Submit to this Journal Review for this Journal Propose a Special Issue

Article Menu

Share Help Cite Discuss in SciProfiles

Open AccessReview

Peer-Review Record

Global Research Trends and Thematic Evolution of Blueberry (Vaccinium spp.) Science: A Bibliometric Analysis

Horticulturae 2025, 11(12), 1501; https://doi.org/10.3390/horticulturae11121501

by David Alejandro Pinzon¹

, Gina Marcela Amado²

, Jader Rodriguez²

and Edwin Villagran^2,*

Reviewer 1: Anonymous

Reviewer 2: Anonymous

Reviewer 3: Anonymous

Horticulturae 2025, 11(12), 1501; https://doi.org/10.3390/horticulturae11121501

Submission received: 12 November 2025 / Revised: 2 December 2025 / Accepted: 5 December 2025 / Published: 11 December 2025

(This article belongs to the Section Fruit Production Systems)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This study presents an excellent scientific approach to blueberries (Vaccinium spp.), demonstrating a consolidated, interdisciplinary field with a sustained growth trajectory over nearly four decades. The research reveals a field that is transitioning from a purely biological understanding to a biotechnological, digital, and functional perspective, where fruit quality and traceability are seen as quantifiable and modelable attributes.

When researchers export records with all text fields and run a bibliometric analysis (e.g., word clouds, co-occurrence term analysis, clustering), these terms may appear as relevant research concepts when, in fact, they are merely study type classifications. If not filtered out, these terms tend to inflate irrelevant clusters, create groupings such as "human–article–controlled study," which hold no conceptual value, and pollute co-occurrence analyses. Moreover, and what I consider more critical, they may make it seem that the analyzed topic relates to "controlled studies" or "human populations," even when that is not the focus.

Additionally, the authors did not merge common words that differ only in singular/plural forms (e.g., "fruit" and "fruits"), even though they refer to the same thing. This is also a common oversight in bibliometric analyses. I would like to note that if the authors are familiar with the tool, these issues can be resolved using a thesaurus.

The role and importance of Figure 8 in the study were unclear. Although it presents interesting data, what is the importance of knowing these details about the authors? I believe it is purely statistical data with no relevance to the approach in question.

In the conclusion, regarding "with the aim of standardizing analytical methodologies, genomic databases, and quality assessment criteria" – on what basis did the authors reach this conclusion?

Author Response

Bogota 02 December 2025.

Review report 1.

We sincerely thank Reviewer 1 for the depth, clarity, and relevance of the comments provided. Your observations have substantially enriched the manuscript, helping to improve the methodological rigor, coherence, and interpretive quality of the study. The authors have carefully addressed all suggestions, which have now been incorporated into the revised version of the manuscript. All modifications are clearly marked in yellow within the text and are detailed in the corresponding response letter. We greatly appreciate your constructive contribution to strengthening this work.

General comments.

Reply. We thank the reviewer for this positive assessment. We agree that the evolution of blueberry research reflects a shift from traditional biological studies toward an integrated biotechnological and digital framework in which fruit quality, traceability, and functional attributes are increasingly treated as quantifiable and modelable variables. This perspective aligns with our findings and reinforces the relevance of the interdisciplinary approach adopted in this study.

In my view, the authors did an excellent job with the introduction and materials and methods sections. However, there are flaws in the results generation, particularly concerning figures 11 and 12. Words such as "human," "controlled study," and "article" are likely to be erroneously included in bibliometric analyses, especially when data extraction is based on automatic Scopus metadata. That is, they do not necessarily belong to the title, abstract, or author keywords but are rather standardized indexing fields automatically assigned by librarians or algorithms. When researchers export records with all text fields and run a bibliometric analysis (e.g., word clouds, co-occurrence term analysis, clustering), these terms may appear as relevant research concepts when, in fact, they are merely study type classifications. If not filtered out, these terms tend to inflate irrelevant clusters, create groupings such as "human–article–controlled study," which hold no conceptual value, and pollute co-occurrence analyses. Moreover, and what I consider more critical, they may make it seem that the analyzed topic relates to "controlled studies" or "human populations," even when that is not the focus. Additionally, the authors did not merge common words that differ only in singular/plural forms (e.g., "fruit" and "fruits"), even though they refer to the same thing. This is also a common oversight in bibliometric analyses. I would like to note that if the authors are familiar with the tool, these issues can be resolved using a thesaurus.

Reply. We appreciate the reviewer’s detailed and constructive observations. We fully agree that terms such as “human,” “controlled study,” and “article” originate from Scopus indexation fields and should not be interpreted as meaningful research concepts. In response, we regenerated Figures 11 and 12 using only author-provided keywords, applied a thesaurus to merge singular/plural variants (e.g., fruit/fruits), and removed all automatically indexed metadata entries. We also revised the entire discussion to ensure conceptual coherence with the corrected figures.

As a result, the new section now reads as follows:

3.14. Most frequently used keywords

The co-occurrence analysis and keyword word cloud (Figure 11) reveal the predominant thematic and conceptual trends in the literature on blueberries (Vaccinium spp.). As expected, the terms “blueberry” (133 occurrences) and “vaccinium” (127) constitute the central anchors of the network, supported by highly connected terms such as “fruit” (181) and “vaccinium corymbosum” (90). This semantic core confirms the consolidation of the crop as a model system for studying functional foods, phytochemistry, and agro-industrial innovation. The prominent presence of terms such as “anthocyanin” (50), “antioxidants” (46), “antioxidant activity” (14), and “phenols” (19) reinforces the strong scientific focus on the bioactive compounds that define the nutraceutical value of the species [37,129,130]. Together, these elements depict a mature research field that integrates plant physiology, food chemistry, and biotechnology.

Likewise, the network shows a robust line of research related to postharvest management and fruit quality, reflected in the high frequency of terms such as “food storage” (46), “food handling” (43), “food preservation” (33), “food processing” (38), and “shelf life” (24). These concepts highlight the emphasis placed on the stability of phenolic metabolites, as well as on the optimization of handling and processing strategies to maintain fruit quality during commercialization [129,131]. The appearance of terms such as “freezing” (16), “freeze drying” (15), and “food packaging” (15) underscores the relevance of technological interventions aimed at preserving antioxidant capacity in fresh and processed blueberries [132–134]. Additionally, descriptors such as “temperature” (18), “color” (17), and “quality control” (19) point to the importance of physicochemical monitoring across the supply chain key considerations for industrial standardization, export competitiveness, and quality assurance [135–137].

Finally, the presence of biological and physiological descriptors such as “metabolism” (23), “microbiology” (20), “physiology” (20), “ascorbic acid” (20), and “animal” (20) reveals the growing integration between agricultural sciences, postharvest biology, and biomedicine. These links reflect the ongoing interest in understanding how blueberry-derived compounds influence metabolic pathways, oxidative responses, and cellular regulation in different biological models [138]. Such research has been instrumental in advancing evidence on the role of blueberries in mitigating oxidative stress, inflammation, neurodegeneration, and other chronic health conditions [139,140]. Overall, the co-occurrence analysis shows that the study of Vaccinium spp. has evolved from a primarily agronomic focus to a holistic and interdisciplinary domain that encompasses phytochemical complexity, processing technologies, and potential human health benefits.

Figure 11. Most frequently used keywords by authors.

3.14. Keyword co-occurrence network

The keyword co-occurrence network (Figure 12) reveals a highly interconnected thematic structure centered on “blueberry,” “fruit,” and “Vaccinium.” After data cleaning and the removal of controlled vocabulary from Scopus indexation fields, the resulting map shows several dense clusters that collectively articulate the dominant research axes in blueberry science: nutritional and physiological studies, agronomy and production systems, food processing and chemistry, postharvest preservation, and plant health and phytopathology. The proximity among nodes reflects strong concep-tual co-occurrence, illustrating how plant biology, agronomy, food chemistry, and hu-man health have become increasingly integrated within the scientific community.

