Three photosynthetic patterns characterized by cluster analysis of gas exchange data in two rice populations

Plant photosynthetic rate is affected by stomatal status and internal CO2 carboxylation. Understanding which process determines photosynthetic rate is essential for developing strategies for breeding crops with high photosynthetic efficiency. In this study, we identified different physiological patterns of photosynthetic rate in two different rice populations. Photosynthetic gas exchange parameters were measured during the flowering stage in two rice populations. Clustering and correlation analyses were performed on the resulting data. Five or six groups were defined by K-means clustering according to differences in net photosynthetic rates(Pn). According to differences in stomatal conductance(gs) and carboxylation efficiency(CE), each group was clustered into three subgroups characterized by physiological patterns stomatal pattern, carboxylation pattern, and intermediate pattern. Pn was significantly correlated with gs(r = 0.810) and CE(r = 0.531). Pn was also significantly correlated with gs and CE in the three physiological patterns. The correlation coefficients were highest in the stomatal pattern(0.905 and 0.957) and lowest in the carboxylation pattern(0.825 and 0.859). Higher correlation coefficients between Pn and gs or CE in the three physiological patterns indicate that clustering is very important for understanding factors limiting rice photosynthesis. ? 2013 Production and hosting by Elsevier B.V. on behalf of Crop Science Society of

Plant photosynthetic rate is affected by stomatal status and internal CO2 carboxylation. Understanding which process determines photosynthetic rate is essential for developing strategies for breeding crops with high photosynthetic efficiency. In this study, we identified different physiological patterns of photosynthetic rate in two different rice populations. Photosynthetic gas exchange parameters were measured during the flowering stage in two rice populations. Clustering and correlation analyses were performed on the resulting data. Five or six groups were defined by K-means clustering according to differences in net photosynthetic rates(Pn). According to differences in stomatal conductance(gs) and carboxylation efficiency(CE), each group was clustered into three subgroups characterized by physiological patterns stomatal pattern, carboxylation pattern, and intermediate pattern. Pn was significantly correlated with gs(r = 0.810) and CE(r = 0.531). Pn was also significantly correlated with gs and CE in the three physiological patterns. The correlation coefficients were highest in the stomatal pattern(0.905 and 0.957) and lowest in the carboxylation pattern(0.825 and 0.859). Higher correlation coefficients between Pn and gs or CE in the three physiological patterns indicate that clustering is very important for understanding factors limiting rice photosynthesis. ? 2013 Production and hosting by Elsevier B.V. on behalf of Crop Science Society of China