In this study, a novel chromotropic acid-based color development method was proposed for quick estimation of soil nitrate (NO3-). The method utilized a 3D printed device integrated with the rear-end camera of a smartphone and a stand-alone application called SMART NP. By analyzing the mean Value (V) component of the sample's image, the SMART NP provides instant predictions of soil NO3- levels. The limit of detection was calculated as 0.1 mg L-1 with a sensitivity of 0.26 mg L-1. The device showed a % bias of 0.9% and a precision of 1.95%, indicating its reliability. Additionally, the device-predicted soil NO3- data, combined with kriging interpolation, showcased spatial variability in soil NO3- levels at the regional level. The study employed a Gaussian model of variogram for kriging, and the high Nugget/Sill ratio indicated low spatial autocorrelation, emphasizing the impact of management factors on the spatial distribution of soil NO3- content in the study area. Overall, the imaging device, along with geostatistical interpolation, provided a comprehensive solution for the rapid assessment of spatial variability in soil NO3-content.
Keywords: imaging device; kriging; nitrate; smartphone; soil.