Current Science

Open Access Open Access  Restricted Access Subscription Access

Bibliometric and Social Network Analysis in Scientific Research on Precision Agriculture


Affiliations
1 Department of Viticulture and Oenology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
2 Departamento de Sociologia y Antropología Social, Universidad de Valencia, UISYS (CSIC-Universidad de Valencia), Blasco Ibanez 13, 46022, Spain
3 Instituto de Ingeniería de Alimentos para el Desarrollo (IIAD), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Spain
4 Ingenio (CSIC-UPV), UISYS (CSIC-Universidad de Valencia), Blasco Ibañez 13, 46022, Spain
 

Precision agriculture (PA) is used to improve agricultural processes. A better understanding of PA as well as the evolution of the research status through the available literature are reported and discussed in this study. The Web of Science (WoS) was used to obtain the research records under study. Indicators of scientific productivity, collaboration between countries and research impact were evaluated through a social network analysis. The keywords included in the publications and subject areas under which the research was published were also evaluated through subject analysis. A total of 2027 articles were analysed from 1994 to 2014. The most productive journals were ‘Computers and Electronics in Agriculture’ (n = 191) and ‘Precision Agriculture’ (n = 110). The most frequent keywords were ‘management’ (n = 243), ‘yield’ (n = 231), ‘soil’ (n = 198) and ‘variability’ (n = 190). The collaboration network showed the United States occupying a central position, in combination with some leading countries such as Brazil, Germany, People’s Republic of China, Canada, Australia and Spain. A steady increase in PA research was identified during the last decade, which was even more sharp between 2010 and 2014. The increased importance of PA research has recently led to the birth of specific journals such as Precision Agriculture. The increasing number of journals that publish articles related to the topics included in the WoS must also be considered. The network analysis identified a number of developed countries in the hotspot of international collaboration.

Keywords

Bibliometrics, Precision Agriculture, Research Collaboration, Scientific Analysis, Social Network.
User
Notifications
Font Size

  • Zarco-Tejada, P. J., Hubbard, N. and Loudjani, P., Precision agriculture: an opportunity for EU farmers 2004–2020. Joint Research Centre (JRC) of the European Commission, Monitoring Agriculture ResourceS (MARS) Unit H04, European Union, 2014; http://www.europarl.europa.eu/studies (accessed on 22 July 2015).

  • Bramley, R. G. V., Lesson from nearly 20 years of precision agriculture research, development, and adoption as a guide to its appropriate application. Crop Pasture Sci., 2009, 60(3), 197–217.

  • Bramley, R. G. V., Precision viticulture: managing vineyard variability for improved quality outcomes. In Understanding and Managing Wine Quality and Safety (ed. Reynolds, A. G.), Woodhead, UK, 2009.

  • Robert, P. C., Precision agriculture: a challenge for crop nutrition management. Plant Soil, 2002, 247(1), 143–149.

  • Srinivasan, A. (ed.), Handbook of Precision Agriculture: Principles and Application, The Haworth Press Inc, Binghamton, New York, USA, 2006.

  • Cox, G. J., Harris, H. D. and Pax, R., Development and testing of a prototype yield mapping system. Proc. Aust. Soc. Sugar Cane Technol., 1997, 19, 38–43.

  • Bramley, R. G. V. and Quabba, R. P., Opportunities for improving the management of sugarcane production through the adoption of precision agriculture – an Australian perspective. In Proceedings of the 24th Congress of the International Society. Sugar Cane Technology, Brisbane, Australia, 17–21 September 2001.

  • Cook, S. E., Adams, M. L., Bramley, R. G. V. and Whelan, B. M., Australia. In Handbook of Precision Agriculture: Principles and Applications (ed. Srinivasan, A.), The Haworth Press Inc, Binghamton, New York, 2006, pp. 529–566.

  • Proffitt, T., Bramley, R., Lamb, D. and Winter, E., Precision viticulture – A new era in vineyard management and wine production. Can. J. Soil Sci., 2006, 82, 9–21.

