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001-es BibID:BIBFORM118989
035-os BibID:(Scopus)85195092002 (WoS)001178828600003
Első szerző:Bhagat, Vipal
Cím:Economic analysis of potential of citrus and walnut fruits by artificial neural network / Vipal Bhagat, Sudhakar Dwivedi, Rafeeya Shams, Kshirod K. Dash, G. V. S. Bhagya Raj, Béla Kovács, Shaikh Ayaz Mukarram
Dátum:2024
ISSN:3004-9261
Megjegyzések:South Asian countries have a wealth of opportunities to use the rainfed lands to the farmers' advantage with the largest amount of rainfed land. The economic circumstances of the farmers operating in these areas are appalling due to the inefficient use of these lands. The work reported in this paper was carried out in the Jammu, Kathua, and Udhampur districts of the Jammu division. Two horticultural crops, viz., citrus and walnuts, were discovered to be cultivated in the chosen sample location. The influence of several elements to the financial potential of these horticultural crops was investigated using production functional analysis and marginal value productivity (MVP). The use of artificial neural networks (ANNs) further assisted this. According to a production functional analysis, the main variables in the districts of Udhampur and Kathua are machine labour and fertilisers, followed by human labour and fertilisers in the Jammu district. However, sensitivity analysis revealed the importance of manure, fertilisers, and manpower. In the rainfed por-tions of Jammu division, manpower combined with fertilisers is often thought of as the key determining factor for the profitability of horticulture crops like citrus and walnut. The absence of better varieties was identified via Garett ranking as the main restriction, followed by a lack of knowledge and expensive inputs, respectively
Tárgyszavak:Agrártudományok Élelmiszertudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Rainfed region
Production function analysis
Marginal value productivity
Artificial neural network
Sensitivity analysis
Megjelenés:Discover Applied Sciences. - 6 (2024), p. 1-16. -
További szerzők:Dwivedi, Sudhakar Shams, Rafeeya Dash, Kshirod Kumar Raj, Bhagya Kovács Béla (1963-) (mezőgazdasági kémia, angol szakfordító) Shaikh, Ayaz Mukarram (1991-) (PhD candidate)
Pályázati támogatás:TKP2021-NKTA-32
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2.

001-es BibID:BIBFORM111151
035-os BibID:(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, G. V. S. Bhagya Raj, 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 Raj, Bhagya Kumar Pandey, Vinay Kovács Béla (1963-) (mezőgazdasági kémia, angol szakfordító) Shaikh, Ayaz Mukarram (1991-) (PhD candidate)
Pályázati támogatás:TKP2021-NKTA-32
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3.

001-es BibID:BIBFORM117648
035-os BibID:(WoS)001168598600001 (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-) (mezőgazdasági kémia, angol szakfordító) Shaikh, Ayaz Mukarram (1991-) (PhD candidate)
Pályázati támogatás:TKP2021-NKTA-32
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4.

001-es BibID:BIBFORM117817
035-os BibID:(WoS)001168394500001 (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, Souvik Giri, 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 Souvik, Giri Raj, Bhagya Tiwari, Ajita Shaikh, Ayaz Mukarram (1991-) (PhD candidate) Kovács Béla (1963-) (mezőgazdasági kémia, angol szakfordító)
Pályázati támogatás:TKP2021-NKTA-32
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5.

001-es BibID:BIBFORM125545
035-os BibID:(Scopus)85209365910 (WoS)001364024600001
Első szerző:Raj, Bhagya
Cím:Development of kiwi fruit leather incorporated with hydrocolloids and betacyanin microcapsules: Rheological behaviour and release kinetics of betacyanin / G. V. S. Bhagya Raj, Kshirod Kumar Dash, Rafeeya Shams, Shaikh Ayaz Mukarram, Béla Kovács
Dátum:2024
ISSN:2772-5022
Megjegyzések:The kiwi fruit leather incorporated with betacyanin microcapsules was prepared using three hydrocolloids namely xanthan gum, gellan gum, and guar gum. The four-kiwi fruit puree prepared for the study were kiwi fruit puree without hydrocolloid (CP), with xanthan gum (XE), with gellan gum (EP), and with guar gum (UP). The influence of various hydrocolloids and temperatures on rheological properties of kiwi fruit puree was investigated using the Cross, Carreau, and modified Powell model. The apparent viscosity was decreased with increase in shear rate and rise of temperature. The incorporation of hydrocolloid also increased viscosity of prepared puree. Cross model (R2>0.989) found to fit the apparent viscosity with respect to shear rate. The flow behaviour index of four kiwi fruit puree samples was found to be less than one depicting pseudoplastic fluid with shear thinning behaviour. For dynamic rheology study in the frequency range of 1?60 rad/s, the storage modulus was higher than loss modulus at specific frequency that implies, elastic properties of puree were dominant over the viscous ones suggesting the weak gel-like network of kiwi fruit puree. The glass transition temperature of prepared kiwi fruit leathers ranged from 59-64 ?C. The in vitro betacyanin release from the leather sample was studied and Peppas-Sahlin model was observed to be one of the ideal model when compared with the other kinetic models. The development of kiwi fruit leather with hydrocolloids and betacyanin microcapsules represented a successful strategy to create a functional snack that combines health benefits with consumer-desirable sensory attributes.
Tárgyszavak:Agrártudományok Élelmiszertudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Controlled release
texture enhancement
cross model
shelf life
elasticity and firmness
Megjelenés:Applied Food Research. - 4 : 2 (2024), p. 1-11. -
További szerzők:Dash, Kshirod Kumar Shams, Rafeeya Shaikh, Ayaz Mukarram (1991-) (PhD candidate) Kovács Béla (1963-) (mezőgazdasági kémia, angol szakfordító)
Pályázati támogatás:TKP2021-NKTA-32
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