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001-es BibID:	BIBFORM111151
035-os BibID:	(cikkazonosító)106425 (Scopus)85154062808 (WoS)000998638700001
Első szerző:	Dash, Kshirod Kumar
Cím:	Modelling of ultrasonic assisted osmotic dehydration of cape gooseberry using adaptive neuro-fuzzy inference system (ANFIS) / Kshirod Kumar Dash, Anjelina Sundarsingh, GVS BhagyaRaj, Vinay Kumar Pandey, Béla Kovács, Shaikh Ayaz Mukarram
Dátum:	2023
ISSN:	1350-4177
Megjegyzések:	In the present investigation, the cape gooseberry (Physalis peruviana L.) was preserved by the application of osmotic dehydration (sugar solution) with ultrasonication. The experiments were planned based on central composite circumscribed design with four independent variables and four dependent variables, which yielded 30 experimental runs. The four independent variables used were ultrasonication power ( ) with a range of 100-500 W, immersion time ( ) in the range ofXP XT 30-55 min, solvent concentration ( ) of 45-65 % and solid to solvent ratio ( ) with range 1:6 -XC XS 1:14 w/w. The effect of these process parameters on the responses weight loss ( ), solid gain (YW ), change in color ( ) and water activity ( ) of ultrasound assisted osmotic dehydration (UOD)YS YC YA cape gooseberry was studied by using response surface methodology (RSM) and adaptive neuro- fuzzy inference system (ANFIS). The second order polynomial equation successfully modeled the data with an average coefficient of determination ( ) was found to be 0.964 for RSM. While forR2 the ANFIS modeling, Gaussian type membership function (MF) and linear type MF was used for the input and output, respectively. The ANFIS model formed after 500 epochs and trained by hybrid model was found to have average value of 0.998. On comparing the value the ANFISR2 R2 model found to be superior over RSM in predicting the responses of the UOD cape gooseberry process. So, the ANFIS was integrated with a genetic algorithm (GA) for optimization with the aim of maximum and minimum , and . Depending on the higher fitness value of 3.4,YW YS YC YA the integrated ANFIS-GA picked the ideal combination of independent variables and was found to be of 282.434 W, of 50.280 min, of 55.836 % and of 9.250 w/w. The predicted andXP XT XC XS experimental values of response at optimum condition predicted by integrated ANN-GA were in close agreement, which was evident by the relative deviation less than 7%
Tárgyszavak:	Agrártudományok Élelmiszertudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Cape gooseberry ultrasonication osmotic dehydration ANFIS
Megjelenés:	Ultrasonics Sonochemistry. - 96 : (2023), p. 1-9. -
További szerzők:	Sundarsingh, Anjelina BhagyaRaj, GVS Kumar Pandey, Vinay Kovács Béla (1963-) (okleveles vegyész, angol szakfordító) Shaikh, Ayaz Mukarram (1991-) (PhD candidate)
Pályázati támogatás:	TKP2021-NKTA-32 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM117648
035-os BibID:	(cikkazonosító)106759 (Scopus)85182505982
Első szerző:	Giri, Souvik
Cím:	Ultrasound assisted phytochemical extraction of persimmon fruit peel: Integrating ANN modeling and genetic algorithm optimization / Souvik Giri, Kshirod Kumar Dash, GVS Bhagya Raj, Béla Kovács, Shaikh Ayaz Mukarram
Dátum:	2024
ISSN:	1350-4177
Megjegyzések:	In the present study, ultrasound assisted extraction (UAE) of phytochemicals from persimmon fruit peel (PFP) was modeled using an artificial neural network (ANN) and optimized byintegrating with genetic algorithm (GA). The range of process parameters selected for conducting the experiments was ultrasonication power (XU) 150 - 350 W, extraction temperatures (XT) 30 - 70°C, solid to solvent ratio (XS) 1:15 - 1:35 g/ml, and ethanol concentration (XC) 40 - 80%. The range of responses total phenolic content (YP), antioxidant activity (YA), total beta carotenoid (Y?) and total flavonoid content (YF) at various independent variables combinations were found to be 7.72 - 24.62 mg GAE/g d.w., 51.44 - 85.58 %DPPH inhibition, 24.78 - 56.56 ?g/g d.w. and 0.29 - 1.97 mg QE/g d.w. respectively. The modelling utilised an ANN architecture with a configuration of 4-12-4. The training process employed the Levenberg?Marquardt method, whereas the activation function chosen for the layers was the log sigmoid. The optimum condition predicted by the hybrid ANN-GA model for the independent variables, XU, XT, XS and XC was found to be 230.18 W, 50.66 ?C, 28.27 g/ml, and 62.75% respectively. The extraction process was carried out for 25 minutes, with 5-minut intervals, at various temperatures between 30 and 60 ?C, to investigate the kinetic and thermodynamic characteristics of the process, under the optimal conditions of XU, XS and XC. The UAE of phytochemicals from persimmon peel followed pseudo second order kinetic modeland the extraction process was endothermic in nature.
