<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="other" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.145558.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Case Study</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>Prediction of Bioethanol from Production of Lignocellulosic Biomass Waste from Agriculture and Livestock Using Regression Analysis Model</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 not approved]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Ludfiani</surname>
                        <given-names>Dini Dwi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-0773-3237</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Arianti</surname>
                        <given-names>Forita Dyah</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Prabowo</surname>
                        <given-names>Agung</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Haryanto</surname>
                        <given-names>Bambang</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Megawati</surname>
                        <given-names>Megawati</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0001-9742-6216</uri>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sasongko</surname>
                        <given-names>Nugroho Adi</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Research Center for Sustainable Production Systems and Life Cycle Assessment, National Research and Innovation Agency Republic of Indonesia, South Tangerang, Banten, Indonesia</aff>
                <aff id="a2">
                    <label>2</label>Chemical Engineering, Faculty of Engineering, Universitas Negeri Semarang, Semarang, Central Java, Indonesia</aff>
                <aff id="a3">
                    <label>3</label>Energy Security Graduate Program, Republic of Indonesia Defense University (UNHAN RI), IPSC Sentul Area, West Java, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:fori001@brin.go.id">fori001@brin.go.id</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>19</day>
                <month>2</month>
                <year>2024</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2024</year>
            </pub-date>
            <volume>13</volume>
            <elocation-id>111</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>18</day>
                    <month>1</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Ludfiani DD et al.</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/13-111/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>Every year, the food supply must need to increase to accommodate population growth and food consumption increases. It causes the production of lignocellulosic biomass waste (LBW) in Indonesia from sector of agriculture and livestock also increase. Contrast to energy supply, energy demand increases but energy supply from fossil fuel become limit. More than 80% of LBW is dumped or burned, whereas the LBW has the potential as raw material of sustainable bioenergy, especially bioethanol to replace or mix with fossil fuel. This study aimed to predict the bioethanol production from potential of LBW to optimize its utilization. Potential of LBW production is estimated based on production of LBW lignocellulose component (cellulose, hemicellulose, and lignin). The novelty of this study is obtained predicted values for bioethanol production based on LBW production using a regression analysis model.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>The data of LBW production is calculated based on converting waste of the crops production (for agriculture sector) and animal unit (AU) (for livestock sector). The data of LBW consist of rice straw, corn stover, sugarcane bagasse, cassava peel, paunch content, and feces. This study use linear regression analysis model to predict bioethanol production from LBW.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>Estimation average LBW lignocellulose production in Indonesia is around 104.47 million tons, and can produce around 59.98 billion gallons (227.01 billion liters) of bioethanol. The regression model based on lignocellulose production (R
                        <sup>2</sup>) was 0.9925 (cellulose), 0.9848 (hemicellulose), and 0.9294 (lignin). Production of LBW in Indonesia is highest in Southeast Asia and has increased 2.07% per year because crops production, ruminant population, and ruminants slaughtered increase. This value will continue to increase, same with bioethanol production from LBW production.</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>Overall, Indonesia has potential to produce bioethanol from LBW. Using the entire the LBW for bioethanol make it possible to meet domestic energy demands in a sustainable.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Bioethanol</kwd>
                <kwd>biofuel</kwd>
                <kwd>biomass</kwd>
                <kwd>regression</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>Introduction</title>
            <p>Asia is the largest of the world&#x2019;s continents by both land area and population. Asia used about 54% of total land area for agriculture and Indonesia has an agricultural land of 62.30 million ha (
                <xref ref-type="bibr" rid="ref8">FAO, 2022</xref>). The primary crop in Asia is paddy (rice), because rice is a staple food. Secondary crops in Indonesia named palawija like as maize, cassava, and sorghum. Paddy is planted during the rainy season and palawija are planted during the dry season. Every year, the food consumption in Indonesia continuously increases, linear with population growth and economic development. Since 2020 until 2021, the crops production, ruminant population, and ruminant slaughtered increase of 1.38%. This increasing number shows that every year food supplies increase to meet food demand.</p>
            <p>The energy demand continuously increases, linear with increasing food demand. The type of the most consumed energy is fossil fuel, but the fossil fuel has an impact on environmental pollution (emission) and has a depletion issue. International Energy Agency (IEA) reported that energy demand is increase 5% and carbon emissions is increase 3.5% in 2022. United States Environmental Protection Agency (US EPA) reported that fossil fuel has contribute to greenhouse gas (CO
                <sub>2</sub>) emissions of 65%. Currently, alternative energy sources (bioenergy) are being explored and developed with the aim of reducing emissions and meet increasing energy demand.</p>
            <p>Continuously increasing of crops production, population of ruminants and ruminants slaughtered to meet food demand causes the lignocellulose biomass waste (LBW) production increase especially agricultural residue such as straw, peel, husk, etc., and livestock waste such as feces, and paunch content waste. The LBW has not been used optimally yet (
                <xref ref-type="bibr" rid="ref11">Fitri et al., 2020</xref>). Only 10-20% the LBW is used as fertilizer and feed, but 80-90% is disposed, burned, piled, or used as mulch for the following crop (
                <xref ref-type="bibr" rid="ref16">Hanafi et al., 2012</xref>; 
                <xref ref-type="bibr" rid="ref47">Vasi&#x0107; et al., 2021</xref>). Burning of LBW is low-cost method for disposal, but this method causes pollution, reduce air quality, and effect on health. The LBW has significant potential as raw material for biofuel or biomass energy (