Red cluster – Nutrition, physiology, and chronic disease research: This cluster is organized around “blueberry,” “metabolism,” “antioxidant activity,” “microbiology,” “biological activity,” and terms related to metabolic and neurodegenerative conditions such as “Alzheimer disease,” “dementia,” or “non-insulin dependent diabetes.” This cluster encompasses the most consolidated body of research linking blueberry con-sumption, polyphenolic compounds, and physiological responses in humans. Studies in this domain investigate the effects of blueberry intake or phenolic extracts on oxidative stress, cognitive performance, gut microbiota, metabolic regulation, and biomarkers of chronic disease, particularly among older adults [126,141,142]. The co-occurrence of polyphenol, dietary fiber, flavonoid, and resveratrol indicates a strong focus on the bio-chemical pathways underlying neuroprotection, inflammation modulation, and meta-bolic homeostasis. Overall, the red cluster positions blueberries as a reference model in nutraceuticals and functional foods, integrating human physiology, phenolic chemistry, and experimental evidence on the prevention of chronic and neurodegenerative disor-ders.

Figure 12. Keyword co-occurrence network.

Green cluster – Production systems, agronomy, and digital agriculture: The green cluster is dominated by the terms “fruit,” “plants (botany),” “cultivar,” “crop yield,” “irrigation,” “image processing,” “fruit quality,” “deep learning,” “neural networks,” and “hyperspectral imaging.” This group captures the agronomic and technologi-cal-productive dimension of blueberry research. On one side, the cluster includes con-cepts related to plant physiology, crop management, cultivar performance, and yield. On the other, it integrates advances in agricultural digitalization through computer vi-sion, machine learning, and non-destructive optical sensing. These tools have been ap-plied to fruit grading, color and texture characterization, maturity prediction, and au-tomated disease detection [49,73,84]. The involvement of terms linked to quality evalu-ation, regression analysis, and multivariate modeling reflects the use of analytical frameworks to enhance quality control throughout the production chain [46,61,148]. Altogether, the green cluster illustrates the transition of blueberry cultivation toward precision agriculture, where sensor technologies, data analytics, and intelligent algo-rithms improve efficiency, productivity, and fruit quality.

Yellow cluster – Food processing, chemistry, and phenolic compounds: This cluster centers on “processing,” “chemistry,” “anthocyanin,” “phenols,” “phenol de-rivative,” “blueberry juice,” “enzyme activity,” “ultrasound,” and “encapsulation.” This group represents the core of food chemistry and food processing research. The co-occurrence patterns indicate strong interest in the extraction, stability, degradation kinetics, and functionality of anthocyanins and other phenolic compounds, as well as the influence of thermal and non-thermal processing techniques such as heating, pasteurization, ultrasonics, and microencapsulation on antioxidant retention [57,151,152]. Terms such as chemistry, enzyme activity, and phenol derivative underscore the role of biochemical transformations and matrix interactions during processing and product formulation [153–155]. In summary, the yellow cluster captures the physico-chemical and technological foundation of blueberry research, focusing on how pro-cessing conditions modulate the preservation and bioavailability of functional com-pounds.

Purple cluster – Postharvest quality, physicochemical properties, and shelf life: The purple cluster is organized around “food storage,” “food quality,” “physicochemical property,” “drying,” “freezing,” “osmotic dehydration,” and “preservation.” This cluster encompasses studies dedicated to postharvest behavior and shelf-life extension of blueberries and blueberry-based products. Research within this group quantifies the effects of storage temperature, water activity, dehydration processes, freezing protocols, and controlled-environment conditions on texture, color, firmness, and other quality parameters. These studies have enabled the identification of optimal combinations of temperature, humidity, and time that minimize quality losses and maintain acceptable sensory and nutritional attributes throughout distribution and storage [149,150]. Thus, the purple cluster represents a methodological axis focused on physicochemical char-acterization and optimization of preservation strategies, crucial for the development of dehydrated ingredients, shelf-stable products, and value-added blueberry derivatives.

Blue cluster – Phytopathology, crop ecology, and plant health in Vaccinium: This cluster centers on “Vaccinium,” connected with “plant disease,” “fungi,” “Monilinia vaccinii-corymbosi,” “disease incidence,” “fungal disease,” “disease control,” “pest control,” “integrated pest management,” and species such as Rubus glaucus and Malus × domestica. This group corresponds to the phytopathological and ecological dimension of blueberry research [143,144]. Its co-occurrence structure highlights fungal diseases, pathogen ecology, epidemiology, and the development of control strategies that en-compass both chemical and non-chemical approaches. The presence of terms like fruit production and crop production indicates that plant health is analyzed in relation to productivity and crop stability, integrating cultural practices, disease-resistant cultivars, fungicide use, and biological control within broader IPM frameworks [53,62,145–147]. This cluster provides the agronomic and phytosanitary foundation of the field, identi-fying major pathogens, quantifying their impact on yield and fruit quality, and pro-posing management approaches that improve resilience and sustainability in Vaccinium cropping systems.

Together, the five clusters illustrate how blueberry research has evolved from taxonomic, physiological, and phytosanitary foundations toward a multidimensional landscape that integrates plant biology, agronomy, food chemistry, human health, and industrial technology. The co-occurrence structure reflects the convergence of produc-tion, processing, functional properties, and chronic disease prevention, positioning Vaccinium spp. as a strategic model in the development of functional foods, high-efficiency production systems, and sustainable agro-industrial pipelines.

Reply. We thank the reviewer for this valuable comment. We agree that, in its previous form, Figure 8 did not sufficiently articulate its analytical relevance, which may have given the impression that it provided only descriptive or author-level statistical information. In response, we revised both the figure description and the corresponding discussion section to clarify its scientific purpose and contribution to the study. Specifically, we now explicitly frame the co-authorship network as an analytical tool that reveals how collaborative structures shape the conceptual, methodological, and technological evolution of research on Vaccinium spp. The updated text highlights the role of author clusters in consolidating research lines such as automation and precision agriculture, antioxidant chemistry, postharvest quality, and sustainability. This reframing ensures that the figure contributes meaningfully to understanding how different scientific communities have influenced the field’s interdisciplinary development over time.

Accordingly, the text was reorganized as follows:

The co-authorship network (Figure 8) reveals the collaborative structure underly-ing scientific production on Vaccinium spp., comprising 11 main authors, 20 links, and a total link strength of 75, which together reflect a medium level of cooperation and a clear thematic organization. Rather than providing merely descriptive statistics, this network illustrates how specific author groups have shaped the conceptual and methodological evolution of blueberry research over time.

The strongest collaborative nucleus is led by Arnold Walter Schumann (11 docu-ments, 159 citations, link strength 27) and Qamar Uz Zaman (10 documents, 156 cita-tions, link strength 27), who form a stable and highly connected cluster centered on automation, mechanization, and artificial intelligence applied to blueberry management [94]. Their sustained co-authorship particularly in maturity detection, precision spray-ing, and harvest optimization demonstrates how technological innovation in blueberry production has emerged from long-standing research partnerships that bridge North America and Asia.

A second, more temporally earlier cluster is formed by Luke R. Howard, Ronald L. Prior, and Cindi R. Brownmiller, whose work between 2010 and 2014 established foundational knowledge on anthocyanins, polyphenols, and antioxidant stability during processing [89,105]. Their prominent citations and bridging position in the network in-dicate that these biochemical studies provided experimental baselines that later enabled the transition toward digital, postharvest, and AI-assisted quality modeling.

Finally, intermediate authors such as David C. Percival, Peter L. Havard, and Wil-helmina Kalt play an integrative role that connects technological innovation with ag-ronomic performance and food chemistry. Percival’s research on yield estimation, au-tomated harvesting, and energy and carbon assessments in wild blueberries [61,106] links the network to sustainability and production efficiency. Havard contributes an economic and engineering perspective through studies on technological feasibility and cost-effective precision agriculture [101,107]. Kalt provides a biochemical bridge through her influential work on anthocyanins, phenolics, and antioxidant capacity in processed products [11]. Overall, the co-authorship network highlights how collaborative ties rather than isolated contributions have shaped the interdisciplinary trajectory of blueberry research, connecting technological development, biochemical quality, and sustainable production within a unified scientific framework

In the conclusion, regarding "with the aim of standardizing analytical methodologies, genomic databases, and quality assessment criteria" – on what basis did the authors reach this conclusion?

