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Simulation and performance yield of soybean and maize crops by AquaCrop, in Campos Gerais, Paraná State

机译:帕兰瓦州坎帕斯·帕萨斯省水上大豆和玉米作物的仿真与性能产量

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The computational models that simulate yield of agricultural crops are important to planning activities. The objective of this study was to verify the performance of AquaCrop model to simulate soybean and maize yield in Campos Gerais region, in different soil types. The AquaCrop was used to estimate yield, requiring climate, soil, crop and soil management input data. In the analysis were used data from 21 and 32 experiments with maize and soybeans, respectively, carried out in the ABC Foundation, from years harvest between 2006 and 2014. For soybean crop, the highest absolute and relative errors of productivity simulations occurred in less productive crops, due to the lack of rain during sowing, water deficit in the harvest or high temperatures in the first weeks after the plants emergence. The highest absolute and relative errors verified in the simulations with maize crop experiments did not allow defined pattern identification. The AquaCrop achieved “very good” and “excellent” performances in the simulations of soybean and maize yield it the analyzed locations. The soil type affected the results from the analyzes of the two crops, and the Latossolos provided better performance and higher correlation compared to other soil types. ?
机译:模拟农作物产量的计算模型对规划活动很重要。本研究的目的是验证Aquacrop模型的性能,以在不同土壤类型中模拟坎波尔·吉拉斯地区的大豆和玉米产量。 Aquacrop用于估算产量,需要气候,土壤,作物和土壤管理输入数据。在分析中,在ABC基金会中分别在21和32个实验中使用了21和32个实验,从2006年至2014年期间进行了多年的收获。对于大豆作物,生产率模拟的最高绝对和相对误差发生在更低的生产率作物,由于播种过程中缺乏雨,在植物出现后的第一周收获或高温的水赤字。在玉米作物实验模拟中验证的最高绝对和相对误差并不允许定义的模式识别。 Aquacrop在大豆和玉米模拟中实现了“非常好的”和“优秀的”表演,产量是分析的地点。土壤类型影响了两种作物的分析结果,与其他土壤类型相比,Latossolos提供了更好的性能和更高的相关性。 ?

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