                <xref ref-type="bibr" rid="ref1">Alrikabi, 2014</xref>). The advantages of LBW are inexpensive resource (
                <xref ref-type="bibr" rid="ref39">Rosado et al., 2022</xref>; 
                <xref ref-type="bibr" rid="ref51">Yang and Wyman, 2008</xref>), low value, renewable, rich in carbohydrate content (
                <xref ref-type="bibr" rid="ref4">Canilha et al., 2012</xref>), high sugar content (
                <xref ref-type="bibr" rid="ref38">Rijal, 2020</xref>), carbon-neutral nature (
                <xref ref-type="bibr" rid="ref48">Wang et al., 2021</xref>), abundant (
                <xref ref-type="bibr" rid="ref31">Novia et al., 2019</xref>) and eco-friendly (
                <xref ref-type="bibr" rid="ref23">Krishnan et al., 2020</xref>). Lignocellulose has the capacity to be converted into biofuels such as bioethanol (
                <xref ref-type="bibr" rid="ref5">Dahman et al., 2019</xref>). The advantage of biofuel is reduced greenhouse gas emission (
                <xref ref-type="bibr" rid="ref44">Sindhu et al., 2019</xref>).</p>
            <p>Biofuel derived from biomass has the potential to be a sustainable transportation fuel and can replace gasoline or fossil fuel (
                <xref ref-type="bibr" rid="ref21">Kim &amp; Dale, 2004</xref>). Biofuel is produced from different converting technologies (biological and physicochemical methods) (
                <xref ref-type="bibr" rid="ref2">Azeez &amp; Al-Zuhairi, 2020</xref>). Bioethanol (C
                <sub>2</sub>H
                <sub>5</sub>OH) is the one of biofuel which the promising biofuel to resolve energy crisis and can meet energy demand by full utilizing bioethanol as fuel (
                <xref ref-type="bibr" rid="ref49">Wang &amp; L&#x00fc;, 2021</xref>). Bioethanol has advantages based on characteristic such as eco-fuel, sustainable, and renewable (
                <xref ref-type="bibr" rid="ref15">Halder et al., 2018</xref>). Bioethanol as biofuel also plays an important role in reducing crude oil consumption and environmental pollution. Bioethanol is produced from carbohydrate substrate such as sugar, starch, lignocellulose, etc. through alcoholic fermentation process by microorganisms (
                <xref ref-type="bibr" rid="ref30">Mohd Azhar et al., 2017</xref>). Characteristic of bioethanol are a liquid, burn cleanly with a bluish flame color (
                <xref ref-type="bibr" rid="ref24">Log &amp; Moi, 2018</xref>). According to 
                <xref ref-type="bibr" rid="ref45">Tanwar et al. (2023)</xref> bioethanol has higher octane rating and heat evaporation than gasoline, and can reduce carbon monoxide gas emission up to 25%.</p>
            <p>The value of biomass conversion into biofuel can be determined through several experiments in the laboratory and in the field, but this process certainly takes time to get optimal results. In calculating the conversion of biomass into bioethanol are usually based on fermentation parameters such as volume of the starting culture and volume of the gas produced during fermentation; and carbohydrate value such as monosaccharides C5 and C6. The novelty of this study is the use of a regression analysis model to prediction of bioethanol production from LBW based on production of lignocellulose component (cellulose, hemicellulose, and lignin). The aim of this study is to predict the bioethanol, production from potential of LBW to optimize its utilization.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <sec id="sec7">
                <title>Data collection</title>
                <p>The data of crops production, ruminant population, and ruminant slaughtered in Indonesia are collected from FAO for prediction of LBW. The calculation of the number of LBW is carried out by considering the proportion of crops: LBW (for agriculture sector) (
                    <xref ref-type="bibr" rid="ref21">Kim &amp; Dale, 2004</xref>; 
                    <xref ref-type="bibr" rid="ref32">Ntelok, 2017</xref>) and based on animal unit (AU) (for livestock sector) (
                    <xref ref-type="bibr" rid="ref10">Felisberto et al., 2011</xref>). The values obtained are converted to the production of LBW lignocellulose component (cellulose, hemicellulose, and lignin). One AU equal to 1 cattle weight 450 kg.</p>
            </sec>
            <sec id="sec8">
                <title>Regression model</title>
                <p>This study use linear regression analysis model to predict bioethanol production. This model is used to predict bioethanol production from the annual amount of LBW based on production of lignocellulose component include cellulose, hemicellulose, and lignin. This approach is in line with 
                    <xref ref-type="bibr" rid="ref33">N&#x00fa;&#x00f1;ez et al. (2011)</xref> method, which prioritize the use of regression model to predict and effect estimation. The following equation describes the linear regression model:
                    <disp-formula id="e1">
                        <mml:math display="block">
                            <mml:mtext>Linear regression model</mml:mtext>
                            <mml:mo>&#x2192;</mml:mo>
                            <mml:mi mathvariant="normal">y</mml:mi>
                            <mml:mo>=</mml:mo>
                            <mml:mi mathvariant="normal">a</mml:mi>
                            <mml:mo>+</mml:mo>
                            <mml:mi mathvariant="normal">bx</mml:mi>
                            <mml:mo>+</mml:mo>
                            <mml:mi mathvariant="normal">&#x03b5;</mml:mi>
                        </mml:math>
                    </disp-formula>
                </p>
                <p>Where y is the dependent variable, x is the independent or explanatory variable, a is the intercept, b is the slope of the line, and &#x03b5; is error or residue.</p>
            </sec>
        </sec>
        <sec id="sec9" sec-type="results|discussion">
            <title>Results and Discussion</title>
            <sec id="sec10">
                <title>Potency of LBW production</title>
                <p>Every year, crops production, population of ruminant, and ruminant slaughtered in Indonesia increases. It is linear with increasing LBW production (
                    <xref ref-type="table" rid="T1">Table 1</xref>). Every year, the average crops production increase 1.99%, population of ruminant 2.85%, ruminant slaughtered 2.23%, and LBW production 2.07%. Indonesian crops consist of 2 types, primary crops (paddy) and secondary crops (maize, cassava, sorghum, and sugarcane). Sorghum is only grown in certain areas in Indonesia.</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>Table 1. </label>
                    <caption>
                        <title>Data of ruminant population, ruminant slaughtered, production of crops and LBW in 2020-2021 in Indonesia.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Materials</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">2020</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">2021</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="3" rowspan="1" valign="top">
                                    <italic toggle="yes">Crops production (million tons)</italic>
                                    <sup>
                                        <xref ref-type="table-fn" rid="tfn1">
