OPTIMIZATION OF IRRADIATED KIWI FRUIT PROPERTIES USING RESPONSE SURFACE METHODOLOGY AND PREDICTION WITH NEURAL NETWORK AND REGRESSION METHOD

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KIANI H.; RAHMATI M.H.; MOHAMMAD RAZDARI A.

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Journal: Journal of Food Technology and Nutrition Year:2019 | Volume:16 | Issue:1 (61) Page(s): 121-129

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Title

OPTIMIZATION OF IRRADIATED KIWI FRUIT PROPERTIES USING RESPONSE SURFACE METHODOLOGY AND PREDICTION WITH NEURAL NETWORK AND REGRESSION METHOD

Author(s)

KIANI H. | RAHMATI M.H. | MOHAMMAD RAZDARI A. | Issue Writer Certificate

Keywords

GAMMA RAYQ1

KIWIFRUITQ2

NEURAL NETWORKQ1

RESPONSE SURFACEQ1

REGRESSIONQ2

Abstract

Introduction: Application of ionizing radiation as a new method in the preservation of agricultural products has been introduced since 35 years ago. Gamma irradiation has been introduced as a new technique to preserve the foods.Materials and Methods: KIWIFRUIT cultivar (Hayward) has been used and the samples with 0 (Control), 0.5, 1 and 2 kGy cobalt-60 were gamma irradiated then refrigerated at 3±1°C for a duration of 0, 30.60 and 90 days. In this study RESPONSE SURFACE Methodology and input parameters consisted of irradiation dose and storage time for optimal conditions for storage of irradiated kiwis were determined. Finally, using REGRESSION and NEURAL NETWORK methods output prediction and RESPONSE SURFACE method were compared.Results: The optimal conditions for storage of irradiated kiwis were determined. The optimum point for shelf-life, radiation dose, weight, color parameters L*, a* and b*, ascorbic acid content and pH value, were proposed respectively, (two months, 1 kGy, 48.13 and 45.86, 11.03 and 12.79, 29.916, 3.2545). By increasing storage time and radiation dose, the weight of stored samples reduced. By increasing irradiation dose and duration of storage a* parameter decreased. By increasing irradiation dose also the b* parameter reduced but by increased storage time, L* increased. Similarly, by increasing storage time and radiation dose, pH value increased and ascorbic acid content reduced.Conclusion: The NEURAL NETWORK and REGRESSION analysis have been employed to predict the changes in color, weight, pH value and ascorbic acid content.

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APA: Copy

KIANI, H., RAHMATI, M.H., & MOHAMMAD RAZDARI, A.. (2019). OPTIMIZATION OF IRRADIATED KIWI FRUIT PROPERTIES USING RESPONSE SURFACE METHODOLOGY AND PREDICTION WITH NEURAL NETWORK AND REGRESSION METHOD. JOURNAL OF FOOD TECHNOLOGY AND NUTRITION, 16(1 (61) ), 121-129. SID. https://sid.ir/paper/143443/en

Vancouver: Copy

KIANI H., RAHMATI M.H., MOHAMMAD RAZDARI A.. OPTIMIZATION OF IRRADIATED KIWI FRUIT PROPERTIES USING RESPONSE SURFACE METHODOLOGY AND PREDICTION WITH NEURAL NETWORK AND REGRESSION METHOD. JOURNAL OF FOOD TECHNOLOGY AND NUTRITION[Internet]. 2019;16(1 (61) ):121-129. Available from: https://sid.ir/paper/143443/en

IEEE: Copy

H. KIANI, M.H. RAHMATI, and A. MOHAMMAD RAZDARI, “OPTIMIZATION OF IRRADIATED KIWI FRUIT PROPERTIES USING RESPONSE SURFACE METHODOLOGY AND PREDICTION WITH NEURAL NETWORK AND REGRESSION METHOD,” JOURNAL OF FOOD TECHNOLOGY AND NUTRITION, vol. 16, no. 1 (61) , pp. 121–129, 2019, [Online]. Available: https://sid.ir/paper/143443/en

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