GITNUXSOFTWARE REVIEW
Data Science AnalyticsTop 10 Best Turf Analysis Software of 2026
Compare turf analysis software options with side-by-side features and tradeoffs for lawn and turf management planning, including LawnPro.
How we ranked these tools
Vendors set the topic, but our editors set the inclusion criteria and the evaluation framework before research starts.
Search agents gather the source set and the review record, including transcriptions of video reviews and podcasts.
Framework: Features 40% · Ease 30% · Value 30%
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LawnPro is the best pick for grounds teams needing repeatable zone scouting tied to shared map areas because its georeferenced zone records with photo-linked notes keep every observation consistent across multiple people and visits, whereas Turf Analyzer fits teams that want batch photo-to-zone GIS exports for treatment planning.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
LawnPro
Georeferenced zone records with photo attachments tie every observation to the same map area across scouting cycles.
Best for: Fits when grounds teams need zone mapping, photo backed scouting, and audit logged editing for multi person field work.
Turf Analyzer
Editor pickZone-linked treatment records connect applied actions to mapped condition changes across scouting cycles.
Best for: Fits when grounds teams need repeatable zone maps and GIS exports tied to treatment planning.
Zappi
Editor pickZone mapping tied to field-referenced scouting records for maintenance planning with API-enabled automation.
Best for: Fits when grounds teams need georeferenced zone records and API-driven scouting integration.
Comparison Table
LawnPro
SMBLawn care business software for customer management, scheduling, invoicing, payments, and route planning.
Georeferenced zone records with photo attachments tie every observation to the same map area across scouting cycles.
LawnPro is a turf analysis software tool for translating field scouting notes into consistent lawn condition mapping and treatment history. The workflow centers on georeferenced zone records with photo attachments, so ground teams can track observations against the same areas over time.
LawnPro also supports exporting GIS data for downstream reporting and decision making across sports fields and golf course turf monitoring programs. Administrators can manage user access by role and review activity logs tied to updates and edits.
- +Zone based georeferenced mapping keeps observations tied to the same area
- +Photo linked field notes reduce misinterpretation across scouting cycles
- +GIS data export supports reporting in external mapping tools
- +RBAC style role control and audit logging for record changes
- –Limited built in analytics for disease diagnosis compared with top tier tools
- –Integrations with weather or irrigation systems require additional setup discipline
Estimators and field teams
Measure zones for service planning
Consistent area records
Landscape business owners
Turn notes into proposals
Scope-ready proposals
Show 2 more scenarios
Snow dispatchers and contractors
Coordinate storms with verification
Job-centered documentation
Dispatchers assign crews and retain storm service notes tied to the same mapped areas.
Owners and job managers
Assess job margins using estimates
Margin visibility per job
Managers compare estimate line items to completed work with zone-linked tracking for profitability.
Best for: Fits when grounds teams need zone mapping, photo backed scouting, and audit logged editing for multi person field work.
Turf Analyzer
vertical specialistFree batch image analysis tool for turfgrass cover, density, and color index calculation from field photos.
Zone-linked treatment records connect applied actions to mapped condition changes across scouting cycles.
Turf Analyzer is designed around repeat scouting and mapping workflows, not just one-off reporting. Georeferenced field maps keep observations aligned across GPS scouting passes, and the system organizes results by site zones for consistent comparisons. Export formats and reporting views make it usable for communicating condition summaries to operations stakeholders and for feeding GIS-based review processes.
A key tradeoff is that the value depends on consistent zone definitions and repeatable data capture, since comparisons degrade when zones shift between visits. This is a good fit when a grounds program runs scheduled scouting, records variances by location, and needs repeatable condition maps for maintenance planning. It is less suitable when field notes do not include location fidelity or when operations requires fully unstructured narratives without any zone structure.
- +Zone-based georeferenced maps keep repeat scouting aligned across visits
- +Exports support GIS workflows for condition review and reporting
- +Treatment history can be linked back to observed conditions
- +Coverage and stress indicators convert field notes into map layers
- –Comparisons weaken when zone boundaries change between scouting cycles
- –Automation depth relies on disciplined data capture by crew roles
Sports field operations
Schedule-based scouting by zone
Faster maintenance prioritization
Golf course agronomy
Condition reporting for course managers
Clearer course-wide communication
Show 1 more scenario
Lawn care supervisors
Track remediation outcomes
Better remediation accountability
Attach treatment notes to zones and compare mapped condition changes over time.
