Fig. 2

Path analysis model illustrating the effect of bolting, stem cell wall composition, and stem strength on lettuce drop severity, evaluated in 2017 (SU17). The final path model was selected based on optimal fit criteria, specifically the lowest Akaike information criterion (AIC) and root mean square error of approximation (RMSEA) values. The model was divided into two parts due to its complexity: Part A (top panel): Standardized regression values show the strength and direction of relationships or paths between predictor (independent) and outcome (dependent) variables. Higher values indicate stronger effects, with positive values reflecting direct relationships and negative values indicating inverse relationships. Part B (bottom panel): Covariances between pairs of variables quantify the extent to which two variables vary together. Positive covariances suggest that the two variables tend to increase together, while negative covariances imply an inverse relationship (e.g., as xylose increases, arabinose tends to decrease).