Comprehensive nutrient analysis in agricultural organic amendments through non-destructive assays using machine learning

A - Papers appearing in refereed journals

Towett, E. K., Drake, L. B., Acquah, G., Haefele, S. M., McGrath, S. P. and Shepherd, K. D. 2020. Comprehensive nutrient analysis in agricultural organic amendments through non-destructive assays using machine learning. PLOS ONE. 15 (12), p. e0242821. https://doi.org/10.1371/journal.pone.0242821

AuthorsTowett, E. K., Drake, L. B., Acquah, G., Haefele, S. M., McGrath, S. P. and Shepherd, K. D.
Abstract

Portable X-ray fluorescence (pXRF) and Diffuse Reflectance Fourier Transformed Mid Infrared (DRIFT-MIR) spectroscopy are rapid and cost-effective analytical tools for material
characterization. Here, we provide an assessment of these methods for the analysis of total Carbon, Nitrogen and total elemental composition of multiple elements in organic amendments. We developed machine learning methods to rapidly quantify the concentrations of macro- and micronutrient elements present in the samples and propose a novel system for the quality assessment of organic amendments. Two types of machine learning methods, forest regression and extreme gradient boosting, were used with data from both pXRF and
DRIFT-MIR spectroscopy. Cross-validation trials were run to evaluate generalizability of models produced on each instrument. Both methods demonstrated similar broad capabilities in estimating nutrients using machine learning, with pXRF being suitable for nutrients and contaminants. The results make portable spectrometry in combination with machine learning a scalable solution to provide comprehensive nutrient analysis for organic amendments.

KeywordsAgriculture; Organic Amendments; Nutrient Management; Non-Destructive Assays; Machine Learning; Portable X-ray fluorescence (pXRF); Diffuse Reflectance Fourier Transformed Mid-Infrared (DRIFT-MIR)
Year of Publication2020
JournalPLOS ONE
Journal citation15 (12), p. e0242821
Digital Object Identifier (DOI)https://doi.org/10.1371/journal.pone.0242821
Web address (URL)https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242821
Open accessPublished as ‘gold’ (paid) open access
FunderBill and Melinda Gates Foundation
Biotechnology and Biological Sciences Research Council
Funder project or codeAfrica Soil Information Service (AfSIS)
S2N - Soil to Nutrition [ISPG]
Publisher's version
Output statusPublished
Publication dates
Online10 Dec 2020
Publication process dates
Accepted09 Nov 2020
PublisherPublic Library of Science (PLOS)
ISSN1932-6203

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