Assessment of Microwave Drying Conditions Effect on Pineapple Color Quality and Stability via Multivariate Data Analysis

Öz

Fruit-based snacks produced via drying methods have gained commercial relevance in the global food industry. Different drying technique distinctly influences food quality attributes. Color is one of the most fundamental quality parameters of a food, and undesirable color changes in dried foods can lead to reduced marketability and final quality. This study was investigated that the effects of microwave power level (200 and 600 W) (MD) and slice thickness (3 and 5 mm) on color retention in pineapples. Colorimetric parameters (L*a*b*Ch), Browning Index (BI), Whiteness Index (WI), and total color difference (ΔE) were evaluated. Additionally, Principal Component Analysis (PCA) and Soft Independent Modeling of Class Analogy (SIMCA) analyses were conducted using color models. The findings demonstrated that MD power intensity and pineapple slice thickness had a pronounced effect on color properties. Increased MD power intensity and slice thickness resulted in significant reductions in L*, b*, C, and WI values, while a*, ΔE, and BI values exhibited marked increases, indicating intensified pigment degradation and non-enzymatic browning reactions. The most favorable visual quality was achieved at 200 W combined with 3 mm slice thickness, minimizing thermal damage and preserving yellow hues. PCA, explained for 97% of the total variance and effectively differentiated the samples according to drying conditions. Furthermore, the SIMCA analysis revealed that pineapple slices obtained through different drying methods could be classified based on their color data with 85% accuracy. The study demonstrates that maintaining the chromatic integrity and visual quality of microwave-dried pineapples requires careful optimization of both power density and slice dimensions.

Anahtar Kelimeler

• Color models
• Functional foods
• Pineapple chips
• Pineapple snacks
• Slice thickness

Mikrodalga Kurutma Koşullarının Ananasın Renk Kalitesi ve Stabilitesi Üzerine Etkisinin Çok Değişkenli Veri Analizleri ile Değerlendirilmesi

Öz

Farklı kurutma yöntemleriyle üretilen meyve bazlı atıştırmalıklar, küresel gıda endüstrisinde ticari önem kazanmıştır. Uygulanan kurutma teknikleri, ürünün kalite parametrelerini belirgin şekilde etkilemektedir. Renk, gıdanın en temel kalite göstergelerinden biridir ve kurutma sürecine bağlı olarak meydana gelen istenmeyen renk değişimleri, ürünün pazarlanabilirliğini ve nihai kalitesini azaltabilir. Bu çalışmada, mikrodalga gücü (200 ve 600 W) ile dilim kalınlığının (3 ve 5 mm), ananas dilimlerinin renk stabilitesi üzerindeki etkileri araştırılmıştır. L*, a*, b*, C*, h, Beyazlık İndeksi (WI), Karamelizasyon İndeksi (BI) ve renk farkı (ΔE) gibi kolorimetrik parametreler değerlendirilmiştir. Ayrıca renk verilerine dayalı olarak Temel Bileşenler Analizi (PCA) ve Sınıf Benzetimi için Bağımsız Modelleme (SIMCA) analizleri uygulanmıştır. Bulgular, mikrodalga gücü ve dilim kalınlığının renk özelliklerini önemli ölçüde etkilediğini göstermiştir. Güç yoğunluğu ve kalınlık arttıkça L*, b*, C* ve WI değerleri azalmış; a*, ΔE ve BI değerlerinde ise artış gözlenmiş, bu durum pigment bozulmaları ve enzimatik olmayan kararma reaksiyonlarının arttığını göstermiştir. En iyi görsel kalite, 200 W ve 3 mm dilim kalınlığında elde edilmiştir. PCA, toplam varyansın %97’sini açıklamış ve örnekleri kurutma koşullarına göre ayırt etmiştir. SIMCA ise renk verilerine göre örnekleri %85 doğrulukla sınıflandırmıştır. Elde edilen veriler, renk bütünlüğünün korunması için mikrodalga gücü ve dilim kalınlığının optimize edilmesi gerektiğini ortaya koymuştur.

