Department of Rural Engineering, School of Agricultural and Veterinarian Sciences, São Paulo State University (Unesp), Via de Acesso Prof. Paulo Donato Castellane, s/n, CEP, Jaboticabal, SP, 14884-900, Brazil.
Int J Biometeorol. 2021 Nov;65(11):1905-1917. doi: 10.1007/s00484-021-02147-4. Epub 2021 May 16.
Studies on the use of deficit irrigation and application of models for estimating agronomic performance of crops can help in more sustainable agricultural managements. The objective of this study was to evaluate the effect of irrigation levels on the agronomic performance of white oat (Avena sativa L.) and accuracy of the CERES-Barley model in simulating white oat growth and yield, as well as performing long-term simulation to identify the best sowing time for each irrigation management. The experiment consisted of five irrigation levels (11%, 31%, 60%, 87%, and 100%), being conducted in two agricultural years in southeastern Brazil. The model was calibrated with data of the treatment without water deficit (100%) of the first year and validated with the data of the other treatments in the 2 years. Long-term analyses, with a historical series of 16 years, were performed to recommend the best sowing dates for each irrigation management. Deficit irrigation linearly reduces the agronomic performance of white oat. The high accuracy of white oat yield estimation (R = 0.86; RMSE = 616 kg ha) using the CERES-Barley model allowed the long-term simulation for establishing the best sowing date for each irrigation level. For higher irrigation levels, sowing in periods with lower temperature (May and June) is more appropriate, as the 1 °C increment in the average temperature before flowering reduces crop yield by 600 kg ha. At irrigation levels with higher deficit, sowing in periods with higher rainfall (March and April) promotes higher crop yield.
研究亏缺灌溉的应用和作物农学性能估算模型,可以帮助实现更可持续的农业管理。本研究的目的是评估灌溉水平对白燕麦(Avena sativa L.)农学性能的影响,以及 CERES-Barley 模型在模拟白燕麦生长和产量方面的准确性,并进行长期模拟,以确定每种灌溉管理的最佳播种时间。该试验包括五个灌溉水平(11%、31%、60%、87%和 100%),在巴西南部的两个农业年度进行。模型采用第一年无水分亏缺(100%)处理的数据进行校准,并在两年内对其他处理的数据进行验证。进行了长期分析,使用了 16 年的历史系列数据,为每种灌溉管理推荐最佳的播种日期。亏缺灌溉会线性降低白燕麦的农学性能。CERES-Barley 模型对白燕麦产量估计具有很高的准确性(R = 0.86;RMSE = 616 kg ha),允许进行长期模拟,以确定每种灌溉水平的最佳播种日期。对于较高的灌溉水平,在温度较低的时期(5 月和 6 月)播种更为合适,因为开花前平均温度每升高 1°C,作物产量会减少 600 kg ha。在亏缺程度较高的灌溉水平下,在降雨量较高的时期(3 月和 4 月)播种可以提高作物产量。