Experimental Design and Response Surface Modeling: A Method Development Application for the Determination of Reduced Inorganic Species in Environmental Samples

Abstract

ABSTRACT.To confirm the significance of reduced inorganic species in nature, it is important to develop sensitive and selective analytical techniques to detect these species in complex environmental matrices. As a model application, we report on the successful use of fractional factorial and Box-Behnken designs in factor screening, optimization and validation of an on-line flow-injection method for the determination of phosphite [P(+III)] in aqueous samples. Fractional factorial results indicated that the combined KI, KIO 3 and ammonium molybdate flow rates, reaction temperature and KIO 3 concentration were the most important single effects. The main interactive effects were between flow rate and reaction temperature, and between sample volume and reaction temperature. The Box-Behnken design further optimized the response with results confirming the significant single effects of flow rate and temperature as well as the interactive effects between flow rate and reaction temperature. Overall, the model from the Box-Behnken design predicted critical values as: flow rate = 0.40 mL·min -1 , reaction temperature = 47 o C, sample volume = 85 μL, KI reagent concentration = 1.06 g·L -1 and KIO 3 reagent concentration = 0.29 g·L -1 . P(+III) determinations in spiked ultra-pure water were performed using the predicted optimized values from the Box-Behnken design and compared favorably with experimental results. In addition, the potential use of such methodology in the development of sensitive laboratory and field-based methods for the detection of a suite of reduced inorganic species in complex matrices was discussed.

Optimizaton of extraction of betalain pigments from beta vulgaris peels by microwave pretreatment

“…A full factorial design typically is suggested for five or fewer variables. Generally, Central Composite Design [15,16] with α value is ideal for RSM but the Box-Behnken design is considered as an efficient alternate option. It has three levels per factor, but does not consider the corners of the space and fills in the combinations of center and extreme levels.…”

“…It has three levels per factor, but does not consider the corners of the space and fills in the combinations of center and extreme levels. It combines a fractional factorial with incomplete block design to avoid the extreme vertices and present an almost rotatable design with three levels per factor [16]. The range of design variables selected for the investigation is given in Table 1.…”

Bio-designing of Culture Conditions for Chlorella vulgaris Using Response Surface Methodology

“…As seen in Table 4, the regression coefficient R 2 of 0.7025 value indicated that the regression model represented 70.25% of the experimental results and expressed a good fit response. The quality of fit explained by the model given by the multiple coefficient of determined R 2 value and if R 2 > 0.7 insured, the model was suitable and adequate in biological production (Hanrahan et al, 2007). By adding factors to the model, the R 2 value increased regardless of factors significant or non-significant (Montgomery, 2001;Myers et al, 2016).…”

Inhibitory Effects of Organic Acids on Bacteria Growth During Food Waste Composting

“…Factorial designs were widely used in experiments involving multiple factors where their joint effects on a response need to be analyzed (Montgomery 2001;Hanrahan et al 2007). Lactic, acetic, propionic and butyric acid are the primary organic acids produced during the initial stage of food waste composting.…”