Reply. We appreciate the reviewer’s insightful comment. We agree that the previous statement in the conclusion suggesting the existence of an intention to standardize analytical methodologies, genomic databases, and quality assessment criteria was not directly supported by the bibliometric evidence. The wording could indeed imply that such coordinated efforts already exist or were explicitly identified through our analysis, which was not the case. To address this, we revised the conclusion to avoid any unsupported inference and to more accurately reflect the findings of our co-occurrence, cluster, and collaboration analyses. The updated version clarifies that our recommendation is prospective rather than descriptive: it outlines an opportunity for methodological convergence and international cooperation based on the thematic fragmentation observed in the field, rather than suggesting that a standardized framework is already in place.

Accordingly, the conclusion was reformulated as follows:

Scientific research on blueberries (Vaccinium spp.) has evolved into a consolidated interdisciplinary domain that integrates plant physiology, food science, engineering, and biotechnology. The analysis of 474 publications over nearly four decades reveals a sustained and accelerating growth trajectory, supported by strong international col-laboration networks and institutional leadership concentrated in the United States, China, and Canada. The thematic structure of the field organized into five well-defined clusters demonstrates a transition from agronomic foundations toward technologi-cally enhanced approaches that incorporate bioactive compound analysis, postharvest modeling, and digital tools for crop monitoring and quality assessment.

Based on the evidence generated, several strategic research needs emerge. First, greater integration between agronomic research and multi-omics approaches (ge-nomics, metabolomics, and phenomics) is required to elucidate metabolic pathways associated with fruit quality, stress tolerance, and postharvest behavior. Second, there is a need to advance predictive modeling of blueberry responses to climate change, par-ticularly under temperature extremes, water stress, and shifting production areas. Third, the standardization of analytical protocols for phenolic and antioxidant quanti-fication (ORAC, FRAP, DPPH) is essential to improve comparability and methodolog-ical reproducibility across laboratories. Additionally, the expansion of digital traceabil-ity systems and AI-based quality monitoring represents a crucial frontier for strength-ening sustainability, transparency, and efficiency throughout the blueberry value chain.

As a final strategic recommendation, the establishment of a global institutional consortium would benefit from a more operational definition. Such a consortium should prioritize: (i) developing shared multi-omics and data-integration repositories to en-hance interoperability, (ii) adopting harmonized analytical and phenotyping protocols, (iii) implementing unified digital traceability and image-based quality-evaluation tools, and (iv) promoting collaborative frameworks for modeling climate-response scenarios. Defining these concrete actions transforms the consortium from a conceptual proposal into a practical mechanism capable of accelerating methodological convergence, im-proving reproducibility, and strengthening the global coherence of Vaccinium research.

Taken together, these findings delineate a clear scientific agenda centered on methodological convergence, integrative analytical frameworks, and technology-driven innovation. Advancing these pillars will enhance global research consistency, support more resilient and knowledge-based production systems, and consolidate Vaccinium spp. as a model crop for interdisciplinary progress within contemporary agricultural and food sciences.

Best regards

The authors

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Overall

This manuscript presents a systematic bibliometric analysis of four decades of blueberry (Vaccinium spp.) research literature from the Scopus database. Utilizing tools like Bibliometrix/Biblioshiny and VOSviewer, this study comprehensively identified the global research landscape by examining publication trends, Co-authorship network, keyword co-occurrence, and thematic evolution. The study identified five main clusters and provided promising future directions. This study revealed a significant paradigm shift in the field, moving from traditional agricultural studies toward a dynamic interdisciplinary convergence encompassing food science, biotechnology, and artificial intelligence.

Comments

1. To strengthen the data's transparency and credibility, the manuscript should specify the precise data retrieval cut-off date and state whether "Early Access" articles were included.

2. To improve methodological reproducibility, please specify the network analysis thresholds (e.g., minimum co-occurrence, node selection criteria) used with Bibliometrix/Biblioshiny and VOSviewer.

3. While the keyword co-occurrence network successfully identifies five main research clusters, the analysis of the temporal evolution of emerging keywords could be strengthened. A more dynamic investigation into how new keywords have emerged and gained traction over time would provide valuable insights into the evolving trajectory of the field.

4. While Section 3.17 commendably identifies key knowledge gaps and future trends, the presentation of these points is somewhat dispersed. To synthesize these insights and provide a more cohesive overview, it is recommended to consolidate them into an integrative framework diagram, similar to the effective visual synthesis achieved in Figure 1.

5. The proposal for a "global institutional consortium" would be strengthened by specifying actionable steps, such as defining priority collaboration areas (e.g., data-sharing platforms, standardized analytical protocols) to transition from a conceptual suggestion to a practical strategy.

6. Table 1 (top institutions) and Table 2 (top authors) are useful but could be supplemented with a brief interpretive summary highlighting key trends.

7. Consider moving Table 4 (top cited articles) to the supplementary materials if it disrupts the flow of the main text.

Author Response

Bogota 02 de December 2025.

Reviewer 2.

We express our sincere appreciation to Reviewer 2 for the constructive and insightful comments provided. Your suggestions significantly improved the methodological precision, transparency, and interpretive robustness of the manuscript. All remarks have been carefully addressed, and the corresponding modifications have been incorporated into the revised version of the manuscript. These changes are clearly highlighted in aqua blue throughout the document and are detailed in the response letter. We greatly value your contribution to strengthening the quality and clarity of this study.

Comments

To strengthen the data's transparency and credibility, the manuscript should specify the precise data retrieval cut-off date and state whether "Early Access" articles were included.

Reply. Thank you for your thoughtful comment. We agree that specifying the data retrieval cut-off date and clarifying the inclusion of Early Access documents strengthens methodological transparency. In response, we have updated the Materials and Methods section to explicitly report both elements. Early Access articles indexed in Scopus at the time of the search were included, as they represent citable and formally indexed scientific output.

The revised sentence is now incorporated in the manuscript as follows:

“All bibliographic data were retrieved from the Scopus database on October 14, 2025, which served as the cut-off date for document inclusion. The dataset comprised peer-reviewed articles, reviews, conference papers, book chapters, and Early Access publications that were already indexed in Scopus at the time of extraction.”

To improve methodological reproducibility, please specify the network analysis thresholds (e.g., minimum co-occurrence, node selection criteria) used with Bibliometrix/Biblioshiny and VOSviewer.

Reply. Added following text:

Scientific mapping makes it possible to examine the conceptual structure and the interrelationships among the different components that shape a research field. This approach facilitates the identification of intellectual, thematic, and structural linkages within the scientific literature [17,18]. To characterize the blueberry (Vaccinium spp.) research domain, we employed bibliometric techniques including citation analysis, bibliographic coupling, co-word analysis, and co-authorship analysis.

To ensure methodological transparency and reproducibility, all network analyses were conducted using clearly defined selection thresholds. In Bibliometrix/Biblioshiny, co-occurrence networks were generated using a minimum occurrence threshold of five keywords, while author and institutional networks were constructed using a minimum productivity threshold of three documents. For VOSviewer analyses, nodes were in-cluded only when they reached the software’s default relevance filter, and networks were visualized using a minimum cluster size of five items and a link strength threshold of one.When integrated with network-based visualization models, these techniques provide a comprehensive view of the dynamics of knowledge generation and transfer. The resulting maps graphically represent the cognitive organization of the field, reveal relationships among authors, institutions, and journals, and expose the thematic con-nections that articulate scientific development. In the present study, this methodolog-ical approach enabled the identification of consolidated research cores, emerging trends, and interdisciplinary linkages, thereby clarifying the intellectual structure and thematic cohesion within global Vaccinium research.

While the keyword co-occurrence network successfully identifies five main research clusters, the analysis of the temporal evolution of emerging keywords could be strengthened. A more dynamic investigation into how new keywords have emerged and gained traction over time would provide valuable insights into the evolving trajectory of the field.

Reply. Thank you for this valuable suggestion. In response, we incorporated a dedicated temporal keyword analysis to enrich the understanding of how research themes have evolved over time. A new overlay visualization (Figure 13. Temporal evolution of keyword co-occurrence in Vaccinium spp. research) was added, generated with VOSviewer using the same co-occurrence threshold applied in the main network. This figure highlights the chronological emergence and consolidation of concepts such as image processing, deep learning, stress tolerance, anthocyanins, and postharvest quality. Additionally, we expanded the discussion to explicitly interpret these temporal patterns, showing how early biochemical and physiological terms have progressively given way to digital agriculture, machine learning, and advanced postharvest technologies. This enhancement provides a more dynamic perspective on the thematic trajectory of the field and improves the longitudinal depth of the bibliometric analysis.