  • Tisseyre, B., Ojeda, H. and Taylor, J., New technologies and methodologies for site-specific viticulture. J. Int. Sci. Vigne Vin., 2007, 41, 63–76.

  • Bramley, R. G. V. and Hamilton, R. P., Understanding variability in winegrape production systems. 1. Within vineyard variation in yield over several vintages. Aust. J. Grape Wine Res., 2004, 10(1), 32–45.

  • Bramley, R. G. V. and Hamilton. R. P., Terroir and precision viticulture: are they compatible? J. Int. Sci. Vigne. Vin., 2007, 41, 1–8.

  • Griffin, T. W. and Lowenberg-DeBoer, J., Worldwide adoption and profitability of precision agriculture. Rev. Pol. Agric., 2005, 14, 20–38.

  • Bramley, R. G. V., Lanyon, D. M. and Panten, K., Whole-ofvineyard experimentation – an improved basis for knowledge generation and decision-making. In Proceedings of the 5th European Conference on Precision Agriculture (ed. Stafford, J. V.), Wageningen Academic Publishers, The Netherlands, 2005, pp. 883–890.

  • Zaman, Q. U. and Schumann, A. W., Performance of an ultrasonic tree volume measurement system in commercial citrus groves. Precis. Agric., 2005, 6(15), 467–480.

  • Zaman, Q. U. and Schumann, A. W., Nutrient management zones for citrus based on variation in soil properties and tree performance. Precis. Agric., 2006, 7(1), 45–63.

  • Stoorvogel, J. and Bouma, J., Precision agriculture: the solution to control nutrient emissions? In Proceedings of the 5th European Conference on Precision Agriculture (ed. Stafford, J. V.), Wageningen Academic Publishers, The Netherlands, 2005, pp. 47–55.

  • Blackmore, S., Precision farming: a dynamic process. In Proceedings of the 6th International Conference on Precision Agriculture and Other Precision Resources Management. Minneapolis, Minnesota (eds Robert, P. C., Rust, R. H. and Larso, W. E.), ASA-CSASSSA, Madison, WI, USA, 2003, pp. 84–104.

  • Blackmore, S., Griepentrog, H., Pedersen, S. and Fountas, S., Europe. In Handbook of Precision Agriculture: Principles and Applications (ed. Srinivasan, A.), The Haworth Press Inc, Binghamton, New York, USA, 2006, pp. 567–613.

  • Zhang, M., Zhihao, Q. and Xue, L., Remote sensed spectral imagery to detect late blight in field tomatoes. Precis. Agric., 2005, 6(6), 489–508.

  • Praat, J. P., Bollen, F., Dewar, D. and Yule, I., Product tracking for profit. In ‘Precision Tools for Improving Land Management. FLRC Occasional report No. 14 (eds Currie, L. D. and Loganathan, P.), Fertilizer and Lime Research Centre, Massey University, Palmerston North, New Zealand, 2001, pp. 107–113.

  • Praat, J. P., Bollen, A. F. and Mowatt, A., Characterising spatial variation in quality. Acta Hortic., 2007, 753, 305–316.

  • Bramley, R. G. V., Cook, S. E. and McMahon, G. G., Precision agriculture – what can it offer the Australian sugar industry? In Proceeding of a Workshop, CSIRO Land and Water, Townsville, 10–12 June 1997, ISBN 0 643 06048 0.

  • Swinton, S. M. and Lowenberg-DeBoer, J., Evaluating the profitability of site-pecific farming. J. Prod. Agric., 1998, 11(4), 439– 446.

  • Pannell, D. J., Marshall, G. R., Barr, N., Curtis, A., Vanclay, F. and Wilkinson, R., Understanding and promoting adoption of conservation practices by rural landholders. Aust. J. Exp. Agric., 2006, 46, 1407–1424.

  • Godwin, R. J., Richards, T. E., Wood, G. A., Welsh, J. P. and Knight, S. M., An economic analysis of the potential for precision farming in UK cereal production. Biosyst. Eng., 2003, 84(4), 533– 545.

