Title Science and Technology Indonesia e-ISSN:2580-4391 p-ISSN:2580-4405 Vol. 7, No. 2, April 2022 Research Paper Optimization of Liquid Smoke from Shorea pachyphylla using Response Surface Methodology and its Characterization Hasan Ashari Oramahi1, Kustiati2, Elvi Rusmiyanto Pancaning Wardoyo2* 1Faculty of Forestry, University of Tanjungpura, Pontianak, 78124, Indonesia2Faculty of Mathematics and Natural Science, University of Tanjungpura, Pontianak, 78124, Indonesia *Corresponding author: elvirusm1971@gmail.com/ elvi.rusmiyanto@fmipa.untan.ac.id AbstractThe present study aims to optimize the processing variables producing liquid smoke from mabang wood (Shorea pachyphylla) byusing Response Surface Methodology (RSM). In this investigation, a design of experiment with different combinations of pyrolysistemperature and pyrolysis time on the liquid smoke yield from mabang wood was applied. The response of the optimal yield,temperature, and time of pyrolysis was predicted using a mathematical model. The optimal operating conditions for the process ofyielding 31.31% liquid smoke were identified at the pyrolysis temperature of 440◦C and pyrolysis time of 124 minutes. The effect ofpyrolysis temperature was more significant than the pyrolysis time (p<0.05). The liquid smoke samples were evaluated by a GC-MS.The main chemical compound of the liquid smoke were 1,2-ethanediol (19.26%), fluoromethane (6.69%), formic acid (4.96%),2-propanone (4.17%), acetic acid (18.64%), acetol (4.80%), furfural (9.94%), 2,4-hexadecanoic acid (3.45%), and guaiacol (2.93%). KeywordsLiquid smoke, Optimization, Pyrolysis, Shorea pachyphylla, Temperature Received: 4 January 2022, Accepted: 14 April 2022 https://doi.org/10.26554/sti.2022.7.2.257-262 1. INTRODUCTION Liquid smoke is a liquid obtained from condensation of gases during the pyrolysis process of wood in the absence of oxy- gen (Lee et al., 2011; Grewal et al., 2018). Liquid smoke has been widely used for termicidal (Adfa et al., 2017), antifungal (Oramahi et al., 2018; Barbero-López et al., 2019), algacidal (Zheng et al., 2018), antimicrobial (Zhang et al., 2019), and insect repelling activity (Rahmat et al., 2014). The controlling of termites fungi using synthetic termicides or insecticides and synthetic fungicides are considered to have negative eect on human health and the environment (Preston, 2000; Manzoor et al., 2016; Bedmutha et al., 2011). Their continuous and ex- cessive use causes human health eectious and environmental pollution. The liquid smoke obtained from Azadirachta excelsa exhib- ited insecticidal activities against Plutella xylostella L. (Sapindal et al., 2018). Optimization of the yield production process in liquid smoke is needed so that it can be used as a biopes- ticide. Several researchers have noted the temperature and time of pyrolysis, as well as particle size of wood on the liquid smoke yield (Akhtar and Amin, 2012; Crespo et al., 2017; Hasan et al., 2017; Oramahi et al., 2020b), and liquid smoke chemical compound (Faisal et al., 2018; Oramahi and War- doyo, 2019). The temperature of pyrolysis is the main factors in the yield of liquid smoke (Akhtar and Amin, 2012). The yield of liquid smoke gained from Eucommia ulmoides Olivers branches was 23.26% at 300-330◦C as the optimal temperature (Hou et al., 2018). The highest phenol compound of liquid smoke was 2.0% at 300◦C of pyrolysis temperature, whereas, the highest acetic acid compound was 8% at 