Statistical Modeling to Analyze the Performance and Carbon Content of Agro-industrial Biomasses

Pinto-Altamiranda, Sania; Gómez R, Sara Manuela; González, María Eugenia; Barrera-Causil, Carlos

Statistical Modeling to Analyze the Performance and Carbon Content of Agro-industrial Biomasses

dc.creator	Pinto-Altamiranda, Sania
dc.creator	Gómez R, Sara Manuela
dc.creator	González, María Eugenia
dc.creator	Barrera-Causil, Carlos
dc.date	2023-08-24
dc.date.accessioned	2025-10-01T23:53:09Z
dc.description	In agroindustry, a significant amount of waste is generated, which can be treated using various thermochemical technologies such as hydrothermal carbonization. Biomass yield and carbon content are two of the most common characteristics studied within the processes generated by these thermochemical technologies, and chemical analyses and statistical techniques are usually employed. These techniques include t-student tests, analysis of variance, or response surface models to optimize or estimate the effects of certain factors. Unlike research conducted in this field of chemistry, this study aimed to introduce alternative statistical techniques for modeling such data, proposing diverse analysis strategies to enhance understanding of the studied phenomena. To achieve this, the statistical modeling of two datasets derived from apple pomace and blueberries was presented, encompassing four factors (time, humidity, power, temperature) and two separate responses (carbon content and process yield). This study reveals that time, temperature, and humidity collectively affect process yield and carbon content in apple biomass. It is concluded that techniques like generalized linear models with beta response and generalized additive models for location, scale, and shape provide a deeper understanding of the phenomenon of interest and the ability to estimate the effects of studied factors on responses that do not naturally follow a normal distribution.	en-US
dc.description	En la agroindustria se genera una considerable cantidad de residuos, los cuales pueden ser tratados usando diversas tecnologías termoquímicas como la carbonización hidrotermal. El rendimiento y contenido de carbono de biomasas son dos de las características más comunes que se estudian dentro del proceso generado en estas tecnologías tecnoquímicas, y usualmente se aplican análisis químicos y técnicas estadísticas, tales como pruebas t-student, análisis de varianza o modelos de superficies de respuestas para optimizar estas respuestas o estimar el efecto que ciertos factores puedan tener sobre estas. A diferencia de las investigaciones abordadas en esta área de la química, este estudio tuvo como propósito introducir diferentes técnicas alternativas de la estadística para la modelación de este tipo de datos con el fin de proponer diferentes estrategias de análisis que permitan ampliar el conocimiento de los fenómenos estudiados en esta área. Para ello, se presentó la modelación estadística de dos bases de datos provenientes de bagazo de manzana y de arándanos que contienen un total de cuatro factores (tiempo, humedad, potencia, temperatura) y dos respuestas a analizar por separado (contenido de carbono y rendimiento del proceso). En este estudio se observa que el tiempo, la temperatura y la humedad tienen un efecto conjunto sobre el rendimiento del proceso y el contenido de carbono de la biomasa proveniente de la manzana. Se concluye que, técnicas como modelos lineales generalizados con respuesta beta y los modelos aditivos generalizados de posición, escala y forma, proporcionan un mayor conocimiento del fenómeno de interés y la capacidad de estimar el efecto de los factores estudiados sobre respuestas que naturalmente no poseen un comportamiento distribucional como el modelo normal.	es-ES
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dc.identifier	https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2677
dc.identifier	10.22430/22565337.2677
dc.identifier.uri	https://hdl.handle.net/20.500.12622/7872
dc.language	spa
dc.publisher	Instituto Tecnológico Metropolitano (ITM)	es-ES
dc.relation	https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2677/2918
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dc.relation	https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2677/3133
dc.relation	https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2677/3220
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dc.rights	Derechos de autor 2023 TecnoLógicas	es-ES
dc.rights	https://creativecommons.org/licenses/by-nc-sa/4.0	es-ES
dc.source	TecnoLógicas; Vol. 26 No. 57 (2023); e2677	en-US
dc.source	TecnoLógicas; Vol. 26 Núm. 57 (2023); e2677	es-ES
dc.source	2256-5337
dc.source	0123-7799
dc.subject	Carbonización hidrotermal	es-ES
dc.subject	contenido de carbono	es-ES
dc.subject	modelación estadística	es-ES
dc.subject	rendimiento del hidrocarbón	es-ES
dc.subject	residuos agroindustriales	es-ES
dc.subject	Hydrothermal carbonization	en-US
dc.subject	carbon content	en-US
dc.subject	statistical modeling	en-US
dc.subject	hydrocarbon yield	en-US
dc.subject	agro-industrial residues	en-US
dc.title	Statistical Modeling to Analyze the Performance and Carbon Content of Agro-industrial Biomasses	en-US
dc.title	Modelación estadística para analizar el rendimiento y contenido de carbono de biomasas agroindustriales	es-ES
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	Research Papers	en-US
dc.type	Artículos de investigación	es-ES