Comparing machine learning metamodels of different scale for pasture nitrogen response rate prediction Article Swipe
Christos Pylianidis
,
Val Snow
,
Hiske Overweg
,
Ioannis N. Athanasiadis
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-egu21-8279
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.5194/egusphere-egu21-8279
<p>In this work we compare the performance of machine learning metamodels of different scale for the prediction of pasture grass nitrogen response rate using a case study across different locations in New Zealand. We first used a range of soil, plant and management parameters known to affect grass growth and/or nitrogen response. These generated a complete factorial that enabled us to run virtual nitrogen response rate experiments, using the APSIM simulation model, in eight locations around the country. We included 40 years of weather data to capture the effect of weather variability on response rate. This created a large database with which to train machine learning models. We created local, regional, and nation-wide models using Random Forest and tested them on known and unknown locations. To evaluate the models, we first calculated the RMSE, MAE and R<sup>2</sup> and then determined if the distributions of the predictions were statistically different using the Mann-Whitney U test. Finally, we explore the generalizability of the models using the error metrics and the results of the statistical test.</p>
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.5194/egusphere-egu21-8279
- OA Status
- gold
- Related Works
- 10
- OpenAlex ID
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https://openalex.org/W4231632689Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5194/egusphere-egu21-8279Digital Object Identifier
- Title
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Comparing machine learning metamodels of different scale for pasture nitrogen response rate predictionWork title
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preprintOpenAlex work type
- Language
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enPrimary language
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2021Year of publication
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2021-03-04Full publication date if available
- Authors
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Christos Pylianidis, Val Snow, Hiske Overweg, Ioannis N. AthanasiadisList of authors in order
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https://doi.org/10.5194/egusphere-egu21-8279Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.5194/egusphere-egu21-8279Direct OA link when available
- Concepts
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Generalizability theory, Nitrogen, Pasture, Machine learning, Interaction, Random forest, Factorial experiment, Statistics, Mathematics, Artificial intelligence, Environmental science, Computer science, Agronomy, Chemistry, Biology, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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