پیش‌بینی فرآیند انتقال جرم در خشک کردن اسمزی انجیر سیاه در سیستم سه گانه: مقایسه روش سطح پاسخ و شبکه عصبی مصنوعی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 عضو هیات علمی مرکز تحقیقات و آموزش کشاورزی فارس، سازمان تحقیقات، آموزش و ترویج کشاورزی

2 بخش فنی و مهندسی کشاورزی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان فارس، سازمان تحقیقات، آموزش و ترویج کشاورزی، شیراز، ایران.

3 بخش تحقیقات فنی و مهندسی کشاورزی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی فارس، سازمان تحقیقات، آموزش و ترویج کشاورزی

چکیده

خشک کردن اسمزی میوه‌های انجیر در محلول سه‌تایی آب، ساکارز و کلرید سدیم در غلظت‌های مختلف محلول، دما و مدت زمان‌های مختلف فرآیند مورد بررسی قرار گرفت. یک رویکرد مقایسه ای بین شبکه عصبی مصنوعی (ANN) و روش سطح پاسخ (RSM) برای پیش‌بینی پارامترهای انتقال جرم انجام شد. نتایج نشان داد که تمامی متغیرهای مستقل به طور مثبت وزن را کاهش دادند به این معنی که افزایش هر یک از عوامل منجر به افزایش کاهش وزن شد و این رابطه خطی بود. انجیرهای خشک شده به روش اسمزی کیفیت بهتری نسبت به نمونه های بدون اسمز داشتند. هر چهار متغیر مستقل 94 درصد کاهش وزن، 90 درصد کاهش رطوبت و 89 درصد افزایش جامد را شرح دادند. شرایط بهینه فرآوری دمای 60 درجه سانتی گراد، غلظت ساکارز 70 درصد، غلظت کلرید سدیم 5 درصد و زمان غوطه وری 5 ساعت بود. نتایج نشان داد که مدل ANN که به درستی آموزش داده شده است در مقایسه با مدل RSM پیش‌بینی دقیق‌تری را انجام می دهد.

چکیده تصویری

پیش‌بینی فرآیند انتقال جرم در خشک کردن اسمزی انجیر سیاه در سیستم سه گانه: مقایسه روش سطح پاسخ و شبکه عصبی مصنوعی

تازه های تحقیق

  • استفاده از یک محلول اسمزی سه جرئی انتقال جرم در مقایسه با یک محلول دو جزئی انتقال جرم را افزایش می‌دهد؛ بنابراین این روش برای کاربرد در صنعت پیشنهاد می‌شود.
  • شرایط بهینه برای خشک‌کردن اسمزی انجیر دمای 60 درجه سلسیوس، غلظت 70 درصد سوکروز، غلظت 5 درصد نمک و زمان غوطه‌وری 5 ساعت می‌باشد.
  • مدل شبکه عصبی مصنوعی در پیش‌بینی تغییرات ML، WR و SG نسبت به روش سطح پاسخ عملکرد بهتری دارد.
  • یک مدل آموزش دیده در پیش‌بینی پارامترهای فرآیند دقیق‌تر عمل می‌کند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Prediction of Mass Transfer during Osmotic Dehydration of Black Fig Fruits (Ficus carica) in Ternary Systems: Comparison of Response Surface Methodology and Artificial Neural Network

نویسندگان [English]

  • Neda Maftoonazad 1
  • Akbar Jokar 2
  • Mashalla Zare 3
1 Agricultural Engineering Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Fars Province, Iran
2 Agricultural Engineering Research Department, Fars Agricultural and Natural Resources Research and Education Center, AREEO, Fars, Shiraz, Iran.
3 AREEO
چکیده [English]

Osmotic dehydration of fig fruits (cv. Sabz) in ternary solution of water, sucrose and sodium chloride at different solution concentrations, temperature and process durations were analyzed. A comparative approach was made between artificial neural network (ANN) and response surface methodology (RSM) to predict the mass transfer parameters. Results showed that all independent variables positively decreased the weight meaning that increasing each factor resulted in increasing weight loss and this relationship was linear. Osmo-dehydrated figs had better quality compared to samples without osmosis. All four independent variables explained 94% of the weight loss, 90% moisture content reduction and 89% of the solid gain. The determined optimum processing conditions were temperature of 60°C, sucrose concentration of 70%, sodium chloride concentration of 5% and immersion time of 5h. The results showed that properly trained ANN model is found to be more accurate in prediction as compared to RSM model.

کلیدواژه‌ها [English]

  • Fig (Ficus carica)"
  • Osmotic dehydration"
  • Artificial neural networks"
  • Response surface methodology"
  • Moisture loss"
  • "
  • Solute gain"

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فناوری‌های جدید در صنعت غذا
دوره 11، شماره 1
آبان 1402
صفحه 61-75

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سابقه مقاله

  • تاریخ دریافت: 12 اسفند 1401
  • تاریخ بازنگری: 08 اردیبهشت 1402
  • تاریخ پذیرش: 15 خرداد 1402

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