Fcr figures and tables
Skill brycewang-stanford/Awesome-Journal-Skills/Field-Crops-Research-Skills/skills/fcr-figures-and-tables
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Use when building tables and figures for a Field Crops Research (FCR) manuscript so exhibits are self-contained, quantitatively complete, and agronomically informative — yield and response curves, AMMI/GGE biplots, observed-vs-simulated plots, and weather-vs-phenology series. FCR exhibits must show units, error (SED/LSD), and sample structure. Designs exhibits; it does not run the analysis.
SKILL.md
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Figures & Tables (fcr-figures-and-tables)
Exhibits are where an agronomy reviewer checks whether the result is real and general. At FCR every exhibit must be self-contained and quantitatively complete: units, sample/replication, and a measure of error or variability (SE, SED, or LSD) belong on the exhibit itself.
When to trigger
- Designing the main results table/figure or a key descriptive exhibit
- Deciding what belongs in the article vs. supplementary material
- A reviewer found an exhibit unclear, mislabeled, or missing error/units
- Presenting G×E, response curves, or model evaluation
Principles
- Self-contained. A reader should understand each exhibit from its caption, axis/column labels, and footnote alone. State the crop, cultivar(s), environments (sites×seasons), N/replication, units (SI), and what the value is (mean? adjusted mean?).
- Show the error. Yield and treatment means need SED or LSD (with α and df) or error bars defined in the caption — never bare means. For curves, show fitted line + CI and the data.
- Right exhibit for the question. Use a response curve for quantitative factors (N, water, density); an AMMI/GGE biplot or Finlay–Wilkinson plot for G×E; observed-vs-simulated with the 1:1 line for model evaluation; time series vs. thermal time/phenology with weather overlays for development.
- Accessible. Colourblind-safe palettes; legible in grayscale; no chartjunk, no 3D, no needless colour. Vector output (PDF/EPS) for print.
- Reproducible & consistent. Numbers match the analysis script and the deposited data; table and figure values are internally consistent and consistent with the text.
Agronomy-specific exhibits
- Yield-gap / boundary-line plots; nitrogen- and water-response curves with fitted models.
- AMMI biplots, GGE biplots, Finlay–Wilkinson stability regressions for multi-environment data.
- Weather (rainfall, temperature, radiation) shown against crop phenology (sowing, anthesis, maturity).
- Maps where spatial/regional variation is the point; observed-vs-simulated panels for modelling.
Exhibit-selection table (question → exhibit → annotation)
The right exhibit follows from the agronomic question. Pair each with the annotation an FCR reviewer expects.
| Question | Exhibit | Must annotate |
|---|---|---|
| Yield vs. N/water/density | fitted response curve + points | model, SED or CI, units |
| Genotype ranking | AMMI / GGE / Finlay–Wilkinson | environments labelled, % variance |
| Model performance | observed-vs-simulated, 1:1 line | RMSE, nRMSE, EF, n; validation only |
| Treatment means by environment | adjusted-means table | SED/LSD, α, df, replication |
Worked exhibit vignette (illustrative)
Illustrative. A first-draft Table 2 for the maize MET lists raw plot means with a/b/c letters across all 5 N rates and no error term — two flags at once: letters on a quantitative dose hide the response shape, and raw means do not match the mixed-model output. The fix is two exhibits: an N response curve per environment with fitted line and SED bar (α = 0.05), plus an adjusted-means table with one SED column — both self-contained and reproducible from the script.
Anti-patterns
- Means with no SED/LSD, error bars, or units
- Mean-separation letters on a quantitative dose where a response curve is appropriate
- Tables that need the prose to be intelligible (not self-contained)
- Colour-only encoding that fails in grayscale or for colourblind readers
- Exhibit values that don't match the analysis output or the data deposit
Operating pass for Field Crops Research
Treat this skill as an executable review pass, not a prose hint. First lock the crop system, environment structure, GxE logic, and yield or physiology endpoint; then judge whether the current manuscript answers the venue's real reader: agronomy reviewers who expect field-based, multi-environment evidence and crop-level general significance.
- Do the pass: Return a claim-evidence-risk ledger rather than a prose-only diagnosis; every recommendation must point to a manuscript location or missing artifact.
- Return a ledger: give
claim / evidence / risk / manuscript locationrows, so the next agent can edit rather than rediscover the issue. - Sibling guard: compare against Agricultural Systems for whole-system modeling, European Journal of Agronomy for agronomic breadth, Crop Science for cultivar or breeding emphasis; if a sibling owns the contribution, recommend re-routing before polishing format.
- Submission-ready gate: do not give final advice until the pack's
resources/official-source-map.mdhas been checked for upload-week rules and the manuscript has one concrete fix for the largest venue-specific risk.
Output format
【Main exhibit】what it shows + why this exhibit type
【Self-contained?】caption + labels + crop/cultivar + envs + N + units present? [Y/N]
【Error shown?】SED / LSD / CI with α stated? [Y/N]
【Accessible?】grayscale-legible + colourblind-safe? [Y/N]
【Article vs supplement】split decided
【Reproducible?】matches analysis output + data deposit? [Y/N]
【Next】fcr-reporting-and-data-policy
Supplementary resources
../../resources/external_tools.md— plotting and G×E-biplot tooling../../resources/official-source-map.md— reporting expectations (units, weather vs. phenology)