380◦C of pyrolysis temperature (Faisal et al., 2018). Fan et al. (2014) found the optimal liquid smoke yield was 43.62% at temperature of py- rolysis, heating rate, reactor pressure, and holding time were 495.5◦C, 19.4◦C, 5.0 kPa, and 50 min, respectively. The combination factors in pyrolysis process, as well as wood type, provide the maximum liquid smoke yield. The liq- uid smoke yield from Tithonia diversifolia maximum was found at temperature of 536.74◦C, ow rate of 129.55 mL/min, par- ticle size of 0.770 mm, and heating rate of 40 min (Bhuyan et al., 2020), meanwhile, the optimal liquid smoke yield at- tainedfrompalmtrunkwas42.05%at temperatureof456.11◦C (Oramahi et al., 2020b). Qu et al. (2011) stated that the yield of liquid smoke obtained from rice straw was 43%, whereas those from corn stalk and peanut vine were 51 and 48%, re- spectively. The Response Surface Methodology (RSM), a response https://crossmark.crossref.org/dialog/?doi=10.26554/sti.2022.7.2.257-262&domain=pdf https://doi.org/10.26554/sti.2022.7.2.257-262 Oramahi et. al. Science and Technology Indonesia, 7 (2022) 257-262 optimization technique with several variabels (Montgomery, 2017), has been used successfully to optimize pyrolysis process of liquid smoke or bio oil for Pearl Millet and Sida cordifolia L. (Laougé et al., 2020), oil palm trunk (Oramahi et al., 2020a), Indonesia ‘bengkirai’ wood (Shorea laevis Ridl) (Oramahi et al., 2020a), risk husk (Lazzari et al., 2019), and mixtures of waste (Pinto et al., 2013). Optimization of corncob hydrothermal conversion for yield of liquid smoke was studied by Gan and Yuan(2013),whofoundtheoptimumconditionoperatingwere gained at temperature, retention time, biomass solid content, and catalyst loadings were 280◦C, 12 min, 21%, and 1.03%, respectively. A previous study stated that particle size of wood, temperature, and time pyrolysis aect the yield of liquid smoke of ‘bengkirai’ wood from Indonesia (Oramahi et al., 2020b). Currently, there is no research on the optimization of liq- uid smoke yields from mabang wood (Shorea pachyphylla). In Indonesian mabang wood has been used as a resources in furni- ture. It produces an enormous waste sawdust. Therefore, this research intends to predict optimal liquid smoke yield obtained from mabang wood using the RSM and element analyses of the liquidsmokesamplegainedat theoptimumpyrolysisoperation condition were evaluated by Gas Chromatografy Mass Spec- trometry (GC-MS) to identied the component of mabang liquid smoke. 2. EXPERIMENTAL SECTION 2.1 Materials Mabang wood used in the study was collected from a sawmill at Pontianak. Production of liquid smoke was accomplished accordingtoTranggonoetal. (1996),DarmadjiandTriyudiana (2006), and Oramahi et al. (2018). 2.2 Experimental Design Based on the literature (Akhtar and Amin, 2012; Crespo et al., 2017) and our previous study (Oramahi et al., 2020b), two critical parameters namely, pyrolysis temperature (X1), and pyrolysis time (X2) was acknowledged as signicant factors that may impact the yield of liquid smoke by pyrolysis. An RSM was used in order to optimize liquid smoke yield from mabang wood. Based on RSM design, two-factor, three coded level, and the code level of temperature 400, 425, and 450◦C and time 105, 120, and 135 minutes are demonstrated in Table 1. Table 1. Range and Level of Independent Variables Variables Symbol coded Range and levels -1 0 1 Temperature of pyrolysis (◦C) X1 400 425 450 Times of pyrolysis (min) X2 105 120 135 The second-order polynomial equation and all interaction terms can be written as follows: Y = 𝛽0 + k∑︁ i=1 𝛽ixi + k∑︁ i=1 𝛽iix 2 i + ∑︁ i ∑︁ j 𝛽i jxixj + Y (1) where 𝛽0 is the constant regression coecients, whereas 𝛽i, 𝛽ii, 𝛽i j are the coecients of linear, quadratic, as well as eects of interaction, whereas xi, xj are the coded independent variables, and Y is the error. 