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A new approach to N fertiliser advice on grassland in the Netherlands

机译:荷兰草原氮肥咨询的新方法

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Advice on the nitrogen (N) fertilisation of grassland is usually based on the N supply of the soil (SNS). Generally, a higher SNS results in advice for lower N fertilisation rate. Recent research showed that the recommended N fertiliser rate can deviate by more than 60 kg ha~(-1) y~(-1) from the optimum. Historic and recent grassland field trial data are, therefore, re-analysed to improve the accuracy of optimum fertiliser rates. Since 1950, over 250 trials were carried out on 140 different locations, resulting in a database with about 10,000 records. The main soil types were sand (46%), clay (21%), river clay (4%) and peat (28%). Analysis showed that the SNS increased over time and that the apparent nitrogen recovery (ANR) was constant over N dosesvarying between 0-350 kg ha~(-1) y~(-1). However ANR varied considerably between sites and years. We used machine learning algorithms (random forest models) to estimate the ANR in response to soil, weather and management. Initial results showed that itwas possible to accurately distinguish fields with ANR.
机译:关于氮气(N)草原施肥的建议通常基于土壤(SNS)的N供应。通常,较高的SNS导致较低的N施肥率的建议。最近的研究表明,推荐的氮肥率可以从最佳偏离60千克HA〜(-1)y〜(-1)。因此,历史和最近的草原场试验数据是重新分析以提高最佳肥料率的准确性。自1950年以来,在140个不同的位置进行了超过250个试验,导致数据库具有约10,000条记录。主要土壤类型是沙子(46%),粘土(21%),河流(4%)和泥炭(28%)。分析表明,SNS随着时间的推移而增加,并且表观氮气回收率(ANR)在0-350kg Ha〜(-1)Y〜(-1)之间的N次含量恒定。然而,ANR在网站之间变化很大。我们使用了机器学习算法(随机林模型)来估计土壤,天气和管理的ANR。初始结果表明,ITWA可以准确地区分具有ANR的字段。

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