The following section was added:

To complement this structural interpretation, the temporal evolution map of keywords (Figure 13) provides additional insight into how research priorities have shifted over the last decade. Early-period terms (2014), represented by darker nodes, are predominantly agronomic and phytopathological (plant disease, irrigation, cultivar, physiology), signaling an initial focus on crop performance and field management. Mid-period concepts (2016–2019) transition toward food chemistry and phytochemical analysis anthocyanin, phenols, antioxidant, food processing reflecting the consolidation of nutraceutical and postharvest research. More recent and emergent terms (>2022), shown in yellow-green nodes, include image processing, deep learning, computer vision, neural networks, and hyperspectral imaging, indicating a decisive shift toward AI-driven quality monitoring, non-destructive sensing, and sustainability-oriented data analytics. This temporal progression demonstrates a clear transition from descriptive biological inquiry to a technologically intensified, data-driven research paradigm within the global blue-berry scientific landscape.

While Section 3.17 commendably identifies key knowledge gaps and future trends, the presentation of these points is somewhat dispersed. To synthesize these insights and provide a more cohesive overview, it is recommended to consolidate them into an integrative framework diagram, similar to the effective visual synthesis achieved in Figure 1.

Reply. We appreciate the reviewer’s constructive suggestions. In response, we developed a new integrative framework diagram (now included as Figure 16: Integrative framework of knowledge gaps and emerging research trends in Vaccinium spp.). This figure synthesizes the dispersed insights presented in Section 3.17 into a single, cohesive visual structure. It organizes the major knowledge gaps and future research directions into four thematic domains structural gaps between physiology, genetics, and metabolomics; limited exploration of wild species; underdeveloped lines in biological control and sensory quality; and the rise of digital and AI-based approaches. This addition enhances conceptual clarity and provides the reader with a unified overview of how the MCA results translate into strategic research priorities.

The proposal for a "global institutional consortium" would be strengthened by specifying actionable steps, such as defining priority collaboration areas (e.g., data-sharing platforms, standardized analytical protocols) to transition from a conceptual suggestion to a practical strategy.

Reply. We appreciate the reviewer’s constructive suggestion regarding the need to operationalize the proposal of a “global institutional consortium.” In response, we have expanded this component of the conclusions by specifying concrete, actionable priorities that such a consortium should address. The revised text now outlines four clearly defined axes shared multi-omics and data-integration repositories, harmonized analytical and phenotyping protocols, unified digital traceability and image-based quality-evaluation tools, and collaborative frameworks for climate-response modeling. By incorporating these elements, the consortium moves from a conceptual recommendation to a practical strategy capable of enhancing methodological convergence, reproducibility, and global coherence in Vaccinium research.

The revised paragraph reads as follows:

“As a final strategic recommendation, the establishment of a global institutional consortium would benefit from a more operational definition. Such a consortium should prioritize: (i) developing shared multi-omics and data-integration repositories to enhance interoperability, (ii) adopting harmonized analytical and phenotyping protocols, (iii) implementing unified digital traceability and image-based quality-evaluation tools, and (iv) promoting collaborative frameworks for modeling climate-response scenarios. Defining these concrete actions transforms the consortium from a conceptual proposal into a practical mechanism capable of accelerating methodological convergence, improving reproducibility, and strengthening the global coherence of Vaccinium research.”

Table 1 (top institutions) and Table 2 (top authors) are useful but could be supplemented with a brief interpretive summary highlighting key trends.

Reply. We thank the reviewer for this valuable suggestion. In response, the sections accompanying Table 1 (top institutions) and Table 2 (top authors) have been revised and expanded to include clear interpretive summaries. These updated paragraphs now highlight the main bibliometric trends, including geographic concentration of institutional leadership, structural roles within international collaboration networks, thematic specialization, and the relative influence of the most productive authors. These modifications strengthen the analytical depth of the manuscript and provide the contextual synthesis requested by the reviewer.

Consider moving Table 4 (top cited articles) to the supplementary materials if it disrupts the flow of the main text.

Reply. We appreciate the reviewer’s suggestion to move Table 4 to the supplementary materials. After careful consideration, we decided to keep the table in the main manuscript because it plays a central interpretive role in Section 3.13. The discussion in this section refers directly and continuously to the specific articles listed in Table 4, using them to explain the historical evolution of research priorities, methodological transitions, and the conceptual foundations of the field. Moving the table to supplementary materials would disrupt this narrative and require constant cross-referencing, reducing the readability and coherence of the section. Nevertheless, we improved the structure of the discussion to ensure a smoother flow and clarified how these highly cited articles inform the thematic development of Vaccinium research. We hope this justification adequately addresses the reviewer’s concern while preserving the analytical clarity of the manuscript.

Best regards

The authors

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

Dear Editor

Thank you for providing this opportunity to review the manuscript entitled “Bibliometric analysis of global research on blueberry (Vaccinium spp.): evolution of scientific output, collaboration networks, and emerging research lines”. After careful observations, I have following minor comments for authors which need to be considered for this Journal.

Comments for authors

Title

The title is generally informative and aligned with the manuscript’s scope; however, it is somewhat long and combines multiple concepts that reduce clarity. Consider simplifying it by focusing on the core elements of the study bibliometric analysis, global research trends, and thematic evolution while avoiding redundancy and improving readability.

Abstract

The abstract is overly long and contains narrative descriptions better suited for the introduction. Please condense the abstract to a maximum of 250 words.

Several claims in the abstract lack numerical support. Please quantify major results to increase scientific rigor.

The abstract should avoid long historical descriptions; instead, emphasize your bibliometric contributions and methodological novelty.

Keywords

Terms such as “science mapping” or “research hotspots” are widely used in bibliometric literature and will increase the visibility of your manuscript across indexing databases.

Introduction

You mention that blueberry research has diversified, but you do not cite recent bibliometric studies or gaps in existing literature. Please strengthen this justification by referencing similar bibliometric work in berries or horticultural crops.

There is notable redundancy in explaining nutraceutical value, global production, and species taxonomy. Condense these into a more concise background.

Materials and methods

The search equation is extremely restrictive. Because you forced inclusion of terms like “protected cultivation,” “processing,” “marketing,” etc., many genetic, ecological, biochemical, and omics papers may have been unintentionally excluded. Please justify this filtering or revise the search query.

Please clarify whether conference papers, book chapters, and reviews were equally weighted in the analysis or treated differently.

Results and discussion

Provide statistical indicators such as R², CAGR, or polynomial regression comparison to strengthen your claims about growth trends.

Consider comparing your field’s document-type distribution with similar horticultural crops to contextualize your findings.

While the discussion is informative, many interpretations for example rise of AI and deep learning require specific citations.

Consider adding an interdisciplinarity index e.g., Rao–Stirling index to give empirical support to claims of multidisciplinarity.

Clarify whether international collaborations were measured using full counting or fractional counting.

Enhance figure 5 readability currently node labels and edge thicknesses are not visually clear.

Interpret institutions’ roles based on data trends, not anecdotal descriptions.

In leading authors section, avoid long biographical descriptions; instead emphasize bibliometric significance (influence, network position, thematic contribution).

In section 3.9, discussion should include what these clusters indicate about thematic specialization.

In section 3.13, many of the top-cited articles are not specific to blueberries but discuss general phenolics or health studies. Please separate blueberry-specific highly cited papers from general foundational papers.

The statement about “weak integration of physiology and metabolomics” is correct but needs data-based justification (e.g., cluster separation distance).

Conclusion

The conclusion reads as an extended discussion and should be substantially shortened.

Provide precise action-oriented recommendations, such as: “the need for integrating multi-omics with agronomy, gaps in modeling blueberry responses to climate change, need for standardization in phenolic analysis”.

A separate "Limitations" section is required for bibliometric transparency.

Author Response

Reviwer 3.

Comments for authors

Title

Reply. We thank the reviewer for this constructive suggestion. We agree that the original title was overly long and combined several concepts that could affect clarity and readability. In response, we revised the title to emphasize the core elements of the study bibliometric analysis, global research trends, and thematic evolution while avoiding redundancy and ensuring a more concise formulation. The updated title enhances coherence and better reflects the analytical focus of the manuscript.

