# Predicting Soil pH by Using Nearest Fields

arXiv: https://arxiv.org/abs/1912.01303 · HTML: https://mlsanity.com/paper/1912.01303/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Dec 2019.

## Built on by (most cited first, 2 of 2)

- [Knowledge Representation in Digital Agriculture: A Step Towards Standardised Model](https://mlsanity.com/paper/2207.07740/) (2022)
- [OAK4XAI: Model towards Out-Of-Box eXplainable Artificial Intelligence for Digital Agriculture](https://mlsanity.com/paper/2209.15104/) (2022)

## Abstract (arXiv)

In precision agriculture (PA), soil sampling and testing operation is prior to planting any new crop. It is an expensive operation since there are many soil characteristics to take into account. This paper gives an overview of soil characteristics and their relationships with crop yield and soil profiling. We propose an approach for predicting soil pH based on nearest neighbour fields. It implements spatial radius queries and various regression techniques in data mining. We use soil dataset containing about 4,000 fields profiles to evaluate them and analyse their robustness. A comparative study indicates that LR, SVR, and GBRT techniques achieved high accuracy, with the R_2 values of about 0.718 and MAE values of 0.29. The experimental results showed that the proposed approach is very promising and can contribute significantly to PA.