                                            <bold>
                                                <italic toggle="yes">*</italic>
                                            </bold>
                                        </xref>
                                    </sup>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Rice</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">54.64</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">54.41</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Maize</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25.32</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20.66</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Sugarcane</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29.30</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">32.20</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Cassava</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18.30</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17.74</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">Total</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">127.56</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">125.01</italic>
                                    </bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="3" rowspan="1" valign="top">
                                    <italic toggle="yes">Population of ruminants (million heads)</italic>
                                    <sup>
                                        <xref ref-type="table-fn" rid="tfn1">
                                            <bold>
                                                <italic toggle="yes">*</italic>
                                            </bold>
                                        </xref>
                                    </sup>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Beef cattle</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17.44</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18.05</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Buffalo</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.18</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Goat</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18.68</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19.22</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Sheep</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17.52</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17.90</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">Total</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">54.79</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">56.35</italic>
                                    </bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="3" rowspan="1" valign="top">
                                    <italic toggle="yes">Ruminants slaughtered (thousand heads)</italic>
                                    <sup>
                                        <xref ref-type="table-fn" rid="tfn1">
                                            <bold>
                                                <italic toggle="yes">*</italic>
                                            </bold>
                                        </xref>
                                    </sup>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Beef cattle</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1007.59</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">972.85</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Buffalo</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">71.12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">80.51</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Goat</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7031.38</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7187.01</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Sheep</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5844.61</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6025.28</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">Total</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">13954.70</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">14265.65</italic>
                                    </bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="3" rowspan="1" valign="top">
                                    <italic toggle="yes">LBW production (million tons)</italic>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Rice straw
                                    <sup>1</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">76.51</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">76.18</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Corn stover
                                    <sup>2</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25.32</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20.66</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Cassava peel
                                    <sup>3</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.66</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.55</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Sugarcane bagasse
                                    <sup>4</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17.58</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19.32</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Paunch content
                                    <sup>5</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.86</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88.04</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Feces
                                    <sup>6</sup>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">273.27</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">282.23</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">Total</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">802.05</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">818.62</italic>
                                    </bold>
                                </td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <fn-group content-type="footnotes">
                            <fn id="tfn1">
                                <label>
                                    <italic toggle="yes">
                                        <sup>*</sup>
                                    </italic>
                                </label>
                                <p>Source: FAO; 
                                    <sup>1,2,4</sup>estimated LBW are 1.4 from rice production, 1.0 from maize (corn) production, 0.6 from sugarcane production (
                                    <xref ref-type="bibr" rid="ref21">Kim &amp; Dale, 2004</xref>); 
                                    <sup>3</sup>estimated LBW 20% from total cassava weight (
                                    <xref ref-type="bibr" rid="ref32">Ntelok, 2017</xref>); 
                                    <sup>5</sup>estimated LBW are 13% BW for buffalo and cattle; 8% BW for goat and sheep (
                                    <xref ref-type="bibr" rid="ref10">Felisberto et al., 2011</xref>); 
                                    <sup>6</sup>estimated LBW is 7% BW for 1 AU per year (365 day).</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