Anahtar Kelimeler

• Renk modelleri
• Fonksiyonel gıdalar
• Ananas cipsleri
• Ananas atıştırmalıkları
• Dilim kalınlığı

Kaynakça

1. Adiletta, G., Di Matteo, M., & Petriccione, M. (2021). Multifunctional role of chitosan edible coatings on antioxidant systems in fruit crops: A review. International Journal of Molecular Sciences, 22(5), 2633. https://doi.org/10.3390/ijms22052633
2. Ainebyona, P. I., Yekoyada, M., Kigozi, J., & Agnes, N. (2023). The effects of slice thickness and pre-treatment concentration on the quality characteristics of solar dried pineapple. European Journal of Agriculture and Food Sciences, 5(4), 47–54. https://doi.org/10.24018/ejfood.2023.5.4.454
3. Ali, M. M., Hashim, N., Abd Aziz, S., & Lasekan, O. (2020). Pineapple (Ananas comosus): A comprehensive review of nutritional values, volatile compounds, health benefits, and potential food products. Food Research International, 137, 109675. https://doi.org/10.1016/j.foodres.2020.109675
4. Arslan, A. (2021). The usability of color and near infrared reflection data in determination of adulteration in dried and powdered organic black carrot [Doctoral dissertation, Hatay Mustafa Kemal University, Department of Biosystem Engineering]. httpss://avesis.mku.edu.tr/yonetilen-tez/56d56224-7242-456a-885a-ceaec8c77048/kurutulup-toz-haline-getirilmis-organik-siyah-havucta-tagsisin-belirlenmesinde-renk-ve-yakin-kizilotesi-yansima-verilerinin-kullanilabilirligi
5. Arslan, A., & Alibas, İ. (2024). Assessing the effects of different drying methods and minimal processing on the sustainability of the organic food quality. Innovative Food Science & Emerging Technologies, 94, 103681. https://doi.org/10.1016/j.ifset.2024.103681
6. Arslan, A., & Alibas, İ. (2025). Non-destructive quality assessment of fresh and dried chili peppers: Prediction of vitamin, protein, macro and micro-nutrient content via color models and multivariate analysis. Microchemical Journal, 215, 114477. https://doi.org/10.1016/j.microc.2025.114477
7. Arslan, A., Aygun, Y. Z., Turkmen, M., Celiktas, N., & Mert, M. (2025a). Combining non-destructive devices and multivariate analysis as a tool to quantify the fatty acid profiles of linseed genotypes. Talanta, 281, 126798. https://doi.org/10.1016/j.talanta.2024.126798
8. Arslan, A., Celiktas, N., Soysal, Y., & Keskin, M. (2025b). Comparison of total phenolic content in organic and conventional carrot under different drying conditions using non-destructive analysis techniques. Microchemical Journal, 208, 112279. https://doi.org/10.101/10.1016/j.microc.2024.112279