2.3 RSM and Statistical Analysis All data acquired were analyzed using software package STA- TISTICAversion6.0 (StatSoft Inc.) andsoftwareSASversion 8.2 (SAS Institute Inc.). The regression analysis was accom- plish by STATISTICA and SAS. The signicance of each term was set on F-test with p-value less than 0.05 (p≤0.05). 2.4 Chemical Composition Characterization of Liquid Smoke The GC-MS identied of the liquid smoke chemical compo- nent was carried out on Shimadzu (QP-210S). The conditions GC–MS assay were (a) capillary columns was DB-624, 30 mx 0.25 mm; (b) the injection temperature was 250◦C, (c) col- umn temperature program was 60-200◦C. Helium was used as carier gas with ow rate of 40.0 mL/min. Briey, the injection volume of sample was 1 mL. The temperature maintained at 60-200◦C. The chemical component was analysis by com- paring with data from standard library (Mun and Ku, 2010; Oramahi et al., 2018) and calculated by the integrated peak areas. 3. RESULTS AND DISCUSSION 3.1 Optimum Operating Conditions to Achieve Maximum Liquid Smoke Yield A total of 12 experimental and the combination of indepen- dent variable are chosen to maximize the liquid smoke yield (Table 2). All data were analyzed using multiple regression to express the model, following the quadratic polynomial equa- tion. The model taken is created on the recommendations agreed by RSM. Interaction relationships of operating process on liquid smoke yield (Table 3). The indicated that temper- ature of pyrolysis contributed signicantly eect on mabang liquid smoke yield, while the eect on X2 variable was not sig- nicant. Oramahi and Rusmiyanto (2021) have investigated that temperature is the most important factor eecting liquid smoke yield. Similar result was reported by Islam et al. (2005). They satated that the dierence in the percentage of liquid smoke yield is predisposed by the pyrolysis temperature. The results of the pyrolysis of liquid smoke at low temperatures are less than at high temperatures because at low temperatures the combustion of wood is not enough, therefore yielding less liquid smoke product. The maximum liquid smoke yield of 31.31% for mabang wood were obtained at the optimal temperature of 440◦C and © 2022 The Authors. Page 258 of 262 Oramahi et. al. Science and Technology Indonesia, 7 (2022) 257-262 Table 2. RSM Design for Liquid Smoke Yield Obtained from Mabang Wood Run Coded variable level The yield of liquid smoke from mabang wood (%) X1 X2 Experimental Predicted 1 -1 -1 23.50 24.63 2 1 -1 31.50 30.71 3 -1 1 27.00 28.83 4 1 1 31.50 30.63 5 -1 0 29.00 26.83 6 1 0 29.50 31.17 7 0 -1 29.50 29.17 8 0 1 31.00 30.83 9 0 0 33.00 30.50 10 0 0 30.00 30.50 11 0 0 30.00 30.50 12 0 0 28.50 30.50 Table 3. Resulths of Variance Analysis and Regression Coe- cients for The Mabang Liquid Smoke Yield Variation sources Polynomial coecient Error t-value Pr>t Intercept 30.50 0.88 34.81 <0.000 X1 2.17 0.78 2.77 0.033 X2 0.83 0.78 1.06 0.329 X1*X1 -1.50 1.17 -1.28 0.249 X2*X1 -0.88 0.96 -0.91 0.397 X2*X2 -0.50 1.17 -0.43 0.685 Coecient