ایجاد یک سیستم‌ کارشناس برای تعیین ویژگی‌های مورد اندازه‌گیری میوه انگور نگهداری شده در سردخانه با استفاده از منطق فازی

نویسندگان
1 گروه تبدیل و نگهداری انگور، پژوهشکده انگور و کشمش، دانشگاه ملایر، ملایر، ایران
2 گروه مهندسی علوم باغبانی و فضای سبز، دانشکده کشاورزی، دانشگاه ملایر، ملایر، ایران
3 گروه ‌علوم و صنایع غذایی، دانشکده فنی و منابع طبیعی تویسرکان، دانشگاه بوعلی سینا، همدان، ایران
4 گروه ‌علوم و صنایع غذایی، دانشکده صنایع غذایی بهار، دانشگاه بوعلی سینا، همدان، ایران
چکیده
افزایش تولید و مصرف میوه انگور در جهان، نیاز به تحقیقات در زمینه ایجاد شرایطی برای حفظ بیشتر این میوه‌ را افزایش داده است و کمبود سنسور‌هایی که بتوانند اطلاعات دقیق را از فرایند تولید و نگهداری برای تصمیم‌گیری در اختیار سیستم‌های کنترل قرار دهند، بدیهی و مشهود می‌باشد. لذا این مطالعه با هدف تعیین برخی از ویژگی‌های میوه انگور (شاخص طعم، pH، سفتی، نشت یونی، E، تعداد کپک و پذیرش کلی) نگهداری شده در سردخانه در دامنه زمان نگهداری صفر تا 60 روز اندازه‌گیری شد و با توجه به اهمیت دست‌یابی به این ویژگی‌ها در طول انبارمانی میوه‌ها، مدلی با استفاده از منطق فازی ایجاد گردید که به عنوان یک سیستم کارشناس با دقت (با ضریب همبستگی بیشتر از 96/0) و سرعت بسیار بالا قادر به پیشگویی و تعیین این ویژگی‌های محصول تنها با استفاده از زمان نگهداری آن بود. این سیستم قادر بود، مقادیر هر یک از این ویژگی‌های مورد مطالعه را در هر زمان نگهداری دلخواه در محدوده‌ی صفر تا 60 روز با دقت بسیار بالا و در کسری از ثانیه به‌دست آورد. از طرفی مشخص گردید که با افزایش زمان نگهداری میزان شاخص طعم، pH، تعداد کپک‌ها، E و نشت یونی نمونه‌ها افزایش ولی میزان سفتی و پذیرش کلی کاهش یافت.
کلیدواژه‌ها

موضوعات


عنوان مقاله English

Development of an expert system to determine the measured characteristics of grape fruit stored in cold storage using fuzzy logic

نویسندگان English

Maryam Ebrahimi 1
Rouhollah Karimi 2
Amir Daraei Garmakhany 3
Narjes Aghajani 4
Alireza Shayeganfar 2
1 Grape Processing and Preservation Department, Faculty of Agriculture, Research Institute of Grape and Raisin, Malayer University, Malayer, Iran
2 Department of Horticulture and Landscape Engineering, Faculty of Agriculture, Malayer University, Malayer, Iran
3 Department of Food Science and Technology, Toyserkan Faculty of Engineering and natural resources, Bu-Ali Sina University, Hamadan, Iran
4 Department of Food Science and Technology, Bahar Faculty of Food Science and Technology, Bu-Ali Sina University, Hamadan, Iran
چکیده English

The increase in the production and consumption of grapes in the world has increased the need for research in the field of creating conditions for further preservation of this fruit, and the lack of sensors that can provide accurate information from the production and storage process to control systems for decision-making is obvious and evident. Therefore, this study aimed to determine some characteristics of grape fruit (taste index, pH, firmness, ion leakage, ∆E, number of mold and general acceptance) stored in cold storage in the range of storage time from 0 to 60 days was measured and according to the importance Achieving these characteristics during fruit storage, a model using fuzzy logic was created as an expert system with accuracy (with a correlation coefficient greater than 0.96) and very high speed capable of predicting and determining these product characteristics only by using It was time to save it. This system was able to obtain the value of each of these studied characteristics at any desired storage time in the range of 0 to 60 days with very high accuracy and in a fraction of a second. On the other hand, it was found that with increasing storage time, the amount of taste index, pH, number of molds, ∆E and ionic leakage of the samples increased, but the degree of hardness and overall acceptance decreased.

