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Abstract: Triticale and wheat are similar crops, but triticale represents a valuable alternative to wheat due to its greater biomass production and grain yield in Mediterranean-type growing conditions. However, despite the higher yield potential and increasing importance of this crop, there are no dynamic crop models available to assist triticale adaptation via simulation experiments. In a previous study, the APSIM-Nwheat model was parameterized for triticale resulting in a new APSIM-Triticale model but the new model was never compared with detailed experimental triticale data in a one-to-one comparison. Here, the new model was tested with detailed field experimental observations. APSIM-Triticale was able to reproduce phenology, biomass, grain yields and soil water dynamics. The model performed well over several years and management options that included different sowing densities, sowing dates and a short and tall cultivar. The tested model was then used to explore management options to maximize triticale yield across the Mediterranean Basin. The response to sowing density was cultivar and rainfall-environment dependent. The simulation analysis indicated that there was no yield advantage with higher sowing densities with a tall cultivar type in high yielding environments, despite its higher biomass growth rates. The highest yields were achieved at the early sowing date at the sowing densities between 100 and 300plants/m2 in the high rainfall regions for both short and the tall cultivars. The simulation study suggests that sowing a short cultivar with a reduced radiation use efficiency but early vigour growth could increase current yields across different regions, seasons and management options in the Mediterranean climate. [Copyright &y& Elsevier]

Abstract: Sowing date and cultivar choice influence yield of wheat in Mediterranean climatic regions where crop production is constrained by waterlogging in winter on clay soils and terminal water deficit in spring. Because of the large seasonal variability in Mediterranean environments, a combination of experimental data and simulation results were used to investigate optimal sowing date and cultivar choice. The Agricultural Production Systems SIMulator (APSIM), which had been rigorously tested for bread wheat (Triticum aestivum L.) in Mediterranean-type environments, was further tested with measured durum wheat (Triticum turgidum L. var. durum) experimental data from the Mediterranean basin. The model reproduced most of the observed seasonal variability of grain yields but tended to overestimate, particularly some of the observed low grain yields. Comparing the model with detailed field experiments from two seasons and three durum wheat cultivars over a wide range of sowing dates highlighted the importance of reproducing the measured phenology and in particularly the observed anthesis dates for the general performance of the model. The use of a specific phyllochron for each sowing date instead of a single value per cultivar regardless of sowing date, as in APSIM, improved anthesis predictions and other aspects of the model. Hence, the phyllochron was varied in the model through a simple relationship based on observed phyllochrons and sowing dates. The new phyllochron routine was then used to explore management options to increase yields by combining the model with 47 years of historical weather records from Oristano, Sardinia, Italy. The simulation results showed that sowing wheat before December can result in higher yields in the absence of waterlogging. However, the high frequency of waterlogging on the clay soils, even with the observed decline of rainfall in the last 20 years in winter, showed no average yield advantage of sowing before December. Early maturing cultivars outperformed late cultivars at standard and late sowing dates. Hence, sowing early cultivars as soon as rainfall has started from December onwards is currently proposed to give the best yields in this environment in most seasons. Increasing temperatures and declining rainfalls in all months of the year as a consequence of future climate change projections will substantially reduce grain yields. Under such conditions, sowing as early as October to avoid terminal water shortage and heat stress will minimise the negative impact from climate change. [Copyright &y& Elsevier]