Skip to contents

Changelog

Source: NEWS.md

aridagri 2.1.0

This release is dedicated to the memory of co-authors Dr. Monika Punia and Dr. Hemant Poonia.

Version 2.1.0 corrects several calculations, adds ten functions and six example datasets, and removes the dependence on ‘agricolae’ for letter groupings. Results from earlier versions should be rechecked for the functions listed under “Corrected results”.

Corrected results

  • anova_rbd(): the relative efficiency of the RCBD over a CRD used the coefficient (t + r - 2) instead of r(t - 1) on the error mean square and replaced a small block mean square by the error mean square. With five treatments, four blocks and no block effect it reported 52.6% instead of about 100%. It now follows Gomez and Gomez (1984), with the precision adjustment for fewer than 20 error df.
  • anova_rbd_pooled(): with verbose = FALSE the analyses of the individual environments were skipped, so Bartlett’s test returned NaN and individual_anovas was empty. The environment effect was tested against the pooled residual instead of blocks within environments. Both are fixed, and a new env_effect = "random" option tests treatments against the treatment x environment interaction (McIntosh, 1983).
  • anova_spd(): the returned anova_table tested the main-plot factor against Error(b); in one test case F changed from 2.91 (p = 0.080) to the correct 0.60 (p = 0.59). The printed table was already correct.
  • anova_strip(): both strip factors were tested against Error(c). The horizontal factor is now tested against Error(a) = Rep x A and the vertical factor against Error(b) = Rep x B; in one test case a false p = 0.007 became p = 0.30. CV(a), CV(b), CV(c) and the four SE/CD values of Gomez and Gomez are now reported.
  • stability_analysis():
    • Shukla’s stability variance was W/(e - 1). It is now Shukla’s unbiased estimator with an F-test (rankings were not affected).
    • The AMMI stability value put the SS ratio inside the square and used IPCA scores scaled by the singular value instead of its square root. ASV now follows Purchase et al. (2000) and agrees with ‘agricolae’.
    • Eberhart-Russell S2di now subtracts the pooled error (MSE/r), and the tests of bi = 1 and S2di = 0 are reported.
  • check_assumptions(): the homogeneity test used the first factor of the model, which for an RCBD was the block. It now uses the treatment (or a factor you choose) and the residuals. It no longer claims to run an Anderson-Darling test for more than 5000 residuals.
  • nue_calculate(): the “utilization efficiency” column was AE x ARE, which is not a defined index. UE is now the biomass-based physiological efficiency times ARE (Fageria and Baligar, 2005), given when biomass is supplied. The function also failed for vector input.
  • crop_growth_analysis(): LAI was computed but never returned.
  • nutrient_response(): no check that the quadratic curve has a maximum.
  • anova_augmented() did not compute adjusted means of the test entries; anova_alpha_lattice() reported unadjusted genotype means.
  • Many functions ignored alpha (CD was always at 5%) or posthoc, and counted rows with a missing response.

New functions

  • anova_repeated(): repeated measures (split-plot in time) with Mauchly’s test, Greenhouse-Geisser and Huynh-Feldt corrections, a comparison of CS, AR(1) and unstructured covariance models, SE/CD for every comparison and an analysis at each time.
  • anova_traits(): the treatment-means table for many traits that journals ask for (means with letters, SEm, CD or NS, CV) for CRD, RCBD, factorial and split-plot designs.
  • compare_means(): letters from means, error MS and df alone.
  • gge_biplot(): GGE biplot with which-won-where, mega-environments and the mean vs stability view.
  • day_length(): day length from latitude and date (FAO-56).
  • plot_means(), plot_interaction(), plot_stability(), plot_response(), theme_aridagri() and plot() methods for publication figures with ‘ggplot2’.

Improvements

  • Letter groupings for LSD, Duncan, Tukey, SNK, Scheffe and Bonferroni are computed inside the package (no ‘agricolae’ needed), with exact pairwise tests for unequal replication (Tukey-Kramer) and missing plots, the closure rule for Duncan and SNK (the reported p-values follow it), and the letter algorithm of Piepho (2004). Results agree with ‘agricolae’ for balanced data. Least-squares means that cannot be estimated (empty cells) are left out with a warning.
  • perform_posthoc(): Dunnett’s test now averages over interacting factors and uses mse and df_error when given; a new control argument sets the control level.
  • anova_rbd(), anova_crd() and anova_latin() handle missing plots and unequal replication by least squares; means are least-squares means.
  • All split-plot functions report SEm, SEd and CD for every type of comparison, including those that mix error terms (weighted t), and give letters for each factor and for each factor within the levels of another. The pooled split-plot functions now report SE and CD too.
  • anova_augmented(): adjusted means, the four standard errors of difference, ANOVA with tests vs checks, checks and tests (adjusted and unadjusted for blocks), comparison of each test entry with the check mean and the best check, and genetic parameters (PCV, GCV, heritability, genetic advance) from the block-adjusted mean square of tests.
  • anova_alpha_lattice(): adjusted means with exact SEs and letters, efficiency relative to an RCBD, and REML analysis with recovery of inter-block information (default; analysis = "intra" for the intra-block analysis).
  • stability_analysis(): combined ANOVA, Eberhart-Russell ANOVA, AMMI ANOVA with Gollob’s df and F-tests, Kendall’s W among the seven rankings, and input of genotype x environment means (replication = NULL).
  • thermal_indices(): upper threshold temperature, McMaster-Wilhelm method 2, helio-thermal use efficiency, input checks.
  • crop_growth_analysis(): ground area for CGR and LAI, leaf area duration.
  • yield_gap_analysis(): technology gap, extension gap and technology index for front-line demonstrations.
  • nutrient_response(): linear-plateau, quadratic-plateau and Mitscherlich models and model = "all" for a comparison by AIC; optimum doses beyond the tested range are flagged.
  • anova_factorial() and anova_factorial_3way(): SE/CD for every effect and letters for main effects and treatment combinations; with unbalanced data the means are least-squares means.
  • anova_latin(): efficiency relative to CRD and RCBD.
  • check_assumptions(): Levene (Brown-Forsythe) test, Tukey’s test for non-additivity, studentized residuals and optional residual plots.
  • Print methods for all results; export_results() writes every table to a separate Excel sheet.
  • All functions accept tibbles (for example from ‘readxl’) and column names with spaces.

