Accept the review only if the manuscript falls sufficiently within your field(s) of expertise to allow a competent assessment of its main methodology, conclusions and claims, and possible impact.

Check for any actual, potential, or perceived conflict of interest. If a relationship with the authors, their institution, funder, commercial product, or a competing project could reasonably affect your impartiality, inform the editorial office before accepting or refuse to review from the start.

Make sure you can return the review within the requested timeframe. If you need a short extension, contact the editorial office as early as possible.

Treat the invitation and manuscript as confidential.

Be objective, evidence-based, and respectful. Critique the work, not the authors.

Do not use the manuscript’s unpublished information obtained through peer review for your own research, grant proposals, publications, commercial activity, or the benefit of another person.

Suggest additional references only when they are genuinely necessary to support, correct, or contextualize the manuscript and discourage excessive self-citation by the authors.

If you suspect plagiarism, duplicate publication, fabricated or manipulated data/images, unethical research, undisclosed conflicts of interest, undisclosed, inappropriate and/or excessive use of AI, or any other integrity problem, report your concern confidentially to the Editor. Do not accuse the authors directly.

Is the manuscript within the journal’s scope and relevant to an international readership in agricultural and biological sciences?

Does it provide a meaningful new finding, method, dataset, synthesis, or practical insight rather than only a (local) description of an already much investigated topic, with limited scientific interpretation and value?

For applied research, is the practical applicability demonstrated with adequate scientific evidence rather than asserted from a single treatment comparison or a solely descriptive observation?

For review articles, do the authors critically synthesize the field and indicate remaining questions and lines for further study? Do they clearly identify their own documented contribution or expertise, as this is required by AGRISP?

Are the objectives and/or hypotheses explicit and logically derived from the Introduction?

Is the design capable of answering the stated question(s)? Check the experimental unit, controls, treatment structure, randomization, and blinding where appropriate, and also the independence of observations.

Are the sampling strategy and the sample size adequate and justified by the study design?

For multi-year, multi-location, greenhouse, or field studies, is the environmental (including meteorological) variation handled appropriately in the design and analysis?

Are species, cultivars, breeds, strains, isolates, cell lines, microorganisms, pests/pathogens, vectors, soils, experimental sites, and other biological or environmental materials identified precisely enough to permit interpretation and replication?

Strong claims about pathogen, pest, microbial, or genetic identity should be supported by validated and, where appropriate, independent methods.

Are methods properly cited, and are any modifications made by the authors clearly indicated and validated?

Are protocols described in enough detail to reproduce the work?

If a commercial product or proprietary method is tested, are its identity, active components or composition, dose, and experimental conditions described sufficiently to evaluate the claim?

Do the statistical methods match the design and type of data?

Are measures of variability, significance and uncertainty reported (for example SD, SE, confidence intervals) and clearly defined?

Are exact sample sizes (n) and the experimental unit clear in text, tables, or figure legends?

Are statistically significant differences distinguished from biological or practical importance?

Are models validated and sufficiently described?

Do the Results report the findings objectively without introducing interpretation that belongs in the Discussion?

Do tables and figures show the underlying pattern clearly and contain the information needed to interpret the analysis?

Check whether values are consistent across the abstract, text, tables, and figures; whether percentages have valid denominators; and whether units and sample sizes are coherent.

For images (e.g., microscopy, electrophoresis, blots, symptoms, histology), are controls, scale bars, labels, and image processing described appropriately? Is the quality of the images sufficient to contribute to exemplify the results of the research?

Are the conclusions and claims (of novelty) directly supported by the data, or do the authors overgeneralize beyond the experimental conditions, locations, species, genotypes, seasons, or sample studied?

Does the Discussion explain how the results agree or conflict with relevant recent literature and offer a scientifically plausible interpretation?

Are alternative explanations and important study limitations acknowledged?

Do the conclusions answer the research objective without simply repeating the Results?

Are key recent and internationally relevant studies cited, including work that may not support the authors’ interpretation?

Are primary sources used for scientific claims whenever possible?

Do not spend excessive time correcting reference style. Where appropriate, give the authors a general reminder to consult the Instructions for Authors on the Journal’s website. Focus on missing, inappropriate, obsolete, or misleading citations that affect scientific interpretation.

Is the field design described (experimental unit/plot size, number of replicates, blocking/randomization, border effects, locations and years)?

Are cultivar/hybrid, predecessor crop(s)/rotation scheme, sowing/planting conditions, soil characteristics, fertilization, irrigation, crop protection, and weather or other key environmental variables reported when they affect interpretation?

Are agronomic treatments compared against appropriate untreated, standard-practice, and/or commercial controls?

If yield, quality, disease/pest incidence and severity, soil indicators, or economic outcomes are claimed, are measurement methods and sampling schemes valid and representative?