9. Arslan, A., Keskin, M., & Soysal, Y. (2023a). Rapid and non-destructive detection of organic carrot powder adulteration using spectroscopic techniques. Journal of Food Composition and Analysis, 123, 105572. https://doi.org/10.1016/j.jfca.2023.105572
10. Arslan, A., Soysal, Y., & Keskin, M. (2020). Mathematical modeling, moisture diffusion and color quality in intermittent microwave drying of organic and conventional sweet red peppers. AgriEngineering, 2(3), 393–407. https://doi.org/10.3390/agriengineering2030027
11. Arslan, A., Soysal, Y., & Keskin, M. (2023b). Comparative investigation of drying and quality characteristics of organic and conventional black carrots dried by intermittent microwave and hot air drying. Journal of Tekirdag Agricultural Faculty, 20(3), 591–604. https://doi.org/10.33462/jotaf.1169657
12. Aygun, Y. Z., Arslan, A., & Mert, M. (2024). Is dual-purpose flax production feasible in the Amik Plain? A preliminary study on cultivar performance and harvesting stage. Mustafa Kemal University Journal of Agricultural Sciences, 29(1), 281–289. https://doi.org/10.37908/mkutbd.1394730
13. Aygun, Y. Z., Eren, Y., & Ertekin, E. N. (2022). Diurnal variation of essential oil ratio and composition of some basil genotypes. Bangladesh Journal of Botany, 51(4), 787–795. https://doi.org/10.3329/bjb.v51i4.63498
14. Aygun, Y. Z., & Mert, M. (2022). Determination of yield characters of some linseed (Linum usitatissimum) cultivars under rainfed condition in Eastern Mediterranean. Journal of Applied Biological Sciences, 16(3), 527–536. https://doi.org/10.71336/jabs.1046
15. Biancolillo, A., De Luca, S., Bassi, S., Roudier, L., Bucci, R., Magrì, A. D., & Marini, F. (2018). Authentication of an Italian PDO hazelnut (“Nocciola Romana”) by NIR spectroscopy. Environmental Science and Pollution Research, 25(29), 28780–28786. https://doi.org/10.1007/s11356-018-1755-2
16. Brendel, R., Schwolow, S., Gerhardt, N., & Fauhl-Hassek, C. (2021). MIR spectroscopy versus MALDI-ToF-MS for authenticity control of honeys from different botanical origins based on soft independent modelling by class analogy (SIMCA)—A clash of techniques? Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 263, 120225. https://doi.org/10.1016/j.saa.2021.120225
17. Boateng, I. D. (2023a). A review of solar and solar‐assisted drying of fresh produce: State of the art, drying kinetics, and product qualities. Journal of the Science of Food and Agriculture, 103(13), 6137–6149. https://doi.org/10.1002/jsfa.12660
18. Boateng, I. D. (2023b). Thermal and nonthermal assisted drying of fruits and vegetables. Underlying principles and role in physicochemical properties and product quality. Food Engineering Reviews, 15(1), 113–155. https://doi.org/10.1007/s12393-022-09326-y
19. Chen, J., Liu, H., Li, T., & Wang, Y. (2023). Edibility and species discrimination of wild bolete mushrooms using FT-NIR spectroscopy combined with DD-SIMCA and RF models. LWT - Food Science and Technology, 180, 114701. https://doi.org/10.1016/j.lwt.2023.114701
20. Chen, R., Xu, L., Zhang, S., Duan, Y., Zhu, C., Zhao, P., & Guo, Y. (2025). Optimizing slicing to boost quality in hot air-dried shiitake mushroom. LWT, 118026. https://doi.org/10.1016/j.lwt.2025.118026
21. Chobot, M., Kozłowska, M., Ignaczak, A., & Kowalska, H. (2024). Development of drying and roasting processes for the production of plant-based pro-healthy snacks in the light of nutritional trends and sustainable techniques. Trends in Food Science & Technology, 104553. https://doi.org/10.1016/j.tifs.2024.104553
