مدل‌سازی ریزپوشانی اسانس آویشن باغی (Thymus vulgaris) در پوشش کازئینات سدیم، مالتودکسترین و نشاسته اصلاح شده با استفاده از دو روش سطح پاسخ و شبکه عصبی مصنوعی

نویسندگان
فائزه شاهکل 1
هاجر عباسی 2
محسن نوروزی مبارکه 3
1 گروه علوم و صنایع غذایی، دانشکده کشاورزی، واحد اصفهان (خوراسگان)، دانشگاه آزاد اسلامی، اصفهان، ایران
2 دانشیار گروه علوم و صنایع غذایی، دانشکده کشاورزی، واحد اصفهان (خوراسگان)، دانشگاه آزاد اسلامی، اصفهان، ایران
3 گروه محیط زیست، دانشکده کشاورزی، واحد اصفهان (خوراسگان)، دانشگاه آزاد اسلامی، اصفهان، ایران
10.22034/FSCT.19.125.225
چکیده
ریزپوشانی با هدف حفاظت ترکیبات فرار و حساس به واکنش‌های شیمیایی صورت می‌گیرد. مدلسازی فرایند می‌تواند در ارزیابی و پیش‌بینی تاثیر شرایط موثر بر ویژگی‌های کیفی محصول مناسب کارآمد باشد.

برای بررسی تأثیر غلظت مواد دیواره، نسبت پروتئین به پلی­ساکارید و مدت زمان اعمال امواج فراصوت بر راندمان ریزپوشانی، فنولیک کل، ظرفیت آنتی اکسیدانی و ترکیبات فرار ریزکپسول‌ها، نانوامولسیون اسانس آویشن باغی در فاز آبی حاوی ترکیب پروتئین (کازئینات سدیم) و پلی­ساکارید (مالتودکسترین و نشاسته اصلاح شده) با کمک امواج فراصوت فراهم شد. مدل­سازی متغیرهای وابسته به روش سطح پاسخ و شبکه عصبی مصنوعی صورت گرفت.

نتایج نشان داد افزایش غلظت مواد دیواره و نسبت پروتئین به پلی­ساکارید باعث بهبود حفظ ترکیبات فرار و ظرفیت آنتی اکسیدانی اسانس ریزپوشانی شده گردید. با افزایش نسبت پروتئین به پلی­ساکارید و مدت زمان امواج فراصوت، راندمان ریزپوشانی افزایش یافت. نتایج مدل­های حاصل از اثر متقابل سطح پاسخ و شبکه عصبی بیانگر حفظ و ابقای ترکیبات فنولیک کل، ظرفیت آنتی اکسیدانی و افزایش راندمان ریزپوشانی در مقادیر بالاتر متغیرها بود. ریز کپسول تولیدی شامل 20% مواد دیواره، 31% نسبت پروتئین به پلی­ساکارید و 97 sزمان امواج فراصوت از نقطه نظر راندمان ریزپوشانی و ترکیبات فرار به عنوان بهترین تیمار معرفی شد. نتایج تجربی حاصل از آزمایشات با شرایط بهینه نشان دهنده عملکرد مناسب و هم‌سوی هر دو روش سطح پاسخ و شبکه عصبی و برتری شبکه‌ عصبی مصنوعی در پیش‌بینی متغیرهای موردنظر است.
کلیدواژه‌ها
سانس آویشن باغی
خشک کردن انجمادی
راندمان ریزپوشانی
ظرفیت آنتی اکسیدانی
کروماتوگرافی گازی

موضوعات

عنوان مقاله English

Modeling the Encapsulation of Thymus Essential Oil (Thymus vulgaris) in Sodium Caseinate, Maltodextrin and Modified Starch Using Response Surface (RSM) and Artificial Neural Network (ANN)

نویسندگان English

Faezeh Shahkol 1
Hajar Abbasi 2
Mohsen Norouzi Mobarakeh 3
1 Department of Food Science and Technology, College Agriculture, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
2 Department of Food Science and Technology, College Agriculture, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
3 Department of environment, College Agriculture, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran
چکیده English

Microencapsulation process is down in protecting volatile and sensitive compounds to chemical reactions. Process modeling can be effective in assessing and predicting the impact of conditions affecting the qualitative properties of the product.

In order to investigated the effect of wall material concentration, protein/polysaccharide ratio and ultrasound waves time on the microencapsulation efficiency, total phenolics, antioxidant capacity and volatile compounds, nano-emulsion of Thymus vulgaris essential oil in aqueous phase containing protein (sodium caseinate) and polysaccharide (maltodextrin and modified starch) was prepared by ultrasound waves. Modeling of dependent variables was done by response surface methodology and artificial neural network. The results showed that increasing the wall concentration and protein/polysaccharide ratio improved the retention of volatile compounds and antioxidant capacity of the encapsulated essential oil, and at higher values of variables the same trend was observed for the phenolic content. Increasing the protein/polysaccharide ratio and ultrasound waves resulted in increased the microencapsulation efficiency. Models obtained from the interaction effects of neural network and Response Surface Method at higher values resulted in better preservation of total phenolic, antioxidant activity and increased of Microencapsulation efficiency of microcapsules. Microencapsulation produced containing of 20% wall material, 31% protein/polysaccharide ratio and 97s ultrasound time were the best treatment in terms of the microencapsulation efficiency and volatile compounds.Experimental results of the experiments indicative appropriate and uniform function of both response surface and neural network methods and the superiority of the artificial neural network in predicting the desired variables.

کلیدواژه‌ها English

Thymus vulgaris essential oil
Freeze drying
Microencapsulation efficiency
Antioxidant capacity
Gas chromatography
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