                <p>Indonesia has various types of ruminants, such as beef cattle, goat, sheep, and buffalo. Every day, ruminants are slaughtered in slaughterhouse (abattoir) to meet food demand (especially meat). One of the most common types of waste produced in large amount from slaughterhouses is paunch content waste. According to 
                    <xref ref-type="bibr" rid="ref34">Pancapalaga et al. (2021)</xref> the paunch content waste is incompletely digested of feed consumed and has still nutrient content that can be used by microbes in the gastrointestinal tract. During raising ruminants, they produce feces and urine every day while abattoir produce paunch content. According to 
                    <xref ref-type="bibr" rid="ref14">Gupta et al. (2016)</xref> ratio of feces and urine is 3:1. Feces and paunch content waste contain nutrients such as fiber or lignocellulose.</p>
                <p>Maize (corn) is composed of 38% grain, 7% cobs, 12% husks, 13% leaves, and 30% stalk (
                    <xref ref-type="bibr" rid="ref26">Ludfiani, 2016</xref>). So, the potency of LBW production from maize is around 62%. Compare to cassava, the LBW production from cassava is around 20% of the total cassava weight, specifically cassava peel (
                    <xref ref-type="bibr" rid="ref32">Ntelok, 2017</xref>). Indonesia also high LBW production in palm oil because palm oil production increase every year and it is potential to be used as biofuel (high potential for biodiesel). In this study is not discussed further about palm oil because in Southeast Asia has only Indonesia and Malaysia produce palm oil.</p>
                <p>BPS-Statistic Indonesia reported palm oil production is 44.75 million tons in 2020, 45.12 million tons in 2021, and 45.58 million tons in 2022. FAO reported that Indonesia is the top 1 producer of palm oil in the world and production in 2021 is around 44.75 million tons of palm oil, 10.17 million tons of palm kernel, 253.31 million tons oil of palm fruit, 4.44 million tons of oil of palm kernel. According to 
                    <xref ref-type="bibr" rid="ref27">Mahlia et al. (2019)</xref> palm oil tree biomass can be converted into biofuels and biopower. About 5% of the biodiesel produced from palm oil can be mixed with petroleum diesel as fuel (
                    <xref ref-type="bibr" rid="ref18">Hassan et al., 2011</xref>). Palm oil plantation residues and residues from the palm oil industry are quite high and also potential to be used fuel. Palm oil empty fruit brunch can produce one third of the power from a direct combustion compare to methane gas for electricity (
                    <xref ref-type="bibr" rid="ref20">Kaniapan et al., 2021</xref>).</p>
                <p>Based on the data in 
                    <xref ref-type="table" rid="T1">Table 1</xref>, the largest amount of LBW production is from livestock sector. Compare to LBW production in Southeast Asia, LBW production in Indonesia is in 1
                    <sup>st</sup> position in Southeast Asia from sector of agricultural and livestock (
                    <xref ref-type="fig" rid="f1">Figure 1</xref>). FAO reported that Indonesia is in 3
                    <sup>rd</sup> position in the world (after China and India) for rice production, and it is in 8
                    <sup>th</sup> position in the world for maize and sugar cane production. This indicates that Indonesia has great potential in producing abundant LBW, and has potential to be used as biofuel such as bioethanol.</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>Figure 1. </label>
                    <caption>
                        <title>The LBW production of countries in Southeast Asia in 2021.</title>
                        <p>(A) Production of LBW from agricultural crops; (B) production of LBW from livestock sector.</p>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/159526/01a75bc6-c450-43f5-bf1a-720fab8bfed6_figure1.gif"/>
                </fig>
                <p>The LBW from agriculture (agricultural residue) and livestock (feces and paunch content) contain nutrients that can be utilized into value-added products. The LBW contain high fiber (80 to 95%) (
                    <xref ref-type="bibr" rid="ref43">Shrotri et al., 2017</xref>). The main components of fiber or lignocellulose of LBW are cellulose, hemicellulose, and lignin. The fiber value of LBW depend on management factor and the part of plant. According to 
                    <xref ref-type="bibr" rid="ref13">Gummert et al. (2019)</xref> variations in fiber content of biomass depend on various factors such as the type or part of the plant, species, type of tissue, growth stage, and growth condition.</p>
                <p>
                    <xref ref-type="table" rid="T2">Table 2</xref> show the potency of LBW production from sector of agriculture and livestock based on lignocellulose component. The average of LBW lignocellulose contents from various types of LBW such as rice straw, corn stover, sugarcane, bagasse, cassava peel, paunch content, and feces are 29.36% of cellulose, 23.76% of hemicellulose, and 16.17% of lignin. Based on these contents, production lignocellulose of LBW can reach 136.99 million tons of cellulose, 112.33 million tons of hemicellulose, and 64.09 million tons of lignin. Feces and rice straw produce higher amount of LBW than other.</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>Table 2. </label>
                    <caption>
                        <title>Lignocellulose content and production of lignocellulose LBW.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="2" valign="top">Type of LBW</th>
                                <th align="left" colspan="3" rowspan="1" valign="top">Lignocellulose composition</th>
                                <th align="left" colspan="1" rowspan="2" valign="top">References</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Cellulose</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Hemicellulose</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Lignin</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="5" rowspan="1" valign="top">
                                    <italic toggle="yes">Lignocellulose content (%)</italic>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Rice straw</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">39.20</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23.50</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">36.10</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <xref ref-type="bibr" rid="ref6">El-Tayeb et al., 2012</xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Corn stover</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">41.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">28.50</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">16.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <xref ref-type="bibr" rid="ref43">Shrotri et al., 2017</xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Sugarcane bagasse</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">45.52</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">29.79</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">21.07</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <xref ref-type="bibr" rid="ref52">Zeinaly et al., 2017</xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Cassava peel</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">11.37</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">NA</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">13.67</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <xref ref-type="bibr" rid="ref50">Williams et al., 2023</xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Paunch content of cattle</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">22.50</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">33.80</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">3.30</td>