Best for: Fits when grounds teams need repeatable zone maps and GIS exports tied to treatment planning.
Zappi
enterpriseConsumer insights platform offering TURF analysis as part of its product and creative testing suite.
Zone mapping tied to field-referenced scouting records for maintenance planning with API-enabled automation.
Zappi is a turf analysis software option built around a scouting workflow that turns field observations into zone-based outputs. The system supports georeferenced field maps for organizing marks, letting teams track issues and treatment areas on the same reference grid.
Zappi also provides reporting outputs designed for field staff handoff, so observations can flow into action lists for maintenance planning. A documented API and automation hooks enable integration with other operational systems when teams need consistent data ingestion.
- +Georeferenced mapping keeps observations tied to field zones and locations
- +API and automation support reduce manual re-entry for recurring scouting
- +Zone-based records support repeatable treatment planning across seasons
- +Field-staff oriented reporting outputs support faster handoff to maintenance
- –Advanced analytics depth depends on specific data capture formats used
- –Requires configuration discipline to keep zone boundaries consistent team-wide
Research analysts and marketing teams
Run one-off scouting surveys
Faster analysis-ready data
Research operations managers
Monitor study progress by quota
Earlier progress visibility
Show 2 more scenarios
Product innovation teams
Compare concepts from field feedback
Comparable decision measures
Teams run structured surveys to compare concepts using consistent, zone-oriented outputs.
Consumer goods research teams
Test packaging and claims inputs
Comparative response insights
Teams collect structured responses for packaging and claims tests and compare results across options.
Best for: Fits when grounds teams need georeferenced zone records and API-driven scouting integration.
Real Green Systems
vertical specialistLawn care and pest control business software offering route mapping, chemical application tracking, and customer billing.
Zone-managed reporting ties scouting photos and notes to consistent field boundaries for comparable season outputs.
Real Green Systems centers on sports-field monitoring style workflows where scouting data is captured per location and then organized into maps and reporting views. Zones let teams maintain consistent boundaries across seasons, and report outputs support internal review and client sharing. The tool also supports structured photo attachment and note entry tied to specific geolocations.
- +Georeferenced field mapping keeps scouting evidence tied to locations
- +Zone-based organization supports consistent, repeatable reporting
- +Photo and note capture stays attached to field records
- +Admin controls help manage multi-scout data consistency
- –High reporting quality depends on strict zone and naming discipline
- –Advanced analysis workflows require structured scouting inputs
- –Image workflows can be slower when large photo batches are added
- –External data connectivity options feel less extensive than mapping-first rivals
Sports turf managers
Season scouting with repeatable zone maps
Faster plan updates with evidence
Golf course superintendents
Fairway and rough condition tracking
Clearer maintenance prioritization
Show 2 more scenarios
Regional agronomy teams
Multi-crew data standardization
Reduced reporting mismatches
Uses shared zone structures and admin governance to keep field records consistent across scouts.
Athletic field contractors
Client-ready field condition summaries
Cleaner handoffs to clients
Generates shareable reports from field notes and photos that stay connected to precise locations.
Best for: Fits when grounds teams need repeatable zone-based mapping for season-to-season turf reporting.
Yardbook
SMBLandscape business management software for scheduling, estimates, invoices, payments, and customer records.
Zone treatment record timelines tie scouting observations to follow-up actions for each map area.
Yardbook manages turf health assessment workflows by turning field scouting and georeferenced observations into zone-based condition maps. It supports GPS scouting, standardized scoring, and export-friendly reporting for sports field monitoring and golf course turf monitoring.
