The farming activities in developing countries are mostly conducted in daytime with varying intensities of natural light throughout the day. Also, the shade trees can further increase the uncertainty of natural light exposure on plants. This research proposes an appropriate method to standardize index values obtained from an RGB digital camera for assessing biophysical properties, especially nitrogen content. Nutrient content in plants is an important factor that characterizes plant yields and health. Determining the status of plant nutrients often requires field observation. The conventional laboratory methods and remote sensing applications (i.e. satellite, airborne and spectrometer) are still expensive. Also, weather and field condition significantly affect the quality of measurement results. The use of consumer-grade digital cameras has been explored as an alternative low-cost tool for non-scientific end users; however, the use of a camera for above-canopy measurement is severely constrained by unfavorable weather condition coupled with limited time available for the measurement that depends on the intensity of incident light and the condition of plantation area. Furthermore, shade trees present in plantation areas reduce the quality of measurement results. By using this newly proposed method, measurement accuracy is improved and the potential use of Red, Green, and Blue (RGB) cameras during daytime is explored. Since many studies showed that the Hue index was a potential tool for estimating biological properties, this study used exposure value (EV) to adjust the digital number (DN) and Hue index to observe the potential of calibrated and standardized DN and Indices for estimating greenness of Robusta coffee plants.
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The research was supported by the General Directorate of Higher Education (DIKTI-Indonesia) and the Asian Institute of Technology (Thailand). The authors would also like to acknowledge the support received from Indonesian Coffee and Cocoa Research Institute (ICCRI) for assisting field data collection.
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Putra, B.T.W., Soni, P. Improving nitrogen assessment with an RGB camera across uncertain natural light from above-canopy measurements. Precision Agric 21, 147–159 (2020) doi:10.1007/s11119-019-09656-8
- Broadband greenness
- Above-canopy measurement
- Nitrogen content
- Coffee plant