کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4517829 1624981 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Prediction of relationship between surface area, temperature, storage time and ascorbic acid retention of fresh-cut pineapple using adaptive neuro-fuzzy inference system (ANFIS)
ترجمه فارسی عنوان
پیش بینی رابطه بین منطقه سطح، دما، مدت زمان نگهداری و حفظ اسید آسکوربیک از آناناس تازه با استفاده از سیستم استنتاج فازی تطبیقی (ANFIS)
کلمات کلیدی
آناناس comosus L؛ اسید اسکوربیک؛ ANFIS؛ تازه برش؛ منطقه سطح؛ آناناس
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم زراعت و اصلاح نباتات
چکیده انگلیسی


• Ascorbic acid (AA) retention during storage of fresh-cut pineapple was studied.
• Adaptive neuro-fuzzy significantly inference system (ANFIS) model was applied in this study.
• Surface area and temperature influence AA degradation during storage of fresh-cut pineapple.
• ANFIS model with triangular-shaped membership function (trimf) provides best prediction.

Adaptive neuro-fuzzy inference system (ANFIS) was developed for the prediction of ascorbic acid (AA) retention during storage of fresh-cut pineapple as a function of surface area, storage temperature and time. Our results demonstrate that surface area and temperature are the two most important factors influencing the degradation of AA in fresh-cut pineapple during storage. The AA in fresh-cut pineapple with a high surface area is more easily destroyed than that with a low surface area at the same storage temperature. In addition, the ANFIS model with triangular-shaped membership function (trimf) (RMSE = 7.88%; R2 = 0.95) provides the best prediction accuracy than models with other membership functions (RMSE = 8.97–10.19%; R2 = 0.91–0.93). Therefore, the high-surface-area fresh-cut fruit should be stored at a relatively low temperature as compared with the low-surface-area produce. The ANFIS model with trimf is an adequate model for the prediction of AA retention during storage of fresh-cut pineapple.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Postharvest Biology and Technology - Volume 113, March 2016, Pages 1–7
نویسندگان
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