In monitoring and field assays is the origin of samples and the number of samples per area/region) properly indicated

for efficacy claims, is evidence sufficiently replicated across relevant conditions to support practical recommendations?

newly developed biological control products should have been tested in vitro (laboratory) and at least in an experimental greenhouse setting, but preferably also under practical greenhouse and field conditions.

Are organisms identified using methods appropriate to the taxonomic claim, and are cultures, isolates, sequences, or other reference materials available where relevant?

Are sampling strategy, spatial/temporal replication, detection limits, contamination controls, and negative/positive controls adequate?

For microbiome or high-throughput data, are sequencing depth, filtering, normalization, compositional-data issues, batch effects, multiple testing, and repository deposition addressed?

For biodiversity or ecological claims, do the sampling design and statistical models support generalization beyond the sampled sites and dates?

Are the construct, strain/cell line, transformation or editing method, selection procedure, controls, and validation of the engineered phenotype described clearly?

For PCR/qPCR and other molecular diagnostics, are primer/probe sequences, amplification conditions, controls, specificity, sensitivity, normalization, and interpretation criteria adequately reported?

For omics, molecular markers, or bioinformatics, are databases, accession numbers, pipelines, software versions, thresholds, and validation steps provided?

For engineered biological systems, are relevant regulatory constraints (prohibition by law), biosafety, off-target effects, stability, reproducibility, and limitations considered where appropriate?

Is approval by an appropriate animal ethics/bioethics committee reported where required, including the protocol or approval information requested by AGRISP?

Are species, breed/line, sex, age, physiological status, housing, feeding, treatment allocation, inclusion/exclusion criteria, and clinical endpoints described when relevant?

Are randomization, blinding, comparator groups, sample-size rationale, adverse events, and humane endpoints addressed where appropriate?

For diagnostic-accuracy studies, is the reference standard defined and are sensitivity, specificity and uncertainty reported appropriately?

For observational or herd-level studies, are clustering, selection bias, and the true experimental/epidemiological unit handled correctly?

Is the purpose and scope of the review clearly defined and scientifically important?

For systematic or evidence-based reviews, are search strategy, databases, eligibility criteria, screening, data extraction, risk-of-bias assessment, and synthesis methods transparent and reproducible?

For narrative reviews, is the literature selection balanced rather than selective, and does the article provide critical synthesis rather than a catalogue of publications?

Does the review identify unresolved questions, conflicting evidence, methodological limitations, and priorities for future research?

Is the authors’ contribution to the field covered by the review adequately demonstrated?

Check that required ethics approval and informed consent/animal welfare information are present when relevant. AGRISP requires ethical information for work involving humans or animals.

Check that funding sources and potential conflicts of interest are disclosed.

If the study involves potentially regulated organisms, pathogens, genetically modified material, field release, or biosafety-sensitive procedures, verify that the manuscript states the approvals or conditions necessary to interpret the work.

Alert the Editor confidentially if you notice (self)plagiarism, substantial text overlap, undisclosed, inappropriate and/or excessive use of AI, duplicate or salami publication, inconsistent or implausible data, image irregularities, copyright issues involving images, undisclosed reuse of data, inappropriate authorship-related information, or another integrity concern.

what the study aimed to do;

what type of evidence was generated;

what you consider the main contribution;

the principal scientific issue(s) that must be addressed, if any.

any issues with language and style.

hypothesis formulation;

experimental design, controls, replication, sampling, or ethics;

methodological validity or reproducibility;

incorrect and/or insufficient statistical analysis;

results that do not support the conclusions and claims;

missing validation or essential data;

major problems concerning originality, scientific context, or interpretation, including indications of plagiarism or self-plagiarism.

your publication recommendation and a short rationale;

conflicts of interest and/or limitations in your own expertise that the Editor should know;

suspected plagiarism, duplicate publication, image/data manipulation, ethical problems, or other integrity concerns.

Do not rewrite the whole manuscript or make (only) language editing the main purpose of the review.

Do not demand experiments that are interesting but unnecessary to test the stated hypothesis or support the central claims.

Do not require authors to cite your work unless it is genuinely relevant and necessary.

Do not make personal comments about the authors, institutions, country, career stage, or presumed competence.

Do not recommend rejection only because results are negative, unexpected, or do not support the reviewer’s preferred hypothesis, provided the study is rigorous and the conclusions match the evidence.

Do not disclose your identity in the report or in file metadata.

ARRIVE guidelines - in vivo animal research;

STROBE-Vet - observational epidemiological studies in veterinary medicine;

REFLECT - randomized controlled livestock and food-safety trials;

PRISMA - systematic reviews and meta-analyses;

MIQE - quantitative real-time PCR experiments;

FAIR principles and discipline-appropriate repositories - research data and reusable digital outputs.