با همکاری انجمن علوم و صنایع غذایی ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

دانشگاه صنعتی اصفهان

چکیده

موز میوه‌ای سرشار از مواد مغذی است که به‌علت داشتن محتوای رطوبتی بالا استفاده از روش‌های نگهداری مناسب به‌منظور افزایش زمان ماندگاری آن ضروری است. آبگیری اسمزی یک فرآیند غیرحرارتی برای کاهش رطوبت و بهبود ویژگی‌های خوراکی محسوب می‌شود. بااین‎وجود، این فرآیند کند بوده و همچنین بافت میوه طی فرآیند دچار تغییرات نامطلوبی می‌گردد. در این پژوهش از لاکتات کلسیم (در غلظت‎های 0%، 2%، 3% و 4%) و اسید سیتریک (در غلظت‌های 0%، 5/0%، 1% و 5/1%) برای بهبود استحکام بافت میوه و افزایش سرعت فرآیند طی آبگیری با محلول اسمزی ساکارز استفاده گردید و الگوریتم ژنتیک به‌منظور بهینه‌سازی شرایط فرآیند به‌کار گرفته شد. نتایج نشان داد استفاده از لاکتات کلسیم و اسید سیتریک سبب کاهش میزان جذب مواد جامد و تغییرات رنگ، افزایش افت رطوبت و همچنین بهبود مقاومت مکانیکی بافت میوه می‌گردد. شرایط بهینه فرآیند نیز برای حصول بیشترین مقدار افت رطوبت و مقاومت مکانیکی و کمترین مقدار جذب مواد جامد و تغییرات رنگ درنظر گرفته شد (غلظت‌های پیش‌بینی‎شده به‌ترتیب 99/3% و 86/0% برای لاکتات کلسیم و اسید سیتریک بود). شرایط بهینه با استفاده از داده‌های آزمایشگاهی اعتبارسنجی گردید. مقادیر شاخص‌های آماری MSE ،NMSE و AME (به‌ترتیب برابر با 062/2، 021/0 و 099/1) بیانگر توانایی بالای الگوریتم ژنتیک برای بهینه‌سازی فرآیند آبگیری اسمزی بود.

کلیدواژه‌ها

عنوان مقاله [English]

Study of osmotic dehydration of banana using calcium lactate and genetic algorithm optimization of process

نویسندگان [English]

  • Zeynab FarhaniNejad
  • Milad Fathi
  • Mohammad Shahedi

Isfahan University of Technology

چکیده [English]

Introduction: Banana is one of the most popular tropical fruits in all over the world with notable post-harvest losses. Due to its high moisture content preventing long preservation period. So, it needs a proper preservation method to prevent product lost especially in main produceing countries. Since banana is an un-freezable fruit, thermal processing such as drying or canning could be more appropriate for prolonging its shelf life. On the other hand, high energy consumption and being cost intensive are two most important disadvantages of thermal processing. In order to decrease the side effects of thermal process on quality parameters, pretreatment of samples could be applied to reduce time of main process.Osmotic dehydration is a non-thermal pretreatment which provides partial removal of water by immersing sample in an osmotic solution.But this process also takes a long immersion time to enough reduction of moisture. So this leads to undesirable effect on texture and colors.This study was performed to eliminate some side effects of osmotic dehydration on quality and finally introduce an optimized condition resulting best performance of process.A novel all-knowing method for optimization of process is genetic algorithm (GA) which is a search heuristic that mimics process of natural selection. It generates solutions for the optimization of problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. In this research, genetic algorithm was applied to predict optimum condition of osmotic dehydration.

Material and methods: Osmotic dehydration was performed using aqueous solution of sucrose in concentration of 45% (w/w) for immersion time of 3 hr. The first challenge was improving mechanical properties of banana slices by adding calcium lactate to sucrose solution in concentrationsof 0, 2, 3 and 4%.For the next step in order to protect samples from enzymatic browning mixture of ascorbic acid (0.25 %) and citric acid (0, 0.5, 1, and 1.5%) were used.The pH of solution was measured for each level of adding citric acids. The efficiency of operation was estimated by computingwater loss and solid gain. Firmness of dehydrated samples wasmeasured using a texture analyzer (INSTRON, 1140, Singapore) and penetration test. Image acquisition technique was applied to measure L*, a* and b* indices.The coefficient of efficiency was defined as the ratio of water loss to solid gain and calculated to estimate performance of treatment in new condition. Finally, optimized conditionsfor maintaining the lowest solid gain and color changes, the highest water loss and firmness waterlosswere predicted by genetic algorithms method. The accuracy of model was investigated using statistical parameters such as mean absolute error (AME), normalized mean square error (NMSE),mean square error (MSE).

