Rapid Identification of Rice Macronutrient Content in Saline Soils Using Smartphone Camera

Abstract

Indonesia’s rice production has decreased by 6.83% (on average) in the last five years (2015 – 2019) because of some factors. Salinity (42%) is one of the leading factors that cause decreasing rice production besides climate change (21%), drought (9%), and other factors (28%). The smartphone camera serves as an alternative technology to prevent macronutrient deficiencies due to salinity. This study used aerial photos from android with visible light (R, G, and B), and the image was taken from a height of 5 m. The observation of macronutrient content in plant biomass was carried out using a free grid to adjust rice fields and saline soil. The formula was obtained from regression analysis and paired t-test between the biomass macronutrient and the extracted digital number of aerial photographs that have been stacked. The results showed that digital number (DN) from a smartphone was reliable to predict nitrogen (N), phosphorus (P), and potassium (K) content in rice with formula N = 0.0035 * DN + 0.8192 (R2 0.84), P = 0.0049 * DN – 0.2042 (R2 0.70), and K = 0.0478 * DN – 2.6717 (R2 0.70). There was no difference between the macronutrient estimation results from the formula and the field’s original data.

Keywords

• remote sensing
• visible light
• android
• nitrogen
• phosphorus
• potassium
• salinity