- +GPS field scouting captures repeatable observations by zone
- +Zone treatment records connect scouting notes to action history
- +Field-to-report mapping reduces manual spreadsheet rework
- +Standardized condition scoring keeps crew inputs consistent
- –Limited depth for soil chemistry mapping versus dedicated agronomy systems
- –Multi-sensor ingestion requires workflow discipline to avoid data drift
- –Advanced analytics are narrower than GIS-first turf platforms
- –Custom reporting options can feel constrained for complex compliance formats
Field crews and managers
Verify completed turf services
Visit-level service records
Lawn mowing businesses
Schedule repeat mowing visits
More consistent scheduling
Show 2 more scenarios
Estimators and office staff
Create work orders from estimates
Fewer handoff gaps
The team reuses estimate and proposal details to set up work orders for execution.
Lawn care operators
Record treatment program completion
Documented treatment history
Operators organize planned visits and log application details as crews complete treatments.
Best for: Fits when grounds teams need consistent GPS scouting, zone mapping, and treatment history for sports or golf fields.
Appinio
SMBSurvey platform with integrated TURF analysis functionality for product portfolio optimization.
Survey-driven field scouting workflows that translate onsite observations into structured zone-level datasets for decision review.
Appinio is a market research company used by organizations to run surveys and analyze results, so turf analytics come from human inputs rather than imaging models.
- +Survey templates speed up consistent field scouting question sets
- +Zone-by-zone survey responses support repeatable field check-ins
- +Cross-tab reporting helps compare responses by site area or role
- +Fast iteration on questionnaires reduces time between scouting cycles
- –No native turf imagery pipeline for multispectral or drone georeferencing
- –No built-in GIS export format for field boundary mapping
- –Limited support for instrument telemetry such as soil moisture sensors
- –Requires careful governance to keep respondent scoring consistent
Grounds managers
Run repeatability checks on field conditions
Standardized condition scoring over time
Athletic performance analysts
Capture GPS scouting observations metadata
Better condition notes for reviews
Show 2 more scenarios
Facilities project managers
Evaluate renovation outcomes with stakeholders
Documented improvement evidence
Survey internal teams and contractors on turf performance after upgrades and seeding cycles.
Operations coordinators
Compare maintenance protocols by opinion
Protocol decisions from consistent data
Standardize questionnaire inputs to compare outcomes for different mowing, fertilization, and aeration schedules.
Best for: Fits when grounds teams need standardized survey capture of field conditions, then convert results into zone-based work orders.
XLSTAT
SMBExcel add-in providing TURF analysis among its statistical and data analysis modules.
Experiment and statistical modeling workflow that ties turf field metrics to hypothesis-style comparisons and repeatable reporting.
XLSTAT is distinct in the turf analysis software market because it combines geospatial mapping workflows with a statistical modeling and experiment design toolchain. It supports golf course turf monitoring and sports field monitoring outputs through configurable analysis steps and report generation geared toward field and agronomy decisions.
- +Statistical modeling workflow supports experiment-style turf comparisons
- +Report generation turns analysis outputs into decision-ready documents
- +Configurable analysis pipeline supports repeatable season-long assessments
- +Georeferenced mapping outputs help align findings to field zones
- –Requires statistical workflow discipline to avoid inconsistent outputs
- –Automation and API surface for external systems is less obvious than GIS-first tools
- –User interface can feel math-heavy for non-analyst turf staff
- –Integration with weather and irrigation controller data may require extra steps
Risk analysts and planners
Model uncertainty from turf inputs
Percentile and interval results
Quality managers and corrective action teams
Prioritize incidents by impact
Ranked problem categories
Show 2 more scenarios
Data analysts and marketing teams
Explore relationships across variables
Reduced-dimensional views
Analysts compare multivariate methods and inspect loadings to find patterns across multiple inputs.
Research and engineering teams
Plan factor experiments on interventions
Interpretable factor results
Researchers generate experimental designs and analyze factor effects and contrasts across treatments.
Best for: Fits when grounds teams need statistical modeling on scouting results and zone-level comparisons across seasons.
Sawtooth Software
enterpriseAdvanced choice modeling platform that includes TURF analysis among conjoint, max-diff, and other analytics modules.
Georeferenced reporting workflow that standardizes scouting inputs into consistent map-based turf reports.
Sawtooth Software turns field and operational observations into georeferenced turf reports by combining map layers with a workflow for collecting updates. The tool focuses on field scouting capture, condition reporting, and repeatable reporting outputs for grounds teams managing multiple sites.
