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001-es BibID:	BIBFORM118989
035-os BibID:	(Cikkazonosító)102
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. BhagyaRaj, 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 BhagyaRaj, GVS 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:	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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