INVESTIGATING MICROCLIMATIC INFLUENCES ON OZONE INJURY IN CLOVER (TRIFOLIUM-SUBTERRANEUM) USING ARTIFICIAL NEURAL NETWORKS

Citation
Gr. Balls et al., INVESTIGATING MICROCLIMATIC INFLUENCES ON OZONE INJURY IN CLOVER (TRIFOLIUM-SUBTERRANEUM) USING ARTIFICIAL NEURAL NETWORKS, New phytologist, 132(2), 1996, pp. 271-280
Citations number
43
Categorie Soggetti
Plant Sciences
Journal title
ISSN journal
0028646X
Volume
132
Issue
2
Year of publication
1996
Pages
271 - 280
Database
ISI
SICI code
0028-646X(1996)132:2<271:IMIOOI>2.0.ZU;2-2
Abstract
Microclimatic factors interact during ozone episodes to influence the sensitivity of plants to ozone and thus are likely to modify the amoun t of injury development. This paper investigates these interactions in an ozone-sensitive cultivar of clover (Trifolium subterraneum cv. Ger aldton). Experiments were conducted using a glasshouse-based closed-ch amber exposure system in which the plants were exposed for 7 h to eith er charcoal-filtered air (CF) or CF plus ozone at concentrations rangi ng from 40 to 160 ppb. The microclimatic conditions inside the chamber s ranged from 16 to 36 degrees C, 0.9-3.6 kPa vapour pressure deficit (VPD), and 80-460 mu mol m(-2) s(-1) Photosynthetically Active Radiati on (PAR). Seven days after ozone exposure, the extent of foliar ozone injury was scored visually. The assessment scoring system was validate d by pigment analysis. The data from these exposures were analysed usi ng artificial neural networks (ANNs), the principles of which are desc ribed in the paper. Two ANNs were used, one to investigate the effects of microclimate on the threshold AOT40 (dose accumulated above a thre shold of 40 ppb) above which injury developed, the other to determine the extent of visible injury development. Both networks used temperatu re, VPD, PAR and AOT40 as inputs. Testing with previously unseen data showed that the networks produced accurate predictions of the threshol d and extent of injury for a range of ozone doses and microclimatic co nditions. For example, the injury score network predicted that at 100 mu mol m(-2) s(-1) PAR and 1 kPa VPD an AOT40 of 350 ppb h was require d to produce an injury score of 1, whereas in conditions of 400 mu mol m(-2) s(-1) PAR and 3.5 kPa VPD, an AOT40 of 460 ppb h was required. Analysis of the weightings of components of the trained networks indic ated that VPD and PAR had a stronger influence on the response to ozon e than did temperature. Furthermore, this approach revealed that micro climate had a greater influence on the extent of ozone injury than on the threshold for injury.