                                <td align="left" colspan="1" rowspan="3" valign="middle">
                                    <xref ref-type="bibr" rid="ref7">Elfaki &amp; Abdelatti, 2015</xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Paunch content of goat</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23.50</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">10.80</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">18.30</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Paunch content of sheep</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">19.70</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">16.60</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">15.70</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Feces of buffalo</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">31.19</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">21.03</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">11.97</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <xref ref-type="bibr" rid="ref9">Fasake &amp; Dashora, 2020</xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Feces of cattle</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">30.30</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">26.10</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">9.40</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <xref ref-type="bibr" rid="ref25">Lucas et al., 1975</xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="5" rowspan="1" valign="middle">
                                    <italic toggle="yes">Lignocellulose production (juta ton)</italic>
                                    <xref ref-type="table-fn" rid="tfn2">
                                        <italic toggle="yes">
                                            <sup>*</sup>
                                        </italic>
                                    </xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Rice straw</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">25.68</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">15.40</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">23.65</td>
                                <td align="left" colspan="1" rowspan="7" valign="middle">Data of production in 2021</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Corn stover</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">7.28</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">5.06</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.84</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Sugarcane bagasse</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.37</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.24</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">0.17</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Cassava peel</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">2.44</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">4.71</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">1.92</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Paunch content</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">20.72</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">17.58</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">10.54</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Feces</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">80.49</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">69.33</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">24.94</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>Total</bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>136.99</bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>112.33</bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">
                                    <bold>64.09</bold>
                                </td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>NA (not available).</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn2">
                                <label>
                                    <sup>*</sup>
                                </label>
                                <p>Estimated calculation based on lignocellulose content.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
                <p>Cellulose is the largest fraction in LBW. According to 
                    <xref ref-type="bibr" rid="ref47">Vasi&#x0107; et al. (2021)</xref> forages and agricultural waste contain lignin around 10-30%. Compare to palm oil tree residue, this value is lower. Palm oil tree residue such as palm oil frond, palm oil empty fruit bunch, and palm oil trunk have chemical composition arranged 34.40-40.70% cellulose, 26.10-31.80% hemicellulose, and 12.45-26.20% lignin (
                    <xref ref-type="bibr" rid="ref20">Kaniapan et al., 2021</xref>).</p>
                <p>Cellulose and hemicellulose are carbohydrate which is the main feedstock for producing energy (
                    <xref ref-type="bibr" rid="ref21">Kim &amp; Dale, 2004</xref>; 
                    <xref ref-type="bibr" rid="ref52">Zeinaly et al., 2017</xref>). Both of them are unavailable carbohydrate (
                    <xref ref-type="bibr" rid="ref36">Paxton, 2020</xref>). The LBW contain carbohydrate structure which can be used as an energy source (
                    <xref ref-type="bibr" rid="ref52">Zeinaly et al., 2017</xref>). To optimize the pre-treatment process and expand the usability value of LBW, it is necessary to be evaluated through proximate analysis and energy content (
                    <xref ref-type="bibr" rid="ref20">Kaniapan et al., 2021</xref>). Cellulose can be synthesized by bacteria and fungi (
                    <xref ref-type="bibr" rid="ref47">Vasi&#x0107; et al., 2021</xref>), and hemicellulose is an important component and it used in biofuels and various bioproducts (
                    <xref ref-type="bibr" rid="ref19">Huang et al., 2021</xref>).</p>
                <p>Based on the data in 
                    <xref ref-type="table" rid="T2">Table 2</xref>, lignocellulose content of paunch content is in the middle value. The paunch content contains groups of microbes and lignocellulose derived from feed which are being degraded by rumen microbes and enzymes in the gastrointestinal tract during the digestion process. This is a factor that affect the chemical content of paunch content because the lignocellulose value is obtained not only from feed, but also from rumen microbes. According to 
                    <xref ref-type="bibr" rid="ref7">Elfaki &amp; Abdelatti (2015)</xref> and 
                    <xref ref-type="bibr" rid="ref42">Sarteshnizi et al. (2018)</xref> paunch content contain various components, such as saliva, anaerobic microbes (fungi, protozoa, and bacteria), nutrient content (cellulose, hemicellulose, protein, fat, carbohydrates, minerals, and vitamins), and enzymes. It also contain volatile fatty acids (VFAs) such as acetate, propionate, and butyrate (
                    <xref ref-type="bibr" rid="ref12">Gleason et al., 2022</xref>; 
