Abstract
Fruit seeds are by-products of fruit processing industries which are rich in bioactive compounds including phenolic compounds. In this study, the efficiency of the microwave-assisted aqueous extraction (MAAE) technique on the recovery of total phenolic content (TPC) from jackfruit, jamun and papaya seeds was explored. The process with three independent parameters (microwave power, treatment time and seed powder to solvent ratio) was developed and optimized individually for all three seeds using both response surface methodology (RSM) and artificial neural network- genetic algorithm (ANN- GA) to maximize the response (TPC). The value of TPC at the RSM optimized condition was 8.79 mg GAE/100 g, 211.87 mg GAE/100 g and 31.38 mg GAE/100 g and at the ANN optimized condition were 30.09 mg GAE/100 g, 252.01 mg GAE/100 g and 37.55 mg GAE/100 g for jackfruit, jamun and papaya seed, respectively, which were significantly higher than that of the control extract. Moreover, the ANN model for all three seeds displayed better performance with higher extraction yield and fewer statistical errors as compared to RSM. Hence, the study concludes that MAAE could be an excellent alternative to extract phenolic compounds from fruit seeds with maximum yield.
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Abbreviations
- MAAE:
-
Microwave-assisted aqueous extraction
- RSM:
-
Response surface methodology
- ANN-GA:
-
Artificial neural network- genetic algorithm
- TPC:
-
Total phenolic content
- GAE:
-
Gallic acid equivalent
- BBD:
-
Box-Behnken design
- FC:
-
Folin-Ciocalteu
- ANOVA:
-
Analysis of variance
- Y:
-
Predicted value of the response
- b:
-
Regression coefficients
- X:
-
Independent variables
- AAD:
-
Average absolute deviation
- MSE:
-
Mean square error
- RMSE:
-
Root mean square error
- NMSE:
-
Normalized mean square error
- NRMSE:
-
Normalized root mean square error
- MPE:
-
Mean percentage error
- R2 :
-
Coefficient of determination
- SD:
-
Standard deviation
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Manoj, A.A., Fathima, A., Naushad, B. et al. Valorization of fruit seeds by polyphenol recovery using microwave-assisted aqueous extraction: modelling and optimization of process parameters. Food Measure 17, 4280–4293 (2023). https://doi.org/10.1007/s11694-023-01955-z
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DOI: https://doi.org/10.1007/s11694-023-01955-z