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

[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>