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    Effect of elevated CO2 on peanut performance in a semi-arid production region

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    With the intensification and frequency of heat waves and periods of water deficit stress, along with rising atmospheric carbon dioxide [CO2], understanding the seasonal leaf-gas-exchange responses to combined abiotic factors will be important in predicting crop performance in semi-arid production systems. In peanut (Arachis hypogaea L.), the availability of developmental stage physiological data on the response to repeated water deficit stress periods in an elevated [CO2] (EC) environment is limited and necessary to improve crop model predictions. Here, we investigated the effects of season-long EC (650 µmol CO2 m−2 s−1) on the physiology and productivity of peanut in a semi-arid environment. This study was conducted over two-growing seasons using field-based growth chambers to maintain EC conditions, and impose water-stress at three critical developmental stages. Our results showed that relative to ambient [CO2] (AC), long-term EC during water-stress episodes, increased leaf-level light-saturated CO2 assimilation (Asat), transpiration efficiency (TE), vegetative biomass, and pod yield by 58%, 73%, 58%, and 39%, respectively. Although leaf nitrogen content was reduced by 16%, there was 41% increase in maximum Rubisco carboxylation efficiency in EC, indicating that there was minimal photosynthetic down-regulation. Furthermore, long-term EC modified the short-term physiological response (Asat) to rapid changes in [CO2] during the water-stress episodes, generating a much greater change in EC (54%) compared to AC (10%). Additionally, long-term EC generated a 23% greater Asat compared to the short-term EC during the water-stress episodes. These findings indicate high levels of physiological adjustment in EC, which may increase drought resilience. We concluded that EC may reduce the negative impacts of repeated water-stress events at critical developmental stages on rain-fed peanut in semi-arid regions. These results can inform current models to improve the projections of peanut response to future climates
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