Using winter wheat as a model, the team investigated how PCCP changes across growth stages and under long-term fertilization. The findings demonstrate that PCCP declines as wheat matures and is strongly influenced by nutrient supply, particularly nitrogen and phosphorus.
Light captured by plants is distributed among several competing pathways: photochemical quenching, chlorophyll fluorescence, and non-photochemical quenching. Balancing these pathways determines whether absorbed energy supports growth or is lost as heat. Until now, researchers lacked an integrated metric to capture this trade-off. Nutrient availability and stomatal regulation are known to influence photosynthesis, but their link to energy allocation has been elusive. The PCCP concept bridges this gap by quantifying the exact light level where photochemical and non-photochemical processes are in equilibrium. Based on this innovation, researchers explored how wheat allocates energy under different fertilizer regimes and across developmental stages.
A study (DOI: 10.1016/j.plaphe.2025.100063) published in Plant Phenomics on 2 June 2025 by Wenxu Dong & Lianhong Gu’s team, Chinese Academy of Sciences, could transform how scientists assess plant energy strategies under changing environments.
In this study, researchers combined long-term fertilization experiments with chlorophyll fluorescence and gas exchange measurements to investigate the dynamics of the photochemical compensation point (PCCP) in winter wheat, examining its variation across growth stages, fertilization treatments, and leaf traits, as well as identifying its major physiological drivers. The results showed that PCCP averaged 272 μmol m⁻² s⁻¹, with a significant decline from 337 μmol m⁻² s⁻¹ at jointing to 291 μmol m⁻² s⁻¹ at flowering, and further to 163 μmol m⁻² s⁻¹ at grain filling, highlighting a strong developmental trend. Fertilization had marked effects: NP and NPK treatments consistently elevated PCCP, whereas nitrogen alone and manure alone showed little or even negative effects, though combined N and M applications enhanced PCCP. In terms of leaf traits, PCCP was positively correlated with nitrogen, phosphorus, potassium, sulfur, leaf thickness, and stomatal conductance under specific regimes, but negatively associated with calcium and sometimes iron, depending on treatment and stage. Manure-amended treatments strengthened positive correlations with macronutrients while enhancing the negative association with calcium. Temporal analysis further revealed stage-specific relationships, such as consistent positive links with phosphorus and sulfur, and variable correlations with nitrogen, potassium, and calcium across growth phases. Physiological traits also played a key role, as PCCP was positively related to stomatal conductance, leaf thickness, and intrinsic water use efficiency, particularly during grain filling. Random forest modeling confirmed these traits as major drivers, with stomatal conductance identified as the most influential predictor, followed by phosphorus, intrinsic water use efficiency, and leaf thickness, collectively explaining nearly 77% of PCCP variation. These findings underscore the complex interplay between fertilization, leaf traits, and physiology in shaping plant energy use strategies.
By introducing PCCP, the study provides a new ecophysiological benchmark for assessing plant energy allocation. The index can serve as a diagnostic tool to evaluate how crops respond to nutrient supply and environmental stress, offering predictive insights into yield potential. Because PCCP reflects a balance between growth-supporting photochemistry and protective dissipation, it could guide sustainable fertilizer practices by identifying nutrient combinations that optimize energy use efficiency. Furthermore, the link between PCCP and stomatal conductance highlights its value for breeding programs that aim to improve crop resilience under water and nutrient limitations. Ultimately, PCCP may help refine crop management strategies to meet food security challenges under climate change.
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References
DOI
10.1016/j.plaphe.2025.100063
Original URL
https://doi.org/10.1016/j.plaphe.2025.100063
Funding information
This research was supported by the National Key Research and Development Program of China (2021YFD1901104, 2022YFD1901604), the “Strategic Priority Research Program” of the Chinese Academy of Sciences (XDA28020303, XDA26040103), and the Key Research and Development Program of Hebei Province (22326410D, 22326412D). LG is supported by the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research Program. ORNL is managed by UT-Battelle, LLC, for DOE under contract DE-AC05-00OR22725.
About Plant Phenomics
Plant Phenomics is dedicated to publishing novel research that will advance all aspects of plant phenotyping from the cell to the plant population levels using innovative combinations of sensor systems and data analytics. Plant Phenomics aims also to connect phenomics to other science domains, such as genomics, genetics, physiology, molecular biology, bioinformatics, statistics, mathematics, and computer sciences. Plant Phenomics should thus contribute to advance plant sciences and agriculture/forestry/horticulture by addressing key scientific challenges in the area of plant phenomics.