<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">AER</journal-id><journal-title-group><journal-title>Advances in Enzyme Research</journal-title></journal-title-group><issn pub-type="epub">2328-4846</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/aer.2014.24013</article-id><article-id pub-id-type="publisher-id">AER-51786</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biomedical&amp;Life Sciences</subject><subject> Engineering</subject><subject> Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  Optimization of Parameters for the Production of Lipase from Pseudomonas sp. BUP6 by Solid State Fermentation
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>anichikkal</surname><given-names>Abdul Faisal</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Erandapurthukadumana</surname><given-names>Sreedharan Hareesh</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Prakasan</surname><given-names>Priji</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Kizhakkepowathial</surname><given-names>Nair Unni</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Sreedharan</surname><given-names>Sajith</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Sasidharan</surname><given-names>Sreedevi</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Moolakkariyil</surname><given-names>Sarath Josh</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Sailas</surname><given-names>Benjamin</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib></contrib-group><aff id="aff1"><addr-line>Enzyme Technology Laboratory, Biotechnology Division, Department of Botany, University of Calicut, Kerala, India</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>benjamin@uoc.ac.in(SB)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>26</day><month>11</month><year>2014</year></pub-date><volume>02</volume><issue>04</issue><fpage>125</fpage><lpage>133</lpage><history><date date-type="received"><day>17</day>	<month>September</month>	<year>2014</year></date><date date-type="rev-recd"><day>23</day>	<month>October</month>	<year>2014</year>	</date><date date-type="accepted"><day>6</day>	<month>November</month>	<year>2014</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Solid-state fermentation (SSF) holds tremendous potentials for the production of industrially significant enzymes. The present study describes the production of lipase by a novel rumen bacterium, Pseudomonas sp. strain BUP6 on agro-industrial residues. Pseudomonas sp. strain BUP6 showed higher lipase production when grown in Basal salt medium (BSM) supplemented with oil cakes. Initially, five different oil cakes (obtained after extracting oil from coconut, groundnut, cotton seed, gingelly or soybean) were screened to find out the most suitable substrate-cum-inducer for the production of lipase. Among them, groundnut cake supported the maximum production of lipase (107.44 U/gds). Box-Behnken Design (BBD), followed by response surface methodology (RSM) was employed to optimize the culture parameters for maximizing the production of lipase. Using the software Minitab 14, four different parameters like temperature, pH, moisture content and incubation time were selected for the statistical optimization, which resulted in 0.7 fold increase (i.e., 180.75 U/gds) in production of lipase under the optimum culture conditions (temperature 28
  &amp;#176C, pH 5.9, moisture 33% and incubation 2 d). Thus, this study signifies the importance of SSF for the production of industrially-significant lipase using agro-industrial residues as solid support.
 
</p></abstract><kwd-group><kwd>Lipase</kwd><kwd> Solid-State Fermentation</kwd><kwd> Basal Salt Medium</kwd><kwd> Oil Cakes</kwd><kwd> Response Surface Methodology</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Lipases (triacylglycerol acyl hydrolase EC 3.1.1.3) are a cluster of enzymes catalyzing the hydrolysis of triacyl- glycerol to form glycerol and free fatty acids. In contrast to esterase, lipases are activated only at an oil-water interface. Many lipases are catalyzing a number of useful reactions including hydrolysis, esterification, trances- terification, acidolysis, alcholysis, and synthesis of peptides [<xref ref-type="bibr" rid="scirp.51786-ref1">1</xref>] . The extensive utilization of lipase has wide range of applications in synthesis of detergents, biosurfactants; organic, oleo-chemical, leather, cosmetic, per- fume, dairy and agrochemical industries; environmental management; biosensors, etc.</p><p>Microorganisms with potentials for producing lipases can be found in different habitats, including wastes of vegetable oils and dairy industries, soils contaminated with oils, seeds, and deteriorated food [<xref ref-type="bibr" rid="scirp.51786-ref2">2</xref>] . Since, lipase is among the most widely used class of enzymes in biotechnological applications and organic chemistry [<xref ref-type="bibr" rid="scirp.51786-ref3">3</xref>] , utili- zation of agro-industrial wastes as alternative sources of substrates would help solving pollution problems. The nature of the substrate is the most important factor affecting fermentative processes. The choice of the substrate depends upon several factors; mainly related to cost and availability.