Accordingly, the title has been modified as follows: “Global Research Trends and Thematic Evolution of Blueberry (Vaccinium spp.) Science: A Bibliometric Analysis”

Abstract

The abstract is overly long and contains narrative descriptions better suited for the introduction. Please condense the abstract to a maximum of 250 words. Several claims in the abstract lack numerical support. Please quantify major results to increase scientific rigor. The abstract should avoid long historical descriptions; instead, emphasize your bibliometric contributions and methodological novelty.

Reply. We thank the reviewer for the thoughtful and constructive comments regarding the abstract. We agree that the original version was overly long, included narrative descriptions better suited for the introduction, and lacked sufficient numerical support for key statements. In response, we thoroughly revised the abstract to reduce it to fewer than 250 words, enhance its focus on the bibliometric methodology, and incorporate quantitative indicators derived directly from the results of the study. These include the total number of documents analyzed (n = 474), the temporal coverage of the dataset (1987–2025), the annual peak of publications (42 articles in 2024), the predominance of research articles (>75% of the total), the leading subject areas, and the geographic and institutional distribution of scientific production. We also removed historical narrative elements and strengthened the emphasis on the methodological contributions of the study, particularly the use of performance analysis, co-authorship networks, bibliographic coupling, and keyword co-occurrence to characterize global research trends and thematic evolution.

Accordingly, the abstract was revised as follows:

Blueberry (Vaccinium spp.) is a high-value crop due to its growing global demand, recognized nutraceutical properties, and strong linkage with emerging technologies in precision agriculture and postharvest management. To characterize the scientific evolution and intellectual structure, we conducted a bibliometric analysis of 474 documents indexed in Scopus between 1987 and 2025. A systematic search strategy based on taxonomic, agronomic, and technological descriptors was applied, followed by data cleaning and analysis with Bibliometrix and VOSviewer. Performance indicators and science-mapping techniques were used to examine temporal growth, geographical distribution, institutional and author leadership, and thematic structure. Scientific output shows a sustained upward trend with a maximum of 42 articles in 2024, confirming the consolidation of blueberry as a model crop for interdisciplinary research. Research articles represent over 75% of the total (359/474), evidencing an application-oriented and experimentally grounded field. Agricultural and Biological Sciences dominate (382 documents), followed by Engineering (70) and Biochemistry, Genetics and Molecular Biology (66), reflecting increasing integration of crop management, technological innovation, and food science. Thematic mapping identified five main clusters: physiology and health, plant protection, agronomic management and digitalization, processing and stability of phenolic compounds, and analytical characterization. The analysis reveals gaps in the integration of physiology, food science, and metabolomics, as well as in the biological validation of biomarkers and the study of peripheral Vaccinium species. Overall, the field exhibits a consolidated and sustainability-oriented interdisciplinarity, highlighting opportunities to advance toward more comparable analytical protocols, digital traceability, and artificial-intelligence-assisted decision support along the blueberry value chain

Keywords

Several of the selected keywords simply repeat the title and do not improve discoverability. Consider including more specific, field-defining terms that reflect the analytical tools and major thematic findings of your study. Terms such as “science mapping” or “research hotspots” are widely used in bibliometric literature and will increase the visibility of your manuscript across indexing databases.

Reply. Thank you for this helpful suggestion. We agree that several of the original keywords partially overlapped with the title and contributed little to improving indexing visibility. Following the reviewer’s recommendation, we replaced them with more specific, field-defining terms aligned with bibliometric research and with the thematic findings of our study. The updated keywords now include methodological descriptors widely used in science-mapping literature (e.g., science mapping, research hotspots, thematic evolution) as well as terms that better represent our analytical approach. These changes significantly enhance the discoverability and indexing accuracy of the manuscript across bibliometric and agricultural science databases.

Accordingly, the keywords were updated as follows: Science mapping; research hotspots; thematic evolution; precision agriculture; post-harvest technology; bioactive compounds.

Introduction

The introduction is very long and contains extensive market, agronomic, and botanical information, which shifts focus away from the bibliometric purpose of the study. Consider summarizing these sections and directly linking them to the need for a bibliometric analysis. You mention that blueberry research has diversified, but you do not cite recent bibliometric studies or gaps in existing literature. Please strengthen this justification by referencing similar bibliometric work in berries or horticultural crops. There is notable redundancy in explaining nutraceutical value, global production, and species taxonomy. Condense these into a more concise background.

Reply. We thank the reviewer for this insightful comment. In response, we substantially shortened the introduction by condensing market, agronomic, and botanical information to retain only the essential context that justifies the scientific relevance of Vaccinium spp. We strengthened the bibliometric rationale by explicitly linking the rapid growth and diversification of blueberry research with the need for a systematic science-mapping approach. Additionally, we incorporated recent bibliometric studies on blueberries and comparative berry crops, highlighting their methodological limitations restricted time coverage, descriptive focus, and absence of network-based analyses which our study addresses through a more comprehensive, longitudinal, and integrative framework. Redundancies related to nutraceutical value, production trends, and taxonomy were removed, resulting in a more concise, coherent, and bibliometrically oriented introduction.

Accordingly, the introduction were updated as follows:

Blueberry (Vaccinium spp.) has emerged over the last decades as one of the most rapidly expanding and strategically valuable berries within the global horticultural sector. Its rise is associated not only with growing consumption driven by its well-recognized nutraceutical properties but also with genetic, physiological, and technological advances that have enabled its cultivation under diverse agro-climatic conditions [1,2]. The genus Vaccinium, comprising between 300 and 400 species across the Northern Hemisphere, places particular emphasis on highbush blueberry (V. co-rymbosum L.), derived from complex interspecific crosses that resulted in high-yielding cultivars with superior firmness and fruit-quality traits [1,3].

Global demand for blueberries, particularly those in the Cyanococcus section, has intensified. North America remains the main consumer, accounting for approximately 58% of the fresh-fruit market, while Europe, China, and Latin America have shown remarkable expansion in cultivated area and export volume [4]. This growth has been driven largely by the development of southern highbush blueberry (SHB; V. corymbosum hybrids), which has enabled production in subtropical and tropical regions such as South Africa, Spain, Morocco, Mexico, Chile, China, Peru, and Argentina. In parallel, innovations in protected agriculture, environmental control, fertigation, and canopy management have increased physiological efficiency, productivity, and profitability [5–7].

Over the past decades, scientific research on blueberry (Vaccinium spp.) has shifted from a predominantly agronomic and physiological lens toward a broader interdisci-plinary framework that now integrates biotechnology, food science, engineering, postharvest technology, and human health [8–10]. This diversification reflects both the geographic expansion of the crop and the growing valuation of its bioactive compounds, resulting in research agendas centered on productivity, quality, traceability, and sus-tainability [11–13]. As scientific output becomes more heterogeneous, synthesis tools are needed to describe the field’s evolution, its core knowledge structures, and its thematic and institutional interdependencies.

Literature reviews play a critical role in synthesizing existing evidence and iden-tifying research gaps [14–16]. Yet the rapid acceleration in global scientific production now generating millions of articles annually poses challenges for monitoring knowledge advancement [15]. Traditional reviews also face limitations related to sub-jective selection criteria or emphasis on high-impact journals [16]. In this context, bib-liometric analysis offers a systematic, transparent, and reproducible approach to map-ping the cognitive organization of a field, identifying influential actors, and tracing thematic evolution over time [17–19].

In this regard, although two previous bibliometric studies on blueberries exist, both exhibit limitations that justify the contribution of the present work. The first, based on Web of Science, focuses primarily on descriptive productivity indicators and does not examine the intellectual structure of the field through co-authorship, coupling, or con-ceptual evolution [20]. The second, a comparative analysis of berries, restricts its scope to the last decade and provides only a partial view of Vaccinium research. In contrast, our study offers a comprehensive, longitudinal, and multi-method mapping of the scientific ecosystem, allowing for a more precise understanding of cognitive architecture, the-matic interdependencies, and emerging research fronts in blueberry (Vaccinium spp.) research [21].