                    <xref ref-type="bibr" rid="ref22">Koppolu &amp; Clements, 2004</xref>).</p>
                <p>According to 
                    <xref ref-type="bibr" rid="ref35">Partama (2019)</xref> ruminant can consume 3.21% of dry matter, and digestibility level of feed is a maximum of 70%. Feed of ruminant consist 60-70% of carbohydrates (cellulose, hemicellulose) and almost 50% of the lignocellulose component is digested by rumen microbes. According to 
                    <xref ref-type="bibr" rid="ref9">Fasake and Dashora (2020)</xref> around 10.86% undigested feed from ruminant feces. The average total digestibility nutrient of fiber from forage is 40-65% in ruminant, so the undigested nutrient will be excreted through the feces (
                    <xref ref-type="bibr" rid="ref17">Hartadi, 2019</xref>). Feces is the undigested residue of feed consumed and contain nutrients content, microbes, or enzyme (
                    <xref ref-type="bibr" rid="ref41">Santoso et al., 2015</xref>). Digestibility of buffalo is higher (2-3%) than cattle (
                    <xref ref-type="bibr" rid="ref37">Prihantoro et al., 2012</xref>).</p>
            </sec>
            <sec id="sec11">
                <title>Potency of bioethanol production by regression analysis model</title>
                <p>Bioethanol production can predict using linear regression model with production factor of lignocellulose LBW (
                    <xref ref-type="table" rid="T3">Table 3</xref>). The analysis result show the regression model based on production of cellulose show bioethanol production (R
                    <sup>2</sup>) of 0.9925, while based on hemicellulose production of 0.9848, and model based on lignin production of 0.9294. Regression analysis can estimate the correlation between the dependent variable and the independent variable. Linear regression is used to predict the linear correlation between predictors (
                    <xref ref-type="bibr" rid="ref28">Maulud &amp; Abdulazeez, 2020</xref>). Linear regression in this study to learn more the variables that affect bioethanol production.</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>Table 3. </label>
                    <caption>
                        <title>Regression models of bioethanol.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Regression model</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Equation</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">R
                                    <sup>2</sup>
                                </th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Based on cellulose</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">y = 1005.6x + 29.043</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.9925</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Based on hemicellulose</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">y = 957.16x + 211.16</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.9848</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Based on lignin</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">y = 6708.1x + 789.01</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.9294</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>Prediction of bioethanol production from lignocellulose LBW production show in 
                    <xref ref-type="table" rid="T4">Table 4</xref>. Average production of lignocellulose LBW in Indonesia in 2021 can reach 104.47 million tons and has potential to bioethanol produce of 59.98 billion gallons (227.01 billion liters). This value is quite high than bioethanol production from grain (1G bioethanol). United State produces 15.25 billion gallons of bioethanol from corn (
                    <xref ref-type="bibr" rid="ref29">Mohanty &amp; Swain, 2019</xref>). The major producer of bioethanol in the world is the United State (55%) and followed Brazil (27%) in 2021 (
                    <xref ref-type="bibr" rid="ref3">Broda et al., 2022</xref>). United State produces ethanol from corn (grain) and Brazil from sugarcane (
                    <xref ref-type="bibr" rid="ref21">Kim &amp; Dale, 2004</xref>). Bioethanol has the potential to become a prime candidate for gasoline substitution (
                    <xref ref-type="bibr" rid="ref15">Halder et al., 2018</xref>). This is because the energy content of bioethanol is higher than gasoline, and it can be blended with gasoline about 5-24% (
                    <xref ref-type="bibr" rid="ref40">S&#x00e1;nchez &amp; Cardona, 2008</xref>).</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>Table 4. </label>
                    <caption>
                        <title>Prediction of bioethanol production from LBW (million gallons US) based on lignocellulose production.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Type of LBW</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Ethanol from cellulose</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Ethanol from hemicellulose</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Ethanol from lignin</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Rice straw</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6815.48</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3949.16</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42124.50</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Corn stover</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1927.73</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1336.33</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5246.74</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Cassava peel</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91.07</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">117.11</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">513.35</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Sugarcane bagasse</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">641.23</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1246.97</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3609.57</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Paunch content</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5497.18</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4502.68</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18881.87</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Feces</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3959.21</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3308.21</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8417.81</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">Total</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">18931.91</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">14460.46</italic>
                                    </bold>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>
                                        <italic toggle="yes">78793.85</italic>
                                    </bold>
                                </td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
                <p>Based on 