Tárgyszavak:	Agrártudományok Élelmiszertudományok kutatási jelentés folyóiratcikk Persimmon peel Ultrasonication Artificial neural network Kinetics
Megjelenés:	Ultrasonics Sonochemistry. - 102 (2024), p. 1-12. -
További szerzők:	Dash, Kshirod Kumar Raj, Bhagya Kovács Béla (1963-) (okleveles vegyész, angol szakfordító) Shaikh, Ayaz Mukarram (1991-) (PhD candidate)
Pályázati támogatás:	TKP2021-NKTA-32 Egyéb
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM117817
035-os BibID:	(cikkazonosító)106762 (Scopus)85182410154
Első szerző:	Pusty, Kasturi
Cím:	Ultrasound assisted phytochemical extraction of red cabbage by using deep eutectic solvent: Modelling using ANFIS and optimization by genetic algorithms / Pusty, Kasturi; Kumar Dash, Kshirod; Raj, Souvik Giri Bhagya; Raj, G.V.S. Bhagya; Tiwari, Ajita; Shaikh, Ayaz Mukarram; Béla, Kovács
Dátum:	2024
ISSN:	1350-4177
Megjegyzések:	The present investigation studied the effect of process parameters on the extraction of phytochemicals from red cabbage by the application of ultrasonication and temperature. The solvent selected for the study was deep eutectic solvent (DES) prepared by choline chloride and citric acid. The ultrasound assisted extraction process was modeled using adaptive neuro-fuzzy inference system (ANFIS) algorithm and integrated with the genetic algorithm for optimization purposes. The independent variables that influenced the responses (total phenolic content, antioxidant activity, total anthocyanin activity, and total flavonoid content) were ultrasonication power, temperature, molar ratio of DES, and water content of DES. Each ANFIS model was formed by the training of three Gaussian-type membership functions (MF) for each input, trained by a hybrid algorithm with 500 epochs and linear type MF for output MF. The ANFIS model predicted each response close to the experimental data which is evident by the statistical parameters (and RMSE <1.165). The integrated hybrid ANFIS-GA algorithm predicted the optimized condition for the process parameters of ultrasound assisted extraction of phytochemicals from red cabbage was found to be 252.114?W for ultrasonication power, 52.715??C of temperature, 2.0677:1 of molar ratio of DES and 25.947?% of water content in DES solvent with maximum extraction content of responses, with fitness value 3.352. The relative deviation between the experimental and ANFIS predicted values for total phenolic content, antioxidant activity, total anthocyanin activity, and total flavonoid content was found to be 1.849?%, 3.495?%, 2.801?%, and 4.661?% respectively.
Tárgyszavak:	Agrártudományok Élelmiszertudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Red cabbage ANFIS Ultrasonication Extraction Genetic algorithm
Megjelenés:	Ultrasonics Sonochemistry. - 102 (2024), p. 1-14. -
További szerzők:	Dash, Kshirod Kumar Raj, Souvik Giri Bhagya Raj, Bhagya Tiwari, Ajita Shaikh, Ayaz Mukarram (1991-) (PhD candidate) Kovács Béla (1963-) (okleveles vegyész, angol szakfordító)
Pályázati támogatás:	TKP2021-NKTA-32 Other
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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