</p><p>Lipases are produced by several microorganisms, viz., bacteria, fungi, yeast, actinomycetes, archea, eucarya, etc. Microbial genera involved in the commercial production of lipases include: Candida, Mucor, Rhizopus, As- pergillus, Penicillium, Geotrichum, Rhizomucor, Bacillus, Pseudomonas and Staphylococcus [<xref ref-type="bibr" rid="scirp.51786-ref4">4</xref>] . Since they perform at wide range of pH and temperature, and they can be produced by solid-state fermentation (SSF) as well as submerged fermentation (SmF), microbial lipases are considered as highly robust. By dint of low pro- duction cost, greater stability, more simplicity and wider availability than SmF, SSF is considered as a novel strategy with higher physiological significance and industrial potentials [<xref ref-type="bibr" rid="scirp.51786-ref5">5</xref>] . Lipases are inducible enzymes; hence, different natural agro-industrial residues such as brans of wheat and rice, sugar cane bagasse, wastes from vegetable oil-refining, etc. can effectively be used as inducers or substrates for lipase production employing SSF strategy [<xref ref-type="bibr" rid="scirp.51786-ref4">4</xref>] -[<xref ref-type="bibr" rid="scirp.51786-ref8">8</xref>] . Deoiled kernels (i.e., cakes) from coconut, olive, gingelly, cotton, Jatropha, etc., obtained after extracting oil have been utilized as solid substrate for the fermentative production of lipases and other industrial enzymes. This is because residual oil and other ingredients contained in it serve as inducers for lipase production [<xref ref-type="bibr" rid="scirp.51786-ref15">15</xref>] .</p><p>Optimization of environmental parameters as well as the culture parameters may enhance the production of value-added products of commercial interest to many folds. Usually, “one parameter at a time” strategy was used for the optimization; but, this method is time consuming and hectic, and that the utilization of statistical tools makes the process easier. Response surface methodology (RSM) is such a kind of statistical tool being ap- plied widely for the optimization, modeling and analysis of problems related to the production of biomolecules [<xref ref-type="bibr" rid="scirp.51786-ref6">6</xref>] . However, the use of different substrates as well as cultivation strategies for the production of lipase still re- mains an emerging area of research. In this context, the present study focused on 1) screening of different oil cakes as solid substrate for the production of lipase by a novel rumen bacterium Pseudomonas sp. strain BUP6, and 2) statistical optimization of parameters for lipase production employing RSM technique.</p></sec><sec id="s2"><title>2. Materials and Methods</title><sec id="s2_1"><title>2.1. Materials</title><p>Analytical and bacteriological-grade chemicals from Himedia (India) and Merck India Ltd. were used for the present study.</p></sec><sec id="s2_2"><title>2.2. Culture Medium</title><p>The pure bacterial culture Pseudomonas sp. strain BUP6 (Genbank Accession No. KF 550910), isolated from the rumen of Malabari goat, was used for this study [<xref ref-type="bibr" rid="scirp.51786-ref9">9</xref>] . The bacterium was cultured on basal salt medium (BSM), supplemented with 0.3% of vegetable oil, and incubated at 37˚C for 24 h. The stock culture was main- tained on BSM agar slants, which was sub-cultured in an interval of 2 weeks. The BSM contained the following ingredients (%): 0.5 NH<sub>4</sub>NO<sub>3</sub>; 0.4(NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>; 0.3 yeast extract; 0.2 K<sub>2</sub>HPO<sub>4</sub>; 0.2 NaCl; 0.01 MgSO<sub>4</sub>. 7H<sub>2</sub>O and 0.01 CaCl<sub>2</sub> in double distilled water.</p></sec><sec id="s2_3"><title>2.3. SSF Using Agro-Industrial Residues</title><p>Deoiled cakes of groundnut (GNC), gingelly (GOC), coconut (COC), soybean (SOC), and cotton seed (CSC) procured from the local market were used as solid substrate-cum-inducer for the production of lipase by SSF. Fermentation was carried out in 100 mL of conical flasks. Five grams of substrate (oil cake) were transferred into 100 mL conical flasks, and then moistened with10 mL of BSM (50%). In order to check the effect of pH on lipase production, the initial pH of the medium was set at 5, 7 and 9. All preparations in the flask were autoc- laved at 121˚C for 15 min, and inoculated with 0.1 mL of inoculum under aseptic condition. Production of lipase was assayed at regular intervals of 24 h for 5 days.</p></sec><sec id="s2_4"><title>2.4. Extraction of Crude Enzyme</title><p>After incubation, the fermented matter in the whole flask was used for lipase assay at regular intervals of 24 h; for the extraction of crude lipase, 10 mL of 0.1 M Tris-HCl buffer was added to the flask and stirred for 10 min. Then the contents of the flask were centrifuged at 9400&#215; g for 15 min at 4˚C, the supernatant was used as crude lipase for the activity assay.</p></sec><sec id="s2_5"><title>2.5. Lipase Activity Assay</title><p>Production of lipase was qualitatively assayed by the method of by Priji et al. [<xref ref-type="bibr" rid="scirp.51786-ref9">9</xref>] . Para-nitro phenyl palmitate (p-NPP) was used as substrate for lipase assay. The assay mixture containing 1.8 ml of 0.1 M Tris-HCl buffer, 0.15 M NaCl and 0.5% Triton X-100 was pre-incubated with 200 &#181;l of cell-free culture supernatant at 37˚C for 10 min. Subsequently, 20 &#181;l of substrate (50 mM p-NPP in acetonitrile) was added to the reaction mixture and incubated at 37˚C for 30 min. The quantity of p-NP liberated was measured spectrophotometrically at<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x6.png" xlink:type="simple"/></inline-formula>. One unit of lipase corresponds to 1 &#181;mol of p-NP liberated per minute under the standard assay conditions. The li- pase activity was calculated as following Equation (1).