22. Cruz-Tirado, J. P., Muñoz-Pastor, D., de Moraes, I. A., Menevseoglu, A., & Barbin, D. F. (2023). Comparing data-driven soft independent class analogy (DD-SIMCA) and one-class partial least square (OC-PLS) to authenticate sacha inchi (Plukenetia volubilis L.) oil using portable NIR spectrometer. Chemometrics and Intelligent Laboratory Systems, 242, 105004. https://doi.org/10.1016/j.chemolab.2023.105004
23. Davies, A. M. C., & Fearn, T. (2008). Back to basics: Multivariate qualitative analysis, ‘SIMCA’. Spectroscopy Europe, 20(6), 15–19.
24. De Souza, R. R., de Sousa Fernandes, D. D., & Diniz, P. H. G. D. (2021). Honey authentication in terms of its adulteration with sugar syrups using UV–Vis spectroscopy and one-class classifiers. Food Chemistry, 365, 130467. https://doi.org/10.1016/j.foodchem.2021.130467
25. Dehghannya, J., & Habibi-Ghods, M. (2025). Influence of microwave power and pulse ratio on color, sensory attributes, and microstructure of potato slices during intermittent microwave-hot-air drying. Journal of Agriculture and Food Research, 102141. https://doi.org/10.1016/j.jafr.2025.102141
26. Esbensen, K. H. (2009). Multivariate data analysis – In practice (5th ed.). Camo Software AS.
27. Galvan, D., Lelis, C. A., Effting, L., Borges, D. L. G., & de Andrade, J. C. (2022). Low-cost spectroscopic devices with multivariate analysis applied to milk authenticity. Microchemical Journal, 181, 107746. https://doi.org/10.1016/j.microc.2022.107746
28. García-Gutiérrez, N., Mellado-Carretero, J., Bengoa, C., & Ferrando, M. (2021). ATR-FTIR spectroscopy combined with multivariate analysis successfully discriminates raw doughs and baked 3D-printed snacks enriched with edible insect powder. Foods, 10(8), 1806. https://doi.org/10.3390/foods10081806
29. Ghiasi, S., & Parastar, H. (2021). Chemometrics-assisted isotope ratio fingerprinting based on gas chromatography/combustion/isotope ratio mass spectrometry for saffron authentication. Journal of Chromatography A, 1657, 462587. https://doi.org/10.1016/j.chroma.2021.462587
30. Godlewska, K., Pacyga, P., Michalak, I., Biesiada, A., Szumny, A., Pachura, N., & Piszcz, U. (2020). Field-scale evaluation of botanical extracts effect on the yield, chemical composition and antioxidant activity of celeriac (Apium graveolens L. var. rapaceum). Molecules, 25(18), 4212. https://doi.org/10.3390/molecules25184212
31. Gunning, Y., Davies, K. S., & Kemsley, E. K. (2023). Authentication of saffron using 60 MHz 1H NMR spectroscopy. Food Chemistry, 404(Part B), 134649. https://doi.org/10.1016/j.foodchem.2022.134649
32. Hossain, M. F., Akhtar, S., & Anwar, M. (2015). Nutritional value and medicinal benefits of pineapple. International Journal of Nutrition and Food Sciences, 4(1), 84–88. https://doi.org/10.11648/j.ijnfs.20150401.22
33. HunterLab. (2008). Application note: Hunter L, a, b color scale. Insight on Color, 8(9), 1–4.
34. Izli, N., Izli, G., & Taskin, O. (2018). Impact of different drying methods on the drying kinetics, color, total phenolic content and antioxidant capacity of pineapple. CyTA – Journal of Food, 16(1), 213–221. https://doi.org/10.1080/19476337.2017.1381174
35. Karabacak, A. Ö., Suna, S., Tamer, C. E., & Çopur, Ö. U. (2018). Effects of oven, microwave and vacuum drying on drying characteristics, colour, total phenolic content and antioxidant capacity of celery slices. Quality Assurance and Safety of Crops & Foods, 10(2), 193–205. https://doi.org/10.3920/QAS2017.1197
36. Karunathilaka, S. R., Kia, A. R. F., Srigley, C., Chung, J. K., & Mossoba, M. M. (2016). Nontargeted, rapid screening of extra virgin olive oil products for authenticity using near‐infrared spectroscopy in combination with conformity index and multivariate statistical analyses. Journal of Food Science, 81(10), C2390–C2397. https://doi.org/10.1111/1750-3841.13432
