Non-Destructive Detection of Nitrogen Deficiency in Kimchi Cabbage Seedlings using Multispectral Imaging

Rapid assessments of nitrogen deficiency in vegetable seedlings are essential when attempting to improve seedling quality and productivity.Multispectral imaging provides a rapid, non-destructive approach for the monitoring of nutrient status and the seedling growth process.In this study, we investigated the applicability of multispectral imaging for detecting nitrogen deficiency in kimchi cabbage (Brassica rapa subsp.pekinensis) seedlings grown under four nitrogen concentrations (0, 40, 80, and 100%) for 30 days after sowing (DAS).Seedling growth declined progressively with a decrease in the nitrogen concentration.Image-based predictions of individual leaf areas achieved high accuracy (R 2 = 0.97), whereas predictions at the plug tray level remained reliable (R 2 = 0.92) despite reduced accuracy caused by leaf overlap and an upright leaf orientation.Significant relationships between vegetation indices and growth parameters emerged from 15 DAS onward, with NDVI, GNDVI, CI green , mrNDVI, and RDVI consistently exhibiting strong correlations with nitrogen-deficiency-induced growth responses.Because the relative performance of the vegetation indices varied according to the target growth parameter and developmental stage, selecting appropriate indices can improve the accuracy of nitrogen deficiency assessments.Overall, these findings demonstrate that multispectral imaging provides an effective, non-destructive tool for the high-throughput, plug-tray-level monitoring of nitrogen deficiency in commercial kimchi cabbage seedling production.