Arabidopsis thaliana is a widely used model in plant biology, where histology (HT), histochemistry (HC), immunohistochemistry (IHC), and immunofluorescence (IF) are applied to study cellular structures, macromolecules, and antigens. Despite their extensive use, protocols lack standardization and exhibit substantial variability in critical aspects such as reagent handling, exposure times, and the proper use of controls. This methodological heterogeneity represents a major gap, limiting reproducibility and comparability between studies. Unlike previous methodological reviews, this work focuses exclusively on A. thaliana, systematically identifies reporting omissions, and proposes a roadmap for standardization. A narrative review of literature retrieved from Scopus and Web of Science was conducted with the aim of analyzing methodological approaches, identifying inconsistencies, and offering recommendations for improved laboratory practices. The analysis revealed frequent omissions in the reporting of critical steps such as dehydration, clearing, antigen retrieval, enzyme blocking, and the incorporation of positive and negative controls, which compromise the reliability of results and hinder inter-laboratory validation. Based on this evidence, three key recommendations are emphasized: (i) organ-specific selection and explicit justification of fixatives and stains; (ii) mandatory incorporation of positive and negative controls in IHC and IF; and (iii) adoption of a minimum reporting checklist to enhance reproducibility. Beyond cell morphology, the reviewed studies demonstrate applications in plant physiology, phytogenetics, and pathophysiology. By combining critical analysis with actionable guidelines, this review contributes a practical reference to strengthen methodological rigor in histological and immunological studies of plants.

Sap analysis provides a fast and promising approach to diagnosing plant nutritional status, yet methodological gaps remain a crucial obstacle to widespread adoption. Understanding how different extraction methods influence sap composition is key to improving the consistency and diagnostic reliability of this technique. Therefore, five methods were compared based on a range of chemical and physical parameters of broccoli petiole sap. Multiple statistical approaches were used to evaluate method effects on individual parameters and their inter-relationships. Extraction method significantly influenced chemical profiles—altering means, variability and distributional shapes—whereas physical attributes varied less across methods. Relationships among traits were observed; however, the consistency of patterns varied depending on the method. Overall, these results suggest that refining method selection could enhance both diagnostic reliability and the depth of interpretive analysis. This calls for rethinking current sap analysis practices, raising awareness of methodological variability and encouraging the development of robust, standardized approaches for reliable and comparable sap-based diagnostics.