Results and discussion: The results of experiments showed a significant increase of firmness by adding lactate calcium. This observation was due to complex formation between calcium and cell wall ingredients. Thesecomplexes have a decreasing effect on solid gain.Because complexes preventedmacromoleculesentering such as sucrose to the cells.On the other hand,calcium lactate and citric acid had interaction on mentioned parameters.Firmness showed less firmness when citric acid was added to the solution. Because citric acid as a chelating agents can blockdivalent cations and prevent from effective reaction with plant cells.Also citric acid can disconnect methoxyl groups from protopectinproducing softer texture.However, treated samples still showed firmer texture than control sample. It could be due to the additional effect of citric acid which makes carboxyl groups available for divalent calcium cations during conversion of protopectin to the pectin.For color parameters,only use of citric acid could not decrease the total change of color because yellow index increased due to the hydration of citric acids. But for the use of two factors, a significant decrease of total change of color was observed.For water loss, increase of solvents in each treatment led to raise of water loss due to the increase of osmotic pressure.In this circumstance determination of suitable concentration for each factorresulting best performance is complex, so it is necessary to apply a system canpredict optimized conditions. Genetic algorithms estimated optimum condition formaximum firmness and water loss, minimum solid gain and total change of color.In this condition the concentrations of lactate calcium and citric acid were %3.99 and %0.86, respectively. Also predicted values for water loss, solid gain, firmness and total change of color were earned %18.01, %5.07, 1.47 N and 11.37.MAE, NMSE and AME parameters (2.062, 0.021, and 1.099 respectively) were used for investigation of difference between estimated and experimental data which showed high efficiency of genetic algorithm for optimization of osmotic dehydration of banana.Investigating the efficiency ofcoefficient of treatments showed that application of both factors (calcium lactate and citric acid) significantly had more efficiency in comparison to the control samples regarding quality factors.

کلیدواژه‌ها [English]

  • Calcium lactate
  • Genetic algorithm
  • Osmotic Dehydration
حسینی، م.، مصطفوی، م.، هادوی، ا.، رضائی، م.، 1391، بررسی اثر اسید آسکوربیک، اسید سیتریک و متابی سولفیت سدیم بر ویژگی های فیزیکوشیمیایی و اورگانولپتیکی برگه زرآلو (Prunus armeniaca) رقم جهانگیری، نشریه علوم باغبانی، 26، 67-63.
فاطمی، ح.، 1386، شیمی مواد غذایی،1386، شرکت سهامی انتشار، تهران، 250-248.
AOAC (1997). Official methods of analysis. Washington: Association of Official Analytical Chemists.
 
Ali, H. S., H. A. Moharram, M. T. Ramadan and G. H. Ragab (2010). "Osmotic Dehydration of Banana Rings and Tomato Halves." Journal of American Science 6(9).
 
Anino, S. V., D. M. Salvatori and S. M. Alzamora (2006). "Changes in calcium level and mechanical properties of apple tissue due to impregnation with calcium salts." Food Research International 39(2): 154-164.
 
Archer, M. C. and J. K. Palmer (1975). "An experiment in enzyme characterization: Banana polyphenoloxidase." Biochemical Education 3(3): 50-52.
 
Barrera, C., N. Betoret and P. Fito (2004). "Ca2+ and Fe2+ influence on the osmotic dehydration kinetics of apple slices (var. Granny Smith)." Journal of Food Engineering 65(1): 9-14.
 
Bico, S. L. S., M. F. J. Raposo, R. Morais and A. Morais (2009). "Combined effects of chemical dip and/or carrageenan coating and/or controlled atmosphere on quality of fresh-cut banana." Food Control 20(5): 508-514.
 
