TY - JOUR ID - 58365 TI - Agricultural crop growth modelling: a tool for dealing with the threat of climate change affecting food security (case study for greenhouse tomato) JO - فصلنامه علمی علوم زمین JA - GSJ LA - fa SN - 1023-7429 AU - Lak, Mohammad Bagher AU - Minaei, Saeid AU - Soufizadeh, Saeid AU - Banakar, Ahmad AD - Ph.D. Student, Biosystems Engineering Department, Tarbiat Modares University AD - Professor, Biosystems Engineering Department, Tarbiat Modares University AD - Assistant Professor, Department of Agroecology, Environmental Sciences Research Institute, Shahid Beheshti University, General Campus, Tehran, Iran AD - Associate Professor, Biosystems Engineering Department, Tarbiat Modares University Y1 - 2018 PY - 2018 VL - 27 IS - Special Journal-106 SP - 83 EP - 90 KW - AquaCrop KW - Biomass KW - Simulation DO - 10.22071/gsj.2018.58365 N2 - Climate change and essentiality of the food security have motived scientists to try innovative approaches, among which, crop growth models can help to predict crop yield. In order to simulate tomato (Solanum lycopersicum) growth, phenological characteristics of a short-life variety of tomato were assessed. Phenologic characteristics included leaf area index (LAI), specific leaf area (SLA), crop height (H), leaf fresh and dry weight (LFW and LDW), and stem fresh and dry weight (SFW and SDW). These parameters were measured at four different times (i.e. 33, 45, 55, and 87 days after planting) during tomato growth and development. Fruit fresh and dry weight (FFW and FDW), harvest index (HI), and water efficiency () were measured at the end of the crop season. This study was done in a randomized complete block design with three levels of irrigation (i.e. at 48h (i1), 72h (i2), and 96h (i3)) in three replications. Irrigation treatment had significant effects on LAI1, LAI2, H2, FLW1, FLW2, DLW1, DLW2, DL2, FSW1, DSW1, DSW2, and DS2 at the 0.01 level, while its effect on SLA1, SLA2, H1, and FSW2 was significant at the level 0.05. Two-tailed correlations among characteristics were investigated and regression models developed for DFW. Dry fruit weight was simulated using both AquaCrop and regression models, separately. It was found that regression model could predict DFW of tomatoes under different treatment better than AquaCrop. It was also concluded that the phenologic characteristics measured at 55 DAP provide good criteria for predicting tomato fruit production. UR - http://www.gsjournal.ir/article_58365.html L1 - http://www.gsjournal.ir/article_58365_762c158a05e27d1714e0d89e2891fe9a.pdf ER -