TY - JOUR T1 - Image-based quantification of size, color, and image texture in meagre (Argyrosomus regius (Asso, 1801)) reared in different culture systems TT - Farklı kültür koşullarında yetiştirilen granyöz’ün (Argyrosomus regius (Asso, 1801)) boyutu, deri rengi ve görsel dokusunun görüntü tabanlı nicel analizi AU - Gümüş, Bahar AU - Ünlü, Canan AU - Gümüş, Erkan AU - Balaban, Murat Ömer PY - 2026 DA - March Y2 - 2026 DO - 10.12714/egejfas.43.1.09 JF - Ege Journal of Fisheries and Aquatic Sciences JO - EgeJFAS PB - Ege Üniversitesi WT - DergiPark SN - 2148-3140 SP - 76 EP - 85 VL - 43 IS - 1 LA - en AB - Meagre is an important fish both regarding fisheries and aquaculture. Visual attributes of whole meagre are important for the purchase intention of consumers. Whole meagre grown in cages and earthen ponds were evaluated by image analysis for visual attributes (length, view area, color of right and left sides, image texture). The fish were weighed, and images of both sides were taken. Weight W vs length L data were fitted a power equation W = A LB. The B values for cage and earthen pond fish were 2.95 and 2.93, respectively. The R2 values for power fit to weight vs view area were 0.976 for cage fish, and 0.983 for earthen pond fish, respectively. The 1st null hypothesis was that the colors of cage and earthen pond-reared fish were not different. The 2nd null hypothesis was that for both type fish the colors of the right and left colors were not different. Specifically, the cage fish were lighter than the earthen pond-reared fish. The L*, a* and b* values of cage fish were statistically different than those of earthen pond fish (p<0.05). The a* values of both sides of cage and earthen pond fish, and b* values of both sides of cage fish were statistically different (p<0.05). Delta E values between the right and left skin colors for cage and earthen pond fish were 1.89, and 1.78, respectively, suggesting noticeable difference upon close examination. Also, there were 13 out of 53 Delta E values greater than 3 for cage fish, and 10 out of 66 for earthen pond fish. Texture change index and color change index of cage and earthen pond fish were statistically different (p<0.05). This suggests considering both sides of the fish should be considered in evaluating color and image texture. KW - Meagre KW - morphometric data KW - color KW - image texture KW - image analysis N2 - Granyöz hem balıkçılık hem de su ürünleri yetiştiriciliği açısından önemli bir balıktır. Granyöz balığının görsel özellikleri, tüketicilerin satın alma niyeti için önemlidir. Kafeslerde ve toprak havuzlarda yetiştirilen bütün granyöz balıkları, görsel özellikler (uzunluk, görüş alanı, sağ ve sol tarafların rengi, görüntü dokusu) açısından görüntü analizi ile değerlendirilmiştir. Balıklar tartıldıktan sonra her iki tarafının görüntüleri alınmıştır. Ağırlık (W) ve uzunluk (L) verileri, W = A LB güç denkleminden yararlanılarak değerlendirilmiştir. Kafes ve toprak havuz balıkları için B değerleri sırasıyla 2,95 ve 2,93’tür. Ağırlık ve görüş alanı arasındaki güç uyumunun R2 değerleri kafes balıkları için 0,976, toprak havuz balıkları için ise 0,983’tür. Çalışmada ortaya konan iki hipotezden birincisi, kafes ve toprak havuzda yetiştirilen balıkların renklerinin farklı olmadığıdır. İkinci ise, her iki balık türü için de sağ ve sol tarafların renklerinin farklı olmadığıdır. Özellikle, kafes balıkları toprak havuzlarda yetiştirilen balıklardan daha hafiftir. Kafes balıklarının L*, a* ve b* değerleri toprak havuz balıklarının değerlerinden istatistiksel olarak farklıdır (p<0.05). Kafes ve toprak havuz balıklarının her iki tarafının a* değerleri ve kafes balıklarının her iki tarafının b* değerleri istatistiksel olarak farklı bulunmuştur (p<0.05). Kafes ve toprak havuz balıkları için sağ ve sol deri renkleri arasındaki Delta E değerleri sırasıyla 1,89 ve 1,78 olup yakından incelendiğinde gözle görülür bir