                    <xref ref-type="fig" rid="f1">Figure 1</xref>, Indonesia, Thailand, and Viet Nam have high potential to LBW production. If we calculate the prediction of bioethanol production based on lignocellulose LBW production, Indonesia, Thailand, and Viet Nam have significant potential to produce quite high amount of bioethanol. Currently, Thailand has been producing bioethanol from corn (1G bioethanol) and it is around 1% (over 1,02 million liters) of worldwide bioethanol production. Indonesia has also produced bioethanol (from sugarcane) but in small quantities and has not been able to supply domestic demand yet. Ministry of Energy and Mineral Resources Indonesia reported that bioethanol production just reached 40 million liters, but bioethanol fuel demand in Indonesia reaches 696 million liters.</p>
                <p>Based on 
                    <xref ref-type="table" rid="T4">Table 4</xref>, the prediction of bioethanol production from lignocellulose LBW production can meet domestic bioethanol demand. This value is expected to continuously increase every year linear with food demand and LBW production. From the analysis result, the predictive value bioethanol production based on lignin production is predicted to reach the highest. It is suspected that the process of breaking down of lignin can contribute quite high fermented sugar than fermented sugar obtained from only breaking down of cellulose and hemicellulose. According to 
                    <xref ref-type="bibr" rid="ref53">Zhong et al. (2021)</xref> lignin is the main contributor to the structure of roughage, but lignin can be broken down or degrades by rumen fungi (
                    <xref ref-type="bibr" rid="ref46">Vahidi et al., 2021</xref>).</p>
            </sec>
        </sec>
        <sec id="sec12" sec-type="conclusion">
            <title>Conclusion</title>
            <p>Using the regression analysis model can predict bioethanol production from LBW based on the production of lignocellulose components (cellulose, hemicellulose, and lignin). Indonesia has the potential to bioethanol production from LBW from sector of agricultural and livestock with production of lignocellulose LBW can reach significant amount 136.99 million tons cellulose, 112.33 million tons hemicellulose, and 64.09 million tons lignin. The estimated average bioethanol production from lignocellulose LBW production can reach 59.98 billion gallons (227.01 billion liters). Using the entire the LBW for bioethanol, Indonesia has great potential to meet domestic energy demand.</p>
        </sec>
        <sec id="sec13">
            <title>Authorship contribution statement</title>
            <p>
                <bold>Dini Dwi Ludfiani:</bold> Conceptualization, Methodology, Formal analysis, Resoures, Writing-original draft, Visualization.</p>
            <p>
                <bold>Forita Dyah Arianti:</bold> Conceptualization, Methodology, Resoures, Writing-original draft, Writing-review &amp; editing, Supervision.</p>
            <p>
                <bold>Agung Prabowo:</bold> Conceptualization, Methodology, Formal analysis, Visualization, Writing-review &amp; editing.</p>
            <p>
                <bold>Bambang Haryanto:</bold> Conceptualization, Methodology, Writing-review &amp; editing, Resouces.</p>
            <p>
                <bold>Megawati Megawati:</bold> Formal analysis, Visualization, Writing-original draft, Writing-review &amp; editing.</p>
            <p>
                <bold>Nugroho Adi Sasongko:</bold> Resouces, Visualization, Writing-original draft, Writing-review &amp; editing.</p>
        </sec>
    </body>
    <back>
        <sec id="sec16" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec17">
                <title>Underlying data</title>
                <p>Figshare: Prediction of Bioethanol from Production of Lignocellulosic Biomass Waste from Agriculture and Livestock Using Regression Analysis Model, 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5281/zenodo.10212631">https://doi.org/10.5281/zenodo.10212631</ext-link>.</p>
                <p>This project contains the following underlying data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>Calculated.xlsx</p>
                        </list-item>
                    </list>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0)</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgments</title>
            <p>This study was supported by the Postdoctoral Program at National Research and Innovation Agency (BRIN) Indonesia (2023-2024).</p>
        </ack>
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    <sub-article article-type="reviewer-report" id="report251956">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.159526.r251956</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Salierno</surname>
                        <given-names>Gabriel</given-names>
                    </name>
                    <xref ref-type="aff" rid="r251956a1">1</xref>
                    <role>Referee</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-2903-0575</uri>
                </contrib>
                <aff id="r251956a1">
                    <label>1</label>Universidad de Buenos Aires, Buenos Aires, Autonomous City of Buenos Aires, Argentina</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>18</day>
                <month>3</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Salierno G</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport251956" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.145558.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>reject</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>The authors suggest that Indonesia possesses remarkable potential for bioethanol production by utilizing LBW. This approach offers a sustainable solution to address the nation's energy needs while reducing dependence on fossil fuels and their associated environmental consequences.</p>
            <p> </p>
            <p> While the study presents promising findings regarding the abundance of lignocellulosic biomass waste (LBW) and its estimated bioethanol yield, crucial aspects of the employed model warrant further clarification.</p>
            <p> </p>
            <p> Firstly, the utilized model lacks transparency. The authors fail to provide a clear definition of the output variables, hindering a comprehensive understanding of the model's function. Additionally, the absence of interpretation for the model parameters limits the reader's grasp of their influence on the predicted bioethanol yield.</p>
            <p> </p>
            <p> Secondly, the sole presentation of the R-squared value (coefficient of determination) is insufficient. While it indicates a good fit between the model and the data, a more thorough analysis encompassing the interpretation of the model's coefficients and their significance levels is necessary.</p>
            <p> </p>
            <p> Furthermore, the terminology employed requires refinement. The phrase "Potency of LBW production" seems imprecise. A more accurate term would be "Potential of LBW production," signifying the inherent capability of LBW to be converted into bioethanol.</p>
            <p> </p>
            <p> While the research holds promise, it suffers from a lack of clarity in several crucial aspects.</p>
            <p> 
                <bold>Model Opacity:</bold> A significant concern lies in the obscurity surrounding the employed model. The authors fail to provide a clear definition or detailed explanation of the model, hindering a comprehensive understanding of its function and underlying assumptions.</p>
            <p> 