</p><disp-formula id="scirp.51786-formula115"><label>(1)</label><graphic position="anchor" xlink:href="http://html.scirp.org/file/1-2880036x7.png"  xlink:type="simple"/></disp-formula><p>where<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x8.png" xlink:type="simple"/></inline-formula>—absorbance at 405 nm;<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x9.png" xlink:type="simple"/></inline-formula>—final volume;<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x10.png" xlink:type="simple"/></inline-formula>—volume of lipase used;<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x11.png" xlink:type="simple"/></inline-formula>—time of hydrolysis;<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x12.png" xlink:type="simple"/></inline-formula>—extinction co-efficient (0.017); gds—dry weight in grams.</p></sec></sec><sec id="s3"><title>3. Statistical Optimization of Lipase Production</title><p>Box-Behnken Design (BBD), followed by RSM was employed to develop a mathematical correlation between different independent variables such as temperature, pH, moisture, and incubation time on the production of li- pase. The software Minitab version 14 (Minitab USA) was used to generate data and to analyze the experimental design of BBD and RSM.</p><sec id="s3_1"><title>3.1. Box-Behnken Design (BBD)</title><p>The culture parameters like temperature (28˚C to 40˚C), pH (5 to 9), moisture (20% to 60%), and incubation time (1 to 5 d) were selected for BBD. BBD at three levels (+1, 0, and −1)—designated as high, medium and low—was used for this study. Based on this design, a set of 27 experimental trials were suggested by the soft- ware. All the trials were carried out in duplicates and the results were analyzed by fitting to a second-order po- lynomial Equation (2). Each experimental trial was set up and lipase was harvested at proper intervals to meas- ure lipase activity as per the design.</p><disp-formula id="scirp.51786-formula116"><label>(2)</label><graphic position="anchor" xlink:href="http://html.scirp.org/file/1-2880036x13.png"  xlink:type="simple"/></disp-formula><p>where <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x14.png" xlink:type="simple"/></inline-formula> represents the response variable; <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x15.png" xlink:type="simple"/></inline-formula>is the interception coefficient; <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x16.png" xlink:type="simple"/></inline-formula>is the coefficient of the linear effect; <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x17.png" xlink:type="simple"/></inline-formula>is the coefficient of quadratic effect; <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x18.png" xlink:type="simple"/></inline-formula>is the coefficient of interaction effect when<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x19.png" xlink:type="simple"/></inline-formula>; and <inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x20.png" xlink:type="simple"/></inline-formula> is the numbers of involved variables.</p></sec><sec id="s3_2"><title>3.2. Validation Experiment</title><p>To check the validity of quadratic model, 4 experiments as predicted by point prediction software Minitab 14 were performed. Lipase activity was estimated and compared with predicted values.</p></sec></sec><sec id="s4"><title>4. Results</title><sec id="s4_1"><title>4.1. Effects of Different Substrates on Lipase Activity</title><p>Five different oil seed cakes (GNC, GOC, COC, SOC and CSC) were used as solid substrate-cum-inducer for the production of lipase by Pseudomonas sp. strain BUP6. GNC, GOC and COC supported the maximum pro- duction of lipase (107.44 U/gds, 86.21 U/gds and 9.97 U/gds, respectively) on Day 3 of incubation, subsequently the lipase activity was decreased sharply; while SOC as well as CSC supported the maximum production of lipase after 24 h of incubation, but in lesser amounts (95.74 U/gds and 5.45 U/gds, respectively) (<xref ref-type="fig" rid="fig1">Figure 1</xref>). Of them, GOC supported the highest lipase production (107.44 U/gds) (<xref ref-type="fig" rid="fig1">Figure 1</xref>). Effects of SOC (95.74 U/gds) and GOC (86.21 U/gds) were comparable to that of GNC (107.44 U/gds), but the other two oil cakes (COC and CSC) showed much lesser activity, i.e., 9.97 and 5.45 U/gds (<xref ref-type="table" rid="table1">Table 1</xref>).</p><fig id="fig1"  position="float"><label><xref ref-type="fig" rid="fig1">Figure 1</xref></label><caption><title> Liapse production by Pseudomonas sp. strain BUP6 on different oil cakes</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-2880036x21.png"/></fig><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Maximum lipase activity in different substrates</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Substrates</th><th align="center" valign="middle" >Maximum lipase activity (U/gds)</th><th align="center" valign="middle" >Incubation (d)</th></tr></thead><tr><td align="center" valign="middle" >Groundnut oil cake</td><td align="center" valign="middle" >107.44</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >Soya bean oil cake</td><td align="center" valign="middle" >95.74</td><td align="center" valign="middle" >1</td></tr><tr><td align="center" valign="middle" >Gingelly oil cake</td><td align="center" valign="middle" >86.21</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >Coconut oil cake</td><td