Data Study Group Network Final Report: Rothamsted Research

A - Papers appearing in refereed journals

Breure, T., Carmona, C. U., Ellisck, S., Evans, B., Fahmi, A., Haefele, S. M., Hassall, K. L., Loning, M., Ruiz, D. P., Shchepanovska, D. and Thomas, C. L. 2020. Data Study Group Network Final Report: Rothamsted Research. Data Study Group Network Final Report: Rothamsted Research. Zenodo. https://doi.org/10.5281/zenodo.3775489

AuthorsBreure, T., Carmona, C. U., Ellisck, S., Evans, B., Fahmi, A., Haefele, S. M., Hassall, K. L., Loning, M., Ruiz, D. P., Shchepanovska, D. and Thomas, C. L.
Abstract

This report describes the work completed during a week long data study group hosted by the Alan Turing Institute. The challenge was provided by Rothamsted Research and looks at predicting soil and plant physicochemical properties from soil infrared (IR) spectra. Three datasets were explored and modelled using a combination of established and more recent data-science strategies. Due to the size, scope and variety in the datasets, multiple conclusions were drawn. Overall, our preliminary findings indicate that soil physiochemical properties were easier to model than plant physicochemical properties. Decision tree based methods were used consistently throughout the three datasets and were overall more robust than other approaches considered in our analysis. Our results are in line with the current literature; IR data can be an effective predictor of the physicochemical properties of soil and by extension, the health of the soil.

Year of Publication2020
JournalData Study Group Network Final Report: Rothamsted Research. Zenodo
Digital Object Identifier (DOI)https://doi.org/10.5281/zenodo.3775489
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
Output statusPublished
Publication dates
Online29 Apr 2020

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