of variation= 6.51%, R2= 0.67 time of 124 minute. The reported maximum liquid smoke of Similar result was reported by Oramahi et al. (2020b) with the maximum liquid smoke of 30.31% from pyrolysis Shorea laevis Ridl at the particle size of wood and and temperature pyrolysis were 3.85 mm and 400◦C, respectively. A three-dimensional Response Surface Methodology plot of liquid smoke from mabang versus pyrolysis temperature and pyrolysis time is given in Figure 1. The association between variables and responses was illustrated in the response surface representation (3D) and the contour plots (2D) generated by the model for the yield of mabang liquid smoke. An empirical model for the results of mabang liquid smoke was gained as trails and the 3D response surface curve and contour plots (2D) is given in Figure 1. The yield of mabang liquid smoke equation consists of a term of second-order, is represented as Equation (2). Y =30.50 + 2.17X1 + 0.83X2 − 1.50X12− 0.88X1.X2 − 0.50X22 (2) Figure 1. Contour (a) and Response Surface Plot (b) of Mabang Liquid Smoke Yield for Pyrolysis Temperature (X1) and Pyrolysis Time (X2) Where, Y is the estimated mabang liquid smoke yield, X1 is pyrolysis temperature, whereas, X2 is pyrolysis time. The regression analysis was obtained from the Equation 2, where the yield of liquid smoke is illustrated as a function of temperature and time of pyrolisis. It reected the accu- racy of the model can be assessed by R2. The R2 for mabang liquid smoke is 0.67 this shows that 67.00% of the total vari- ation in the results of mabang liquid smoke comes from the experimental variables studied (Table 3). Li et al. (2017) show that the experimental values were predicted by a second-order polynomial model. As already mentioned, the linear pyrolysis temperature (X1) had a signicance (p<0.05), which indicates that the temperature of the pyrolysis variable (X1) is the most signicant factor in the liquid smoke yield (p<0.05). 3.2 The Chemical Compound of Liquid Smoke from Ma- bang Wood Identication of compounds in selected of liquid smoke op- timal yield for optimal pyrolysis temperature and pyrolysis time was accomplished by GC-MS. The composition of liquid smoke from mabang wood at optimal temperature (400◦C) and the main compounds of liquid smoke identied were 1,2- ethanediol (19.26%), uoromethane (6.69%), formic acid (4.96 %), 2-propanone (4.17%), acetic acid (18.64%), acetol (4.80%), furfural (9.94%), 2,4-hexadecanoic acid (3.45%), and guaiacol (2.93%). Similarly, Suresh et al. (2019) main identied sub- stances in the liquid smoke obtained from softwood mixture was 40-45% such as phenols, aldehyde, and organic acid. They reported that the liquid smoke showed the strongest antifun- gal activity against Trametes versicolor. Souza et al. (2012) re- ported that main compounds observed of the two liquid smoke obtained from Eucalyptus sp. and commercial folier fertilizer company were formic acid (4.96%), acetic acid (18.64%), and © 2022 The Authors. Page 259 of 262 Oramahi et. al. Science and Technology Indonesia, 7 (2022) 257-262 Table 4. Phytochemical Compound of Mabang Liquid Smoke Identied by GC-MS Analysis at The Condition of Optimum Temperature Pyrolysis RT Phytochemical compound Area (%) 2.130 Carbamimidic acid 0.13 2.464 Acetaldehyde 1.18 2.526 1,2-Ethanediol 19.26 2.600 Fluoromethane 6.69 2.690 Formic acid 4.96 3.474 Propionaldehyde 0.28 3.551 2-Propanone 4.17 3.708 Methyl ketone 0.26 3.881 