37. Karunathilaka, S. R., Yakes, B. J., He, K., Huang, Y., & Elliott, C. T. (2018). Non-targeted NIR spectroscopy and SIMCA classification for commercial milk powder authentication: A study using eleven potential adulterants. Heliyon, 4(9), e00806. https://doi.org/10.1016/j.heliyon.2018.e00806
38. Keskin, M., Arslan, A., Soysal, Y., Sekerli, Y. E., & Celiktas, N. (2022). Feasibility of a chromameter and chemometric techniques to discriminate pure and mixed organic and conventional red pepper powders: A pilot study. Journal of Food Processing and Preservation, 46(6), e15846. https://doi.org/10.1111/jfpp.15846
39. Kooti, W., & Daraei, N. (2017). A review of the antioxidant activity of celery (Apium graveolens L.). Journal of Evidence-Based Complementary & Alternative Medicine, 22(4), 1029–1034. https://doi.org/10.1177/21565872177174
40. Kręcisz, K., Nowacka, M., & Witrowa-Rajchert, D. (2023). Quality assessment of dried fruits: Color, texture, and acceptability thresholds. Food Control, 144, 109339. https://doi.org/10.1016/j.foodcont.2022.109339.
41. Lalhruaitluangi, N., & Mandal, D. (2024). Medicinal and nutritional characteristics of pineapple in human health: A review. Journal of Postharvest Technology, 12(2), 1–13. https://doi.org/10.48165/jpht.2024.12.2.01
42. Le Nguyen Doan, D., Nguyen, Q. C., Marini, F., & Biancolillo, A. (2021). Authentication of rice (Oryza sativa L.) using near infrared spectroscopy combined with different chemometric classification strategies. Applied Sciences, 11(1), 362. https://doi.org/10.3390/app11010362
43. Lixourgioti, P., Goggin, K. A., Zhao, X., & Kemsley, E. K. (2022). Authentication of cinnamon spice samples using FT-IR spectroscopy and chemometric classification. LWT - Food Science and Technology, 154, 112760. https://doi.org/10.1016/j.lwt.2021.112760
44. Majumder, P., Sinha, A., Gupta, R., & Sablani, S. S. (2021). Drying of selected major spices: Characteristics and influencing parameters, drying technologies, quality retention and energy saving, and mathematical models. Food and Bioprocess Technology, 14(6), 1028–1054. https://doi.org/10.1007/s11947-021-02646-7
45. Mehraj, M., Das, S., Feroz, F., Waheed Wani, A., Dar, S. Q., Kumar, S., & Farid, A. (2024). Nutritional composition and therapeutic potential of pineapple peel – A comprehensive review. Chemistry & Biodiversity, 21(5), e202400315. https://doi.org/10.1002/cbdv.202400315
46. Ming, R. (Ed.). (2018). Genetics and genomics of pineapple. Springer International Publishing. Netto, J. M., Honorato, F. A., Celso, P. G., Borges, D. L. G., & de Andrade, J. C. (2023). Authenticity of almond flour using handheld near infrared instruments and one class classifiers. Journal of Food Composition and Analysis, 115, 104981. https://doi.org/10.1016/j.jfca.2022.104981
47. Pathare, P. B., Opara, U. L., & Al-Said, F. A. J. (2013). Colour measurement and analysis in fresh and processed foods: A review. Food and Bioprocess Technology, 6, 36–60. https://doi.org/10.1007/s11947-012-0867-9
48. Redwan, R. M., Saidin, A., & Kumar, S. V. (2015). Complete chloroplast genome sequence of MD-2 pineapple and its comparative analysis among nine other plants from the subclass Commelinidae. BMC Plant Biology, 15(1), 196. https://doi.org/10.1186/s12870-015-0587-1
49. Sabarez, H. T. (2016). Airborne ultrasound for convective drying intensification. In Innovative Food Processing Technologies (pp. 361–386). Woodhead Publishing. https://doi.org/10.1016/B978-0-08-100294-0.00014-6