fark olduğunu göstermektedir. Ayrıca, kafes balıkları için 53 Delta E değerinden 13'ü, toprak havuz balıkları için ise 66 Delta E değerinden 10'u 3'ten büyüktür. Kafes ve toprak havuz balıklarının doku değişim indeksi ve renk değişim indeksi istatistiksel olarak farklıdır (p<0.05). Bu, renk ve görüntü dokusunu değerlendirirken balığın her iki tarafının da dikkate alınması gerektiğini göstermektedir. CR - Alçiçek, Z., & Balaban, M.O. (2012). Development and application of “The Two Image” method for accurate object recognition and color analysis. Journal of Food Engineering, 111(1), 46 51. https://doi.org/10.1016/j.jfoodeng.2012.01.031 CR - Arzate-Vazquez, I., Chanona-Perez, J., Calderon-Dominguez, G., Terres-Rojas, E., Garibay-Febles, V., Martinez-Rivas, A., & Gutierrez-Lopez, G.V. (2012). Microstructural characterization of chitosan and alginate films by microscopy techniques and texture image analysis. Carbohydrat Polymer, 87(1), 289-299. https://doi.org/10.1016/j.carbpol.2011.07.044 CR - Balaban, M.O. (2008). Quantifying non-homogeneous colors in agricultural materials. Part I: Method development. Journal of Food Science, 73(9), 431-437. https://doi.org/10.1111/j.1750-3841.2008.00807.x CR - Balaban, M.O., Şengör, G.F.Ü., Soriano, M.G.,& Ruiz, E.G. (2010). Using image analysis to predict the weight of Alaskan salmon of different species. Journal of Food Science, 75(3), E157 162. https://doi.org/10.1111/j.1750-3841.2010.01522.x CR - Balaban, M.O., Stewart. K., Fletcher, G.C., & Alcicek, Z. (2014). Color change of the snapper (Pagrus auratus) and gurnard (Chelidonichthys kumu) skin and eyes during storage: effect of light polarization and contact with ice. Journal of Food Science, 79(12), E2456-E2462. https://doi.org/10.1111/1750-3841.12693 CR - Başaran, A.K., Aksu, M., & Egemen, Ö. (2006). Ildır Koyu’nda (İzmir-Ege Denizi) açık deniz ağ kafeslerde yapılan balık yetiştiriciliğinin su kalitesi üzerine etkilerinin izlenmesi. Tarım Bilimleri Dergisi, 13 (1) 22-28. https://doi.org/10.1501/Tarimbil_0000000449 CR - Bavčević, L., Čolak, S., Barić, R., Petrović, S., & Klanjscek, T. (2025). Sardine-based diet mitigates growth depression at low temperatures in juvenile meagre (Argyrosomus regius Asso, 1801). Fishes, 10(7), 314. https://doi.org/10.3390/fishes10070314 CR - Bobori, D.C., Moutopoulos, D.K., Bekri, M., Salvarina, I., & Munoz, A.I.P. (2010). Length-weight relationships of freshwater fish species caught in three Greek lakes. Journal of Biological Research, Thessalon. 14, 219-224. CR - Bodur, T. (2018). Sarıağız (Argyrosomus regius, Asso 1801) Balığının Toprak Havuzlarda Ticari Yetiştiriciliğinde Bazı Büyüme Parametrelerinin Belirlenmesi. Süleyman Demirel Üniversitesi Eğirdir Su Ürünleri Fakültesi Dergisi, 14(3):232-240. https://doi.org/ 10.22392/egirdir.397705 CR - Bök, T.D., Göktürk, D., Kahraman, A.E., Alicli, T.Z., Acun. T., & Ateş, C. (2011). Length-weight relationship of 34 fish species from the sea of Marmara, Turkey. Journal of Animal and Veterinary Advances, 10(23), 3037-3042. https://doi.org/10.3923/javaa.2011.3037.3042 CR - Duncan, D. (1955). Multiple range and multiple F tests. Biometrics. 11(1), 1–42. CR - Duncan, N.J., Estevez, A., Fernández-Palacios, H., Gairin, I., Hernandez‐Cruz, M., Roo, J., Schuchardt, D., & Vallés, R. (2013). Aquaculture production of meagre (Argyrosomus regius): hatchery techniques, ongrowing and market. Advances in Aquaculture Hatchery Technology, 519-541. https://doi.org/10.1533/9780857097460.3.519 CR - FAO. Global Aquaculture Production Quantity (1950–2021). (2023). Available online: https://www.fao.org/fishery/statistics query/en/aquaculture/aquaculture_quantity (Accessed 9 January 2025) CR - Fountoulaki, E., Grigorakis, K., Kounna, C., Rigos, G., Papandroulakis, N., Diakogeorgakis, J., & Kokou, F. (2017). Growth performance and product quality of meagre (Argyrosomus regius) fed diets of different protein/lipid