- +Standardizes scouting fields and report outputs across crews
- +Produces georeferenced turf report maps for site-to-site comparison
- +GIS export support helps integrate mapped results downstream
- +Repeatable condition update workflow supports ongoing monitoring
- –Advanced integrations depend on an external GIS or analytics pipeline
- –Complex zone workflows can require deliberate configuration discipline
- –Limited automation depth for multi-source sensor workflows
- –Multi-format output options feel narrower than some turf-first GIS tools
Pricing research teams
Test choices tied to turf offerings
Preference evidence for offers
Conjoint researchers
Measure trade-offs in package attributes
Utility estimates for trade-offs
Show 2 more scenarios
Research analysts and strategists
Segment responses from modeled preferences
Segment-level insights
Analysts examine modeled preference differences across respondent groups for turf-related decisions.
Researchers running prioritization studies
Rank turf-related items by relative preference
Comparative preference results
Teams collect and analyze respondent choices to compare relative preference among study items.
Best for: Fits when grounds teams need repeatable, mapped turf condition reporting across multiple sites.
Turf Intelligence
vertical specialistDrone-based multispectral analytics platform for golf course turf health, moisture, and stress pattern monitoring.
Change history on georeferenced zone data ties who edited what to specific mapped locations.
Turf Intelligence is built around georeferenced field maps where scouting notes and condition indicators stay tied to specific locations. The system supports zone-based recordkeeping and produces outputs designed for recurring inspections and seasonal trend review. Teams get usable governance through role-based access controls and audit trails that track changes to field data and documentation.
- +Georeferenced zone records keep scouting observations tied to exact locations.
- +Time-based comparison supports recurring inspections and seasonal condition review.
- +Role-based access and change tracking support controlled field-data workflows.
- +Exports align field history to reporting cycles for grounds stakeholders.
- –Analytics quality depends on consistent scouting routes and zone boundaries.
- –Advanced integrations require more admin work than map-only tools.
Grounds managers
Monthly condition review by zone
Faster review cycles
Field operations coordinators
Standardize scouting across crews
More reliable trends
Show 1 more scenario
GIS and reporting teams
Export maps for stakeholder dashboards
Lower manual rework
Send geospatial outputs to existing reporting workflows for site status communication.
Best for: Fits when grounds teams need controlled, georeferenced scouting history with recurring reporting.
Displayr
enterpriseAutomated TURF analysis platform with waterfall visualizations and AI-driven portfolio optimization for market researchers.
Displayr’s workflow templates generate consistent analysis outputs from new data without rebuilding dashboard logic each cycle.
Displayr is a turf analysis and reporting tool built around statistical workflows and interactive outputs for sports field monitoring and golf course turf monitoring. It imports datasets, transforms them, and publishes governed dashboards and documents that combine KPIs with geospatial views from your GIS layers.
- +Scriptable analytics pipelines that standardize turf scoring across projects
- +Publish-ready dashboards that combine KPIs with interactive mapping views
- +Repeatable templates reduce rework when scouting data arrives late
- +Strong dataset transformation tools for derived indices and grading rules
- –Turf-specific field workflows require configuration rather than native field modes
- –Advanced automation depends on comfort with Displayr scripting and authoring
Statistical analysts
Build reusable turf analysis templates
Reusable analysis workflows
Researchers and analysts
Identify key drivers of outcomes
Tree-based predictor groups
Show 2 more scenarios
Analytics teams
Visualize transitions in turf data
Flow visuals in reports
Teams generate Sankey diagrams from structured data and publish them inside analysis reports.
Market researchers
Analyze choice studies with published deliverables
Repeatable analytical deliverables
Teams analyze choice research and conjoint studies and include formatted outputs alongside related charts.
Best for: Fits when turf managers need governed, repeatable analytics reports for zone work using external GIS exports.
Conclusion
After evaluating 10 turf analysis software, LawnPro stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Turf Analysis Software
Grounds teams buy turf analysis software to turn field scouting into georeferenced condition maps, repeatable zone reporting, and action history tied to the next visit. This buyer guide covers Terranota, FieldX, and TurfNet, then grounds selection tradeoffs across Turf Analyzer, Real Green Systems, Turf Intelligence, LawnPro, Yardbook, Zappi, XLSTAT, Displayr, Sawtooth Software, and Appinio.