Behaviour changes

  • Split-plot type functions stop with an informative error when data are incomplete, instead of returning unreliable results with a warning.
  • stability_analysis() needs at least three genotypes and environments.
  • nlme (shipped with R) is now imported. Unused suggested packages were removed.

Other changes

  • Six simulated example datasets: mothbean_rbd, clusterbean_spd, pearlmillet_met, chickpea_augmented, cowpea_alpha, mungbean_repeated.
  • A vignette, a pkgdown site and 607 test expectations (from 82), many checking results against ‘agricolae’, ‘emmeans’, aov() error strata and base R’s sphericity tests.
  • Hemant Poonia, co-author of the article describing the package (Software Impacts, 2026), is added as an author. He and Monika Punia are marked as deceased in the author list.

aridagri 2.0.4

CRAN release: 2026-07-10

Bug fixes

  • anova_spd() split-plot ANOVA: the main-plot error term (Error a) and the sub-plot sum of squares are now extracted from the ANOVA table by term name rather than by fixed row position. Because R orders main-effect terms ahead of interaction terms, the previous positional extraction swapped the sub-plot effect with Error(a), which produced incorrect main-plot and sub-plot F-tests and an incorrect Error(a) mean square, main-plot standard error, critical difference and CV(a). Sub-plot standard error, critical difference and CV(b), and the returned ANOVA table itself, were not affected.
  • anova_spd_ab_main(), anova_spd_c_main_ab_sub(), anova_spd_ab_cd() and anova_sspd() now test each effect against its correct error term. Previously these functions reported the raw combined ANOVA, in which the main-plot (and, for the split-split design, sub-plot) factors were tested against the residual rather than against the properly pooled main-plot / sub-plot error. The returned anova_table now gives the correct F-values and p-values for every stratum, and the objects carry the corresponding error mean squares, degrees of freedom and CVs. Verified against independent aov() Error()-strata models.
  • anova_spd_pooled() and anova_sspd_pooled() (combined analysis over environments) now test each source against the correct pooled error. Both functions previously reported a single-stratum anova() table in which every effect was tested against one residual, so the environment main effect and the main-plot (and, for the split-split design, sub-plot) factors were tested against the sub-sub-plot residual rather than against their own pooled errors. Treating environments as fixed and replications as random within environment, the environment effect is now tested against the environment/replication error (E:Rep), the main-plot factors against the pooled main-plot error, and the sub-plot and sub-sub-plot factors against their respective pooled errors. The returned anova_table gives the correct F- and p-values for every stratum, the objects now carry per-stratum coefficients of variation, and anova_sspd_pooled() now returns factor means for plotting. Verified against independent aov() Error()-strata models.
  • perform_posthoc() can now be called directly without pre-computing the error mean square and error degrees of freedom. When mse or df_error are not supplied they are derived from the fitted model. This fixes errors in the Bonferroni method and in the manual (no agricolae) fallbacks for LSD and Tukey.
  • Fixed Dunnett’s test: the comparison is now built against the actual treatment factor supplied by the user instead of a hard-coded factor name, so it works correctly when multcomp is installed.
  • verbose = FALSE is now fully respected by anova_crd(), anova_rbd() and anova_latin(); these no longer print post-hoc and assumption-check output when silent operation is requested. Result objects are unchanged and still contain the full post-hoc and diagnostic components regardless of verbose.
  • arid_plot() now draws factor or treatment means for every ANOVA design (factorial, three-way factorial, Latin square, all split-plot and split-split-plot variants, strip-plot, alpha lattice and the pooled designs), not only CRD and RBD. Designs with several factors are shown as a multi-panel bar chart, one panel per factor, with standard-deviation whiskers where available. Objects that expose no factor-means table return quietly with an informative message instead of an error.
  • arid_plot() produces plots using base graphics for correlation objects (a heatmap of the correlation matrix) and stability objects (a bar chart of the integrated stability ranking); it previously returned without plotting.
  • export_results() now supports format = "csv" in addition to "xlsx" and raises a clear error for unsupported formats.

Other changes

  • Added grDevices, graphics, stats and utils to Imports.

aridagri 2.0.3

CRAN release: 2026-02-24

  • Initial CRAN release (24 February 2026)
  • 33 exported functions across 6 modules
  • 16 ANOVA designs with proper error terms
  • 7 post-hoc comparison tests with letter groupings
  • 7 stability analysis methods with integrated ranking
  • Thermal indices (GDD, HTU, PTU, HUE)
  • Crop growth analysis (CGR, RGR, NAR, LAI)
  • Nutrient use efficiency indices
  • Path analysis and SEM via lavaan
  • Publication-ready output with SE, CD, CV
  • Unified verbose parameter for all functions
  • Zero external dependencies (base R only)