align="center" valign="middle" >9.97</td><td align="center" valign="middle" >3</td></tr><tr><td align="center" valign="middle" >Cotton cake</td><td align="center" valign="middle" >5.45</td><td align="center" valign="middle" >1</td></tr></tbody></table></table-wrap></sec><sec id="s4_2"><title>4.2. Statistical Optimization of Lipase Production</title><p>GNC which supported the maximum production of lipase was selected as substrate for the optimization studies. Four parameters (temperature, pH, moisture, and incubation) were considered for BBD analysis, followed by RSM to find out the optimum conditions for maximizing the production of lipase. A set of 27 experiments was conducted according to BBD, and the results showed that the predicted and experimental values for lipase activ- ities did not show significant difference (<xref ref-type="table" rid="table2">Table 2</xref>), i.e., the R<sup>2</sup> value was 0.95-close to unity. A second order po- lynomial equation was fitted to the experimental lipase activity, which resulted in the following regression Equ- ation (3).</p><disp-formula id="scirp.51786-formula117"><label>(3)</label><graphic position="anchor" xlink:href="http://html.scirp.org/file/1-2880036x22.png"  xlink:type="simple"/></disp-formula><p>where<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x23.png" xlink:type="simple"/></inline-formula>—pH,<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x23.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x24.png" xlink:type="simple"/></inline-formula>—Temperature,<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x23.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x24.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x25.png" xlink:type="simple"/></inline-formula>—Moisture,<inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x23.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x24.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x25.png" xlink:type="simple"/></inline-formula><inline-formula><inline-graphic xlink:href="http://html.scirp.org/file/1-2880036x26.png" xlink:type="simple"/></inline-formula>—Incubation.</p><p>The results were analyzed by standard analysis of ANOVA (<xref ref-type="table" rid="table3">Table 3</xref>). Based on these results, the model was utilized to generate response surfaces for the analysis of the variable effect on the production of lipase. The re- sponse surface plots obtained using Equation (3) is depicted in <xref ref-type="fig" rid="fig2">Figure 2</xref>.</p><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Experimental trials according to BBD model for the optimization of lipase production</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Run order</th><th align="center" valign="middle" >Temperature (˚C)</th><th align="center" valign="middle" >pH</th><th align="center" valign="middle" >Moisture (%)</th><th align="center" valign="middle" >Incubation (d)</th><th align="center" valign="middle" >Observed (U/gds)</th><th align="center" valign="middle" >Predicted (U/gds)</th></tr></thead><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >137.86</td><td align="center" valign="middle" >155.597</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >112.35</td><td align="center" valign="middle" >119.362</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >155.98</td><td align="center" valign="middle" >160.407</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >158.89</td><td align="center" valign="middle" >152.592</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >97.68</td><td align="center" valign="middle" >101.597</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >26.37</td><td align="center" valign="middle" >35.46</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >5.08</td><td align="center" valign="middle" >7.429</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >6.43</td><td align="center" valign="middle" >13.952</td></tr><tr><td align="center" valign="middle" >9</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >129.66</td><td align="center" valign="middle" >121.105</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >98.97</td><td align="center" valign="middle" >101.595</td></tr><tr><td align="center" valign="middle" >11</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >86.95</td><td align="center" valign="middle" >93.814</td></tr><tr><td align="center" valign="middle" >12</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >51.23</td><td align="center" valign="middle" >69.274</td></tr><tr><td align="center" valign="middle" >13</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >133.52</td><td align="center" valign="middle" >125.784</td></tr><tr><td align="center" valign="middle" >14</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >111.3</td><td align="center" valign="middle" >112.359</td></tr><tr><td align="center" valign="middle" >15</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >27.07</td><td align="center" valign="middle" >35.5</td></tr><tr><td align="center" valign="middle" >16</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >69.74</td><td align="center" valign="middle" >86.965</td></tr><tr><td align="center" valign="middle" >17</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >171.25</td><td align="center" valign="middle" >168.312</td></tr><tr><td align="center" valign="middle" >18</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >161.2</td><td align="center" valign="middle" >157.807</td></tr><tr><td