levels at industrial scale. Italian Journal of Animal Science, 16(4), 685–694. https://doi.org/10.1080/1828051X.2017.1305259 CR - Froese, R. (2006). Cube law, condition factor and weight-length relationships: history, meta-analysis and recommendations. Journal of Applied Ichthyology, 22, 241 253. https://doi.org/10.1111/j.1439 0426.2006.00805.x CR - Gerami, M.H., Abdollahi, D., Patimar, R., & Abdollahi, M. (2013). Length–weight relationship of two fish species from Cholvar River, western Iran: Mastacembelus mastacembelus (Banks & Solander, 1794) and Glyptothorax silviae Coad, 1981. Journal of Applied Ichthyology, 30 (1), 214-215. https://doi.org/10.1111/jai.12352 CR - Gümüş, B., Balaban, M.O., & Ünlüsayın, M. (2011). Machine vision applications to aquatic foods: A Review. Turkish Journal of Fisheries & Aquatic Science, 11, 171-181. https://doi.org/10.4194/trjfas.2011.0124 CR - Gümüş, B., Gümüş, E., & Balaban, M.O. (2022a). Image analysis to determine length-weight and area-weight relationships, and color differences in scaled carp and mirror carp grown in fiberglass and concrete tanks.Turkish Journal of Fisheries & Aquatic Science, 23 (1), TRJFAS21260. https://doi.org/10.4194/TRJFAS21260 CR - Gümüş, B., Gümüş, E., Odabaṣı-Kırlı, A., & Balaban, M.O. (2022b). Image analysis-based quantification of the visual attributes of fish, with emphasis on color and visual texture. International Journal of Food Engineering, 18(5), 411-423. https://doi.org/10.1515/ijfe-2022-0014 CR - Haffray, P., Malha, R., Sidi, M.O.T., Prista, N., Hassan, M., Castelnaud, G., Karahan-Nomm, B., Gamsız, K., Sadek, S., Bruant, J.S., Balma, P., & Bonhomme, F. (2012). Very high genetic fragmentation in a large marine fish, the meagre Argyrosomus regius (Sciaenidae, Perciformes): Impact of reproductive migration, oceanographic barriers and ecological factors. Aquatic Living Resources, 25(2), 173 183. https://doi.org/10.1051/alr/2012016 CR - Kounna, C., Fountoulaki, E., Miliou, H., & Chatzifotis, S. (2021). Water temperature effects on growth performance, proximate body and tissue composition, morphometric characteristics and gastrointestinal evacuation processes of juvenile meagre, Argyrosomus regius (Asso 1801). Aquaculture, 540, 736683. https://doi.org/10.1016/j.aquaculture.2021.736683 CR - Larkin, K.G. (2016). Reflections on Shannon information: in search of a natural information entropy for images. Available from: https://arxiv.org/abs/1609.01117 (Accessed 10 January 2025). Lazo, J.P., Holt, J.G., Fauvel, C., Suquet, M., & Quéméner, L. (2010). Drum-fish or Croakers (Family: Sciaenidae). In: Finfish Aquaculture Diversification. CAB International, Cambridge, USA, 405-416. CR - Lozano, A.R., Borges, P., Robaina, L., Betancor, M., Hernandez-Cruz, C.M., Romero Garcia, J., Caballero, M.J., Vergara, J.M., & Izquierdo, M. (2017). Effect of different dietary vitamin E levels on growth, fish composition, fillet quality and liver histology of meagre (Argyrosomus regius). Aquaculture, 468, 175 183. https://doi.org/10.1016/j.aquaculture.2016.10.006 CR - Luzuriaga, D.A., Balaban, M.O., & Yeralan, S. (1997). Analysis of visual quality attributes of white shrimp by machine vision. Journal of Food Science, 62(1), 113 119. https://doi.org/10.1111/j.13652621.1997.tb04379.x CR - Misimi, E., Erikson, U., & Skavhaug, A. (2008). Quality grading of Atlantic salmon (Salmo salar) by computer vision. Journal of Food Science, 73(5), E211–E217. https://doi.org/10.1111/j.1750-3841.2008.00779.x CR - Mylonas, C.C., Mitrizakis, N., Papadaki, M., & Sigelaki, I. (2013). Reproduction of hatchery-produced meagre Argyrosomus regius in captivity I. Description of the annual reproductive cycle. Aquaculture, 414/415, 309–317. https://doi.org/10.1016/j.aquaculture.2013.09.009 CR - Navarro, A., Lee-Montero, I., Santana, D., Henríquez, P., Ferrer, M.A., Morales, A., Soula, M., Badilla, B., Negrín-Báez, D., Zamorano, M.J., & Afonso, J.M. (2016). IMAFISH_ML: