Non-Destructive Estimation Of Leaf Area In Cinchona Micrantha And Cinchona Pubescens Using Linear Regression Models

Huaccha Castillo,Annick Estefany

Non-Destructive Estimation Of Leaf Area In Cinchona Micrantha And Cinchona Pubescens Using Linear Regression Models

dc.contributor.author	Huaccha Castillo,Annick Estefany
dc.date.accessioned	2026-01-22T20:00:34Z
dc.date.available	2026-01-22T20:00:34Z
dc.date.issued	2025-07-25
dc.description.abstract	Accurate quantification of leaf area is essential for ecophysiological, agronomic, and conservation studies, especially in threatened species such as Cinchona micrantha and Cinchona pubescens. This study evaluated simple, quadratic, and composite linear regression models to estimate leaf area non-destructively using morphometric measurements (length and width). A sample of n=800 leaves from 32 individuals was systematically collected and analyzed using a standardized photographic protocol with digital processing in ImageJ. The most robust models were those incorporating composite variables such as the product of length and width (L × W) and the sum squared of both dimensions ((L + W)²), reaching coefficients of determination higher than 0.97. These models consistently outperformed models based on single variables, providing higher accuracy and lower prediction error. High correlations were observed between leaf dimensions and area, and C. pubescens showed greater morphological variability. These findings establish that simple linear models based on L × W are efficient, replicable, and low-cost tools for non-destructive estimation of leaf area, which improves ecological monitoring and supports sustainable forest management, essential for the conservation of these Cinchona species, important from an ecological and medicinal point of view, in tropical ecosystems.
dc.format	application/pdf
dc.identifier.doi	https://doi.org/10.18280/ijdne.200804
dc.identifier.uri	http://hdl.handle.net/20.500.14689/1061
dc.language.iso	eng
dc.publisher	International Information and Engineering Technology Association
dc.publisher.country	GB
dc.rights	info:eu-repo/semantics/openAccess
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.source	Universidad Nacional de Jaén\|\|Repositorio Institucional – UNJ
dc.subject	cinchona tree
dc.subject	leaf morphometry
dc.subject	forest conservation
dc.subject	allometric analysis
dc.subject.ocde	https://purl.org/pe-repo/ocde/ford#4.01.02
dc.title	Non-Destructive Estimation Of Leaf Area In Cinchona Micrantha And Cinchona Pubescens Using Linear Regression Models
dc.type	info:eu-repo/semantics/article
dc.type.version	info:eu-repo/semantics/publishedVersion
renati.author.dni	72552959