Rubus glaucus Benth, called Andean blackberry, is a species of significant economic and ecological importance. Despite its relevance, scientific research on this plant remains fragmented and scattered across disciplines.
Objective
This study aims to systematically assess the state of scientific knowledge on R. glaucus, identifying research trends, collaborations, and thematic evolutions within the global research community.
Methods
We employed a comprehensive bibliometric analysis integrated with Latent Dirichlet Allocation (LDA) and HJ-Biplot methodologies to analyze publications from Scopus and Web of Science databases.
Results
Our findings reveal a substantial increase in research interest from the 1990s, reaching a peak in the early 2010s before a recent decline. The study highlights significant contributions from the United States, the United Kingdom, Canada, Italy, and Colombia, with notable international collaborations. Thematic analysis underscored the ecological role, nutritional benefits, and genetic improvement of R. glaucus as focal areas of research, pointing out gaps in pest management and sustainable cultivation practices.
Conclusions
This comprehensive bibliometric analysis offers valuable insights into the research landscape of R. glaucus, underscoring the need for focused research efforts on underexplored areas. The study lays the groundwork for future research directions, encouraging interdisciplinary collaboration to leverage the plant's full potential for agricultural innovation.
RamírezF. Latin American Blackberries Biology: Mora de Castilla (Rubus glaucus Benth.), vol. 1. Cham, Switzerland: Springer Nature, 2023. DOI: https://doi.org/10.1007/978-3-031-31750-7.
FrancoGBernalJACiprianoE, et al.Tecnología para el cultivo de la mora (Rubus glaucus Benth.). In: Colección Transformación del Agro. Bogotá, Colombia: AGROSAVIA, 2020, pp.188.
4.
Carrillo-PerdomoEAllerACruz-QuintanaSM, et al.Andean berries from Ecuador: A review on botany, agronomy, chemistry and health potential. J Berry Res2015; 5: 49–69. DOI: https://doi.org/10.3233/JBR-140093.
5.
Cancino-EscalanteGOQuevedo GarcíaEVillamizarCE, et al.Propagación in vitro de materiales seleccionados de Rubus glaucus Benth (mora de Castilla) en la provincia de Pamplona, región nororiental de Colombia. Rev Colomb Biotecnol2015; 17: 7–15.
6.
PopenoeW. The Andes berry. Journal of Heredity1921; 12: 387–393.
7.
MoralesCVillegasB. Mora (Rubus glaucus Benth.). Manual para el cultivo de frutales en el trópico. Bogotá, Colombia: Produmedios, 2012.
8.
FischerGOrduz-RodríguezJ. Ecofisiología en frutales. Manual para el cultivo de frutales en el trópico. Bogotá, Colombia: Produmedios, 2012.
9.
IzaMViteriPHinojosaM, et al.Diferenciación morfológica, fenológica y pomológica de cultivares comerciales de mora (Rubus glaucus Benth). Enfoque UTE2020; 11: 47–57.
10.
FosterTMBassilNVDossettM, et al.Genetic and genomic resources for Rubus breeding: a roadmap for the future. Hortic Res2019; 6: 116. DOI: https://doi.org/10.1038/s41438-019-0199-2.
11.
AriasJRincónJCLópezAM, et al.Transcriptome assembly and expression analysis in Colletotrichum gloeosporioides-tolerant rubus glaucus benth. Chil J Agric Res2019; 79: 565–575. DOI: https://doi.org/10.4067/S0718-58392019000400565.
12.
Rubio OchoaEPérez SánchezREÁvila ValTC, et al.Propiedades fisicoquímicas de frutos silvestres de Rubus con potencial nutracéutico y alimenticio. Rev Mex De Cienc Agric2019; 23: 291–301. DOI: https://doi.org/10.29312/remexca.v0i23.2028.
13.
Alarcón-BarreraKSArmijos-MontesinosDSGarcía-TenesacaM, et al.Wild Andean blackberry (Rubus glaucus Benth) and Andean blueberry (Vaccinium floribundum Kunth) from the Highlands of Ecuador: Nutritional composition and protective effect on human dermal fibroblasts against cytotoxic oxidative damage. J Berry Res2018; 8: 223–236. DOI: https://doi.org/10.3233/JBR-180316.
14.
GarzónGARiedlKMSchwartzSJ. Determination of Anthocyanins, Total Phenolic Content, and Antioxidant Activity in Andes Berry (Rubus glaucus Benth). J Food Sci2009; 74: C227–C232. DOI: https://doi.org/10.1111/j.1750-3841.2009.01092.x.
15.