Chauhan, O. P., P. S. Raju, D. K. Dasgupta and A. S. Bawa (2006). "Instrumental textural changes in banana (var. Pachbale) during ripening under active and passive modified atmosphere." International Journal of Food Properties 9(2): 237-253.
 
Chiralt, A. and P. Talens (2005). "Physical and chemical changes induced by osmotic dehydration in plant tissues." Journal of Food Engineering 67(1): 167-177.
 
Fathi, M., M. Mohebbi and S. M. A. Razavi (2011). "Application of fractal theory for prediction of shrinkage of dried kiwifruit using artificial neural network and genetic algorithm." Drying Technology 29(8): 918-925.
 
Fathi, M., M. Mohebbi and S. M. A. Razavi (2011). "Application of image analysis and artificial neural network to predict mass transfer kinetics and color changes of osmotically dehydrated kiwifruit." Food and Bioprocess Technology 4(8): 1357-1366.
 
Fernandes, F. A., S. Rodrigues, O. C. Gaspareto and E. L. Oliveira (2006). "Optimization of osmotic dehydration of bananas followed by air-drying." Journal of Food Engineering 77(1): 188-193.
 
Fernandes, F. A. N. and S. Rodrigues (2008). "Application of ultrasound and ultrasound-assisted osmotic dehydration in drying of fruits." Drying Technology 26(12): 1509-1516.
 
Fernandes, F. A. N. and S. Rodrigues (2011). Ultrasound application as pre-treatment for drying of fruits. Proceedings of the International Congress on Engineering and Food.
 
Garcia-Noguera, J., F. I. P. Oliveira, C. L. Weller, S. Rodrigues and F. A. N. Fernandes (2012). "Effect of ultrasonic and osmotic dehydration pre-treatments on the colour of freeze dried strawberries." Journal of Food Science and Technology: 1-6.
 
Hailu, M., T. S. Workneh and D. Belew (2013). "Review on postharvest technology of banana fruit." African Journal of Biotechnology 12(7): 635-647.
 
Jaworska, G. y., W. Kmiecik and J. Slupski (2004). "Effect of technological measures on the quality of canned banana desserts." Food Science and Technology 7(1).
 
Mohebbi, M., F. Shahidi, M. Fathi, A. Ehtiati and M. Noshad (2011). "Prediction of moisture content in pre-osmosed and ultrasounded dried banana using genetic algorithm and neural network." Food and Bioproducts Processing 89(4): 362-366.
 
FAO – Food and Agriculture Organization of the United Nations, 2011. http://www.fao.org (accessed June, 2011).
 
Silva, K. S., M. A. Fernandes and M. A. Mauro (2014a). "Osmotic Dehydration of Pineapple with Impregnation of Sucrose, Calcium, and Ascorbic Acid." Food and Bioprocess Technology 7(2): 385-397.
 
Silva, K. S., M. A. Fernandes and M. A. Mauro (2014b). "Effect of calcium on the osmotic dehydration kinetics and quality of pineapple." Journal of Food Engineering 134: 37-44.
 
Torres, J. D., P. Talens, I. Escriche and A. Chiralt (2006). "Influence of process conditions on mechanical properties of osmotically dehydrated mango." Journal of Food Engineering 74(2): 240-246.
 
Vega-Galvez, A., R. Lemus-Mondaca, C. Bilbao-Sainz, P. Fito and A. Andres (2008). "Effect of air drying temperature on the quality of rehydrated dried red bell pepper (var. Lamuyo)." Journal of Food Engineering 85(1): 42-50.
 
Verma, D., N. Kaushik and P. S. Rao (2013). "Application of High Hydrostatic Pressure as a Pretreatment for Osmotic Dehydration of Banana Slices (Musa cavendishii) Finish-Dried by Dehumidified Air Drying." Food and Bioprocess Technology: 1-17.
 
Wang, R., M. Zhang and A. S. Mujumdar (2010). "Effects of vacuum and microwave freeze drying on microstructure and quality of potato slices." Journal of Food Engineering 101(2): 131-139.
 
Zhao, D., C. Zhao, H. Tao, K. An, S. Ding and Z. Wang (2013). "The effect of osmosis pretreatment on hot-air drying and microwave drying characteristics of chili (Capsicum annuum L.) flesh." International Journal of Food Science & Technology 48(8): 1589-1595.
CAPTCHA Image