For this reason, the objective of this study was to analyze the evolution, structure, and dynamics of global scientific knowledge on blueberry through a bibliometric ap-proach capable of revealing the intellectual organization, the most influential actors, and major thematic trends. Specifically, we asked: (i) how has scientific production progressed in temporal, geographical, and institutional terms? (ii) which topics, approaches, and technologies dominate or emerge as future research fronts? and (iii) what gaps persist at the interface between production, postharvest, and sustainability? To address these questions, we conducted a systematic search of Scopus (1987–2025), ex-tracted metadata from peer-reviewed documents, and analyzed them using Biblio-metrix/Biblioshiny (R) and VOSviewer. Performance indicators and co-authorship, bib-liographic coupling, and keyword co-occurrence networks were applied to provide a comprehensive and quantitative perspective on the blueberry research landscape, identifying major lines of development, thematic interconnections, and strategic gaps for future inquiry

Materials and methods

Reply. We appreciate the reviewer’s comment and understand the concern regarding the potential restrictiveness of the search equation. However, the query was intentionally designed to capture the scientific corpus specifically related to the production, management, postharvest, and technological dimensions of blueberry systems, which is the core thematic scope of this study. Our objective was not to map all existing literature on Vaccinium spp. including genomics, ecology, or omics but to characterize the evolution of research directly linked to agronomic performance, protected cultivation, processing, fruit quality, and value-chain sustainability. For this reason, the equation integrates three conceptual filters: (i) taxonomic identity, (ii) production systems and technological environments, and (iii) crop management, postharvest, and commercialization. This strategy aligns with best practices in thematic bibliometric reviews, where the search equation is scoped to the domain under analysis to avoid inflating the dataset with literature from unrelated biological subfields. Importantly, before finalizing the query, we conducted sensitivity tests comparing broader and narrower versions, confirming that the selected equation provided the most coherent dataset for our research objectives without excluding relevant agronomic or postharvest studies.

In addition, the following text is added to the methodology:

The search strategy was designed to delimit the bibliometric analysis to scientific output directly related to blueberry (Vaccinium spp.) production systems, agronomic management, postharvest handling, technological innovation, and value-chain sustainability. For this purpose, the search equation integrated three complementary components: (i) taxonomic descriptors (“blueberry,” “Vaccinium spp.,” “Vaccinium corymbosum”), (ii) production-system terms associated with protected cultivation, processing, and agro-industrial environments, and (iii) management-related descriptors covering irrigation, fertigation, crop protection, harvest, storage, shelf life, and com-mercialization. This structure combined taxonomic, agronomic, and technological de-scriptors, ensuring the inclusion of interdisciplinary studies related to blueberry pro-duction, quality, sustainability, and value chain.

Rather than aiming to retrieve the entire biological, ecological, or genomic litera-ture on Vaccinium spp., the query was intentionally scoped to reflect the thematic boundaries of this study, which focuses on agronomic performance, technological de-velopment, postharvest behavior, and sustainable production frameworks. Prior to final selection, broader and narrower versions of the equation were tested, and the adopted query demonstrated the best balance between thematic specificity and disciplinary in-clusiveness, avoiding both the overexpansion of unrelated genomic or purely ecological studies and the omission of relevant agronomic or postharvest research. This approach aligns with best practices in targeted bibliometric reviews, where the search strategy is tailored to the conceptual domain under analysis rather than to the entire taxonomic group.

Please clarify whether conference papers, book chapters, and reviews were equally weighted in the analysis or treated differently.

Reply. Thank you for the opportunity to clarify this aspect of the methodology. In our analysis, all document types retrieved from Scopus research articles, review articles, conference papers, book chapters, and editorials were treated equally and included without differential weighting. This decision was made because the objective of the study was to provide a comprehensive overview of the scientific production related to blueberry (Vaccinium spp.) across its entire spectrum of academic dissemination. Accordingly, all documents were incorporated into both descriptive indicators (annual output, subject areas, country productivity) and network analyses (co-authorship, bibliographic coupling, and keyword co-occurrence). While we acknowledge that document types differ in review rigor and citation behavior, including them uniformly ensured consistent dataset structure and avoided selection bias across disciplines, especially in areas where conference papers or book chapters are common dissemination channels. This approach aligns with bibliometric practices in broad thematic mappings where the intention is to represent the full landscape of scientific output rather than restrict the analysis to a single publication format.

Results and discussion

Provide statistical indicators such as R², CAGR, or polynomial regression comparison to strengthen your claims about growth trends.

Reply. We appreciate the reviewer’s valuable observation regarding the need for quantitative indicators to support the interpretation of growth trends. In response, we recalculated the temporal evolution of scientific production and incorporated two widely used metrics in bibliometric and scientometric analyses. First, we fitted a linear regression model to the annual number of publications, obtaining an explanatory power of R² = 0.82, which demonstrates the statistical consistency of the long-term upward trend. Second, we computed the Compound Annual Growth Rate (CAGR) for the period 1987–2025, resulting in 9.8%, thus quantifying the sustained rate at which the field has expanded over nearly four decades. These indicators were added directly to Figure 2 and integrated into the text to strengthen methodological rigor and better substantiate the observed growth behavior.

The new version of the discussion remains as follows:

The bibliometric analysis of the annual evolution of scientific production on blue-berry (Vaccinium spp.) (Figure 2) confirms a robust and statistically consistent growth trajectory over nearly four decades. The linear regression fitted to the annual output shows a high explanatory power (R² = 0.82), indicating that the increase in publications follows a stable long-term trend rather than random year-to-year fluctuations. Similarly, the compound annual growth rate (CAGR) of 9.8% between 1987 and 2025 quantitatively reinforces the sustained expansion of scientific activity in this field.

Between 1987 and 2005, growth remained modest, corresponding to an exploratory phase characterized by isolated contributions in physiology, pathology, ecology, and basic agronomic management [30–33]. From 2006 onward, however, a clear structural transition is observed, marked by thematic diversification, the formation of specialized research groups, and the integration of blueberry into global agendas related to nutri-tion, biotechnology, precision agriculture, food science, and agricultural sustainability [34–38]. This inflection point coincides with the commercial expansion of the crop and the emergence of new producing regions, factors that collectively increased the visibility and demand for scientific knowledge on Vaccinium spp.

During the most recent period (2016–2025), scientific production intensified no-ticeably, culminating in a historical peak of 42 published articles in 2024, which positions blueberry as a consolidated model system in interdisciplinary horticultural research. Although certain fluctuations appear in specific years likely reflecting cyclic funding dynamics and the variability of international collaborations, the general tendency re-mains upward and statistically consistent. The accumulated total of 474 documents underscores the maturity of the field and its expansion toward advanced domains such as genomics, stress physiology, postharvest technologies, bioactive compounds, and sustainable production systems [34,39,40]. Taken together, Figure 2 portrays a field undergoing scientific consolidation, with increasing productivity, methodological so-phistication, and thematic specialization. These patterns position research on Vaccinium spp. at an advanced stage of development, with strong strategic projection within con-temporary agricultural, technological, and food science research.

Consider comparing your field’s document-type distribution with similar horticultural crops to contextualize your findings.

Reply. We appreciate the reviewer’s valuable suggestion to contextualize the document-type distribution by comparing it with findings from similar horticultural crops. In response, we revised the discussion and incorporated a comparative perspective using evidence from a recent bibliometric assessment of strawberry research. This study reported that research articles represented 96.8% of all publications, with reviews accounting for only 3.2% and other document types remaining below 1%. We integrated these results into the manuscript to highlight that blueberry research exhibits a comparable pattern dominated by peer-reviewed articles while also showing a slightly more diversified document-type structure. This addition strengthens the comparative depth of our analysis and situates blueberry research within the broader scientific dynamics of berry crops.

The revised text now includes the following paragraph at the end of the section:

“A comparative perspective reinforces the solidity of these findings. For example, a recent bibliometric assessment of strawberry research reported that articles represented 96.8% of all publications, with reviews accounting for only 3.2%, and book chapters or proceedings papers remaining below 1%[45]. This distribution highly concentrated in peer-reviewed articles and with minimal presence of non-article formats is consistent with what we observe for blueberry (Vaccinium spp.), although the latter shows a comparatively more diversified structure with a larger proportion of reviews and complementary document types. Such parallels suggest that berry-related horticultural research tends to consolidate around experimental, article-driven dissemination, reinforcing the idea that blueberry has reached a mature stage within global horticultural science, comparable to other strategic berry crops.”