Methyl acetate 1.46 5.567 2,3-Butanedione 1.38 5.796 2-Butanone 0.68 6.100 Formic acid 0.24 6.289 Furan 0.41 7.737 Acetic acid 18.64 9.472 Acetol 4.80 11.846 Propanoic acid 1.84 14.212 1-Hydroxy-2-butanone 1.62 15.433 Propylene oxide 0.76 15.925 Butanoic acid 0.24 16.843 2-Furanmethanol 1.48 17.142 Furfural 9.94 18.828 Furfuryl alcohol 0.84 19.307 2-Butanone 1.05 20.532 2-Cyclopenten-1-one 0.54 20.947 Ethanone 0.33 23.543 Ethenyl ester 1.63 23.651 2,3-Pentanedione 0.98 23.781 5-Methylfurfural 2.35 26.866 2,4-Hexadienoic acid 3.45 29.382 Guaiacol 2.93 33.711 2-Methoxy-4-methyl-phenol 1.97 37.083 4-Ethyl-2-methoxy-phenol 0.51 40.277 2,6-Dimethoxy-phenol 1.86 44.153 1,2,4-Trimethoxybenzene 1.10 2,4-hexadienoic acid (3.45%), meanwhile, the phenols com- pound were guaiacol (2.93%), 2-methoxy-2-methyl phenol (1.97%), and 1,2,4-trimethoxy benzene (1.10%). The chemical composition of liquid smoke from almond shell including phenols and their derivatives (30.13%), organic acids (40.89%), furan derivative (7.43%), and ketone group (15.85%). The abundant compound of organic acid was acetic acid (32.18%), whereas the phenols compound was phenol (5.54%) (Li et al., 2017). Wang et al. (2018) reported that the main chemical component of liquid smoke prepared by hydrothermolysis of the cotton stalk were acids, phenols, ke- tone, and furan derivatives. Mungkunkamchao et al. (2013) investigated that liquid smoke from eucalyptus were acetic acid (30.39%), propanoic acid (6.08%), phenol (3.75%), 2-methoxy- phenol (12.31%), methyl-thiirane (26.96%), 2-furancarboalde- hyde (6.39%), and 2-methoxy-4-methyl phenol (6.27%). Liq- uid smoke obtained from coconut shell at nal pyrolysis tem- perature of 575◦C including phenolic, acid and ketone (Gao etal.,2016). Rabiuetal. (2019) characterized liquidsmokeob- tained from palm kernel shell were phenols, eldehydes, ketones, and esters. Liquid smoke of sawdust contains several main chemical compound including: palmitic acid (19,40%), dotria- contane (15,21%), benzenesulfonic acid, 4-hydroxy (10,69%), acetic acid (9,81%), and 1,2-dihydroxyoctadecane (7,96%). Lu et al. (2019) reported that main compound of liquid smoke obtained from Cunninghamia lanceolate waste were acids, phe- nols, alcohols, kenones, and esters. GC-MS analysis of the optimized liquid smoke from cotton stalk designated the oc- currence of main chemical compounds such as acids, phenols, benzamide, and aromatic compounds (Li et al., 2017). Aguirre et al. (2020) investigated that the dominant component of liq- uid smoke obtained from forest pine were acetic acid (3.09%), 1-hydroxi-2-propanone (1.39%), hydroxiacetaldehyde (1.18%), furfural (0.31%), and levoglucosan (0.16%). The quantity dierence of chemical compound of liquid smoke due to the dierent types of raw materials for produce of liquid smoke, proximate anlysis such as cellulose, hemicel- lulose, lignin, temperature (Demiral and Ayan, 2011; Abnisa et al., 2013) and time pyrolysis (Oramahi et al., 2020b). How- ever, for sake of practicality, we concentrating on pyrolysis temperature and time pyrolysis in this study. 4. CONCLUSIONS The optimum liquid smoke yield study was conducted with dierent pyrolysis temperature and pyrolysis time using RSM. The predicted optimum pyrolysis condition was obtained at pyrolysis temperature of 440◦C and pyrolysis time of 124 min for maximum predicted liquid smoke yield of 31.31%. The abundant chemical compound of the liquid smoke was 1,2- ethanediol, uoromethane, formic acid, 2-propanone, acetic acid, acetol, furfural, 2,4-hexadecanoic acid, and guaiacol. The ongoing study and recent information on liquid smoke pro- posed noteworthy potential for production and application of liquid smoke in agriculture and forestry. 