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The durations of the subsequent phases between anthesis and physiological maturity were left unchanged. The phyllochron interval was set to 75 oC d based on our observation for cv.
APSIM VS DSAT PLUS
To account for earlier commencement of anthesis in barley, the duration of the phases from floral initiation to flowering was modified to 2 phyllochrons plus 80 degree-days ( oC d) compared to 5 phyllochrons plus 80 oC d used in the wheat model. The cultivar-specific parameters determining the sensitivities to photoperiod and vernalisation were calibrated for the cv. Grimmet crops grown at a wide range of sowing dates and water supply regimes at three sites in southern Qld: Hermitage Research Station, Roma, and Wellcamp. The parameters that were necessary to adapt the APSIM-Wheat module to simulate barley were derived mostly from extensive field data reported by Goyne et al. The performance of the APSIM-Barley model was tested on an independent set of data from commercial barley crops. Here we present the adaptation of the APSIM-Wheat module to simulate growth and development of barley by altering the key variables describing the distinguishing physiological traits between the two species. the ratio of biomass to total evapotranspiration. These result in reduced evaporative loss of water from the soil surface, and greater water-use efficiency for above-ground biomass production, i.e. 2006) suggest that the higher yielding ability of barley in drier environments is largely due to (i) earlier commencement of flowering and maturity, and (ii) faster rate of leaf canopy development and root growth early in the season when vapour pressure deficit is low. Experimental results from comparative studies on wheat and barley (López-Castañeda and Richards 1994 Manschadi et al. Although APSIM provides simulation capabilities for more than twenty crop species, including wheat, no such a capability exists for barley ( Hordeum vulgare L.).
APSIM VS DSAT SIMULATOR
The Agricultural Production Systems Simulator (APSIM) has proven to be a valuable tool to explore the likely impacts of management decisions and environmental conditions on crop productivity and has been used extensively to develop improved risk management practices (Keating et al. Modelling, phenology, leaf area index, biomass, water deficit, sowing date Introduction Further studies are required to evaluate the capability of APSIM-Barley to predict quality aspects such as grain protein concentration and grain size distribution. The model was capable of explaining 81% of variation in grain yield of commercial crops (RMSD = 0.56 t ha -1). Model performance was subsequently tested against an independent set of data collected from 9 farmers’ fields in Victoria. Simulation of biomass at maturity and grain yield explained 91 and 82% of the variance (RMSD = 108.2 and 69.7 g m -2), respectively. Overall, APSIM-Barley was able to predict the observed responses of crop growth attributes to a wide range of management and environmental conditions.
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An extensive data set from barley crops grown in southern QLD was used to derive the model parameters describing crop phenology, leaf canopy development, grain filling, and water extraction.
![apsim vs dsat apsim vs dsat](https://www.apsim.info/wp-content/uploads/2019/09/image044-1.gif)
This paper describes the adaptation of the APSIM-Wheat module to simulate growth and development of barley by altering the key variables describing the distinguishing physiological traits between the two species.