  • Bramley, R. G. V., Proffitt, A. P. B., Hinze, C. J., Pearse, B. and Hamilton, R. P., Generating benefits from precision viticulture through selective harvesting. In Proceedings of the 5th European Conference on Precision Agriculture (ed. Stafford, J. V.), Wageningen Academic Publishers, The Netherlands, 2005, pp. 891–898.

  • Bramley, R. G. V. and Hamilton, R. P., Hitting the zone – making viticulture more precise. In Proceedings of the 12th Australian Wine Industry Technical Conference (eds Blair, R. J., Williams, P. J. and Pretorius, I. S.), 2005, pp. 57–61.

  • Vain, P., Trends in GM crop, food and feed safety literature. Nature Biotechnol., 2007, 25(16), 624–626.

  • Lanza, E. and Svendsen, B. A., Tell me who you are and I might be able to tell you what language(s) you speak: social network analysis, multilingualism, and identity. Int. J. Biling., 2007, 11(3), 275–300.

  • Ho, Y. S., Bibliometric analysis of adsorption technology in environmental science. J. Environ. Protect. Sci., 2007, 1, 1–11.

  • Chiu, W. T. and Ho, Y. S., Bibliometric analysis of tsunami research. Scientometrics, 2007, 73, 3–17.

  • Aleixandre, J. L., Aleixandre-Tudó, J. L., Bolaños, M. and AleixandreBenavent, R., Mapping scientific research on wine and health. J. Agric. Food Chem., 2013, 61(49), 11871–11880.

  • Batagelj, V. and Mrvar, A., Pajek: analysis and visualization of large networks. Lect. Notes Comput. Sci., 2002, 2265, 477– 478.

  • Dudnik, N. S., Thormann, L. and Hodgkin, T., The extent and use of plant genetic resources in research – a literature survey. Crop Sci., 2001, 41, 6–10.

  • Dalpe, R., Bibliometric analysis of biotechnology. Scientometrics, 2002, 55, 189–213.

  • Vain, P., Plant transgenic science knowledge. Nature Biotechnol., 2005, 23(11), 1348–1349.

  • Quixabeira, V. B. L., Nabout, J. C. and Rodrigues, F. M., Trends in genetic literature with use of flow cytometry. Cytometry, 2010, 77A(3), 207–210.

  • Leonidou, C. N. and Leonidou, L. C., Research into environmental marketing/management: a bibliographic analysis. Eur. J. Market, 2011, 45(1/2), 68–103.

  • Queiroz, J. C. B., Vieira, T. O., Araujo, P. P., Matos, F. A., Amin, M. M. and Salame, C. W., Three-dimensional geostatistical estimation of soil units: a case study from Capitao Pocinho, Para, Brazil. Soils Rocks, 2007, 40, 187–194.

  • Guo, K., Liu, Y. F., Zeng, C., Chen, Y. Y. and Wei, X. J., Global research on soil contamination from 1999 to 2012: a bibliometric analysis. Acta Agric. Scand., 2014, 64(5), 377–391.

  • Crisostomo, C., Bteich. M. R., Moschitz, H. and Pugliese, P., Organic farming policy in Portugal: analysis of the policy network. New Medit., 2012, 11(4), 27–30.

  • Kondo, T., Nanba, H., Takezawa, T. and Okumura, M., Technical trend analysis by analyzing research papers’ titles. Lect. Notes Comput. Sci., 2011, 6562, 512–521.

  • Ferguson, R. S. and Lovell, S. T., Permaculture for agroecology: design, movement, practice, and worldview. A review. Agron. Sustain. Dev., 2014, 34, 251–274.

  • Dabbert, S., Häring, A. M. and Zanoli, R., Organic Farming: Policies and Prospects, Zed Books, London, UK, 2003.

  • Cañas-Guerrero, I., Mazarrón, F. R., Pou-Merina, A., Calleja-Perucho, C. and Díaz-Rubio, G., Bibliometric analysis of research activity in the ‘agronomy’ category from the Web of Science, 1997–2011. Eur. J. Agron., 2013, 50, 19–28.

