, Volume 51, Issue 4, pp 531–540 | Cite as

Development of models for estimating leaf chlorophyll and nitrogen contents in tree species with respect to seasonal changes

  • D. MizusakiEmail author
  • K. Umeki
  • T. Honjo
Original Papers


Models were developed to estimate nondestructively chlorophyll (Chl) content per unit of leaf area (Chlarea) and nitrogen content per unit of leaf area (Narea) using readings of two optical meters for five warm-temperate, evergreen, broadleaved tree species (Castanopsis sieboldii, Cinnamomum tenuifolium, Eurya japonica, Machilus thunbergii, and Neolitsea sericea). It was determined whether models should be adjusted seasonally. Readings (were obtained six times during a year period and Chlarea and Narea were determined using destructive methods. Bayesian inference was used to estimate parameters of models that related optical meter readings to Chlarea or Narea for each species. Deviance information criterion values were used to select the best among models, including the models with seasonal adjustment. The selected models were species-specific and predicted Chlarea accurately (R 2 = 0.93–0.96). The best model included parameters with seasonal adjustments for one out of five species. Model-based estimates of Narea were not as accurate as those for Chlarea, but they were still adequate (R 2 = 0.64–0.82). For all species studied, the best models did not include parameters with seasonal adjustments. The estimation methods used in this study were rapid and nondestructive; thus, they could be used to assess a function of many leaves and/or repeatedly on individual leaves in the field.

Additional key words

Agriexpert PPW-3000 Bayesian statistics evergreen broad-leaved species leaf chlorophyll content leaf nitrogen optical meter seasonal change SPAD-502 



Castanopsis sieboldii


Cinnamomum tenuifolium




chlorophyll content per unit of leaf area


deviance information criterion


Eurya japonica


Machilus thunbergii


nitrogen content per unit of leaf area


Neolitsea sericea


coefficient of determination


root mean squared error


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Graduate School of HorticultureChiba UniversityChibaJapan

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