align="center" valign="middle" >19</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >139.53</td><td align="center" valign="middle" >121.994</td></tr><tr><td align="center" valign="middle" >20</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >106.44</td><td align="center" valign="middle" >88.449</td></tr><tr><td align="center" valign="middle" >21</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >109.47</td><td align="center" valign="middle" >107.044</td></tr><tr><td align="center" valign="middle" >22</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >20</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >25.59</td><td align="center" valign="middle" >27.679</td></tr><tr><td align="center" valign="middle" >23</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1.87</td><td align="center" valign="middle" >−21.148</td></tr><tr><td align="center" valign="middle" >24</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >114.76</td><td align="center" valign="middle" >96.258</td></tr><tr><td align="center" valign="middle" >25</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >155.76</td><td align="center" valign="middle" >151.007</td></tr><tr><td align="center" valign="middle" >26</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >158</td><td align="center" valign="middle" >151.007</td></tr><tr><td align="center" valign="middle" >27</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >139.26</td><td align="center" valign="middle" >151.007</td></tr></tbody></table></table-wrap><table-wrap id="table3" ><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Analysis of variance for the second-order polynomial model for optimization of lipase production [Degree of free- dom (DF), Sequential sum of square (Seq SS), Adjacent sum of square (Adj SS), Adjacent mean square (Adj MS), Text of statistics (F), Probability (P)]</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Source</th><th align="center" valign="middle" >DF</th><th align="center" valign="middle" >Seq SS</th><th align="center" valign="middle" >Adj SS</th><th align="center" valign="middle" >Adj MS</th><th align="center" valign="middle" >F</th><th align="center" valign="middle" >P</th></tr></thead><tr><td align="center" valign="middle" >Regression</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >72999.4</td><td align="center" valign="middle" >72999.4</td><td align="center" valign="middle" >5214.2</td><td align="center" valign="middle" >19.51</td><td align="center" valign="middle" >0.000</td></tr><tr><td align="center" valign="middle" >Linear</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >15241.7</td><td align="center" valign="middle" >4271.3</td><td align="center" valign="middle" >1067.8</td><td align="center" valign="middle" >3.99</td><td align="center" valign="middle" >0.028</td></tr><tr><td align="center" valign="middle" >Square</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >45364.5</td><td align="center" valign="middle" >45364.5</td><td align="center" valign="middle" >11341.1</td><td align="center" valign="middle" >42.43</td><td align="center" valign="middle" >0.000</td></tr><tr><td align="center" valign="middle" >Interaction</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >12393.1</td><td align="center" valign="middle" >12393.1</td><td align="center" valign="middle" >2065.5</td><td align="center" valign="middle" >7.73</td><td align="center" valign="middle" >0.001</td></tr><tr><td align="center" valign="middle" >Residual Error</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >3207.8</td><td align="center" valign="middle" >3207.8</td><td align="center" valign="middle" >267.3</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Lack-of-Fit</td><td align="center" valign="middle" >10</td><td align="center" valign="middle" >2998.3</td><td align="center" valign="middle" >2998.3</td><td align="center" valign="middle" >299.8</td><td align="center" valign="middle" >2.86</td><td align="center" valign="middle" >0.287</td></tr><tr><td align="center" valign="middle" >Pure Error</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >209.5</td><td align="center" valign="middle" >209.5</td><td align="center" valign="middle" >104.7</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Total</td><td align="center" valign="middle" >26</td><td align="center" valign="middle" >76207.2</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr></tbody></table></table-wrap></sec><sec id="s4_3"><title>4.3. Validation of Lipase Production</title><p>Four random experimental conditions were evaluated for the validation of the model. In all these instances, model prediction was in good agreement with the experimental data (considering the experimental error), and correlation coefficient was found to be 0.96 (<xref ref-type="table" rid="table4">Table 4</xref>).</p><p>Correlation coefficient was close to 1.0, suggesting the significance of the model. The optimum production of lipase was found to be 180.75 U/gds (at 28˚C, pH 5.9, moisture 33%, and incubation period 2 d). Thus, the sta- tistical optimization resulted in 0.7 fold of lipase activity over the unoptimized condition.