  • de Aquino, R. E., Campos, M. C. C., Marques, J., de Oliveira, I. A., Mantovaneli, B. C. and Soares, M. D. R., Geostatistics in assessment of physical properties in a latossolo (oxisol) under native forest and grassland in Manicore, Amazonas, Brazil. Rev. Bras. Ciênc. Solo, 2014, 38, 397–406.

  • de Aquino, R. E., Campos, M. C. C., Soares, M. D. R., de Oliveira, I. A., Franciscon, U. and Silva, D. M. P., Chemical soil attributes evaluated by multivariate techniques and geostatistics in the area with agroforestry and sugarcane in Humaita, AM, Brazil. BioScience J., 2016, 32, 61–72.

  • Righini, R. and Grossi Gallegos, H., Utilización preliminar de información GOES y métodos geoestadísticos para la evaluación del recurso solar en Brasil. Avances en Energías Renovables y Medio Ambiente, 2001, 5, 19–24.

  • Ferreira, A. B. et al., A streamlined approach by a combination of bioindication and geostatistical methods for assessing air contaminants and their effects on human health in industrialized areas: a case study in Southern Brazil. Front. Plant. Sci., 2017, 8, 1557.

  • Konur, O., The scientometric evaluation of the research on the production of bioenergy from biomass. Biomass Bioenerg., 2012, 47, 504–515.

  • Vandermeulen, A. V., Prins, W. B. S., Nolte, A. G. and Van Huylenbroeck, How to measure the size of a bio-based economy: evidence from Flanders. Biomass Bioenerg., 2011, 35(10), 4368– 4375.

  • Meho, L. I. and Yang, K., Impact of data sources on citation counts and rankings of LIS faculty: web of science versus Scopus and Google Scholar. J. Am. Soc. Inf. Sci. Technol., 2007, 58(13), 2105–2125.

  • Bullock, D. S., Kitchen, N. and Bullock, D. G., Multidisciplinary teams: a necessity for research in precision agriculture systems. Crop Sci., 2007, 47, 1765–1769.


Abstract Views: 429

PDF Views: 133




  • Bibliometric and Social Network Analysis in Scientific Research on Precision Agriculture

Abstract Views: 429  |  PDF Views: 133

Authors

Jose Luis Aleixandre-Tudo
Department of Viticulture and Oenology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
Lourdes Castello-Cogollos
Departamento de Sociologia y Antropología Social, Universidad de Valencia, UISYS (CSIC-Universidad de Valencia), Blasco Ibanez 13, 46022, Spain
Jose Luis Aleixandre
Instituto de Ingeniería de Alimentos para el Desarrollo (IIAD), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Spain
Rafael Aleixandre-Benavent
Ingenio (CSIC-UPV), UISYS (CSIC-Universidad de Valencia), Blasco Ibañez 13, 46022, Spain

Abstract


Precision agriculture (PA) is used to improve agricultural processes. A better understanding of PA as well as the evolution of the research status through the available literature are reported and discussed in this study. The Web of Science (WoS) was used to obtain the research records under study. Indicators of scientific productivity, collaboration between countries and research impact were evaluated through a social network analysis. The keywords included in the publications and subject areas under which the research was published were also evaluated through subject analysis. A total of 2027 articles were analysed from 1994 to 2014. The most productive journals were ‘Computers and Electronics in Agriculture’ (n = 191) and ‘Precision Agriculture’ (n = 110). The most frequent keywords were ‘management’ (n = 243), ‘yield’ (n = 231), ‘soil’ (n = 198) and ‘variability’ (n = 190). The collaboration network showed the United States occupying a central position, in combination with some leading countries such as Brazil, Germany, People’s Republic of China, Canada, Australia and Spain. A steady increase in PA research was identified during the last decade, which was even more sharp between 2010 and 2014. The increased importance of PA research has recently led to the birth of specific journals such as Precision Agriculture. The increasing number of journals that publish articles related to the topics included in the WoS must also be considered. The network analysis identified a number of developed countries in the hotspot of international collaboration.

Keywords


Bibliometrics, Precision Agriculture, Research Collaboration, Scientific Analysis, Social Network.

References





DOI: https://doi.org/10.18520/cs%2Fv115%2Fi9%2F1653-1667