5. ACKNOWLEDGMENT The authors is very grateful acknowledge Directorate General of Higher Education of Indonesia through Research Grant (Fundamental Research) in 2019 and 2020. REFERENCES Abnisa, F., A. Arami-Niya, W. W. Daud, J. Sahu, and I. Noor (2013). Utilization of Oil Palm Tree Residues to Produce Bio-Oil and Bio-Char via Pyrolysis. Energy Conversion and Management, 76; 1073–1082 Adfa, M., A. J. Kusnanda, W. D. Saputra, C. Banon, M. Efdi, and M. Koketsu (2017). Termiticidal Activity of Toona sinen- © 2022 The Authors. Page 260 of 262 Oramahi et. al. Science and Technology Indonesia, 7 (2022) 257-262 sis Wood VinegarAgainst Coptotermes curvignathus Holmgren. Rasayan Journal of Chemistry, 10(4); 1088–1093 Aguirre, J. L., J. Baena, M. T. Martín, L. Nozal, S. González, J. L. Manjón, and M. Peinado (2020). Composition, Age- ing and Herbicidal Properties of Wood Vinegar Obtained through Fast Biomass Pyrolysis. Energies, 13(10); 2418 Akhtar, J. and N. S. Amin (2012). A Review on Operating Parameters for Optimum Liquid Oil Yield in Biomass Py- rolysis. Renewable and Sustainable Energy Reviews, 16(7); 5101–5109 Barbero-López, A., S. Chibily, L. Tomppo, A. Salami, F. J. Ancin-Murguzur, M. Venäläinen, R. Lappalainen, and A. Haapala (2019). Pyrolysis Distillates from Tree Bark and Fibre Hemp Inhibit The Growth of Wood-Decaying Fungi. Industrial Crops and Products, 129; 604–610 Bedmutha, R., C. J. Booker, L. Ferrante, C. Briens, F. Berruti, K. K.-C. Yeung, I. Scott, and K. Conn (2011). Insecticidal and Bactericidal Characteristics of The Bio-Oil from The Fast Pyrolysis of Coee Grounds. Journal of Analytical and Applied Pyrolysis, 90(2); 224–231 Bhuyan, N., R. Narzari, S. M. Bujar Baruah, and R. Kataki (2020). Comparative Assessment of Articial Neural Net- work and Response Surface Methodology for Evaluation of The Predictive Capability on Bio-Oil Yield of Tithonia diversifoliaPyrolysis. Biomass ConversionandBiorenery; 1–16 Crespo, Y. A., R. A. Naranjo, Y. G. Quitana, C. G. Sanchez, and E. M. S. Sanchez (2017). Optimisation and Characteri- sation of Bio-Oil Produced by Acacia mangium Willd Wood Pyrolysis. Wood Science and Technology, 51(5); 1155–1171 Darmadji, P. and H. Triyudiana (2006). Proses Pemurnian Asap Cairdan Simulasi Akumulasi KadarBenzopyrene Pada Proses Perendaman Ikan. Agritech, 26(2); 74–83 (in Indone- sia) Demiral, İ. and E. A. Ayan (2011). Pyrolysis of Grape Bagasse: Eect of Pyrolysis Conditions on The Product Yields and Characterization of The Liquid Product. Bioresource Tech- nology, 102(4); 3946–3951 Faisal, M., A. Yelvia Sunarti, and H. Desvita (2018). Char- acteristics of Liquid Smoke from The Pyrolysis of Durian Peel Waste at Moderate Temperatures. Rasayan Journal of Chemistry, 11(2); 871–876 Fan, Y., Y. Cai, X. Li, H. Yin, N. Yu, R. Zhang, and W. Zhao (2014). Rape Straw as a Source of Bio-Oil via Vacuum Pyrolysis: Optimization of Bio-Oil Yield using Orthogonal Design Method and Characterization of Bio-Oil. Journal of Analytical and Applied Pyrolysis, 106; 63–70 Gan, J. and W. Yuan (2013). Operating Condition Optimiza- tion of Corncob Hydrothermal Conversion for Bio-Oil Pro- duction. Applied Energy, 103; 