</p></sec></sec><sec id="s5"><title>5. Discussion</title><p>Research on lipase progressed very rapidly during the past few decades, giving much emphasis on the exploita- tion and recycling of agro-industrial residues. The present study proved that Psuedomonas sp. strain BUP6 is an efficient producer of lipase on solid medium (oil cakes). Nowadays, SSF strategy is increasingly employed as a method for the production of lipase on different lipid-bound waste materials, because of the several advantages of SSF such as better yield and easy to control. As a part of this study, different natural substrate such as COC, GNC, SOC, GOC, and CSC were screened to spot out the best solid medium for lipase production. Of them, GNC supported the highest production of lipase (107.44 U/gds at 72 h). The cultivation period varies with the microorganism, i.e., fast growing bacteria were found to secrete lipase within 24 h [<xref ref-type="bibr" rid="scirp.51786-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.51786-ref11">11</xref>] . Bacteria normally grow in a complex nutrient medium containing carbon (oil, sugars, mixed carbon sources), nitrogen and phos- phorous sources and mineral salts. Other significant factors influencing lipase production include: initial pH, growth temperature, incubation period and moisture percentage (water activity). Temperature of the substrate during SSF critically affects the growth of microorganisms, and product formation [<xref ref-type="bibr" rid="scirp.51786-ref5">5</xref>] . Lipase yield by Pseudo- monas sp. BUP6 appeared to be dependent on moisture content. Results showed that lipase production (ex- pressed as enzyme activity) gradually increased from 20% to 60% moisture content and reached its maximum at 60%, and found that the moisture content was directly proportional to production of lipase; but high moisture content led to more contamination (may be due to poor aeration). The maximum lipase activity (114.75 U/gds) was obtained at 60% moisture content. Like moisture content, incubation time was also an important parameter that influenced the production of lipase. In the present study, 48 h of incubation was found to be optimum for lipase production. Incubation periods ranging from few hours to several days have been found to be best suited for the maximum lipase production by bacteria. For instance, an incubation period of 12 h was found optimum for the lipase production by Acinetobacter calcoaceticus and Bacillus sp. RSJ1 [<xref ref-type="bibr" rid="scirp.51786-ref10">10</xref>] and 16 h for B. thermoca- tenulatus [<xref ref-type="bibr" rid="scirp.51786-ref11">11</xref>] ; while, in the case of Pseudomonas sp., P. fragia and P. fluorescens BW 96CC, the maximum li- pase activity was obtained at 72 h and 96 h of incubation, respectively [<xref ref-type="bibr" rid="scirp.51786-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.51786-ref13">13</xref>] . Employing Candida rugosa, Benjamin and Pandey [<xref ref-type="bibr" rid="scirp.51786-ref1">1</xref>] reported the use of mixed-solid substrate containing wheat bran and coconut oil cake for lipase production. Fermentation was carried out for 72 h, and the maximum lipase yield was 118.2 U/g. Si- milarly, in the present study, the maximum activity of lipase obtained (107.44 U/gds) was at 72 h of incubation using GNC as substrate. It seems that the residual oil in the cake acted as both inducer and additional nutrient.</p><fig id="fig2"  position="float"><label><xref ref-type="fig" rid="fig2">Figure 2</xref></label><caption><title> Response surface plots (3D) showing the effects of different parameters (X<sub>1</sub>: pH; X<sub>2</sub>: temperature, ˚C; X<sub>3</sub>: moisture, %; and X<sub>4</sub>: incubation time, d) on production of lipase by Pseudomonas sp. strain BUP6</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/1-2880036x27.png"/></fig><table-wrap id="table4" ><label><xref ref-type="table" rid="table4">Table 4</xref></label><caption><title> Experimental trails for the validation of the predicted model</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Run Order</th><th align="center" valign="middle" >Temperature (˚C)</th><th align="center" valign="middle" >pH</th><th align="center" valign="middle" >Moisture (%)</th><th align="center" valign="middle" >Incubation (d)</th><th align="center" valign="middle" >Observed (U/gds)</th><th align="center" valign="middle" >Predicted (U/gds)</th></tr></thead><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >5.9</td><td align="center" valign="middle" >33</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >180.75</td><td align="center" valign="middle" >187.92</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >50</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >135.15</td><td align="center" valign="middle" >125.92</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >6</td><td align="center" valign="middle" >33</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >147.66</td><td align="center" valign="middle" >157.31</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >5.9</td><td align="center" valign="middle" >50</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >141.85</td><td align="center" valign="middle" >134.07</td></tr></tbody></table></table-wrap><p>Therefore, at the later stage of fermentation, the lipase activity was decreased; this might be an indication of the depletion of nutrient in the medium, i.e., lipase production is dependent on the nutrient status.