Principal principal component analysis, EV and V.

Aeroponic systems offer a sustainable and efficient platform for cultivating high-quality leafy greens, such as lettuce (Lactuca sativa L.). This study investigated the performance of five distinct lettuce cultivars (‘Summer Star’, ‘Grand Rapid’, ‘Tango’, ‘Bingo’, and ‘Black Rose’) within a controlled aeroponic environment to identify superior varieties and elucidate the intricate relationships among key agronomic traits. A comprehensive suite of statistical analyses was employed, including Analysis of Variance (ANOVA), Pearson correlation analysis, Principal Component Analysis (PCA), and genetic variability assessment using GCV and PCV. Results revealed significant differences among cultivars for growth parameters, yield components, and quality attributes. Notably, ‘Bingo’ exhibited the highest total leaf weight, while ‘Summer Star’ demonstrated superior yield per hectare. Correlation analysis highlighted strong positive associations between plant height, leaf area index, and chlorophyll content, whereas yield exhibited a negative correlation with total chlorophyll content. PCA identified key underlying factors contributing to the observed variation, with the first two principal components explaining 86.13% of the total variance, underscoring the importance of leaf morphology and chlorophyll concentration in driving aeroponic growth and productivity. The findings underscore the potential of aeroponics to contribute to global food security by enhancing the productivity and quality of leafy greens.