2018 Volume 14 Issue 4 Pages 302-318
In the recently proposed integrated approach for designing the entire agro-industrial process, there has been a lack of consideration on interannual meteorological variability consequences on production for particular plant cultivars/varieties grown at a specific region. In this study, we discuss how this shortcoming influences the simulation of productivity and GHG emission using a case study on two sugarcane cultivars and their processing system producing raw sugar and bioethanol. We also explore if consideration of interannual weather variability is possible by widely available meteorological data. From the results, we confirmed that it was possible to construct a modified multiple linear regression model that reflect the interannual variability of meteorological conditions from commonly available data sets without any additional data collection requirement, and that the productivity and GHG emission results derived by the simulation with and without such enhancement may disagree in some cases.