Crop and Environment (Jun 2022)

Estimating photosynthetic parameter values of rice, wheat, maize and sorghum to enable smart crop cultivation

  • Dong Wang,
  • Winda Rianti,
  • Fabián Gálvez,
  • Peter E.L. van der Putten,
  • Paul C. Struik,
  • Xinyou Yin

Journal volume & issue
Vol. 1, no. 2
pp. 119 – 132

Abstract

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Crop models can support the design of smart crop management practices. The Farquhar-von Caemmerer-Berry (FvCB) model is increasingly being used in these models for quantifying leaf photosynthesis. Nitrogen (N) is required for many functional machineries of photosynthesis, thus relationships between FvCB-model parameters and leaf N content (LNC) should be established. We conducted combined gas exchange and chlorophyll fluorescence measurements on fully expanded leaves of two C3 crops, rice (Oryza sativa) and wheat (Triticum aestivum), and two C4 crops, maize (Zea mays) and sorghum (Sorghum bicolor), grown under three N levels. Photosynthetic parameters were estimated and linear relationships between these parameters and LNC were quantified in both C3 and C4 crop types. The efficiency of converting incident light into linear electron transport for C3 crops or into ATP production for C4 crops showed a weak increase with LNC. The maximum electron transport rate (Jmax) for C3 crops or the maximum ATP production rate (Jmax,atp) for C4 crops significantly increased with LNC. The increase in Rubisco carboxylation capacity (Vcmax) with LNC was significantly higher in C3 than in C4 crops. Triose phosphate utilization for C3 crops and PEP carboxylation capacity (Vpmax) for C4 crops increased significantly with LNC as well. Except for Jmax at 21% O2 and Vcmax of C3 crops, there was no significant difference among crops in the relationship between estimated photosynthetic parameters and LNC. The tight associations of photosynthesis parameters with LNC were discussed in view of decision making on N management in the context of smart farming.

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