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- W60191846 abstract "Experiments were carried out in greenhouse from May 2009 to March 2010 in Haidong region of Qinghai Province and Nanjing of Jiansu Province,wherein environmental and plant stomatal conductance data were collected and analyzed.Results indicated that there was a positive relationship between leaf stomatal conductance and the leaf temperature of tomato in greenhouse,and the stomatal conductance was negative relevant to CO2 concentration and vapor press deficit(VPD).There was no significant effect of photosynthetic active radiation(PAR) on the stomatal conductance.Then the model was established to simulate the stomatal conductance of based on bp artificial neural net(ANN).The determination coefficients(R2) between the simulations and measurements for the stomatal conductance daily change of cv.sufen 8 and cv.R2 were 0.760,and 0.674,respectively,and RMSE were 0.054 and 0.061 mol·m-2·s-1.The prediction accuracy of the Bp ANN based model is significantly higher than that of Ball-berry model." @default.
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- W60191846 date "2011-01-01" @default.
- W60191846 modified "2023-09-23" @default.
- W60191846 title "Modelling of stomatal conductance for greenhouse tomato using Bp artificial neural net" @default.
- W60191846 hasPublicationYear "2011" @default.
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