                <bold>Uncertain Output Variables:</bold> Furthermore, the research neglects to define how bioethanol production is calculated. This ambiguity raises questions about the data's validity. It remains unclear whether the provided data, presumably from the Food and Agriculture Organization (FAO), has actually undergone any conversion process to yield bioethanol.</p>
            <p> 
                <bold>Missing Process Information:</bold> A critical shortcoming lies in the complete absence of information regarding the conversion process itself. The research fails to mention crucial details such as whether separate steps for saccharification and fermentation are employed, or if a combined approach is utilized.</p>
            <p> 
                <bold>Limited Model Interpretation:</bold> The analysis solely reports the R-squared value, which signifies the model's goodness-of-fit. However, it disregards the interpretation of the model's parameters, which are essential for understanding the influence of individual variables on bioethanol production.</p>
            <p> 
                <bold>Language Considerations:</bold> The manuscript requires thorough language polishing to enhance clarity and conciseness. Several instances require correction: 
                <list list-type="bullet">
                    <list-item>
                        <p>"Potency of LBW production" should be replaced with "Potential of LBW production".</p>
                    </list-item>
                    <list-item>
                        <p>"Bioethanol production can predict using linear regression model with production factor of lignocellulose LBW" can be rephrased as "A linear regression model can be used to predict bioethanol production based on the lignocellulose content of LBW".</p>
                    </list-item>
                    <list-item>
                        <p>"Prediction of bioethanol production from lignocellulose LBW production show in Table 4" can be improved as "Table 4 presents the predicted bioethanol production based on the lignocellulose content of LBW".</p>
                    </list-item>
                    <list-item>
                        <p>"Linear regression in this study to learn more the variables that affect bioethanol production" should be revised to "This study employs linear regression to identify factors influencing bioethanol production".</p>
                    </list-item>
                </list> 
                <bold>Recommendations for Improvement:</bold>
            </p>
            <p> To strengthen the research, the authors should provide: 
                <list list-type="bullet">
                    <list-item>
                        <p>A clear description of the utilized model, including its purpose and underlying assumptions.</p>
                    </list-item>
                    <list-item>
                        <p>A definition of the bioethanol production calculation method and clarification regarding the conversion process of the FAO data (if any).</p>
                    </list-item>
                    <list-item>
                        <p>Detailed information about the conversion process, specifying whether separate or combined saccharification and fermentation steps are involved.</p>
                    </list-item>
                    <list-item>
                        <p>An in-depth interpretation of the model parameters beyond just the R-squared value.</p>
                    </list-item>
                    <list-item>
                        <p>Addressing the identified grammatical errors and awkward phrasing throughout the manuscript.</p>
                    </list-item>
                </list> By incorporating these recommendations, the research can achieve greater clarity, address the identified limitations, and contribute more effectively to the field of bioethanol production from LBW.</p>
            <p>Is the case presented with sufficient detail to be useful for teaching or other practitioners?</p>
            <p>No</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Partly</p>
            <p>Is the background of the case&#x2019;s history and progression described in sufficient detail?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>Clean energy technology</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.</p>
        </body>
        <sub-article article-type="response" id="comment11374-251956">
            <front-stub>
                <contrib-group>
                    <contrib contrib-type="author">
                        <name>
                            <surname>ludfiani</surname>
                            <given-names>dini dwi</given-names>
                        </name>
                    </contrib>
                </contrib-group>
                <author-notes>
                    <fn fn-type="conflict">
                        <p>
                            <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                    </fn>
                </author-notes>
                <pub-date pub-type="epub">
                    <day>4</day>
                    <month>4</month>
                    <year>2024</year>
                </pub-date>
            </front-stub>
            <body>
                <p>
                    <bold>Recommendations for Improvement from reviewer:</bold> 
                    <list list-type="bullet">
                        <list-item>
                            <p>A clear description of the utilized model, including its purpose and underlying assumptions</p>
                        </list-item>
                    </list> 
                    <bold>Response: </bold>We have done this. 
                    <list list-type="bullet">
                        <list-item>
                            <p>A definition of the bioethanol production calculation method and clarification regarding the conversion process of the FAO data (if any).</p>
                        </list-item>
                    </list> 
                    <bold>Response: </bold>Bioethanol production calculations are obtained based on FAO data conversion. The calculations have been described below in Table 1. Raw data can be seen in "data availability". 
                    <list list-type="bullet">
                        <list-item>
                            <p>Detailed information about the conversion process, specifying whether separate or combined saccharification and fermentation steps are involved.</p>
                        </list-item>
                    </list> 
                    <bold>Response: </bold>The conversion process is enzymatic saccharification, and already described in the manuscript. 
                    <list list-type="bullet">
                        <list-item>
                            <p>An in-depth interpretation of the model parameters beyond just the R-squared value.</p>
                        </list-item>
                    </list> 
                    <bold>Response: </bold>Interpretation of the model parameter&#x00a0;has been explained in the results and discussion section. 
                    <list list-type="bullet">
                        <list-item>
                            <p>Addressing the identified grammatical errors and awkward phrasing throughout the manuscript.</p>
                        </list-item>
                    </list> 
                    <bold>Response: </bold>We have done this</p>
            </body>
        </sub-article>
    </sub-article>
</article>
