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Predicting Soil pH by Using Nearest Fields
Date Issued
2019-12-19
Date Available
2021-05-26T10:50:41Z
Abstract
In precision agriculture (PA), soil sampling and testing op-eration is prior to planting any new crop. It is an expensive operationsince there are many soil characteristics to take into account. This papergives an overview of soil characteristics and their relationships with cropyield and soil profiling. We propose an approach for predicting soil pHbased on nearest neighbour fields. It implements spatial radius queriesand various regression techniques in data mining. We use soil dataset containing about 4,000 fields profiles to evaluate them and analyse theirrobustness. A comparative study indicates that LR, SVR, andGBRTtechniques achieved high accuracy, with the R2 values of about 0.718 and MAEvalues of 0.29. The experimental results showed that the pro-posed approach is very promising and can contribute significantly to PA.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Origin Enterprises
Type of Material
Conference Publication
Publisher
Springer
Series
Lecture Notes in Computer Science
11927
Lecture Notes in Artificial Intelligence
11927
Copyright (Published Version)
2019 Springer
Language
English
Status of Item
Peer reviewed
Part of
Bramer, M., Petridis, M. (eds.). Artificial Intelligence XXXVI: 39th SGAI International Conference on Artificial Intelligence, AI 2019, Cambridge, UK, December 17–19, 2019, Proceeding
Conference Details
The 39th SGAI International Conference on Artificial Intelligence (AI 2019), Cambridge, United Kingdom, 17-19 December 2019
ISBN
978-3-030-34884-7
This item is made available under a Creative Commons License
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