50. Shamsudin, R., Che Man, H., Ariffin, S. H., & Azmi, N. S. (2023). Kinetics of color changes during pretreatment blanching of pineapple (Ananas comosus) fruit variety ‘MD2’. Pertanika Journal of Tropical Agricultural Science, 46(4), 1–13. https://doi.org/10.47836/pjtas.46.4.13
51. Shawky, E., El-Khair, R. M. A., & Selim, D. A. (2020). NIR spectroscopy–multivariate analysis for rapid authentication, detection and quantification of common plant adulterants in saffron (Crocus sativus L.) stigmas. LWT - Food Science and Technology, 122, 109032. https://doi.org/10.1016/j.lwt.2019.109032
52. Stilo, F., Jiménez-Carvelo, A. M., Liberto, E., Bicchi, C., Reichenbach, S. E., Cuadros-Rodríguez, L., & Cordero, C. (2021). Chromatographic fingerprinting enables effective discrimination and identification of high-quality Italian extra-virgin olive oils. Journal of Agricultural and Food Chemistry, 69(31), 8874–8889. https://doi.org/10.1021/acs.jafc.1c02981
53. Soysal, Y. (2004). Microwave drying characteristics of parsley. Biosystems Engineering, 89(2). https://doi.org/10.1016/j.biosystemseng.2004.07.008
54. Soysal, Y. (2005). Mathematical modeling and evaluation of microwave drying kinetics of mint (Mentha spicata L.). Journal of Applied Sciences, 5(7), 1266–1274. https://doi.org/10.3923/jas.2005.1266.1274
55. Soysal, Y., Öztekin, S., & Eren, Ö. (2006). Microwave drying of parsley: Modelling, kinetics, and energy aspects. Biosystems Engineering, 93(4), 403–413. https://doi.org/10.1016/j.biosystemseng.2006.01.017
56. Soysal, Y., Keskin, M., Arslan, A., & Sekerli, Y. E. (2018, October 31- November 2). Infrared drying characteristics of pepper at different maturity stages. [Paper presentation]. In International Conference on Energy Research (pp. 1–2).
57. Totaro, M. P., Squeo, G., De Angelis, D., Summo, C., & Pasqualone, A. (2023). Application of NIR spectroscopy coupled with DD-SIMCA class modelling for the authentication of pork meat. Journal of Food Composition and Analysis, 118, 105211. https://doi.org/10.1016/j.jfca.2023.105211
58. Tiliwa, E. S., Boateng, I. D., Zhou, C., & Xu, B. (2023). Role of drying technologies on the drying kinetics, physical quality, aroma, and enzymatic activity of pineapple slices. Sustainability, 15(22), 15906. https://doi.org/10.3390/su152215906
59. Vega-Mercado, H., Góngora-Nieto, M. M., & Barbosa-Cánovas, G. V. (2001). Advances in dehydration of foods. Journal of Food Engineering, 49(4), 271–289. https://doi.org/10.1016/S0260-8774(00)00224-7
60. Wali, N. (2019). Pineapple (Ananas comosus). In Nonvitamin and Nonmineral Nutritional Supplements (pp. 367–373). Academic Press. https://doi.org/10.1016/B978-0-12-812491-8.00050-3
61. Wang, P., Lv, W., & Wang, H. (2025). Effects of freeze-hot air drying on physicochemical properties and anti-tyrosinase activity of quince peels. Food Chemistry, 463, 141507. https://doi.org/10.1016/j.foodchem.2024.141507.
62. Wilde, A. S., Sørensen, S., Kucheryavskiy, S., & Sand, S. (2023). Patterns in official food control data—Modelling dioxin and PCB profiling data for authentication of Baltic Sea salmon. Journal of Food Composition and Analysis, 124, 105607. https://doi.org/10.1016/j.jfca.2023.105607
63. Xu, B., Tiliwa, E. S., Wei, B., Wang, B., Hu, Y., Zhang, L., & Ma, H. (2022). Multi-frequency power ultrasound as a novel approach improves intermediate-wave infrared drying process and quality attributes of pineapple slices. Ultrasonics Sonochemistry, 88, 106083. https://doi.org/10.1016/j.ultsonch.2022.106083
64. Yan, W. M., Chen, C. Y., Chen, B. L., Amani, M., Chien, L. H., & Li, W. K. (2025). Optimization of microwave vacuum drying of pineapples: A three-stage approach. Results in Engineering, 25, 104228. https://doi.org/10.1016/j.rineng.2025.104228