Torres MejíaJATorres MejíaF. Evaluación fisicoquímica del vino de mora (RUBUS GLAUCUS), elaborado en Santa Rosa de Copán, Honduras. Nexo Revista Científica2022; 35: 60–71. DOI: https://doi.org/10.5377/nexo.v35i01.13916.
16.
Barreno-AvilaEMBalladares-PazmiñoMDLÁBarreno-AvilaAF, et al.Blackberry (Rubus Glaucus) natural-fiber reinforced polymeric composites: An overview of mechanical characteristics. In: Lecture Notes in Electrical Engineering, vol. 763. Cham, Switzerland: LNEE, 2021, pp.300–315. DOI: https://doi.org/10.1007/978-3-030-72212-8_22.
17.
AriaMCuccurulloC. Bibliometrix: an R-tool for comprehensive science mapping analysis. J Informet2017; 11: 959–975.
GalindoMP. Una alternativa de representación simultánea: HJ-Biplot. Questiio1986; 10: 13–23.
21.
Vicente-Villardón. MultBiplotR: Multivariate Analysis using Biplots. R package2020. DOI: 10.32614/CRAN.package.MultBiplotR.
22.
HarzingA-WAlakangasS. Google scholar, scopus and the web of science: a longitudinal and cross-disciplinary comparison. Scientometrics2016; 106: 787–804.
23.
Pilacuan-BoneteLGalindo-VillardónPDelgado-ÁlvarezF. HJ-Biplot as a tool to give an extra analytical boost for the Latent Dirichlet Assignment (LDA) model: with an application to digital news analysis about COVID-19. Mathematics2022; 10: 2529.
24.
WhiteHD. Bibliometrics. Annual Review of Information Science and Technology (ARIST)1989; 24: 119–186.
DiMaggioPNagMBleiD. Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper coverage of U.S. government arts funding. Poetics2013; 41: 570–606. DOI: https://doi.org/10.1016/j.poetic.2013.08.004.
27.
De la Hoz-MJFernández-GómezMJMendesS. LDAShiny: an R package for exploratory review of scientific literature based on a Bayesian probabilistic model and machine learning tools. Mathematics2021; 9: 1671.
28.
TangDWeiFYangN, et al.Learning sentiment-specific word embedding for twitter sentiment classification. 52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference, vol. 1, 2014. DOI: https://doi.org/10.3115/v1/p14-1146.
29.
BleiDMLaffertyJD. Topic models. Text Mining: Classification, Clustering, and Applications2009; 10: 34.
30.
GemanSGemanD. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans Pattern Anal Mach Intell1984; PAMI-6: 721–741. DOI: https://doi.org/10.1109/TPAMI.1984.4767596.
31.
RöderMBothAHinneburgA.Exploring the space of topic coherence measures. WSDM 2015 - Proceedings of the 8th ACM International Conference on Web Search and Data Mining, 2015. DOI: https://doi.org/10.1145/2684822.2685324.
32.
ChangJBoyd-GraberJGerrishS, et al.Reading tea leaves: How humans interpret topic models. Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference, 2009.
33.
GabrielKR. The biplot graphic display of matrices with application to principal component analysis. Biometrika1971; 58: 453–467. DOI: https://doi.org/10.1093/biomet/58.3.453.
34.
XiongHChengYZhaoW, et al.Analyzing scientific research topics in manufacturing field using a topic model. Comput Ind Eng2019; 135. DOI: https://doi.org/10.1016/j.cie.2019.06.010.
35.
XiongHChengYZhaoW, et al.Analyzing scientific research topics in manufacturing field using a topic model. Comput Ind Eng2019; 135: 333–347.
36.
EscobarKMVicente-VillardonJLde la Hoz-MJ, et al.Frequency of neuroendocrine tumor studies: using latent dirichlet allocation and HJ-Biplot statistical methods. Mathematics2021; 9: 2281.
37.
Montes-EscobarKDe la Hoz-MJBarreiro-LinzánMD, et al.Trends in agroforestry research from 1993 to 2022: a topic model using latent dirichlet allocation and HJ-Biplot. Mathematics2023; 11: 2250.
38.
Montes-EscobarKDe la Hoz-MJBarreiro-LinzánMD, et al.Trends in agroforestry research from 1993 to 2022: a topic model using latent dirichlet allocation and HJ-Biplot. Mathematics2023; 11: 2250.
39.
Montes-EscobarKde la Hoz-MJCastillo-CordovaP, et al.Glioblastoma: a comprehensive approach combining bibliometric analysis, latent dirichlet allocation, and HJ-Biplot. Neurosurg Rev2024; 47: 1–18.
