JPA publishes original research, reviews, methods papers, and data resources that advance precision agriculture and digital farming. Submissions should demonstrate rigorous methods and clear agronomic or operational relevance.

Interdisciplinary studies that connect agronomy, engineering, geospatial analytics, and farm economics are encouraged. Explain how the technology or workflow improves decision making at field or enterprise scale.

We welcome validated approaches for crop, soil, and resource management, including scalable workflows that can be replicated across regions or seasons.

If the work introduces new sensors, algorithms, or automation systems, describe how performance was benchmarked against existing practices. Clear comparisons help readers understand adoption tradeoffs and operational fit.

Organize the manuscript so readers can trace the workflow from data collection to management outcomes. Use clear section headings and provide enough detail for replication.

• Title page with author affiliations and corresponding author details
• Structured abstract with objectives, methods, results, and conclusions
• Introduction that defines the agronomic context and research gap
• Methods with detailed field sampling and analytical protocols
• Results with validated outcomes and clear interpretation
• Discussion linking findings to management or sustainability implications
• Conclusion highlighting key contributions and future work

Use concise, consistent language to describe agronomic workflows, equipment settings, and analytical outputs. Avoid mixing units or terminology across sections to keep results interpretable for interdisciplinary readers.

• Use clear headings and consistent terminology
• Define abbreviations and crop or zone codes at first use
• Provide units for all measurements and metrics
• Include figure legends that describe sample sizes and data sources
• Prepare tables in editable format with clear headings
• Label supplementary files clearly and reference them in the text

Authors should provide data availability statements and, when possible, deposit data in trusted repositories. Code or pipelines should be shared or documented to support reproducibility.

Describe dataset versions, metadata standards, and any preprocessing decisions so readers can reproduce analyses with the same inputs.

• Include accession numbers or repository links
• Describe preprocessing and quality control steps
• Document software versions and computational environments
• State any access restrictions for sensitive data

Describe field boundaries, management zones, and geospatial reference systems so results can be replicated and compared across sites. If variable rate treatments are used, summarize prescription logic and the equipment settings that were applied.

Report calibration procedures for yield monitors, sensors, and UAV or satellite imagery. Include dates of calibration and any validation checks performed before or after the trial.

When trials span multiple seasons, summarize year to year differences in weather, management, and field conditions. This context helps readers interpret variability across sites and seasons.

Explain how sensor, imagery, and yield datasets were aligned in space and time. Provide a clear description of data fusion steps, interpolation methods, and any filtering applied to remove noise or outliers.

If models or decision support tools are used, report training data, validation datasets, and benchmark baselines. Discuss limitations related to field heterogeneity, missing data, or operational constraints.

Include uncertainty estimates or confidence intervals for predictive outputs. Clear uncertainty reporting improves decision readiness for growers and advisors.

When available, report cost, labor, or input savings alongside yield or quality outcomes. Explain the assumptions behind economic calculations so readers can interpret applicability across farm contexts.

Sustainability metrics such as water use efficiency, nutrient balance, or emissions estimates should include units, baselines, and methods. Clear reporting helps readers compare interventions across seasons and regions.

Describe any software or firmware dependencies that could affect reproducibility. If proprietary tools are used, note how results could be independently verified.

Provide documentation for data cleaning steps and any manual adjustments to sensor outputs. Transparent processing details reduce ambiguity during peer review.

Figures should be legible at publication size and include map legends, scale bars, and north arrows where appropriate. Use consistent color scales for spatial data to avoid misinterpretation.

• Submit high resolution figures in standard formats
• Label axes and include units for quantitative plots
• Provide color blind friendly palettes when possible
• Ensure tables are editable and include footnotes

• Ensure references are complete and consistent
• Include DOIs where available
• Use standard citation formats
• Confirm all in text citations appear in the reference list

• Provide trial permissions or data use agreements
• Disclose conflicts of interest and funding sources
• Follow reporting standards for precision agriculture studies
• Describe limitations and generalizability

Before submission, ensure file names are descriptive and match the order in the manuscript. Include a concise cover letter that summarizes scope fit, novelty, and data availability.

JPA uses single blind peer review. Reviewers evaluate study rigor, data quality, and clarity of reporting. Initial decisions are typically issued within about 12 days depending on reviewer availability.

Provide complete responses to reviewer comments and highlight changes in a revision note to keep the workflow on schedule.

Accepted manuscripts move to production for copyediting, proof review, and DOI registration. Articles are published under CC BY 4.0 to support open access reuse with attribution.

Authors should review proofs promptly to confirm accuracy of figures, tables, and metadata.

If data or code links change during production, notify the editorial office so metadata can be updated before publication.

APCs are applied after acceptance and cover peer review management, production, and archiving services. Partial waivers may be available for eligible authors. Contact the editorial office for guidance.

Manuscripts submitted via ManuscriptZone (https://oap.manuscriptzone.net/) or the Simple Submission Form (https://openaccesspub.org/manuscript-submission-form) follow the same APC policy and review standards.

Use this short checklist to ensure the submission is complete and ready for review. Keeping the checklist concise helps authors confirm compliance without burying key steps.

• Scope alignment confirmed
• Data availability statement included
• Field protocols and permissions documented
• Cover letter prepared with scope summary
• Data use and disclosure statements included

Manuscripts should clearly state how findings translate into management decisions or operational improvements. Include any economic, efficiency, or sustainability implications that would guide adoption in real farm settings.

If the work targets advisory services or extension use, summarize the recommended actions and the conditions under which they apply.

For questions about formatting or submission steps, contact [email protected].

The editorial office can advise on scope fit, data availability wording, and presentation of agronomic outcomes.

Share a short pre submission summary if you need rapid scope confirmation.

JPA is committed to rigorous, transparent publishing in precision agriculture and digital farming. We emphasize reproducible field trials, clear reporting of agronomic outcomes, and ethical compliance across all article types.

The editorial office supports authors, editors, and reviewers with clear guidance and responsive communication. For questions about scope or workflow, contact [email protected].

We encourage continuous improvement in reporting practices and share updates that help the community maintain high standards in agricultural data science, field validation, and technology transfer.