Fernando Damián Barajas Godoy, Marco A Martínez-Cinco, José G Rutiaga-Quiñones, Otoniel Buenrostro-Delgado, Jose Mendoza
{"title":"The significance of biowaste drying analysis as a key pre-treatment for transforming it into a sustainable biomass feedstock.","authors":"Fernando Damián Barajas Godoy, Marco A Martínez-Cinco, José G Rutiaga-Quiñones, Otoniel Buenrostro-Delgado, Jose Mendoza","doi":"10.7717/peerj.18248","DOIUrl":null,"url":null,"abstract":"<p><p>The objective of this study is to investigate the drying kinetics of fruit and vegetable peel biowaste using a sustainable technique as a key-pretreatment for its conversion into useful feedstock. Biowaste represents a missed potential source of bioenergy and bioproducts, but moisture removal is required, and conventional drying methods are expensive since they require great quantity of energy supplied, almost always, by a non-renewable energy. In this study six batches with the same quantity of biowaste, and heterogeneous physical composition were dried under open-sun conditions. We evaluated the influence of the interaction between drying area and the initial moisture content on drying rate. Eight semi-theoretical models were fitted using Levenberg-Marquardt algorithm to predict drying rate, and their accuracy was assessed through goodness-of-fit tests. Maximum moisture content to preserve biomass (10%) was reached on 5<sup>th</sup> day and the equilibrium on 16<sup>th</sup> day of drying. According to goodness-of-fit test (<i>R</i> <sup>2</sup> = 0.999, <i>χ</i> <sup>2</sup> = 4.666 × 10<sup>-5</sup>, RMSE = 0.00683) the best model to predict drying rate was Two-term model. The mathematical model obtained from Fick's second law is reliable to predict drying kinetics, R<sup>2</sup> (0.9648 ± 0.0106); despite the variation between drying area and initial moisture content. Kruskal-Wallis test showed that drying rates between batches are not significantly different (<i>p</i> = 0.639; 0.05); nor effective diffusion coefficient (<i>D</i> <sub><i>eff</i></sub> = 4.97 × 10<sup>-11</sup> ± 0.3491 × 10<sup>-11</sup>), (<i>p</i> = 0.723; 0.05). The study of drying kinetics is crucial for selecting the optimal biowaste treatment based on its generation context. This could enable its use as feedstock for bioproduct or bioenergy production, thereby reducing waste accumulation in landfills and environmental impact.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11531745/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.7717/peerj.18248","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
The objective of this study is to investigate the drying kinetics of fruit and vegetable peel biowaste using a sustainable technique as a key-pretreatment for its conversion into useful feedstock. Biowaste represents a missed potential source of bioenergy and bioproducts, but moisture removal is required, and conventional drying methods are expensive since they require great quantity of energy supplied, almost always, by a non-renewable energy. In this study six batches with the same quantity of biowaste, and heterogeneous physical composition were dried under open-sun conditions. We evaluated the influence of the interaction between drying area and the initial moisture content on drying rate. Eight semi-theoretical models were fitted using Levenberg-Marquardt algorithm to predict drying rate, and their accuracy was assessed through goodness-of-fit tests. Maximum moisture content to preserve biomass (10%) was reached on 5th day and the equilibrium on 16th day of drying. According to goodness-of-fit test (R2 = 0.999, χ2 = 4.666 × 10-5, RMSE = 0.00683) the best model to predict drying rate was Two-term model. The mathematical model obtained from Fick's second law is reliable to predict drying kinetics, R2 (0.9648 ± 0.0106); despite the variation between drying area and initial moisture content. Kruskal-Wallis test showed that drying rates between batches are not significantly different (p = 0.639; 0.05); nor effective diffusion coefficient (Deff = 4.97 × 10-11 ± 0.3491 × 10-11), (p = 0.723; 0.05). The study of drying kinetics is crucial for selecting the optimal biowaste treatment based on its generation context. This could enable its use as feedstock for bioproduct or bioenergy production, thereby reducing waste accumulation in landfills and environmental impact.