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library(rio) # Data import
library(metan) # corr_plot() – correlation matrix with visual output
library(ggplot2)Correlation Analysis
Pearson correlation matrix among leaf area, leaf number, and plant height across all measurement dates and treatments.
Overview
This section examines the linear associations among the three vegetative growth traits measured at each harvest:
- Leaf area per plant (
af_planta, cm² plant⁻¹) - Leaf number per plant (
n, leaves plant⁻¹) - Plant height (
cp, cm)
A Pearson correlation matrix with significance stars is produced via metan::corr_plot().
Required packages
Correlation plot
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import("../df_model_cresc.xlsx") |>
# Select the three growth variables; corr_plot() handles pairwise correlations
corr_plot(af_planta, n, cp)
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ggsave("../figs/correlacao.jpg", width = 6, height = 6)
Note
All three traits are expected to be positively and strongly correlated given that they are all driven by the same thermal-time accumulation process.
Session information
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sessionInfo()
## R version 4.5.1 (2025-06-13 ucrt)
## Platform: x86_64-w64-mingw32/x64
## Running under: Windows 11 x64 (build 26200)
##
## Matrix products: default
## LAPACK version 3.12.1
##
## locale:
## [1] LC_COLLATE=Portuguese_Brazil.utf8 LC_CTYPE=Portuguese_Brazil.utf8
## [3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C
## [5] LC_TIME=Portuguese_Brazil.utf8
##
## time zone: America/Sao_Paulo
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggplot2_4.0.2 metan_1.19.0 rio_1.2.4
##
## loaded via a namespace (and not attached):
## [1] gtable_0.3.6 xfun_0.56 htmlwidgets_1.6.4
## [4] ggrepel_0.9.7 GGally_2.4.0 lattice_0.22-9
## [7] mathjaxr_2.0-0 numDeriv_2016.8-1.1 vctrs_0.7.1
## [10] tools_4.5.1 Rdpack_2.6.6 generics_0.1.4
## [13] tibble_3.3.1 pkgconfig_2.0.3 R.oo_1.27.1
## [16] Matrix_1.7-4 RColorBrewer_1.1-3 S7_0.2.1
## [19] readxl_1.4.5 lifecycle_1.0.5 compiler_4.5.1
## [22] farver_2.1.2 textshaping_1.0.4 ggforce_0.5.0
## [25] codetools_0.2-20 lmerTest_3.2-0 htmltools_0.5.9
## [28] yaml_2.3.12 pillar_1.11.1 nloptr_2.2.1
## [31] tidyr_1.3.2 MASS_7.3-65 R.utils_2.13.0
## [34] reformulas_0.4.4 boot_1.3-32 nlme_3.1-168
## [37] ggstats_0.12.0 tidyselect_1.2.1 digest_0.6.39
## [40] dplyr_1.2.1 purrr_1.2.1 labeling_0.4.3
## [43] splines_4.5.1 polyclip_1.10-7 fastmap_1.2.0
## [46] grid_4.5.1 cli_3.6.5 magrittr_2.0.4
## [49] patchwork_1.3.2 dichromat_2.0-0.1 withr_3.0.2
## [52] scales_1.4.0 rmarkdown_2.30 otel_0.2.0
## [55] lme4_1.1-38 cellranger_1.1.0 ragg_1.5.0
## [58] R.methodsS3_1.8.2 evaluate_1.0.5 knitr_1.51
## [61] rbibutils_2.4.1 rlang_1.1.7 Rcpp_1.1.1
## [64] glue_1.8.0 tweenr_2.0.3 rstudioapi_0.18.0
## [67] minqa_1.2.8 jsonlite_2.0.0 R6_2.6.1
## [70] systemfonts_1.3.1