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Bernués A. - Autor o Coautor
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Topics and trends in Mountain Livestock Farming research: a text mining approach

Publicado en:Animal. 15 (1): 100058- - 2021-01-01 15(1), doi: 10.1016/j.animal.2020.100058

Bernués A.;


Agroscope, Forage Prod & Grassland Syst, Reckenholzstr 191, CH-8046 Zurich, Switzerland - Autor o Coautor
Aristotle Univ Thessaloniki, Sch Hlth Sci, Dept Vet Med, Lab Anim Husb, Thessaloniki 54124, Greece - Autor o Coautor
BOKU Univ Nat Resources & Life Sci, Dept Sustainable Agr Syst, Div Livestock Sci, Vienna, Austria - Autor o Coautor
Centro de Investigación y Tecnología Agroalimentaria de Aragón - Entidad de origen
Free Univ Bolzano, Fac Sci & Technol, Livestock Prod Syst, Univ Pl 5, I-39100 Bolzano, Italy - Autor o Coautor
Norwegian Univ Life Sci, Fac Biosci, N-1434 As, Norway - Autor o Coautor
Scotlands Rural Coll SRUC, South & West Fac, Hill & Mt Res Ctr, Kirkton Farm FK20 8RU, Crianlarich, England - Autor o Coautor
Univ Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 St Genes Champanelle, France - Autor o Coautor
Univ Ljubljana, Biotech Fac, Groblje 3, Domzale 1230, Slovenia - Autor o Coautor
Univ Padua, Dept Anim Med Prod & Hlth, Viale Univ 2, I-35020 Padua, Italy - Autor o Coautor
Univ Udine, Dept Food Agr Environm & Anim Sci, Via Sondrio 2-A, I-33100 Udine, Italy - Autor o Coautor
Univ Zaragoza, Unidad Prod & Sanidad Anim, Ctr Invest & Tecnol Agroalimentaria Aragon CITA, Inst Agroalimentario Aragon IA2,CITA, Zaragoza, Spain - Autor o Coautor
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Resúmen: Pasture-based and small-scale livestock farming systems are the main source of livelihood in the mountain primary sector, ensuring socioeconomic sustainability and biodiversity in rural communities throughout Europe and beyond. Mountain livestock farming (MLF) has attracted substantial research efforts from a wide variety of scientific communities worldwide. In this study, the use of text mining and topic modelling analysis drew a detailed picture of the main research topics dealing with MLF and their trends over the last four decades. The final data corpus used for the analysis counted 2 679 documents, of which 92% were peer-reviewed scientific publications. The number of scientific outputs in MLF doubled every 10 years since 1980. Text mining found that milk, goat and sheep were the terms with the highest weighed frequency in the data corpus. Ten meaningful topics were identified by topic analysis: T1-Livestock management and vegetation dynamics; T2-Animal health and epidemiology; T3-Methodological studies on cattle; T4-Production system and sustainability; T5-Methodological studies; T6-Wildlife and conservation studies; T7-Reproduction and performance; T8-Dairy/meat production and quality; T9-Land use and its change and T10-Genetic/genomic studies. A hierarchical dustering analysis was performed to explore the interrelationships among topics, and three main clusters were identified: the first focused on sustainability, conservation and socioeconomic aspects (T4; T6 and T9), the second was related to food production and quality (17 and T8) and the last one considered methodological studies on mountain flora and fauna (T1 ; 12; T3; TS and T10). The 10 topics identified represent a useful and a starting source of information for further and more detailed analysis (e.g. systematic review) of specific research or geographical areas. A truly holistic and interdisciplinary research approach is needed to identify drivers of change and to understand current and future challenges faced by livestock farming in mountain areas. (C) 2020 The Authors. Published by Elsevier Inc. on behalf of The Animal Consortium.

Palabras clave: animal production; mountain agriculture; research topics; ruminants; Agricultura de montaña; Agricultural land; Agriculture; Animal; Animal production; Animals; Bovine; Cattle; Data mining; Europe; Explotaciones ganaderas; Farms; Livestock; Mountain agriculture; Research topics; Ruminants; Sheep; Text mining

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