Non-destructive Detection of Growth and Quality in Basil Seedlings Grown in a Plant Factory

Background and objective: Basil is one of the high-value crops cultivated in plant factories. The production of uniform and healthy seedlings has a direct impact on the yield and quality of the final harvest. The objectives of this study were; (1) to ascertain whether non-destructive detecting parameters [projected canopy area (PCA) and vegetation indices (VIs)] could predict changes in growth and quality of basil seedlings, and (2) to determine the feasibility of grading basil seedlings based on PCA to establish a baseline for stable yields after transplanting.Methods: Basil seedlings were grown in 2- and 3-day irrigation cycles for 25 days after sowing, and the growth parameters and image analysis parameters using a multispectral camera were examined at regular intervals. The correlations between growth parameters and PCA/VIs were investigated to detect growth and quality of basil seedlings. At the time of transplanting, the basil seedlings were classified into grades A-D based on their PCA values, and the growth and yield after transplanting of basil seedlings in each grade were evaluated.Results: The basil seedlings in the 3-day irrigation treatment showed higher growth, and the correlation between the PCA values and the leaf area and fresh weight resulted in a coefficient of determination greater than 0.93. Among the VIs, the VARI, GI, and NGRDI were correlated with the growth and quality with coefficients of determination greater than 0.6. And, the growth and yield after transplanting were dependent on the seedling grade based on PCA values at the time of transplanting.Conclusion: This study confirmed that it is possible to predict the growth and quality of basil seedlings using non-destructive image analysis, and that the grading criteria for basil seedlings that can be expected to produce stable yields after transplanting can be determined using image analysis.