Response surface methodology (RSM) was used in the modeling of cucumber (Cucumissativus) yield under different Nitrogen, phosphorus, potassium (NPK) fertilizer application rates and tillage methods at experimental farm Department Agricultural Bio-Resources Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria. From field experiment conducted, three methods; conventional (CT), man...

Barhi dates are widely consumed at Khalal maturity stage and preserving the freshness quality of this is a challenging task as period short fruits more perishable. In study, response surface methodology (RSM) was applied to optimize infrared (IR) treatment storage conditions for physicochemical, microbial, bioactive attributes fresh dates. The effect four factors, IR temperature (50, 70, 90, 11...

Introduction: Advanced oxidation processes (AOPs) suggest a highly reactive, nonspecific oxidant namely hydroxyl radical (OH•), that oxidize a wide range of pollutants fast and non-selective in wastewater and water. Materials and methods: In this work, the nitrogen-doped titanium dioxide nanoparticles were primed by sol-gel method, characterized by X-ray diffraction and Scanning Elect...

response surface methodology was applied to determine the optimum processing conditions that lead to maximum water loss, weight reduction and minimum solid gain as well as water activity during osmotic dehydration of carrots. temperature (30-50?c), processing time (120-240 min), glucose syrup de=42 (30-50% w/w) and salt (5-15%) concentrations were the factors investigated with respect to water ...

enzymatic hydrolysis of yellowfin tuna visceral protein with neutrase has been carried out by response surface methodology using factorial design. peptide chain length was estimated as the response surface to the hydrolysis conditions (enzyme activity, reaction temperature, and reaction time). the tuna visceral protein hydrolysate had relatively high protein (74.56%) and low lipid content (1.86...

R surface methodology (RSM) is a widely used method for simulation optimization. Its strategy is to explore small subregions of the decision space in succession instead of attempting to explore the entire decision space in a single attempt. This method is especially suitable for complex stochastic systems where little knowledge is available. Although RSM is popular in practice, its current appl...