term photosynthetically active radiation observations

Tomoko Akitsu, Kenlo Nishida Nasahara, Yasuo Hirose, Osamu Ijima, Atsushi Kume

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


Long-term accurate data of photosynthetically active radiation (PAR) are needed because PAR is one of the standard environmental statistics needed to evaluate plant photosynthesis. Therefore, PAR observation sites are globally distributed, particularly in flux observation sites. Quantum sensors have been used for half a century to observe PAR; however, their accuracy is still uncertain. This study evaluates the accuracies of nine quantum sensor products by examining their spectral and cosine responses. On the basis of these data as well as reference spectrum data provided by our standard spectrometric measurement, we performed the following analyses: (1) a simulation of errors caused by the sensors’ non-ideal spectral response in three types of radiation inputs (open sky, forest canopy transmission, and forest canopy reflection), (2) a simulation of the errors caused by a complex combination of the sensors’ non-ideal spectral and cosine responses in three diurnal variation types of incident radiation (clear sky, partial clouds, and an overcast sky), and (3) an observation of the sensors’ long-term sensitivity degradation outdoors. Based on the results, we recommend two quantum sensors with minimal errors, LI-COR LI-190 encased in a weather-proof external housing with a glass dome and PREDE PAR-02D. The findings of this study contribute in establishing a long-term PAR observation protocol and should become a basis for quality checks and controls of PAR observation values that have previously been obtained worldwide.

Original languageEnglish
Pages (from-to)171-183
Number of pages13
JournalAgricultural and Forest Meteorology
Publication statusPublished - May 1 2017

All Science Journal Classification (ASJC) codes

  • Forestry
  • Global and Planetary Change
  • Agronomy and Crop Science
  • Atmospheric Science


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