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field-crops-research

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.

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brycewang-stanford/Awesome-Journal-Skills
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2026년 6월 20일 03:05
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field-crops-research
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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`, and `agriculture-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.md` and `../../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-phytologist` or `the-plant-journal`. ## Output format ```text [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> ```
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