Can a Non-Destructive Method Predict the Leaf Area of Species in the Caatinga Biome?

Understanding the leaf area is essential in plant physiology and ecological studies, as it directly influences photosynthesis, transpiration and plant productivity. This study aimed to develop non-destructive allometric models to estimate the leaf area of three species from the Caatinga biome: Cynophalla flexuosa, Libidibia ferrea and Tabebuia aurea. A total of 1293 leaves were collected from these species, scanned, and analysed using ImageJ software to obtain their length, width, and actual leaf area. In addition, the product of length and width was calculated. Linear, power and exponential regression models were used. The best equations were chosen based on the coefficient of determination, Pearson’s linear correlation coefficient, Willmott’s agreement index, mean squared error, root mean squared error, mean absolute error and mean absolute percentage error. The best equations for all species were constructed using linear and power models, which were indicated for accurate prediction of leaf area. These findings confirm the efficiency of allometric equations as a non-destructive method for predicting leaf area, providing an accessible and economical alternative for ecological studies in semi-arid environments.

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Publication Details

Journal
Diversity
Published
2025-03-26
DOI
https://doi.org/10.3390/d17040234
Citations
1
Primary Topic
Leaf Properties and Growth Measurement
Type
article
Field-Weighted Citation Impact
1.75

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article

Can a Non-Destructive Method Predict the Leaf Area of Species in the Caatinga Biome?

Toshik Iarley da Silva, Pablo Henrique de Almeida Oliveira, Allysson Jonhnny Torres Mendonça, Ester dos Santos Coêlho et al.
1 citations
Diversity
Leaf Properties and Growth Measurement
1.75
article

Can a Non-Destructive Method Predict the Leaf Area of Species in the Caatinga Biome?

Toshik Iarley da Silva, Pablo Henrique de Almeida Oliveira, Allysson Jonhnny Torres Mendonça, Ester dos Santos Coêlho, Marcos Roberto Santos Correia, A. E. Rubio‐Casal, Aurélio Paes Barros Júnior, Antônio Gideilson Correia da Silva, Thieres George Freire da Silva, Alexandre Maniçoba da Rosa Ferraz Jardim, Elania Freire da Silva, João L. M. P. de Lima, João Everthon da Silva Ribeiro, Thainan Sipriano dos Santos, Maria Carolina Borges de Oliveira Ribeiro
article en
1 citations

Abstract

Understanding the leaf area is essential in plant physiology and ecological studies, as it directly influences photosynthesis, transpiration and plant productivity. This study aimed to develop non-destructive allometric models to estimate the leaf area of three species from the Caatinga biome: Cynophalla flexuosa, Libidibia ferrea and Tabebuia aurea. A total of 1293 leaves were collected from these species, scanned, and analysed using ImageJ software to obtain their length, width, and actual leaf area. In addition, the product of length and width was calculated. Linear, power and exponential regression models were used. The best equations were chosen based on the coefficient of determination, Pearson’s linear correlation coefficient, Willmott’s agreement index, mean squared error, root mean squared error, mean absolute error and mean absolute percentage error. The best equations for all species were constructed using linear and power models, which were indicated for accurate prediction of leaf area. These findings confirm the efficiency of allometric equations as a non-destructive method for predicting leaf area, providing an accessible and economical alternative for ecological studies in semi-arid environments.

DiversityVol. 17(4)
Universidade Federal do Recôncavo da Bahia (BR), Universidade Federal Rural de Pernambuco (BR), University of Coimbra (PT), Universidad de Sevilla (ES), Universidade Federal Rural do Semi-Árido (BR), Universidade Estadual Paulista (Unesp) (BR)
Fundação de Amparo à Pesquisa do Estado de São Paulo, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Openalex Percentile: Top 16%
Leaf Properties and Growth Measurement
1.75
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