Development and implementation of an affordable high-throughput imaging system for phenotyping enzymatic browning in apples
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Date
2025-11-20
Authors
Miranda, CarlosIrisarri Sarto, Patricia
Crespo Martínez, Sara
Bielsa González, Francisco Javier
Iturmendi, Nerea
Romeo, Haizea
Urrestarazu Vidart, Jorge
Pina Sobrino, Ana
Santesteban García, Luis Gonzaga
Castel Duaso, Lourdes
Errea Abad, María Pilar
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier B.V.
Typology
Artículo oríginalAbstract
Enzymatic browning (EB) substantially affects the visual quality and marketability of fresh-cut apples. This study aimed to develop an affordable high-throughput imaging system for phenotyping EB in apples. Browning was quantified using four CIELab-derived indices; a browning Index (BI), the difference in BI (∆BI), a normalized CIE color difference (∆E*); and a CIEDE2000 color difference (∆E00) at multiple time points post-cutting to evaluate browning speed (SEB) and intensity (IEB) in 142 apple cultivars, including commercial and traditional Spanish cultivars from germplasm collections. The image-based system has demonstrated high accuracy and practical relevance, overcoming limitations associated with traditional colorimeter-based approaches. A wide phenotypic range was observed, in which elite reference cultivars fell within a narrow band at the lower end of the range. Measurements taken at 30 min post-cutting were found to be nearly equivalent to those at 60 min, allowing to optimize the phenotyping protocol without compromising precision. EB has been shown to be an inherently stable trait, though different year effects were noted, particularly for BI and ∆BI. Among the indices evaluated, ∆E00 proved less effective for cultivar differentiation, whereas ∆BI showed the highest discriminant capacity and strongest correlation with visual browning, making it the most suitable index for phenotyping purposes. These findings provide a robust methodological basis for screening low-browning apple genotypes, establish a classification framework for EB expression levels, and highlight the potential of underutilized traditional cultivars in developing improved fresh-cut apple products.
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Bibliographic citation
Miranda, C., Irisarri, P., Crespo-Martínez, S., Bielsa, F. J., Iturmendi, N., Romeo, H., Urrestarazu, J., Pina, A., Santesteban, L. G., Castel, L., & Errea, P. (2026). Development and implementation of an affordable high-throughput imaging system for phenotyping enzymatic browning in apples. Postharvest Biology and Technology, 233, 114066. https://doi.org/10.1016/j.postharvbio.2025.114066
AGROVOC subjects
Malus domesticaPardeamiento enzimático
Recurso genético vegetal
Análisis de imágenes
Fisiología postcosecha
Sponsorship
This work has been funded by the projects PID2019-108081RR-C21-C22, and PID2022–141847OR-C31-C32 funded by MCIN/AEI 10.13039/501100011033 ERDF, UE and the consolidated group A12 of Gobierno de Aragón – European social fund of the European Union. Open access funding provided by Universidad Pública de Navarra.