A simple digital imaging method for estimating black-soil organic matter under visible spectrum

ABSTRACT

Soil organic matter (SOM) plays a key role in soil, and is used to determine soil quality. Conventional soil property analysis is relatively slow, expensive and laborious. Although using a spectrometer can quickly assess a large amount of organic matter content, it is an expensive, complex and undefined process. This article presents a potential simple method for estimating black-SOM that uses a digital camera that is cheaper and easier to operate than a spectrometer. RGB (red, green and blue) image-intensity values of the soil from a digital camera were measured, to research the relationship between black-SOM and RGB. The results show the red image-intensity values provide the greatest correlation with SOM, with a correlation coefficient (r) reaching 0.73. A comparison with spectrometer results for SOM predictions shows that the best prediction result for the digital camera (R² = 0.72, root-mean-square error [RMSE] = 0.40) is slightly better than the spectrometer (R² = 0.65, RMSE = 0.45) at certain band points. Thus, a low-cost digital camera that is easy to operate can be used as an alternative tool for the rapid and accurate estimation of black-SOM content.

KEYWORDS:

• Soil organic matter
• digital camera
• soil spectrum
• sampling area

Acknowledgments

The authors gratefully acknowledge Professor Jianxin Xia for his scientific suggestions. This research was supported by projects of scientific technological research and development plan of Chengde (grant number 20155004), colleges and universities scientific research project of Hebei province (grant number QN2016308) and the subject of Chengde municipal finance bureau (grant number CZ2013011).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research was supported by projects of scientific technological research and development plan of Chengde [grant number 20155004]; Colleges and universities scientific research project of Hebei province [grant number QN2016308] and the subject of Chengde Municipal Finance Bureau [grant number CZ2013011].