Development of on-the-go soil organic matter sensor

W AIMRUN; A GHOLIZADEH; J N A ASMINDA; M S M AMIN

doi:10.56093/ijas.v84i10.44134

Authors

W AIMRUN University Putra Malaysia, Serdang, Selangor, 43400, Malaysia
A GHOLIZADEH University Putra Malaysia, Serdang, Selangor, 43400, Malaysia
J N A ASMINDA University Putra Malaysia, Serdang, Selangor, 43400, Malaysia
M S M AMIN University Putra Malaysia, Serdang, Selangor, 43400, Malaysia

https://doi.org/10.56093/ijas.v84i10.44134

Keywords:

Ground sensor, Organic matter, Precision farming, SOMSENSE, Variability map.

Abstract

Soil organic matter (OM) greatly influences soil quality and productivity. Conventional soil OM analysis is expensive, time consuming and laborious. To practice precision farming, one important step is to describe the variability of a farm and the conventional analysis is always delayed. Quick ground sensor or on-the-go sensor can help to achieve this need. With the development of a new technology, the soil OM information can be gathered in a real time basis by using Soil Organic Matter Sense (SOMSENSE) with the integration of software developed using MATLAB. A model of soil OM estimation based on Red, Green, and Blue (RGB) scales showed significant findings when plotting on 1:1 line. This technique will help farmers or farm managers to determine their field variability quickly to practice precision farming based on OM variability map.

Downloads

Download data is not yet available.

References

Adamchuk V I, Hummel J W, Morgan M T and Upadhyaya S K. 2004. On-the-go soil sensors for precision agriculture. Computers and Electronics in Agriculture 44: 71–91. DOI: https://doi.org/10.1016/j.compag.2004.03.002

Coleman T L, Gudapati L and Derrington J. 1990. Monitoring forest plantations using Landsat Thematic Mapper data. Remote Sensing of Environment 33: 211–21. DOI: https://doi.org/10.1016/0034-4257(90)90032-H

Jain A K and Dorai C. 1997. Practicing vision; integration, evaluation and applications. Pattern Recognition 30(2): 193– 6. DOI: https://doi.org/10.1016/S0031-3203(96)00073-8

National Research Council. 1993. Monitoring and managing soil quality. Soil and Water Quality. National Academy Press, Washington DC, pp 189–236.

Schulze D G, Nagel J L, Van Scoyoc G E, Henderson T L, Baumgardner M F and Scott D E. 1993. Significance of organic matter in determining soil colors. (In) Soil Color pp 71– 90.Ciolkosz E J (Eds). DOI: https://doi.org/10.2136/sssaspecpub31.c5

Soil Science Society of America, Madison, W I. Bigham J M, Searcy S W. 2003. Precision farming: A new approach to crop management. Texas Agricultural Extension Service, The Texas A & M University System, College Station, Texas, USA.

Shonk G A, Gaultney L D, Schulze D G and Van Scoyoc G E. 1991. Spectroscopic sensing of soil organic matter content. Transactions of ASAE 34(5): 1 978–84. DOI: https://doi.org/10.13031/2013.31826

Steinhardt G C and Franzmeier D P. 1979. Camparison of organic matter content with soil color for silt loam soils of Indiana. Communication in Soil Science and Plant Analysis 10: 1 271– 7. DOI: https://doi.org/10.1080/00103627909366981

Sudduth K A and Hummel J W. 1993. Soil organic matter, CEC and moisture sensing with a portable NIR spectrophotometer. Transactions of ASAE 36(6): 1 571–82. DOI: https://doi.org/10.13031/2013.28498

Viscarra Rossel R A, Fouad Y, Walter C. 2008. Using a digital camera to measure soil organic carbon and iron contents. Biosystem Engineering 100: 149–59. DOI: https://doi.org/10.1016/j.biosystemseng.2008.02.007