While the discussion is informative, many interpretations for example rise of AI and deep learning require specific citations.

Reply. We thank the reviewer for this important observation. Several elements of our discussion particularly those referring to the rise of artificial intelligence, deep learning, and digital technologies were originally presented as conceptual inferences derived from thematic patterns in the dataset. To address this concern and strengthen the evidential basis of our interpretations, we have now incorporated specific citations from studies actually identified in our bibliometric corpus, including works that apply machine learning to fruit quality prediction, computer vision for blueberry detection, and AI-based decision-support systems.

Consider adding an interdisciplinarity index e.g., Rao–Stirling index to give empirical support to claims of multidisciplinarity.

Reply. We appreciate the reviewer’s suggestion. We have incorporated an explicit interdisciplinarity assessment into the manuscript and added the Rao–Stirling diversity index to provide empirical support for our claims regarding multidisciplinarity. Accordingly, we added the following paragraph at the end of the section:

Taken together, the figure evidences a scientifically mature field with increasing interdisciplinarity, in which blueberry research is shifting from pure biological under-standing toward the integration of engineering tools, data science, and machine learning, shaping a domain with strong prospects for precision agriculture and circular bio-economy. To empirically support this interpretation, we calculated the Rao–Stirling diversity index using Scopus subject‐area co-classifications as disciplinary inputs [61]. The resulting value (Drs = 0.75 on a 0–1 scale) indicates a highly diversified knowledge base, where contributions extend beyond Agricultural and Biological Sciences into En-gineering, Chemistry, Medicine, Environmental Science, and Computer Science. This quantitative evidence confirms that research on Vaccinium spp. has evolved into a genuinely multidisciplinary field, integrating technological innovation, health sciences, and sustainability.

Clarify whether international collaborations were measured using full counting or fractional counting.

Reply. We appreciate the reviewer’s observation. We clarified this methodological aspect in the manuscript. International collaborations were calculated using a full counting scheme, in which each country listed in the authors’ affiliations receives one full credit for a publication. This corresponds to the default procedure in Bibliometrix and VOSviewer. The following sentence was added to the methodological section: “International collaboration was assessed using a full counting approach, whereby each country received full credit for its participation in a publication.”

Enhance figure 5 readability currently node labels and edge thicknesses are not visually clear.

Reply. The graphics have been improved with a better resolution.

Interpret institutions’ roles based on data trends, not anecdotal descriptions.

Reply. Thank you for this insightful comment. Following your recommendation, we revised the section on leading institutions to remove anecdotal descriptions and focus strictly on bibliometric interpretations derived from publication volume, network position, and thematic distribution. The updated text now highlights the structural roles of institutions within the global research system, rather than describing their individual research agendas. The revised section reads as follows:

The institutional analysis shows that scientific production on blueberry is strongly concentrated in a small group of North American entities, which occupy the highest positions both in publication volume and in their structural centrality within the col-laboration network (Table 1). The USDA Agricultural Research Service, the United States Department of Agriculture, and Dalhousie University each contribute 25 docu-ments, forming the most cohesive institutional core. Their prominence reflects not only sustained research productivity but also a central role in shaping shared methodological frameworks and acting as reference nodes in the global knowledge structure [92–96].

A second tier, composed of the University of Florida (23 documents) and the University of Georgia (21), reinforces the diversification of research lines identified in the subject-area and keyword analyses. Their publication profiles show strong partici-pation across agronomic management, ecophysiology, postharvest, and technological innovation, which suggests that these institutions function as bridging nodes that link traditionally biological research with advances in engineering and data-driven ap-proaches [98–102]. Their presence in multiple thematic clusters indicates an integrative institutional behavior rather than specialization in a single domain.

Overall, the institutional distribution reveals a highly asymmetric but structurally coherent system dominated by North American organizations. These institutions an-chor the intellectual and methodological development of the field, while emerging contributors from Europe, Latin America, and Asia participate mainly through thematic niches. This pattern supports the interpretation of blueberry research as a globally connected but hierarchically organized network, where a limited number of institutions define the disciplinary standards and scientific direction of the field.

In leading authors section, avoid long biographical descriptions; instead emphasize bibliometric significance (influence, network position, thematic contribution).

Reply. We appreciate this observation. Following the reviewer’s recommendation, the section on leading authors has been fully revised to remove biographical or narrative descriptions. The updated version now focuses strictly on bibliometric indicators (productivity, citation impact, h-index), network metrics (degree, link strength, centrality), and thematic contribution within the co-authorship structure. This change aligns the text with standard practices in science mapping. The revised section now reads as follows:

The analysis of leading authors (Table 2) and their position within the co-authorship network reveals a structurally organized research system with clear thematic concentra-tions. Arnold Walter Schumann and Qamar Uz Zaman constitute the central axis of the network, exhibiting the highest productivity (11 and 10 documents, respectively), strong citation performance, and the largest total link strength. Their high degree and centrality confirm their role as structural hubs in research fronts related to automation, sensing technologies, and precision management of blueberry production systems. Their recurrent co-authorship and strong connectivity reflect the consolidation of a technologically oriented cluster with high internal cohesion.

Luke R. Howard, Bin Li, and Changying Li occupy positions characterized by high citation impact and thematic specialization. Howard acts as a core node in the bio-chemical and functional-quality cluster, with his contributions shaping the foundations of anthocyanin stability and processing effects. Bin Li’s research strengthens the metabolomics-oriented front, supported by high-impact publications on anthocyanin transformation and advanced analytical methods. Meanwhile, Changying Li contributes to the engineering and digitalization cluster, particularly in computer vision and AI-based phenotyping, reflected in the strong thematic coherence of his citation profile.

Together, these authors form structurally differentiated but interconnected sub-networks that articulate the main thematic domains of blueberry research: precision agriculture, postharvest and processing, and biochemical characterization. Their prominence is not derived from biographical attributes, but rather from demonstrable bibliometric influence citation impact, network centrality, link strength, and thematic leadership within the global science mapping of Vaccinium spp.

In section 3.9, discussion should include what these clusters indicate about thematic specialization.

Reply. We appreciate the reviewer’s observation. Following this suggestion, Section 3.9 has been revised to explicitly explain what each cluster represents in terms of thematic specialization. We now clarify how the main author groups correspond to technological–engineering, biochemical–nutraceutical, and integrative agronomic research domains. The updated paragraph has been incorporated as shown above.

The strongest collaborative nucleus is led by Arnold Walter Schumann (11 docu-ments, 159 citations, link strength 27) and Qamar Uz Zaman (10 documents, 156 cita-tions, link strength 27), who form a stable and highly connected cluster centered on automation, mechanization, and artificial intelligence applied to blueberry management [98]. Their sustained co-authorship particularly in maturity detection, precision spraying, and harvest optimization positions this cluster as the technological–engineering specialization, where research is oriented toward digital agriculture, computer vision, and intelligent mechanization.

A second, temporally earlier cluster is formed by Luke R. Howard, Ronald L. Prior, and Cindi R. Brownmiller, whose work between 2010 and 2014 established foundational knowledge on anthocyanins, polyphenols, and antioxidant stability during processing [93,109]. This group represents the biochemical–nutraceutical specialization, focusing on the behavior of phenolic compounds, antioxidant mechanisms, and the functional quality of the fruit. Their bridging role in the network indicates that this fundamental biochemical corpus provided the experimental basis that later enabled advances in postharvest modeling and AI-assisted quality assessment.

Finally, intermediate authors such as David C. Percival, Peter L. Havard, and Wilhelmina Kalt play an integrative role that connects technological innovation with agronomic performance and food chemistry. Percival’s research on yield estimation, automated harvesting, and energy and carbon assessments in wild blueberries [65,110] links the network to sustainability and production efficiency. Havard contributes an economic and engineering perspective through studies on technological feasibility and cost-effective precision agriculture [105,111], while Kalt provides a biochemical bridge through her influential work on anthocyanins, phenolics, and antioxidant capacity in processed products [11]. Together, this group forms a hybrid or integrative specialization, articulating agronomics, sustainability, and food chemistry.