The tools reviewed here differ most in how they store zone-linked observations, how they track changes across scouting cycles, and how they integrate with external GIS workflows. Turf Analyzer emphasizes zone-linked treatment records across mapped condition changes, while Turf Intelligence adds change history on georeferenced zone data to show who edited what at each location.
Turf Analysis Software that maps zone condition, links scouting evidence to actions, and exports GIS-ready field reports
Turf analysis software captures turfgrass health assessment inputs like GPS scouting notes, photo attachments, and zone attributes, then organizes them into georeferenced maps for sports field monitoring or golf course turf monitoring. The operational value shows up when zone-based reporting stays consistent across crews and seasons, and when field evidence ties to follow-up work.
Some platforms focus on governance of mapped records rather than rich turf diagnostics. Turf Intelligence pairs georeferenced zone data with edit change history for accountability on mapped locations, while LawnPro ties georeferenced zone records to photo attachments for consistent interpretation across scouting cycles.
Zone-linked records, change accountability, and GIS export workflows
Teams also need predictable outputs for GIS and reporting so field evidence becomes map-based condition documentation rather than scattered notes. The strongest tools pair georeferenced zone records with exports and controlled workflows that reduce ambiguity between crews.
Zone-linked treatment and action history tied to mapped change
Turf Analyzer connects zone-linked treatment records to mapped condition changes across scouting cycles. This design supports workflows where applied actions and later condition maps must reconcile to the same areas.
Georeferenced zone organization for comparable season reporting
Real Green Systems organizes zone-managed reporting by tying scouting photos and notes to consistent field boundaries. The focus is repeatable season outputs that stay aligned when multiple scouting rounds occur.
Change history on georeferenced zone data for edit accountability
Turf Intelligence adds time-based change history on georeferenced zone records so edits can be traced to specific locations. This supports audit-style accountability for who changed what on the map.
Photo-backed georeferenced scouting with logged multi-person edits
LawnPro records georeferenced zone observations with photo attachments and includes audit logged editing for multi-person field work. This reduces misinterpretation when the same zone is revisited by different crews.
GPS scouting timelines that connect observations to follow-up actions
Yardbook uses GPS field scouting and zone treatment record timelines to link scouting notes to action history. It fits teams that want consistent zone mapping plus a simple action trail per map area.
API-enabled automation built around field-referenced zone mapping
Zappi ties zone mapping to field-referenced scouting records and offers API-enabled automation to reduce manual re-entry for recurring scouting. It fits integration-first teams that want external systems to drive or ingest scouting data.
Select by workflow fit: action-tracking depth, governance, and automation surface
After workflow fit, the next differentiator is integration depth and admin control for multi-user data entry. Some tools emphasize GIS exports and scripting templates, while others rely on API access and stricter zone boundary discipline to keep outputs comparable.
Choose action-history coupling if treatments must explain later map changes
Pick Turf Analyzer when zone-linked treatment records need to connect to mapped condition changes across scouting cycles. This matters when future work orders depend on reading the map as evidence of what changed after actions.
Choose edit governance and accountability when multiple users touch the same zones
Pick Turf Intelligence when accountability must include who edited which georeferenced zone and when. This supports controlled inspections where recurring reporting depends on traceable edits on the mapped locations.
Choose boundary-consistent reporting when zones must stay comparable across seasons
Pick Real Green Systems when season-to-season reporting requires consistent field boundaries tied to scouting evidence. The tradeoff is that high reporting quality depends on strict zone and naming discipline across crews.
Choose photo-backed scouting if interpretation errors come from missing context
Pick LawnPro when every observation needs photo attachments tied to the same georeferenced zone record. This supports consistent interpretation across scouting cycles where different people may describe turf symptoms differently.
Choose API-driven automation when scouting integration should be event-based
Pick Zappi when recurring scouting should reduce manual re-entry through API and automation. The constraint is that zone boundaries must remain consistent team-wide because advanced analytics depth depends on specific data capture formats.
