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Crop simulation models use allometric relationships to predict plant height from vegetative characteristics. The objective of this study was to find relationships between plant height (PH) and number of leaves on main stem (NLMS), stem dry weight (SDW) (g plant-1) and total vegetative components (leaves and stems) dry weight (TVDW) (g plant-1) in wheat (Triticum aestivumL.). For this purpose, an experiment was conducted using seven wheat cultivars including two durum wheat cultivars (Arya and Taro) and five bread wheat cultivars (Darya, Kuhdasht, Shiroudi, Tajan and Zagros) under irrigated and rainfed conditions during 2008–2009 at Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran. The experimental design was a randomized complete block design with four replications. Sampling was started from beginning of tillering and continued until maturity. A segmented nonlinear regression model was used to describe allometric relationships between PH and the vegetative characteristics. The results showed that there was no significant difference between cultivars and the two conditions for allometric relationships, so one equation was usable for all cultivars under both irrigated and rainfed conditions. Significant relationships were found between PH and NLMS (R2= 0.94), SDW (R2= 0.95) and TVDW (R2= 0.95). These equations can be used for estimation of PH in simulation models of wheat.

Iran, with its more than 80 million people, is located in a politically unstable region. The country’s future food supply and sufficiency is at stake because of the over-exploitation of land and water resources. In this study, a modeling framework was used to estimate production of plant species as influenced by different scenarios for the year 2030. The scenarios capture different agricultural water resources, improved irrigation efficiency and narrowing of crop yield gaps (i.e, difference between current farm yield and potential yield). Food demand, given a range of diets and loss and waste scenarios was also evaluated using the modeling framework. We found that limiting current agricultural water withdrawal to a safe level for the environment (from 86.0 to 38.5 billion m3per year) until 2030, along with an increase in population (from 80 to 90 million people) during the same period led to a decline in self-sufficiency from of 83% to only 39%, assuming current production management, current diet and food loss and waste. Implementation of a highly-improved production scenario (narrowing relative yield gap from the current 60% to 40% and increasing irrigation efficiency from the current 38% to 53%) restored self-sufficiency to 61% using the current diet, loss and waste and to 69% using a medium-change demand scenario (a modified diet and 15% reduction in loss and waste). Avoiding water over-withdrawal by agriculture until 2030 won’t be possible without sacrificing a degree of self-sufficiency. To achieve the highest self-sufficiency results, a combination of increased production and controlled demand are necessary.