</p><p>Few studies reported that oil cakes as the best solid substrate-cum-inducer for the production of lipase by SSF [<xref ref-type="bibr" rid="scirp.51786-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.51786-ref15">15</xref>] . D’Annibale et al. [<xref ref-type="bibr" rid="scirp.51786-ref16">16</xref>] reported that olive mill waste water as a growth medium for lipase production, which showed the highest lipase activity of 9.23 U/ml. Brozzoli et al. [<xref ref-type="bibr" rid="scirp.51786-ref17">17</xref>] studied the lipase production in bench-top reactor using the olive mill waste water medium and obtained the maximum production as 20.4 U/ml. Salihu et al. [<xref ref-type="bibr" rid="scirp.51786-ref18">18</xref>] used the statistical optimization of nutrient components to enhance lipase production by C. cy- lindracea, and the maximum activity was 20.26 U/ml. Vishnupriya et al. [<xref ref-type="bibr" rid="scirp.51786-ref19">19</xref>] assessed the lipase production by Sterptomyces grisesus, and found the maximum activity as 51.9 U/ml. Compared to all these studies, present study reports higher lipase activity (180.75 U/gds) at optimized condition.</p><p>Various physico-chemical parameters evaluated for the maximum production of lipase. Four parameters like temperature, pH, moisture, and incubation time for the lipase production were statistically optimized. Optimiza- tion is a complex process, which can be performed in two different ways: conventional and modern methods. The conventional method of optimization defined as the one-at-time strategy, but modern multivariate RSM technique enables optimization of more than one parameter at a time [<xref ref-type="bibr" rid="scirp.51786-ref6">6</xref>] , which can be performed for assessing the relationship between environmental and cultural parameters, so as to produce 3D contour and surface plots. This is more effective than conventional methodology, i.e., effective, easier, faster and more economical [<xref ref-type="bibr" rid="scirp.51786-ref6">6</xref>] . Groundnut cake which supported the maximum lipase production was selected for the optimization process. Under optimized conditions (28˚C, pH 5.9, moisture 33%, and incubation 2 d), the maximum production of li- pase was 180.75 U/gds on GNC, which was 0.7 fold higher than that of unoptimized conditions. R<sup>2</sup> value (0.95) represents the good fixity of experiments with predicted values.</p></sec><sec id="s6"><title>6. Conclusion</title><p>Briefly, this study investigated the lipase activities of Pseudomonas sp. BUP6 on agro-industrial residues as substrate, which showed that groundnut oil cake was the best for enhancing lipase production on solid medium. By statistically optimizing the culture parameters, the lipase production was further enhanced. Thus, this study focuses on the need for the exploitation of agro-industrial residues for the production of industrially-significant and human-friendly biomolecules; moreover, its low cost increases the industrial potentials.</p></sec><sec id="s7"><title>Acknowledgements</title><p>The financial assistance (Grant No. 026/SRSLS/2012/CSTE) from Kerala State Council for Science, Technology and Environment (KSCSTE), Government of Kerala, is gratefully acknowledged.</p></sec><sec id="s8"><title>NOTES</title></sec></body><back><ref-list><title>References</title><ref id="scirp.51786-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Benjamin, S. and Pandey, A. (1998) Mixed-Solid Substrate Fermentation—A Novel Process for Enhanced Lipase Production by Candida rugosa. Acta Biotechnologica, 18, 315-324. &lt;br /&gt;http://dx.doi.org/10.1002/abio.370180405</mixed-citation></ref><ref id="scirp.51786-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Sharma, R., Chisti, Y. and Banerjee, U.C. (2001) Production, Purification, Characterization, and Applications of Lipases. Biotechnology Advances, 19, 627-662. http://dx.doi.org/10.1016/S0734-9750(01)00086-6</mixed-citation></ref><ref id="scirp.51786-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Gupta, R., Gupta, N. and Rathi, P. (2004) Bacterial Lipases: An Overview of Production, Purification and Biochemical Properties. Applied Microbiology and Biotechnology, 64, 763-781. &lt;br /&gt;http://dx.doi.org/10.1007/s00253-004-1568-8</mixed-citation></ref><ref id="scirp.51786-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Aravindan, R., Anbumathi, P. and Viruthagiri, T. (2007) Lipase Applications in Food Industry. Indian Journal of Biotechnology, 6, 141-158.</mixed-citation></ref><ref id="scirp.51786-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Pandey, A., Selvakumar, P., Soccol, C.R. and Nigam, P. (1999) Solid State Fermentation for the Production of Industrial Enzymes. Current Science, 77, 149-162.</mixed-citation></ref><ref id="scirp.51786-ref6"><label>6</label><mixed-citation publication-type="other" xlink:type="simple">John, R.P., Sukumaran, R.K., Nampoothiri, K.M. and Pandey, A. (2007) Statistical Optimization of Simultaneous Saccharification and l (+)-Lactic Acid Fermentation from Cassava Bagasse Using Mixed Culture of Lactobacilli by Response Surface Methodology. Biochemical Engineering Journal, 36, 262-267. 
http://dx.doi.org/10.1016/j.bej.2007.02.028</mixed-citation></ref><ref id="scirp.51786-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">Santis-Navarro, A., Gea, T., Barrena, R. and Sánchez, A. (2011) Production of Lipases by Solid State Fermentation Using Vegetable Oil-Refining Wastes. Bioresource Technology, 102, 10080-10084.&lt;br /&gt; 
http://dx.doi.org/10.1016/j.biortech.2011.08.062</mixed-citation></ref><ref id="scirp.51786-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Joshi, C. and Khare, S.K. (2013) Purification and Characterization of Pseudomonas aeruginosa Lipase Produced by SSF of Deoiled Jatropha Seed Cake. Biocatalysis and Agricultural Biotechnology, 2, 32-37. 
