Plant growth stage and leaf part to diagnose sweet corn nitrogen status using chlorophyll sensor and scanner image analysis

Abstract

The application and use of image analysis to assess the plant nitrogen (N) status has gained importance especially in precision agriculture for cereal plants using aerial remote sensing or even ground-based commercial N sensors. The objective of this work was to propose the plant growth stage and leaf parts possible to be used in sweet corn plant for N diagnosis using the SPAD chlorophyll meter and a table scanner images. A field experiment was carried out at the Federal University of Viçosa. A randomized block design was used, in a 4x3x5 factorial scheme (growth stages x leaf parts x N doses), with five replications. SPAD reading and scanner images were obtained for Red, Green and Blue (RGB) were obtained using the ImageJ® software. The data were submitted to analysis of variance and Pearson's correlation analysis at a 5% probability. Reading position on the middle part of the leaf at V10 and at R1 growth stages are suitable for assessing sweet corn N status using SPAD with 51.40 and 45.09 as an optimal reference value, respectively. RGB values determined with the scanner also was suitable for assessing the N status of sweet corn. The technique does not require special expertise for its application. It is proposed table containing optimal reference values of SPAD and RGB colors in the medial part of the sweet corn leaf at V10 and R1 development stages of corn plant.