A smartphone-mediated system for soil organic carbon detection

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Published Nov 26, 2021
https://doi.org/10.47164/ijngc.v12i5.442
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Volume 12, Special Issue 5, November 2021

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Suresh Balpande
a:1:{s:5:"en_US";s:61:"Shri Ramdeobaba College of Engineering and Management, Nagpur";}
https://orcid.org/0000-0003-4514-5724
AKANSHA CHAUHAN

Abstract

The soil health is decided on the basis of primary and secondary elements. The primary elements includes Nitrogen
(N), Phosphorous (P), and Potassium (K). In addition, soil pH, conductivity and organic carbon (OC) are also used
to estimate soil health and suitability for specic land use. Soil testing is often conducted to state soil nutrients
recommendations to attain higher crop yields. However, traditional soil testing methods is time-consuming,
laborious and resource intensive. Smartphones are nearly ubiquitous and oer a ready capability for providing
point-of-care testing facility. An attempt has been made to quantify soil OC contents using smartphone camera
as a portable re
ectometer, database of 114 samples and machine learning algorithm. An android application
has been developed to convert colour space into nutrients concentration i.e. relating test strips color to the
concentration of soil OC. It was employed to analyze soil samples encompasses a wide range of organic carbon in
the range of 0.47 - 0.84 % with an accuracy ranging from 85 % to 97%.

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Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Balpande, S., & CHAUHAN , A. . (2021). A smartphone-mediated system for soil organic carbon detection. International Journal of Next-Generation Computing, 12(5). https://doi.org/10.47164/ijngc.v12i5.442
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References

  1. Balpande, S.S.; Bhaiyya, M. P. R. 2017. Low-cost fabrication of polymer substrate-based piezoelectric microgenerator with PPE, IDE and ME. Electronics Letters 53, (5), 341{343.
  2. Balpande S. S., P. R. S. and M, P. R. 2016. Design and low cost fabrication of green vibration energy harvester. Sensors and Actuators A: Physical 251, 134{141.
  3. Confalonieri, M. Foi, R. C. e. a. 2013. Development of an app for estimating leaf area index using a smartphone. trueness and precision determination and comparison with other indirect methods. Computers and Electronics in Agriculture Vol.96, 67{74.
  4. Davis, Maggie R., e. 2018. Review of soil organic carbon measurement protocols: A us and brazil comparison and recommendation. Sustainability 10 , 1{53.
  5. Dhone, Mayuri; Gawatre, P. and Balpande, S. 2018. Frequency band widening technique for cantilever-based vibration energy harvesters through dynamics of uid motion. Materials Science for Energy Technologies 1/1, 84{90.
  6. esdac report. 2021. Soil organic carbon content. https://esdac.jrc.ec.europa.eu/ESDBArchive/ octop/octop-download.html. retrieved- on- 20th Aug 2021.
  7. Golicz, K.; Hallett, S. and Sakrabani, R. e. a. 2019. The potential for using smartphones as portable soil nutrient analyzers on suburban farms in central east china. Sci Rep 9 16424, https://doi.org/10.1038/s41598{019{52702{8.
  8. Karolina Golicz, Stephen Hallett, R. S. and Ghosh, J. 2020. Adapting smartphone app used in water testing for soil nutrient analysis. Computers and Electronics in Agriculture Vol.175, 1{9.
  9. Online-Document. 2020. Machine learning with python.
  10. https://www.tutorialspoint.com/machine learning with python/machine learning with
  11. python classi cation algorithms support vector machine.html. retrieved on 06th Sept 2021.
  12. Online-Document. 2021. Image processing concepts. https://www.ques10.com/p/33595/whatis-image-processing-explain-fundamental-steps.retrieved on 20th Sept 2021.
  13. Rewatkar Prakash, B. S. and Jayu, K. 2018. Design and development of PDMS based channel for fluid analysis. Indian Journal of Science and Technology ISSN 0974 -5645.
  14. S. Prasad, S. K. P. and Ghosh, D. 2014. Energy ecient mobile vision system for plant leaf disease identi cation. In IEEE Wireless Communications and Networking Conference (WCNC '14). pp.3314{3319.
  15. Sumriddetchkajorn, S. 2013. Mobile device-based optical instruments for agriculture. In Sensing Technologies for Biomaterial, Food, and Agriculture, Vol-8881, Ed. The International Society for Optical Engineering, Proceedings of SPIE, pp.331{338.
  16. Suporn Pongnumkul, P. C. and Surasvadi, N. 2015. Applications of smartphone-based sensors in agriculture: A systematic review of research. Journal of sensors, Hindawi Vol.2015, 195308, 1{18.
  17. Suresh S. Balpande, R. S. P. and Patrikar, R. M. 2021. Grains level evaluation and performance enhancement for piezoelectric energy harvester. Ferroelectrics 572:1, 71{93.
  18. Wu, Y. and Chang, K. 2013. An empirical study of designing simplicity for mobile application interaction. In 19th Americas Conference on Information Systems (AMCIS '13), Vol-1, Ed. pp.331{338.