40.
Van SchaikCPTerborghJWWrightSJ. The phenology of tropical forests: adaptive significance and consequences for primary consumers. Annu Rev Ecol Syst1993; 24: 353–377.
41.
Klimis-ZacasDRodriguez-MateosA.Berries and Berry Bioactive Compounds in Promoting Health. Croydon, United Kingdom: The Royal Society of Chemistry2022. DOI: https://doi.org/10.1039/9781839165450.
42.
BaseliceAColantuoniFLassDA, et al.Trends in EU consumers’ attitude towards fresh-cut fruit and vegetables. Food Qual Prefer2017; 59: 87–96.
43.
GuptaAAlstonLNeedhamC, et al.Factors influencing implementation, sustainability and scalability of healthy food retail interventions: a systematic review of reviews. Nutrients2022; 14: 94.
44.
PollardJKirkSFLCadeJE. Factors affecting food choice in relation to fruit and vegetable intake: a review. Nutr Res Rev2002; 15: 373–387.
45.
Toscano-ÁvilaJATeránDADebutA, et al.Shelf life estimation of Blackberry (Rubus glaucus Benth) with bacterial cellulose film coating from Komagataeibacter xylinus. Food Sci Nutr2020; 8: 2173–2179.
46.
García-MuñozMCCardonaWACalvo-SalamancaAM, et al.Packaging design proposal motivated by the identification of damages in Andean blackberry (Rubus glaucus Benth). Heliyon2020; 6: e05300.
47.
Bernal-RoaLJMeloLADíaz-MorenoC. Aromatic profile and antioxidant properties during blackberry (Rubus glaucus Benth.) fruit ripening. Acta Hortic2014; 1016: 39–45. DOI: https://doi.org/10.17660/ActaHortic.2014.1016.3.
48.
SadrasVOVillalobosFJFereresE. Crop development and growth. Principles of agronomy for sustainable agriculture. Cham: Springer International Publishing, 2016, 141–158. DOI: https://doi.org/10.1007/978-3-319-46116-8_11.
49.
GokI. Bioactive compounds modulating inflammation and oxidative stress in some traditional functional foods and beverages. In: Current advances for development of functional foods modulating inflammation and oxidative stress. London, United Kingdom: Elsevier, 2022, 1–16. DOI: https://doi.org/10.1016/B978-0-12-823482-2.00013-3.
González-CastroYManzano-DuránOGarcía-HoyaO. Puntos críticos de la cadena productiva de la mora (Rubus glaucus Benth), en el municipio de Pamplona, Colombia. Revista de Investigación, Desarrollo e Innovación2019; 10: 9– 22. DOI: https://doi.org/10.19053/20278306.v10.n1.2019.10008.
52.
KumarNUpadhyayGChoudharyS, et al.Resource conserving mechanization technologies for dryland agriculture. In: Enhancing resilience of dryland agriculture under changing climate. Singapore, Singapore: Springer Nature Singapore, 2023, p. 657–688. DOI: https://doi.org/10.1007/978-981-19-9159-2_33.
Kaleem-UllahMShabirS. The significant effects of agricultural systems on the environment. Journal of World Science2023; 2: 798–805.
55.
MontemurroFMaioranaM. Agronomic practices at low environmental impact for Durum wheat in Mediterranean conditions. J Plant Nutr2015; 38: 624–638.
56.
BocchiSChristiansenSOweisT, et al.Research for the innovation of the agri-food system in international cooperation. Italian Journal of Agronomy2012; 7: 36.
57.
ClarkJRFinnCE. Blackberry cult ivation in the world. Rev Bras Frutic2014; 36: 46–57.
58.
StrikBCClarkJRFinnCE, et al.Worldwide blackberry production. Horttechnology2007; 17: 205–213.
59.
ShahHMSSinghZKaurJ, et al.Trends in maintaining postharvest freshness and quality of Rubus berries. Compr Rev Food Sci Food Saf2023; 22: 4600–4643.
60.
HebelIJofreEJañaR, et al.Coincident evidence demonstrates evolutionary aspects and the potential expansion of Rubus geoides under climate change. Authorea2023. DOI: https://doi.org/10.22541/au.168907655.52241517/v1.
61.
SoaresMSPLuduvicoKPChavesVC, et al.The Protective Action of Rubus sp. Fruit Extract Against Oxidative Damage in Mice Exposed to Lipopolysaccharide. Neurochem Res2021; 46. DOI: https://doi.org/10.1007/s11064-021-03248-7.
