MEVA-SABZAVOT XOMASHYOSIDAN BIOLOGIK FAOL MODDALARNI FERMENTATIV EKSTRAKSIYALASH JARAYONINING TEXNOLOGIK PARAMETRLARINI OPTIMALLASHTIRISH

Abstract

Maqolada meva-sabzavot xomashyosidan biologik faol moddalarni fermentativ ekstraksiyalash jarayonini Response Surface Methodology asosida optimallashtirish metodikasi ishlab chiqilgan. Ferment konsentratsiyasi, harorat, pH, gidroliz vaqti va qattiq/suyuq nisbat asosiy omillar sifatida qabul qilinib, Box–Behnken dizayni, ikkinchi darajali polinom, ANOVA va desirability funksiyasi qo‘llanishi asoslangan. TPC, TFC, antioksidant faollik va ekstraksiya chiqimi javob funksiyalari sifatida taklif etilgan. Model adekvatligini lack-of-fit, adjusted va predicted R² hamda tasdiqlash tajribalari bilan baholash tartibi berilgan.

V statye razrabotan metodicheskiy podxod k optimizasii fermentativnoy ekstraksii biologicheski aktivnыx veщyestv iz plodovo-ovoщnogo sыrya metodom Response Surface Methodology. V kachestve faktorov predlojenы konsentratsiya fermenta, temperatura, pH, prodoljitelnost gidroliza i sootnosheniye tverdoy i jidkoy faz. Obosnovano primeneniye plana Box–Behnken, kvadratichnoy regressionnoy modeli, ANOVA i funksii desirability. V kachestve otklikov rassmatrivayutsya obщyeye soderjaniye fenolov, flavonoidov, antioksidantnaya aktivnost i vыxod ekstrakta. Opisana prosedura validasii optimuma nezavisimыmi opыtami.

A Response Surface Methodology framework for optimizing enzyme-assisted extraction of bioactive compounds from fruit and vegetable matrices is presented. Enzyme concentration, temperature, pH, hydrolysis time and solid-to-liquid ratio are treated as the key process variables. A Box–Behnken design, quadratic polynomial regression, ANOVA and desirability-based multiresponse optimization are proposed. Total phenolics, total flavonoids, antioxidant activity and extraction yield are used as responses. Model adequacy is assessed through lack-of-fit, adjusted and predicted R-squared values and independent validation experiments.