Abstract

summaryMicroclimatic factors interact during ozone episodes to influence the sensitivity of plants to ozone and thus are likely Co modify the amount of injury development. This paper investigates these interactions in an ozone‐sensitive cultivar of clover (Trifolium subterraneum cv. Geraldton). Experiments were conducted using a glasshouse‐based closed‐chamber exposure system in which the plants were exposed for 7 h to either charcoal‐filtered air (CF) or CF plus ozone at concentrations ranging from 40 to 160 ppb. The microclimatic conditions inside the chambers ranged from 16 to 36 C, 0‐9‐3‐6 kPa vapour pressure deficit (VPD), and 80–460 μmol m−2s−1Photosynthetically Active Radiation (PAR). Seven days after ozone exposure, the extent of foliar ozone injury was scored visually. The assessment scoring system was validated by pigment analysis. The data from these exposures were analysed using artificial neural networks (ANNs), the principles of which are described in the paper. Two ANNs were used, one to investigate the effects of microclimate on the threshold AOT40 (dose accumulated above a threshold of 40 ppb) above which injury developed, the other to determine the extent of visible injury development. Both networks used temperature. VPD, PAR and AOT40 as inputs. Testing with previously unseen data showed that the networks produced accurate predictions of the threshold and extent of injury for a range of ozone doses and microclimatic conditions. For example, the injury score network predicted that at 100 μmol m2s1PAR and 1 kPa VPD an AOT40 of 150 ppb h was required to produce an injury score of 1, whereas in conditions of 400 μmol m−2s−1s′ PAR and 3.5 kPa VPD, an AOT40 of 460 ppb h was required. Analysis of the weightings of components of the trained networks indicated that VPD and PAR had a stronger influence on the response to ozone than did temperature. Furthermore, this approach revealed that microclimate had a greater influence on the extent of ozone injury than on the threshold for injury.

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