Evaluating Dry Matter Production and Grain Yield of Dual-Purpose Winter Wheat Using Field Experiment and Modelling

Abstract

The potential of a winter wheat (Triticum aestivum L.) cultivar Wedgetail to provide grazing and grain yield under different sowing times, grazing times, and watering regimes, under current and future climate, was investigated using field experiment and simulation modelling. For the field experiment, there were two watering treatments (unirrigated (D) and irrigated (I)) and four simulated grazing treatments (ungrazed, simulated grazed at growth stage (GS) 25, simulated grazed at growth stage (GS) 32, and grazed at both GS 25 and GS 32). These were designated as D0, D1, D2, and D3, respectively, for the unirrigated treatment and I0, I1, I2, and I3, respectively, for the irrigated treatment. It was found that the soil water depletion was significantly higher (p < 0.05) for the irrigated/ungrazed treatment than that for the simulated grazed treatment. The crop simulated grazed at GS 25 recovered quicker than the crop grazed at GS 32, especially for the unirrigated treatment. As the sowing time is delayed, above-ground dry matter (AGDM) production decreases. For D2 and D3, the amount of simulated grazed AGDM was 3.46 t ha−1 and 3.55 t ha−1, respectively. For I2 and I3, the amount of simulated grazed AGDM was 4.73 t ha−1 and 4.34 t ha−1, respectively. For D1, simulated grazing increased grain yield by 7%, while for D2 and D3, it increased by 18% and 24%, respectively. For I1, simulated grazing reduced grain yield by 16%, while for I2 and I3, it decreased by 42% and 42%, respectively. Simulation using the Agricultural Production Systems sIMulator (APSIM) showed that, for winter wheat sown in the second week of March, the maximum AGDM expected one in two years at the ends of May, June, and July is 4.5 t ha−1, 5.8 t ha−1, and 6.8 t ha−1, respectively. If the crop is sown mid-April, these values are 0.8 t ha−1, 2.2 t ha−1, and 4.3 t ha−1, respectively. Yield did not show response to times of sowing from March to early April. The maximum value reached was about 4.5 t ha−1 when sown in the fourth week of March, after which it started decreasing and reached the lowest value of about 4.1 t ha−1 when sown by the end of May. The total above-ground dry matter (AGDM) obtained by grazing earlier during the feasible grazing period and again towards the end of this period was not significantly different from grazing only once towards the end of this period. The simulation results showed that winter wheat Wedgetail flowering date was less sensitive to sowing time and that yield did not show a significant response to times of sowing, with the maximum occurring for the fourth week of March sowing and the lowest for the fourth week of May sowing.

Relevance of soil fertility spatial databases for parameterizing APSIM-wheat crop model in Moroccan rainfed areas

“…These findings were consistent with results reported in Mohanty et al (2012) which showed that the prediction of SWC by APSIM-wheat was relatively accurate (RMSEs in the 0-15 cm soil layer were below 0.04 m 3 .m -3 ) in non-water stress conditions. In contrast, a weak prediction of SWC in the soil surface layer by APSIM-wheat was reported in Australia, in dry conditions with only 160 mm in-season rainfall (Zeleke 2020). In Zeleke's work, APSIM-wheat was also found to overestimate SWC in the surface layer (i.e., 0-15 cm) in unirrigated and irrigated plots.…”

Diversifying the Landscape with Animal Integration: An Introduction to the Environmental Sustainability of Crop–Livestock Systems

“…This study shows that understanding soil processes and adapting agricultural management could allow for greater SOC storage, while improving pasture quality. In "Evaluating Dry Matter Production and Grain Yield of Dual-Purpose Winter Wheat Using Field Experiment and Modelling" by Ketema Tilahun Zeleke [8], the potential of 'Wedgetail' winter wheat to provide grazing and grain yield under various conditions in Australia was analyzed. The experiment involved variations in sowing times, grazing times, and watering regimes under present and future climate scenarios.…”