A fully-automated image analysis software for assessing fish morphometric traits on gilthead seabream (Sparus aurata L.), meagre (Argyrosomus regius) and red porgy (Pagrus pagrus). Computers and Electronics in Agriculture, 121, 66-73. https://doi.org/10.1016/j.compag.2015.11.015 CR - Oikonomou, S., Tasiouli, K., Tsaparis, D., Manousaki, T., Vallecillos, A., Oikonomaki, K., Tzokas, K., Katribouzas, N., Batargias, C., Chatziplis, D., & Tsigenopoulos, C. S. (2025). Genomic evaluation for body weight, length and growth estimates in meagre Argyrosomus regius. Aquaculture, 595, 741622. https://doi.org/10.1016/j.aquaculture.2024.741622 CR - Pastor, E., Grau, A., Massutí, E., & Sánchez-Madrid, A. (2002). Preliminary results on growth of meagre, Argyrosomus regius (Asso, 1801) in sea cages and indoor tanks. EAS Especial Publication, 32, 422-423. CR - Ribeiro, L., Soares, L., Quental-Ferreira, H., Gonçalves, A., & Pousão-Ferreira, P. (2013). Portuguese research studies meagre production in earthen ponds. Global Aquaculture Advocate, 16, 38-40. CR - Saavedra, M., Pereira, T.G., Carvalho, L.M., Pousão-Ferreira, P., Grade, A., Teixeira, B., Quental-Ferreira, H., Mendes, R., Bandarra, N., & Gonçalves, A. (2017). Wild and farmed meagre, Argyrosomus regius: A nutritional, sensory and histological assessment of quality differences. Journal of Food Composition and Analysis, 63, 8-14. https://doi.org/10.1016/j.jfca.2017.07.028 CR - Saavedra, M., Pereira, T.G., Candeias, M.A., Carvalho, L., Pousão, F.P., & Conceição, L.E.C. (2018). Effect of increased dietary protein level in meagre (Argyrosomus regius) juvenile growth and muscle cellularity. Aquaculture Nutrition, 24, 1153 1159. https://doi.org/10.1111/anu.12654 CR - Sinanoglou, V.J., Proestos, C., Lantzouraki, D.Z., Calokerinos, A.C. & Miniadis-Meimaroglou, S. (2014). Lipid evaluation of farmed and wild meagre (Argyrosomus regius). European Journal of Lipid Science and Technology, 116, 134-143. https://doi.org/10.1002/ejlt.201300346 CR - Şengör, Ü.G.F., Balaban, M., Topaloğlu, B., Ayvaz, Z., Ceylan, Z., & Doğruyol, H. (2018). Color assessment by different techniques of gilthead seabream (Sparus aurata) during cold storage. Food Science Technology, 39(3), 696-703. https://doi.org/10.1590/fst.02018 CR - TÜİK. (2024). https://data.tuik.gov.tr/Bulten/Index?p=Su Urunleri 202353702 (Accessed 5 January 2026) CR - Vallecillos, A., María-Dolores, E., Villa, J., Rueda, F.M., Carrillo, J., Ramis, G., Soula, M., Afonso, J.M., & Armero, E. (2021). Phenotypic and genetic components for growth, morphology, and flesh-quality traits of meagre (Argyrosomus regius) reared in tank and sea cage. Animals, 11(11), 3285. https://doi.org/10.3390/ani11113285 CR - Vallecillos, A., María-Dolores, E., Villa, J., Afonso, J.M., & Armero, E. (2023). Potential use of image analysis in breeding programs for growth and yield traits in meagre (Argyrosomus regius). Journal of Marine Science and Engineering, 11(11), 2067. https://doi.org/10.3390/jmse11112067 CR - Yavuzer, E., & Köse, M. (2022). Prediction of fish quality level with machine learning. International Journal of Food Science & Technology, 57(8), 5250–5255. https://doi.org/10.1111/ijfs.15853 CR - Young, B.C., Alzahrani, I.S., & AL Shaikhi, A. (2022). Current status of marine cage culture in Saudi Arabia. World Aquaculture, 53(4), 52-54. CR - Young, B.C., & AL Shaikhi, A. (2024). Meagre (Argyrosomus regius) culture in high salinity conditions. Bulgarian Journal of Agricultural Science, 30(5), 883–887 CR - Zupa, R., Hala, E., Ventriglia, G., Pousis, C., Passantino, L., Quaranta, A., Corriero, A., & De Virgilio, C. (2023). Reproductive maturation of meagre Argyrosomus regius (Asso, 1801) reared in floating cages. Animals,13(2), 223. https://doi.org/10.3390/ani13020223 UR - https://doi.org/10.12714/egejfas.43.1.09 L1 - https://dergipark.org.tr/tr/download/article-file/5382455 ER -