Salt stress estimation in pumpkin germplasm based on maximum likelihood statistical modeling of the leaf color space distribution

Abstract

Breeding salt-tolerant pumpkin cultivars is crucial for improving crop quality and yield. In this study, a high-resolution imaging-based phenotyping platform was developed to capture true leaf images of pumpkin seedlings subjected to salt stress, and plant experts conducted field assessments to determine the severity of salt damage. After image preprocessing, binary mask images were generated, and the maximum likelihood values of normalized intensity were extracted in the red, green, and blue channels to establish a salt stress status index (β) for characterizing stress levels. The β value shows a strong correlation with SPAD value, which indicates that it can effectively reflect the chlorophyll content in leaves, thereby reflecting the physiological changes in leaves affected by salt stress. A leaf texture factor (α) was employed to investigate the directional characteristics of the leaf texture, it can facilitate the effective differentiation of the clusters identified in the clustering analysis and enhance model precision by incorporating detailed leaf structural features. The performance of machine learning, deep learning, and statistical modeling approaches was compared. Statistical model integrating β and α exhibited superior predictive accuracy, with a coefficient of determination, root mean square error, and mean absolute error of 0.901, 0.057, and 0.046, respectively, in the validation dataset. Accuracy assessment among 49 germplasm accessions achieved 95.65 %, demonstrating the model’s reliability. Compared to conventional salt injury assessment, this approach offers higher efficiency and greater objectivity, enabling rapid and accurate identification of salt stress levels in pumpkin seedlings. This study provides a rapid and efficient method for assessing salt stress in pumpkin seedlings, contributing to a deeper understanding of stress response mechanisms and facilitating the selection of salt-tolerant cultivars. Moreover, these findings offer a valuable reference for salt stress identification in other plant species.