Unique contributions of chlorophyll and nitrogen to predict crop photosynthetic capacity from leaf spectroscopy

Sheng Wang, Kaiyu Guan, Zhihui Wang, Elizabeth A Ainsworth, Ting Zheng, Philip A Townsend, Kaiyuan Li, Christopher Moller, Genghong Wu, Chongya Jiang

Research output: Contribution to journalArticlepeer-review


The photosynthetic capacity or the CO2-saturated photosynthetic rate (Vmax), chlorophyll, and nitrogen are closely linked leaf traits that determine C4 crop photosynthesis and yield. Accurate, timely, rapid, and non-destructive approaches to predict leaf photosynthetic traits from hyperspectral reflectance are urgently needed for high-throughput crop monitoring to ensure food and bioenergy security. Therefore, this study thoroughly evaluated the state-of-the-art physically based radiative transfer models (RTMs), data-driven partial least squares regression (PLSR), and generalized PLSR (gPLSR) models to estimate leaf traits from leaf-clip hyperspectral reflectance, which was collected from maize (Zea mays L.) bioenergy plots with diverse genotypes, growth stages, treatments with nitrogen fertilizers, and ozone stresses in three growing seasons. The results show that leaf RTMs considering bidirectional effects can give accurate estimates of chlorophyll content (Pearson correlation r=0.95), while gPLSR enabled retrieval of leaf nitrogen concentration (r=0.85). Using PLSR with field measurements for training, the cross-validation indicates that Vmax can be well predicted from spectra (r=0.81). The integration of chlorophyll content (strongly related to visible spectra) and nitrogen concentration (linked to shortwave infrared signals) can provide better predictions of Vmax (r=0.71) than only using either chlorophyll or nitrogen individually. This study highlights that leaf chlorophyll content and nitrogen concentration have key and unique contributions to Vmax prediction.

Original languageEnglish (US)
Article numbereraa432
Pages (from-to)341-354
Number of pages14
JournalJournal of experimental botany
Issue number2
StatePublished - Feb 2 2021


  • Hyperspectral leaf reflectance
  • maize
  • radiative transfer model
  • nitrogen
  • partial-least-squares regression
  • chlorophyll
  • the CO2 saturated photosynthetic rate
  • partial least squares regression
  • CO -saturated photosynthetic rate
  • hyperspectral leaf reflectance
  • Bioenergy crop

ASJC Scopus subject areas

  • Physiology
  • Plant Science


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