2026-04-14T04:51:02Zhttps://recercat.cat/oai/request

oai:recercat.cat:20.500.12327/29072025-10-22T11:26:02Zcom_2072_4428com_2072_4427col_2072_487898

00925njm 22002777a 4500 dc Ezenarro, Jokin author García Pizarro, Angel author Busto, Olga author de Juan, Anna author Boqué, Ricard author 2023-10-09 Digital images are commonly used to monitor processes that are based on colour changes due to their simplicity and easy capture. Colour information in these images can be analysed objectively and accurately using colour histograms. One such process is olive ripening, which is characterized by changes in chemical composition, sensory properties and can be followed by changes in physical appearance, mainly colour. The reference method to quantify the ripeness of olives is the Maturity Index (MI), which is determined by trained experts assigning individual olives into a colour scale through visual inspection. Instead, this study proposes a methodology based on Chemometrics Assisted Colour Histogram-based Analytical Systems (CACHAS) to automatically assess the MI of olives based on R, G, and B colour histograms derived from digital images. The methodology was shown to be easily transferable for routine analysis and capable of controlling the ripening of olives. The study also confirms the high potential of digital images to understand the ripening process of olives (and potentially other fruits) and to predict the MI with satisfactory accuracy, providing an objective and reproducible alternative to visual inspection of trained experts. Ezenarro, Jokin, Ángel García-Pizarro, Olga Busto, Anna De Juan, and Ricard Boqué. 2023. “Analysing Olive Ripening With Digital Image RGB Histograms.” Analytica Chimica Acta 1280: 341884. doi:10.1016/j.aca.2023.341884. 0003-2670 http://hdl.handle.net/20.500.12327/2907 https://doi.org/10.1016/j.aca.2023.341884 Analysing olive ripening with digital image RGB histograms