Related Experiment Video
Updated: Dec 20, 2025
Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
Published on: October 16, 2018
Mapping the probability of detecting Burkholderia pseudomallei in rural rice paddy soil based on indicator kriging
Wacharapong Saengnill1, Kitsanai Charoenjit1, Karnjana Hrimpeng2
1Faculty of Geoinformatics, Burapha University, Chonburi, Thailand.
Background:
Melioidosis is an infectious disease commonly found in Thailand. This infectious disease is caused by Burkholderia pseudomallei in soil. This study aims to analyze the association between spatial soil factors and B. pseudomallei detection, as well as to map the probability of B. pseudomallei contamination based on indicator kriging in paddy soil.
Methods:
Seventy-eight soil samples were collected randomly on 22 April 2018 in various paddy fields. Oxidase, Gram staining and monoclonal antibody-based latex agglutination assays were performed to confirm the presence of B. pseudomallei in soil samples. The association between B. pseudomallei detection and spatial soil factors including soil temperature, soil pH, soil texture and soil drainage were analyzed by the Mann-Whitney U test and χ2 test. Subsequently, a semivariogram model and indicator kriging were used to map the probability of B. pseudomallei contamination.
Results:
Of the 78 samples, B. pseudomallei was detected in 32 (41.03%). The presence or absence of B. pseudomallei was not significantly associated with spatial soil factors. The semivariogram model showed that the lag distance between positive B. pseudomallei samples was 90.51 m.
Conclusion:
The empirical semivariogram and indicator kriging are an alternative option for predicting the spatial distribution of B. pseudomallei in soil.