کلیدواژه‌ها English

Grapes
storage time
Qualitative characteristics
Fuzzy Logic
[1] Farzaneh, V., Ghodsvali, A., Bakhshabadi, H., Dolatabadi, Z., Farzaneh, F., Carvalho I.S. and Sarabandi, K. 2018. Screening of the alterations in qualitative characteristics of grape under the impacts of storage and harvest times using artificial neural network. Evolving Systems, 9: 81–89.
[2] Gallo, M., Formato, A., Giacco, R., Riccardi, G., Lungo, D., Formato, G., Amoresano, A. and Navigli, D. 2019. Mathematical optimization of the green extraction of polyphenols from grape peels through a cyclic pressurization process. Heliyon,5: Article e01526.
[3] Majeed, U., Shafi, A., Majeed,H., Akram, K., Liu, X., Ye, J. and Luo, Y. 2023. Grape (vitis vinifera L.) phytochemicals and their biochemical protective mechanisms against leading pathologies. Food Chemistry, 405. 10.1016/j.foodchem.2022.134762.
[4] Câmpean, S.I., Bechea, G.A., Tăbăcaru, M.B., Scutaru, L.M., Dragomir, G., Brezeanu, A.L., Șerban, A. and Năstase, G. 2023. Preservation of black grapes by isochoric freezing. Heliyon, 9(7): e17740, ISSN 2405-8440, https://doi.org/10.1016/j.heliyon.2023.e17740
[5] Droby, S. and Lichter, A. 2004. Post-harvest Botrytis infection: etiology, developmentand management. In: Elad, Y., Williamson, B., Tudzynski, P., Delen, N. (Eds.), Botrytis: Biology, Pathology and Control. Kluwer Academic Publishers, London,UK, pp. 349–367.
[6] Retamales, J., Defilippi, B.G., Arias, M., Castillo, O. and Manriquez, D. 2003. High CO2 controlled atmospheres reduce decay incidence in Thampson Seedless and Red Globe table grapes. Postharvest Biology and Technology, 29: 177-182.
[7] Lado, J., Gurrea, A., Zacarias, L. and Rodrigo, M.J. 2019. Influence of the storage temperature on volatile emission, carotenoid content and chilling injury development in Star Ruby red grapefruit. Food Chemistry, 295: 72–81.
[8] Yuan, X.Z., Wu, Z.M., Li, H.D, Wang, Y., Liu, F., Cai, H., Newlove, A.A. and Wang, Y. 2014. Biochemical and proteomic analysis of ‘Kyoho’ grape (Vitis labruscana) berries during cold storage. Postharvest Biology and Technology, 88:79–87.
[9] Chen, S.J., Wang, H.O., Wang, R.R., Fu, Q.Q. and Zhang, W. 2018. Effect of gaseous chlorine dioxide (ClO2) with different concentrations and numbers of treatments on controlling berry decay and rachis browning of table grape. Journal of Food Processing and Preservation, 42 (7): e13662.
[10] Rosales, R., Fernandez-Caballero, C., Romero, I., Escribano, M.I., Merodio, C. and Sanchez-Ballesta M.T. 2013. Molecular analysis of the improvement in rachis quality by high CO2 levels in table grapes stored at low temperature. Postharvest Biology and Technology, 77: 50–58.
[11] Farzaneh, V., Ghodsvali, A., Bakhshabadi, H., Ganje, M., Dolatabadi, Z. and S.Carvalho, I. 2017. Modelling of the Selected Physical Properties of the Fava Bean with Various Moisture Contents Using Fuzzy Logic Design. Journal of Food Process Engineering, 40: e12366. https://doi.org/10.1111/jfpe.12366.
[12] Nassiri, A.M., Tahavoor, A. and Jafari, A. 2022. Fuzzy logic classification of mature tomatoes based on physical properties fusion. Information Processing in Agriculture, 9(4): 547-555.
[13] Zandi, M., Ganjloo, A., Bimakr, M., Nikoomanesh, N., Moradi, N. 2021. Application of fuzzy logic and neural-fuzzy inference system (ANFIS) for prediction of physicochemical changes and quality classification of coated sweet lemon during storage'. Iranian Food Science and Technology Research Journal, 17(2): 339-351. (In Persian).
[14] Magalhães, B., Gaspar, P.D., Corceiro, A., João, L. and Bumba, C. 2022. Fuzzy Logic Decision Support System to Predict Peaches Marketable Period at Highest Quality. Climate, 10(3): 29. https://doi.org/10.3390/cli10030029
[15] Sajadian, H., Shamili, M., Hokmabadi, H., Tajabadipour, A. and Hasheminasab, H. 2019. Physiological Responses of Some Rootstocks and Interspecific Hybrids of Pistachio to Cold Stress under Greenhouse Conditions'. Journal of Nuts, 10(2): 139-151.
[16] Vargas, M., Albors, A., Chiralt, A. and Gonzalez-Martinez, C. 2006. Quality of cold-stored strawberries as affected by chitosan–oleic acid edible coatings. Postharvest Biology and Technology, 41: 164–171.