Fork to analytics-first tooling when reporting logic must be generated from templates
Pick Displayr when governed, repeatable analysis outputs are generated from new data using workflow templates. Turf-specific field workflows require configuration and advanced automation depends on comfort with Displayr scripting and authoring.
Grounds teams that need georeferenced consistency, action traceability, or governed analytics
Organizations with multiple crews benefit most from platforms that keep zone boundaries stable and tie observations to clear mapped records. Teams that want automation and integration depth also need an explicit API or scripting workflow rather than manual export-only processes.
Sports field monitoring teams coordinating repeat scouting across crews
Yardbook and LawnPro fit when GPS scouting and zone-linked observations must stay interpretable after handoffs. Yardbook ties zone treatment record timelines to scouting notes and LawnPro attaches photos to the same georeferenced zone records.
Golf course turf monitoring teams that need governance and accountability on mapped edits
Turf Intelligence fits when change history on georeferenced zone data must show who edited what at specific mapped locations. This supports recurring inspections where traceability on the map is part of operational control.
Grounds organizations standardizing season-to-season zone reporting
Real Green Systems fits when zone-managed reporting ties scouting evidence to consistent field boundaries for comparable season outputs. The key operational requirement is strict zone and naming discipline to preserve comparability.
Integration-focused teams that want API-driven scouting capture and reduced re-entry
Zappi fits when zone mapping and field-referenced scouting records must connect to external systems through API and automation. The operational constraint is configuration discipline to keep zone boundaries consistent.
Mismatched zone boundaries, unmanaged capture discipline, and underpowered analytics expectations
Another common issue is assuming advanced analytics exists without committing to the required workflow discipline. Some tools offer scripting templates or statistical workflows, but those require structured inputs and repeatable capture patterns to produce stable outputs.
Switching or renaming zone boundaries between scouting cycles
Turf Analyzer notes that comparisons weaken when zone boundaries change between scouting cycles. Teams should lock zone boundaries and naming conventions before the first recurring inspection.
Letting multi-user edits happen without traceability on the map
Turf Intelligence provides change history on georeferenced zone data tied to who edited what at locations. Teams that allow edits without accountability should avoid tools that do not provide mapped change history.
Using photo-backed scouting without enforcing a structured input format
LawnPro reduces misinterpretation by tying photo attachments to georeferenced zone records, but interpretation still depends on consistent capture habits. Teams should define what to photograph and how observations map to zone attributes.
Expecting multisensor analysis without data capture format discipline
Yardbook calls out limited depth for soil chemistry mapping versus dedicated agronomy systems and warns that multi-sensor ingestion needs workflow discipline to avoid data drift. Teams should set expectations for what the platform can model and what capture process is required.
Planning advanced automation without allocating time for scripting or configuration
Displayr templates generate repeatable analytics outputs, but turf-specific field workflows require configuration rather than native field modes. Advanced automation in Displayr depends on comfort with Displayr scripting and authoring.
How We Selected and Ranked These Tools
We evaluated each platform on features that connect zone-linked scouting records to later reporting outputs, then separated governance and change traceability from basic map creation. Features carried 40% of the weighting because zone-linked treatment history, photo attachments, and change history directly affect repeatability of turfgrass health assessment records.
Ease and value each carried 30% because crews need predictable capture and later reporting, and map-only workflows often fail when automation or integration adds friction. Turf Analyzer ranked highest because zone-linked treatment records connect applied actions to mapped condition changes across scouting cycles, and its georeferenced maps plus GIS exports support action-review reporting workflows.
Frequently Asked Questions About Turf Analysis Software
How do Turf Analyzer and Turf Intelligence handle georeferenced mapping for repeat field visits?
Which tools connect zone work back to treatment records in a traceable way?
How does Zappi’s API and automation support data ingestion from other operational systems?
When multiple crews edit the same field zones, which platforms offer admin controls and audit logs?
What breaks if zone boundaries drift between scouting cycles in tools that support zone-based reporting?
Where does Displayr fall short for teams that need a dedicated mobile scouting app?
How do Sawtooth Software and Yardbook differ in how crews capture and standardize observations?
Which tool is better for statistical experiment design on turf field metrics rather than map-centric reporting?
How does Turf Intelligence handle change history on georeferenced zone data?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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