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A global experimental dataset for assessing grain legume production

机译:用于评估谷物豆类产量的全球实验数据集

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摘要

Grain legume crops are a significant component of the human diet and animal feed and have an important role in the environment, but the global diversity of agricultural legume species is currently underexploited. Experimental assessments of grain legume performances are required, to identify potential species with high yields. Here, we introduce a dataset including results of field experiments published in 173 articles. The selected experiments were carried out over five continents on 39 grain legume species. The dataset includes measurements of grain yield, aerial biomass, crop nitrogen content, residual soil nitrogen content and water use. When available, yields for cereals and oilseeds grown after grain legumes in the crop sequence are also included. The dataset is arranged into a relational database with nine structured tables and 198 standardized attributes. Tillage, fertilization, pest and irrigation management are systematically recorded for each of the 8,581 crop*field site*growing season*treatment combinations. The dataset is freely reusable and easy to update. We anticipate that it will provide valuable information for assessing grain legume production worldwide.
机译:谷物豆类作物是人类饮食和动物饲料的重要组成部分,并且在环境中具有重要作用,但是农业豆类物种的全球多样性目前尚未得到充分利用。需要对谷物豆类的性能进行实验评估,以鉴定高产的潜在物种。在这里,我们介绍了一个数据集,其中包括发表在173篇文章中的现场实验的结果。选择的实验是在五大洲的39种豆类作物上进行的。该数据集包括谷物产量,空中生物量,作物氮含量,残留土壤氮含量和水分利用的测量值。如果有的话,还包括谷物序列中的豆类作物之后生长的谷物和油料种子的产量。数据集被安排到具有九个结构化表和198个标准化属性的关系数据库中。系统记录了8,581种作物*田地*生长期*处理组合中每一种的耕作,施肥,病虫害和灌溉管理。该数据集可自由重用且易于更新。我们预计它将为评估全球谷物豆类生产提供有价值的信息。

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