http://dx.doi.org/10.1016/j.bcab.2012.08.006</mixed-citation></ref><ref id="scirp.51786-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Priji, P., Unni, K.N., Sajith, S., Binod, P. and Benjamin, S. (2014) Production, Optimization and Partial Purification of Lipase from Pseudomonas sp. Strain BUP6, a Novel Rumen Bacterium Characterized from Malabari Goat. Biotechnology and Applied Biochemistry. http://dx.doi.org/10.1002/bab.1237</mixed-citation></ref><ref id="scirp.51786-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Sharma, R., Soni, S.K., Vohra, R.M., Jolly, R.S., Gupta, L.K. and Gupta, J.K. (2002b) Production of Extracellular Alkaline Lipase from a Bacillus sp. RSJ1 and Its Application in Ester Hydrolysis. Indian Journal of Microbiology, 42, 49-54.</mixed-citation></ref><ref id="scirp.51786-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Schmidt-Dannert, C., Rua, M.L., Rua, M.L. and Schmid, R.D. (1997) Two Novel Lipases from the Thermophile Ba cillus thermocatenulatus: Screening, Purification, Cloning, Over Expression and Properties. Methods in Enzymology, 284, 194-219. http://dx.doi.org/10.1016/S0076-6879(97)84013-X</mixed-citation></ref><ref id="scirp.51786-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Pabai, F., Kermasha, S. and Morin, A. (1996) Use of Continuous Culture to Screen for Lipase-Producing Microorganisms and Interesterification of Butterfat by Lipase Isolates. Canadian Journal of Microbiology, 42, 446-452. 
http://dx.doi.org/10.1139/m96-061</mixed-citation></ref><ref id="scirp.51786-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Dong, H., Gao, S., Han, S. and Cao, S. (1999) Purification and Characterization of a Pseudomonas sp. Lipase and Its Properties in Non-Aqueous Media. Applied Microbiology and Biotechnology, 30, 251-256.</mixed-citation></ref><ref id="scirp.51786-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">Ramachandran, S.S., Singh, S.K., Larroche, C., Soccol, C.R. and Pandey, A. (2007) Oil Cakes and Their Biotechnological Applications—A Review. Bioresource Technology, 98, 2000-2009.&lt;br /&gt; 
http://dx.doi.org/10.1016/j.biortech.2006.08.002</mixed-citation></ref><ref id="scirp.51786-ref15"><label>15</label><mixed-citation publication-type="book" xlink:type="simple">Singhania, R.R., Soccol, C.R. and Pandey, A. (2008) Application of Tropical Agro-Industrial Residues as Substrate for Solid-State Fermentation Processes. In: Pandey, A., Soccol, C.R. and Larroche, C., Eds., Current Development in Solid- State Fermentation, Springer, New York, 412-442.</mixed-citation></ref><ref id="scirp.51786-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">D’Annibale, A., Sermanni, G.G., Federici, F. and Petruccioli, M. (2006) Olive-Oil Waste Waters: A Promising Substrate for Microbial Lipase Production. Bioresource Technology, 97, 1828-1833.&lt;br /&gt; 
http://dx.doi.org/10.1016/j.biortech.2005.09.001</mixed-citation></ref><ref id="scirp.51786-ref17"><label>17</label><mixed-citation publication-type="other" xlink:type="simple">Brozzoli, V., Crognale, S., Sampedro, I., Federici, F., D’Annibale, A. and Petruccioli, M. (2009) Assessment of Olive- Mill Wastewater as a Growth Medium for Lipase Production by Candida cylindracea in Bench-Top Reactor. Bioresource Technology, 100, 3395-3402. http://dx.doi.org/10.1016/j.biortech.2009.02.022</mixed-citation></ref><ref id="scirp.51786-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">Salihu, A., Alam, M.Z., AbdulKarim, M.I. and Salleh, H.M. (2011) Optimization of Lipase Production by Candida cylindracea in Palm Oil Mill Effluent Based Medium Using Statistical Experimental Design. Journal of Molecular Catalysis B: Enzymatic, 69, 66-73. http://dx.doi.org/10.1016/j.molcatb.2010.12.012</mixed-citation></ref><ref id="scirp.51786-ref19"><label>19</label><mixed-citation publication-type="other" xlink:type="simple">Vishnupriya, B., Sundaramoorthi, C., Kalaivani, M. and Selvam, K. (2010) Production of Lipase from Streptomyces griseus and Evaluation of Bioparameters. International Journal of ChemTech Research, 2, 1380-1383.</mixed-citation></ref></ref-list></back></article>