Agent Skills
› brycewang-stanford/Awesome-Journal-Skills
› field-crops-research
field-crops-research
GitHub用于评估农学/作物生理稿件是否适合投稿至《Field Crops Research》期刊。提供选题匹配、框架重构建议及拒稿风险预判，强调多环境重复田间试验的严谨性与可推广性。
Trigger Scenarios
作者指定该期刊并需进行稿件适配性或框架检查
需要将管理或基因型结果调整为跨环境通用性表述
在该期刊与其他农学期刊间进行选择决策
需了解关于实验重复性和田间有效性的快速拒稿标准
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill field-crops-research -g -y
SKILL.md
Frontmatter
{
"name": "field-crops-research",
"description": "Use when targeting Field Crops Research or deciding whether an agronomy \/ crop-physiology manuscript fits this venue. Encodes the journal's fit, the field-scale multi-environment and replication bar, data-reporting expectations, house style, official-submission re-check, and desk-reject heuristics."
}
Field Crops Research (field-crops-research)
Journal positioning
Field Crops Research, published by Elsevier, is an agronomy and crop-physiology journal centred on field-scale crop performance: yield and its determinants, resource-use efficiency (water, nitrogen, radiation), cropping systems, crop modeling, and management across environments. Its defining expectation is rigorous, adequately replicated field experimentation that generalizes across environments — multi-site and/or multi-season evidence, or modeling validated against field data. A single site-year, unreplicated trial, or a pot/glasshouse study generalized to the field without field validation is a poor fit. This skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current author guidelines. Before submitting, re-check the live Field Crops Research author guidance.
When to trigger
- The author names Field Crops Research and wants a fit/framing check for a field-agronomy or crop-physiology paper.
- A management, genotype, or resource-efficiency result must be framed for generalizability across environments rather than as a one-off trial.
- The author is choosing between Field Crops Research,
agronomy-for-sustainable-development, andagriculture-ecosystems-and-environment. - The author needs the venue's desk-reject heuristics around replication and field validity.
Scope & topic fit
- Crop yield and yield-component determinants under field conditions across genotypes and environments.
- Resource-use efficiency: water-, nitrogen-, and radiation-use efficiency and the trade-offs among them.
- Cropping systems and management: rotations, intercropping, planting density, sowing date, and agronomic interventions evaluated in the field.
- Crop physiology underpinning yield formation: phenology, source–sink relations, canopy and root function at field scale.
- Crop simulation modeling calibrated and validated against field data, including genotype × environment × management analysis.
- Yield-gap analysis and benchmarking across regions and production systems.
Method & evidence bar
- The contribution must be field-relevant and generalizable: adequately replicated experiments across sites and/or seasons, or modeling validated on independent field data.
- Experimental design must be sound: stated design (RCBD, split-plot, etc.), true replication, randomization, and appropriate error terms; pseudoreplication is disqualifying.
- Statistics must match the design: mixed models for multi-environment data, correct treatment of site/year as random or fixed, and reported variance/uncertainty.
- Yield and efficiency claims need full agronomic context: soil, weather, inputs, and management documented so results are interpretable and reproducible.
- Models must report calibration/validation separately, skill metrics against measured data, and parameter sources; data and key code/inputs should be available per Elsevier policy.
Structure & house style
- Standard IMRaD; the introduction must state the agronomic problem and the across-environment question, not just describe a local trial.
- Materials and methods must fully document environments (soil, climate), design, replication, and management so the study is reproducible.
- Figures/tables should carry the across-environment argument (G×E×M, response curves, yield-gap or efficiency comparisons) with variability shown.
- A data-availability statement and complete agronomic metadata are expected; supplementary material carries site-by-site detail.
Official-submission checklist
- Before giving submission-ready advice, read
../../resources/source-basis.mdand../../resources/official-source-map.md; start from the official source anchors, then cite the current Field Crops Research page you checked. - Search the live site for "Field Crops Research guide for authors" and follow the current Elsevier version.
- Re-check article types, structure, word/figure expectations, and abstract format.
- Confirm the data-availability/repository policy and reporting of environmental and management metadata.
- Re-check competing-interests, funding, author-contribution, and AI-use disclosure, and open-access terms.
- If the live official instructions conflict with this skill, the official instructions win.
Pre-submission self-check
- Evidence spans multiple sites and/or seasons, or modeling is validated on independent field data.
- The design has true replication and randomization; there is no pseudoreplication.
- Statistics match the design (e.g., mixed models for multi-environment data) with uncertainty reported.
- Soil, weather, inputs, and management are fully documented for reproducibility.
- Models report calibration and validation separately with skill metrics against measured data.
- Data-availability statement and agronomic metadata are prepared.
Common desk-reject triggers
- A single site-year, unreplicated trial presented as a general agronomic finding.
- A pot/glasshouse-only study generalized to the field with no field validation.
- Pseudoreplication, or statistics that ignore site/year structure in multi-environment data.
- Yield/efficiency claims with missing soil, weather, or management context.
- A crop model reported without independent validation or skill metrics against field data.
Re-routing decision
- Explicit sustainability framing, or review/meta-analysis of cropping systems →
agronomy-for-sustainable-development. - Environmental fluxes (GHG, nutrient losses), biodiversity, or water quality dominant →
agriculture-ecosystems-and-environment. - Soil-process mechanism (SOM, microbial, nutrient cycling) is the core →
soil-biology-and-biochemistry. - Broad food-systems significance →
nature-food. - Crop physiology/genetics with mechanistic plant-science reach →
new-phytologistorthe-plant-journal.
Output format
[Fit] High / Medium / Low (one-line reason)
[Target] Field Crops Research
[Topic tags] <2–3 closest field-agronomy topics>
[Generalizability] <multi-environment evidence or validated model that transfers>
[Method/evidence] <does replication + design + statistics clear Field Crops Research's bar?>
[Top risk] <the single most likely reason for rejection>
[Official items to re-check] <article type / data policy / metadata reporting / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>
Version History
- 1839142 Current 2026-07-05 12:17
