## 2 Materials and Methods
### Optimization of Fermentation Parameters  
The RSM (Response Surface Methodology) optimization studies for dilute acid pretreatment, enzymatic saccharification, and fermentation were carried out using vetiver grass grown on control soil. Minitab(r) 17, a statistical design of experiments (DOE) software was used for experimental design by response surface methodology for the sequential lignocellulosic biomass to ethanol processes [32]. Factors for optimization of dilute acid pretreatment included acid concentration, biomass loading, and time and temperature of treatment. Table S1a displays treatment factors and levels of treatment used in the DOE with a central composite design (CCD). Values for levels of treatment were based on the NREL standard protocol for determination of carbohydrates and lignin from lignocellulosic biomass [26]. Replicates of two were built in. The total number of experimental combinations was equal to n = 60. Each of the experimental combinations was carried out in 125 mL Erlenmeyer flasks using an automatic Yamato autoclave for varying time and temperature factors. The total volume of sulfuric acid was 50 mL for each trial. Following dilute acid pretreatment, the hemicellulose hydrolysate was analyzed for monomeric carbohydrate and inhibitor content using high performance liquid chromatography (HPLC) following methods described by [PERSON], 2009 [33]. Total monosaccharide, furfural, 5-hydroxymethyl furfural, and acetic acid concentrations (g/L) were the response variables entered into Minitab(r) 17 following chromatogram analysis. The software's Response Optimizer was used to manipulate the factor levels simultaneously for maximum total monosaccharides and targets of 0.1 g/L, 0.5 g/L and 2.0 g/L for furfural, 5-hydroxymethylfurfural, and acetic acid, respectively. Prior to RSM optimized DOE for enzymatic saccharification, the biomass was washed three times, each with a volume of deionized water 3\(\times\) that of the biomass, with 10 min of agitation on a rotaryshaker set to 150 rpm, and vacuum filtered [34]. Optimization of the process was based on buffer pH, time and temperature of treatment, and cellulase and \(\beta\)-glucosidase loading [34]. Table S1b shows the evaluated factors and their levels of treatment used in a central composite design (CCD). Minitab(r)17 RSM DOE created 66 different factor combinations for response analysis for treatment, according to [PERSON] et al., (2008) [34]. Based on the control lignocellulosic content, 0.15 g (dry weight) of vetiver biomass was added to 20 mL scintillation vials at 105 \({}^{\circ}\)C [34]. Five milliliters of 0.1 M sodium citrate buffer were added to the biomass. 100 \(\mu\)L of 2% sodium azide were added to the vials for antimicrobial effects. The contents of the vial were incubated and brought to the appropriate temperatures. Cellulose and \(\beta\)-glucosidase were obtained from MP Biomedicals, LLC., Ohio, USA. Enzyme volumes of cellulase and \(\beta\)-glucosidase were loaded, and the vial contents were brought to a final volume of 10 mL with deionized water. The vials were capped and incubated for the indicated length of treatment time on a rotary shaker set to 160 rpm. Following enzymatic treatment, the vials were heated at 80 \({}^{\circ}\)C for 10 min. One milliliter samples were drawn and filtered, using a 3 mL Luer-lock syringe a 0.45 \(\upmu\)m nylon syringe filter, into HPLC vials for analysis. Glucose concentrations in g/L were entered into Minitab(r) 17 as the response variable. The Response Optimizer was used to determine which level of treatment for each factor would liberate the most glucose from cellulose. The determined time and temperature of treatment, pH, and enzyme loading concentrations for optimal glucose yield were performed on dilute-acid pretreated vetiver to obtain cellulosic hydrolysate for use in fermentation optimization and the achieved glucose yield was compared to the predicted value.