[17] Hashemi Shahraki, M., Mashkour, M., & Garmakhany, A. D. 2014. Development and application of a computer vision system for the measurement of the colour of Iranian sweet bread. Quality Assurance and Safety of Crops and Foods, 6(1): 33-40.
[18] Valverde, J.M., Valero,D.,Martianez-romero,D., Guillean, F., Castillo, S. and Serrano, M. 2005. Novel Edible Coating Based onAloe vera Gel To MaintainTable Grape Quality and Safety. Agricultural and Food Chemistry, 53: 7807-7813
[19] Granato, D., Katayama, U. and de Castro, A. 2011. Phenolic composition of South American red wines classified according to their antioxidant activity, retail price and sensory quality. Food Chemistry, 129: 366–373.
[20] Khalil, U., Rajwana, I.A., Razzaq, K., Farooq, U., Saleem, B.A. and Brecht, J.K. 2023. Quality attributes and biochemical changes in white and colored table grapes as influenced by harvest maturity and ambient postharvest storage. South African Journal of Botany, 154: 273-281.
[21] Ghodsvali, A., Mohamadi, M., Mohamdi Chianeh, S. and Rashidzadeh, S. 2016. An investigation on the effect of harvest time and storage on the quality properties of red grape, the variety of fakhri shahrood. Journal of crop production and processing, 5(18): 1-13. (In Persian).
[22] Hosseinpoor, F., Rabiei, V., Amiri, M., Soleimani, A. 2017. Influence of hot water treatment and nano-packaging on qualitative characterestics of nectarine fruit cv. ‘Sunglo’ during storage. Journal of Crops Improvement, 18(4): 1001-1015.
[23] Garcia, S., Santesteban, L.G., Miranda, C. and Royo, J.B. 2011. Variety and storage time affect the compositional changes that occur in grape samples after frozen storage. Australian Journal of Grape and Wine Research, 17: 162-168.
[24] Ngo, T., Nguyen, T. H., Dang, T., Do, T., Reungsang, A., Chaiwong, N. and Rachtanapun, P. 2021. Effect of Pectin/Nanochitosan-Based Coatings and Storage Temperature on Shelf-Life Extension of "Elephant" Mango (Mangifera indica L.) Fruit. Polymers, 13(19): 3430.
[25] Shewfelt, R.L. and Purvis, A.C. 1995. Toward a comprehensive model for lipid peroxidation in plant tissue disorders. Hort Science, 30: 213-218.
[26] Suwapanich, R. and Haewsungcharoen, M. 2007. Effect of temperature and storage time on the thermal properties of Mango Nam Dok Mai cv. Si Thong during storage. Journal of Agricultural Technology, 1-6.
[27] Esmaeili, N., Naghshband, R. and Zare Nahandi, F. 2019. Evaluation of the effect of harvest time and fruit cold storage period on some of qualitative characteristics of Cornelian cherry fruit'. Journal of Food Research, 29(3): 69-84.
[28] Deng, Y., Wu, Y., and Li, Y. 2006. PHysiological responses and quality attributes of Kyoho grapes to controlled atmosphere storage. LWT - Food Science & Technology, 39: 584–590
[29] Maftoonazad, N. and Ramaswamy, H. 2005. Postharvest shelf-life extension of avocado using methyl cellulose-based coating. LWT - Food Science & Technology, 38: 617-624.
[30] Lee, J. 2017. Light exclusion influence on grape anthocyanin. Heliyon, 3. e00243. https://doi.org/10.1016/j.heliyon.2017.e00243.
[31] Sadeghipour, M., Badii, H., Behmadi, H. and Bazyar, B. 2012. The effect of methyl cellulose based active edible coatings on the storage life of tomato. Food Science and Technology, 9 (35): 89-99. (In Persian).
[32] Ziaolhagh, S. 2021. Effects of some salts on the shelf life of Shahrood Sorkh-e-Fakhri table grapes stored in cold storage'. Iranian Food Science and Technology Research Journal, 16(6): 101-110.
[33] Eshghi, S., Karimi, R., Shiri, A., Karami, M. and Moradi, M. 2022. Effects of polysaccharide-based coatings on postharvest storage life of grape: measuring the changes in nutritional, antioxidant and phenolic compounds. Food Measurement and Characterization, 16: 1159–1170.
[34] Agha Babaei, L., Mortazavi, S., AJovanmard Dakhali, M., Elhami Rad, A.H. and Meshkani, S.M. 2014. Optimizing the formulation of methyl cellulose edible coating and Shirazi thyme extract on the quality and shelf life of grapes. Innovation in Food Science and Technology (Food Science and Technology), 7(2): 15-24. (In Persian).
[35] Picouet, P.A., Hurtado, A., Jofré, A., Bañon, S., Ros, J. and Guàrdia, M.D. 2016. Effects of Thermal and High-Pressure Treatments on the Microbiological, Nutritional and Sensory Quality of a Multi-Fruit Smoothie. Food and Bioprocess Technology, 9: 1219–1232.