350–357 Gao, Y., Y. Yang, Z. Qin, and Y. Sun (2016). Factors Aecting The Yield of Bio-Oil from The Pyrolysis of Coconut Shell. SpringerPlus, 5(1); 1–8 Grewal, A., L. Abbey, and L. R. Gunupuru (2018). Production, Prospects and Potential Application of Pyroligneous Acid in Agriculture. Journal of Analytical and Applied Pyrolysis, 135; 152–159 Hasan, M. M., X. S. Wang, D. Mourant, R. Gunawan, C. Yu, X. Hu, S. Kadarwati, M. Gholizadeh, H. Wu, and B. Li (2017). Grinding Pyrolysis of Mallee Wood: Eects of Pyrolysis Conditions on The Yields of Bio-Oil and Biochar. Fuel Processing Technology, 167; 215–220 Hou, X., L. Qiu, S. Luo, K. Kang, M. Zhu, and Y. Yao (2018). Chemical Constituents and Antimicrobial Activity of Wood Vinegars at Dierent Pyrolysis Temperature Ranges Ob- tained from Eucommia ulmoides Olivers Branches. RSC Ad- vances, 8(71); 40941–40949 Islam, M. N., M. R. A. Beg, and M. R. Islam (2005). Pyrolytic Oil from Fixed Bed Pyrolysis of Municipal Solid Waste and its Characterization. Renewable Energy, 30(3); 413–420 Laougé, Z. B., A. S. Çığgın, and H. Merdun (2020). Optimiza- tion and Characterization of Bio-Oil from Fast Pyrolysis of Pearl Millet and Sida cordifolia L. by using Response Surface Methodology. Fuel, 274; 117842 Lazzari, E., A. dos Santos Polidoro, B. Onorevoli, T. Schena, A. N. Silva, E. Scapin, R. A. Jacques, and E. B. Caramão (2019). Production of Rice Husk Bio-Oil and Compre- hensive Characterization (Qualitative and Quantitative) by HPLC/PDA and GC× GC/qMS. Renewable Energy, 135; 554–565 Lee, S., P. H’ng, A. Lee, A. Sajap, B. Tey, and U. Salmiah (2011). Production of Pyroligneous Acid from Lignocel- lulosic Biomass and their Eectiveness Against Biological Attacks. Journal of Applied Sciences, 10(20); 2440–2446 Li, X., B. Wang, S. Wu, X. Kong, Y. Fang, and J. Liu (2017). Optimizing The Conditions for The Microwave-Assisted Pyrolysis of Cotton Stalk for Bio-Oil Production using Re- sponse Surface Methodology. Waste and Biomass Valorization, 8(4); 1361–1369 Lu, X., J. Jiang, J. He, K. Sun, and Y. Sun (2019). Pyrolysis of Cunninghamia Lanceolata Waste to Produce Wood Vinegar and its Eect on The Seeds Germination and Root Growth of Wheat. BioResources, 14(4); 8002–8017 Manzoor, F., A. Zafar, and I. Iqbal (2016). Heterotermesindi- cola (Wasmann) (Isoptera: Rhinotermitidae) Responses to Extracts from Three Dierent Plants. Kuwait Journal of Science, 43(3); 128–134 Montgomery, D. C. (2017). Design and Analysis of Experiments. John Wiley & Sons Mun, S. P. and C. S. Ku (2010). Pyrolysis GC-MS Analysis of Tars Formed During The Aging of Wood and Bamboo Crude Vinegars. Journal of Wood Science, 56(1); 47–52 Mungkunkamchao, T., T. Kesmala, S. Pimratch, B. Toomsan, and D. Jothityangkoon (2013). Wood Vinegar and Fer- mented Bioextracts: Natural Products to Enhance Growth and Yield of Tomato (Solanum lycopersicum L.). Scientia Hor- ticulturae, 154; 66–72 Oramahi, H., F. Diba, and T. Yoshimura (2020a). Optimiza- tion of Production of Lignocellulosic Biomass Bio-Oil from Oil Palm Trunk. Procedia Environmental Sciences, 28; 769– 777 © 2022 The Authors. Page 261 of 262 Oramahi et. al. Science and Technology Indonesia, 7 (2022) 257-262 Oramahi, H. and E. Rusmiyanto (2021). Optimization of Wood Vinegar from Pyrolysis of Jelutung Wood (Dyera lowii Hook) by using Response Surface Methodology. In Journal of Physics: Conference Series, 1940; 012062 Oramahi, H. and E. R. P. Wardoyo (2019). Optimization of Pyrolysis