Comparação de métodos não destrutivos para estimar a área foliar de Cinchona officinalis L. por meio de processamento digital de imagens: Comparison of non-destructive methods for estimating the leaf area of Cinchona officinalis L. using digital image processing
Year: 2025
Type: article
Abstract: Cinchona officinalis is an important plant species, was the only treatment for malaria for more than three centuries. The objective of this study was to compare the accuracy of four non-destructive digital image processing methods (LeafArea and three ImageJ algorithms) for estimating the leaf area of young C. officinalis plantations in two establishment conditions: forest stands and enrichment strips. Leaves were photographed at a distance of 8 cm using a 24 MP smartphone and processed using the methods evaluated. Statistical analysis included box-and-whisker plots, Pearson correlation, and Friedman test. The results showed that ImageJ methods M3 and M4 had the highest accuracy (r = 0.99), with no significant differences between them, and with overestimations detected in M1 and M2. It is concluded that M3 and M4 are fast, low-cost, and highly accurate options for field monitoring of C. officinalis foliage.
Language: English
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W7214833705