Overall, the co-authorship network highlights how collaboration clusters corre-spond to distinct thematic specializations technological engineering, biochemical quality, and integrative agronomic research demonstrating that the interdisciplinary evolution of blueberry research has been structured around stable, highly productive author groups that collectively define the intellectual architecture of the field.

Reply. We thank the reviewer for this important observation. In response, Section 3.13 was fully revised to clearly differentiate between (i) highly cited foundational papers on phenolics, bioavailability, and human health whose influence provides the biochemical and biomedical frameworks underpinning blueberry research and (ii) the genuinely blueberry-specific top-cited articles addressing fruit quality, postharvest technologies, anthocyanin stability, and processing effects. This restructuring improves conceptual clarity and aligns the discussion with bibliometric best practices. The revised text now reads as follows:

The analysis of the ten most cited documents (Table 4) reveals two complementary layers of scientific influence that structure the evolution of blueberry research. The first layer comprises foundational studies in phenolic chemistry, bioavailability, and human health papers that, although not exclusively focused on blueberries, have provided the biochemical and biomedical frameworks on which blueberry-specific research has been built. The second layer consists of articles directly centered on blueberry quality, post-harvest behavior, processing effects, and technological innovation.

The foundational group is led by the highly influential review “Chlorogenic acids and other cinnamates nature, occurrence and dietary burden” (1,255 citations), which provides an exhaustive mapping of chlorogenic acids and cinnamates across foods and their meta-bolic relevance. While its scope transcends blueberries, it established the chemical and nutritional foundations required for characterizing phenolic compounds in Vaccinium spp. In parallel, “Dietary factors affecting polyphenol bioavailability” (464 citations) eluci-dates the mechanisms governing absorption, metabolism, and interactions of poly-phenols within the food matrix and human physiology. Complementary biomedical frameworks are provided by “Flavonoids, cognition, and dementia: actions, mechanisms, and potential therapeutic utility for Alzheimer disease” (412 citations), which details neuropro-tective mechanisms of dietary flavonoids, and “Effects and mechanisms of resveratrol on aging and age-related diseases” (273 citations), a seminal review outlining antioxidant, anti-inflammatory, and anti-aging pathways relevant to compounds also present in blueberries. Together, these papers constitute the conceptual base that supports mechanistic interpretations in blueberry-related nutrition and health studies.

Conversely, the second group of highly cited articles is directly focused on blue-berry research and its technological, nutritional, and postharvest dimensions. The re-view “Recent research on the health benefits of blueberries and their anthocyanins” (469 cita-tions) is the most influential Vaccinium-specific work, synthesizing epidemiological, clinical, and biochemical evidence linking blueberry consumption with improvements in cardiovascular function, metabolic regulation, and cognitive health. In the techno-logical domain, “Atmospheric cold plasma inactivation of aerobic microorganisms on blueber-ries and effects on quality attributes” (298 citations) introduced a novel non-thermal preservation technology capable of reducing microbial load while preserving key qual-ity traits such as firmness and color. The effects of processing and storage are thor-oughly documented in “Processing and storage effects on monomeric anthocyanins, percent polymeric color, and antioxidant capacity of processed blueberry products” (279 citations) and “Anthocyanins, phenolics, and antioxidant capacity of processed lowbush blueberry products” (194 citations), which collectively demonstrate significant anthocyanin loss (>50% over time) and highlight the necessity of improved preservation strategies for maintaining bioactive stability.

Additional influential studies expand the phytochemical and functional context. “Berry antioxidants: small fruits providing large benefits” (236 citations) positions blueber-ries within the broader category of antioxidant-rich berries, emphasizing their nutraceutical potential, while “Fruit cuticular waxes as a source of biologically active triterpenoids” (211 citations) broadens the biochemical perspective to structural com-pounds with biological activity, reinforcing the multidimensional nature of blueberry phytochemistry.

Taken together, this citation structure reveals dual knowledge architecture: (i) general phenolic, nutritional, and biomedical frameworks that underpin mechanistic understanding, and (ii) blueberry-specific research addressing fruit quality, processing stability, and technological innovation. This duality reflects the interdisciplinary nature of the field and explains why the most influential articles range from broad biochemical reviews to highly specialized studies on Vaccinium spp.

The statement about “weak integration of physiology and metabolomics” is correct but needs data-based justification (e.g., cluster separation distance).

Reply. Done.

Conclusion

The conclusion reads as an extended discussion and should be substantially shortened. Provide precise action-oriented recommendations, such as: “the need for integrating multi-omics with agronomy, gaps in modeling blueberry responses to climate change, need for standardization in phenolic analysis”.

Reply. We appreciate the reviewer’s observation regarding the structure and focus of the conclusion. In response, the entire section was thoroughly revised to ensure that it is concise, non-redundant, and clearly distinct from the discussion. The new version now synthesizes the main bibliometric findings, highlights the thematic structure revealed by our analyses, and presents action-oriented research priorities fully grounded in the evidence generated.

Accordingly, we incorporated the key elements suggested by the reviewer: (i) the need to integrate multi-omics with agronomic research; (ii) current gaps in predictive modeling of blueberry responses to climate change; and (iii) the importance of standardizing analytical protocols for phenolic and antioxidant assessment. Finally, we added a closing paragraph that provides a coherent forward-looking perspective based strictly on our results.

The revised conclusion now reads as follows:

As a final strategic recommendation, the establishment of a global institutional consortium would benefit from a more operational definition. Such a consortium should prioritize: (i) developing shared multi-omics and data-integration repositories to en-hance interoperability, (ii) adopting harmonized analytical and phenotyping protocols, (iii) implementing unified digital traceability and image-based quality-evaluation tools, and (iv) promoting collaborative frameworks for modeling climate-response scenarios. Defining these concrete actions transforms the consortium from a conceptual proposal into a practical mechanism capable of accelerating methodological convergence, improving reproducibility, and strengthening the global coherence of Vaccinium research.

A separate "Limitations" section is required for bibliometric transparency.

Reply. Thank you for this valuable observation. In response to your recommendation, we incorporated a dedicated “Limitations” section to ensure methodological transparency, in line with best practices in bibliometric research. This section explicitly addresses constraints related to database coverage, metadata quality, citation-based indicators, and indexing heterogeneity. Additionally, we included a concluding paragraph detailing the actions taken to mitigate these limitations through systematic data cleaning, metadata verification, and the use of standardized bibliometric tools (Bibliometrix/Biblioshiny and VOSviewer).

The newly added section reads as follows:

As with any bibliometric study, the present analysis is constrained by its reliance on a single bibliographic database (Scopus). Although Scopus provides extensive mul-tidisciplinary coverage, it may omit publications indexed exclusively in Web of Science, PubMed, AGRIS, or regional repositories, potentially leading to an underrepresentation of research from emerging scientific communities. In addition, variations in database indexing policies and metadata completeness may influence document retrieval, cita-tion counts, or subject classifications, meaning that the results reflect the scientific landscape captured within Scopus rather than an exhaustive representation of all global blueberry research.

A second limitation arises from the inherent dependency on metadata quality. Inconsistencies in institutional affiliations, automated subject-area assignment, and database-specific author disambiguation may affect the accuracy of collaboration net-works and productivity indicators. Similarly, citation-based metrics tend to favor older documents and may understate the early impact of recent advances in areas such as metabolomics, digital agriculture, machine learning, and advanced postharvest tech-nologies. These structural characteristics of bibliometric data must therefore be con-sidered when interpreting temporal trends or influence patterns.

To mitigate these limitations, rigorous data-cleaning procedures were imple-mented, including the removal of non-relevant indexing terms, manual verification of author clusters, and harmonization of institutional names. All analyses were performed using standardized bibliometric software (Bibliometrix/Biblioshiny and VOSviewer), ensuring reproducibility and methodological transparency. While the study acknowl-edges the intrinsic constraints of metadata-driven approaches, these methodological safeguards substantially reduced noise, improved cluster validity, and strengthened the reliability of the thematic and network structures reported.

Bets regards

The authors

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

Considering the adjustments made to the manuscript, which improve and clarify the procedures, I consider the article suitable and appropriate for publication.

Article Menu

Global Research Trends and Thematic Evolution of Blueberry (Vaccinium spp.) Science: A Bibliometric Analysis

Further Information

Guidelines

MDPI Initiatives

Follow MDPI