Non-destructive measurement of chlorophyll content in Sonchus oleraceus L. (Asteraceae) under variations in cultivation and planting season using digital image analysis

Accurate assessment of chlorophyll content in plants is crucial for understanding their health and physiological performance. In this study, we investigated the feasibility of using digital image analysis as a non-destructive approach to determine chlorophyll levels in Sonchus oleraceus L., a less explored species with potential to serve as an alternative commercial crop tolerant to abiotic stress, satisfying specific niche needs. We compared the effectiveness of digital image analysis with traditional biochemical methods considering seasonal variations and cultivation systems. Image analysis involved assessing leaf color intensities, focusing on the Green color scale. Results revealed a strong correlation between leaf color intensities in digital images and chlorophyll levels determined by biochemical methods. Additionally, it was observed that the Green color scale exhibited the highest intensity, emerging as the most promising for future analyses. Statistical analysis revealed that the Spearman correlation method was most suitable for this type of study, especially in the second growing season. In conclusion, digital image analysis proved to be an effective and non-destructive tool for assessing chlorophyll content in S. oleraceus L., with potential application in agricultural and environmental studies.