Condition for Bioactive Compounds of Wood Vinegar from Oil Palm Empty Bunches using Response Sur- face Methodology (RSM). In IOP Conference Series: Materials Science and Engineering, 633; 012058 Oramahi, H. A., T. Yoshimura, F. Diba, and D. Setyawati (2018). Antifungal and Antitermitic Activities of Wood Vinegar from Oil Palm Trunk. JournalofWoodScience, 64(3); 311–317 Oramahi, H. A., T. Yoshimura, E. Rusmiyanto, and K. Kus- tiati (2020b). Optimization and Characterization of Wood Vinegar Produced by Shorea laevis Ridl Wood Pyrolysis. In- donesian Journal of Chemistry, 20(4); 825–832 Pinto, F., F. Paradela, I. Gulyurtlu, and A. M. Ramos (2013). Prediction of Liquid Yields from The Pyrolysis of Waste Mixtures using Response Surface Methodology. Fuel Pro- cessing Technology, 116; 271–283 Preston, A. (2000). Wood Preservation: Trends of Today that will Inuence The Industry Tomorrow. Forest Products Journal, 50(9); 12–19 Qu, T., W. Guo, L. Shen, J. Xiao, and K. Zhao (2011). Exper- imental Study of Biomass Pyrolysis Based on Three Major Components: Hemicellulose, Cellulose, and Lignin. Indus- trial&EngineeringChemistryResearch, 50(18); 10424–10433 Rabiu, Z., K. N. Mahmud, R. Hasham, and Z. A. Zakaria (2019). CharacterizationandAntioxidantPropertiesofEthyl Acetate Fractions from Pyroligneous Acid Obtained by Slow Pyrolysis of Palm Kernel Shell. Malaysian Journal of Funda- mental and Applied Sciences, 15(5); 645–650 Rahmat, B., D. Pangesti, D. Natawijaya, and D. Sufyadi (2014). Generation of Wood-Waste Vinegar and its Eectiveness as a Plant Growth Regulator and Pest Insect Repellent. BioRe- sources, 9(4); 6350–6360 Sapindal, E., K. H. Ong, and P. J. H. King (2018). Ecacy of Azadirachta excelsa Vinegar Against Plutella xylostella. Interna- tional Journal of Pest Management, 64(1); 39–44 Souza, J. B. G., N. Ré-Poppi, and J. L. Raposo Jr (2012). Characterization of Pyroligneous Acid used in Agriculture by Gas Chromatography-Mass Spectrometry. Journal of The Brazilian Chemical Society, 23(4); 610–617 Suresh, G., H. Pakdel, T. Rouissi, S. K. Brar, I. Fliss, and C. Roy(2019). In Vitro Evaluation of Antimicrobial Ecacy of Pyroligneous Acid from Softwood Mixture. Biotechnology Research and Innovation, 3(1); 47–53 Tranggono, Suhardi, B. Setiadji, P. Darmadji, Supranto, and Sudarmanto (1996). Identikasi Asap Cair dari Berbagai Jenis kayu dan Tempurung Kelapa. Jurnal Ilmu dan Teknologi Pangan, 1(2); 15–24 (in Indonesia) Wang, C., S. Zhang, S. Wu, Z. Cao, Y. Zhang, H. Li, F. Jiang, andJ.Lyu(2018). StudyonanAlternativeApproachforThe Preparation of Wood Vinegar from The Hydrothermolysis Process of Cotton Stalk. Bioresource Technology, 254; 231– 238 Zhang, F., J. Shao, H. Yang, D. Guo, Z. Chen, S. Zhang, and H. Chen (2019). Eects of Biomass Pyrolysis Derived Wood Vinegar on Microbial Activity and Communities of Activated Sludge. Bioresource Technology, 279; 252–261 Zheng, H., C. Sun, X. Hou, M. Wu, Y. Yao, and F. Li (2018). Pyrolysis of Arundo donax L. to Produce Pyrolytic Vinegar and its Eect on The Growth of Dinoagellate Karenia brevis. Bioresource Technology, 247; 273–281 © 2022 The Authors. Page 262 of 262 INTRODUCTION EXPERIMENTAL SECTION Materials Experimental Design RSM and Statistical Analysis Chemical Composition Characterization of Liquid Smoke RESULTS AND DISCUSSION Optimum Operating Conditions to Achieve Maximum Liquid Smoke Yield The Chemical Compound of Liquid Smoke from Mabang Wood CONCLUSIONS ACKNOWLEDGMENT