Evaluation of a Digital Camera and a Smartphone Application, Using the Dark Green Color Index, in Assessing Maize Nitrogen Status

Abstract

ABSTRACT Nitrogen (N) fertilization is crucial for maximizing maize (Zea mays L.) yield, but optimizing the amount of N to apply for maize must also consider potential impact on the environment from nitrate-N pollution. The dark green color index (DGCI) technology determines the greenness of maize leaves to assess maize N status. Spectrum Technologies used this DGCI technology to develop a smartphone app called Greenindex+. The objective of this study was to determine if DGCI values made by the app (DGCIapp) agree with values determined by a digital camera (DGCIcam), and to identify the sources of potential discrepancies between the camera and the app for determining DGCI. Field experiments were conducted at six sites across the state of Arkansas during 2013 and 2014 with N rates ranging from 0 to 360 kg N ha−1. Dark green color index measurements were made at tasseling both in the field using the app under ambient lighting conditions and in the laboratory under fluorescent lighting using the camera and the app. There was a significant linear–plateau relationship (P ≤ 0.05, R2 = 0.60, 0.89) between DGCIcam and leaf N concentration. However, the relationship between DGCIapp and leaf N concentration was more variable (R2 = 0.33, 0.69) than between DGCIcam and leaf N concentration when measured in the laboratory. Under field conditions, DGCIapp was also more variable than DGCIcam measured in the laboratory. The variability between DGCIcam and DGCIapp is because DGCIcam uses the whole leaf for color analysis while DGCIapp uses only the center portion of the leaf for color analysis.