IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v173y2019icp27-38.html
   My bibliography  Save this article

Optimizing management of dairy goat farms through individual animal data interpretation: A case study of smart farming in Spain

Author

Listed:
  • Belanche, Alejandro
  • Martín-García, A. Ignacio
  • Fernández-Álvarez, Javier
  • Pleguezuelos, Javier
  • Mantecón, Ángel R.
  • Yáñez-Ruiz, David R.

Abstract

Dairy goat production systems in developed countries are experiencing an intensification process in terms of higher farm size, electronic identification, reproductive intensification, genetic selection and milking automation. This new situation generates “big data” susceptible to be used to aid farmers during the decision making process. This case study describes how the farm management can be improved by the use of the “Eskardillo”, a tool with a smart-phone terminal which relies on three principles: i) systematic individual data recording (milking control, productivity, genetic merit, morphology, phylogeny, etc.), ii) big data processing and interpretation and iii) interactive feedback to the farmer to optimize farm management. This study evaluated the effectiveness of the Eskardillo tool by monitoring the productive parameters from 2013 to 2016 in 12 conventional Murciano-Granadina dairy goat farms which implemented the Eskardillo (ESK) in late 2014. Moreover, 12 conventional farms without Eskardillo were also monitored as control farms (CTL). Results demonstrated that ESK farms were able to better monitor the productivity and physiological stage of each animal and Eskardillo allowed selecting animals for breeding, replacement or culling according to each animal's records. As a result, goats from ESK farms decreased their unproductive periods such as the first partum age (−30 days), and the dry period length (−20 days) without negatively affecting milk yield per lactation. This study revealed an acceleration in the milk yield in ESK farms since this innovation was implemented (+26 kg / lactation per year) in comparison to the situation before (+7.3) or in CTL farms (+6.1). Data suggested that this acceleration in milk yield in ESK farms could rely on i) a greater genetic progress as a result of a more knowledgeable selection of high merit goats, ii) the implementation of a more effective culling off strategy based on the production, reproductive and health records from each animal, and iii) the optimization of the conception timing for each animal according to its physiological stage and milk yield prospects to customize lactation length while keeping a short and constant dry period length (2 months). Moreover, this study demonstrated a decrease in the seasonality throughout the year in terms of percentage of animals in milking and milk yield allowing an increment in the production of off-season milk (+17%) since Eskardillo was applied. In conclusion, it was demonstrated that the implementation of the Eskardillo tool can be considered a useful strategy to optimize farm management and to contribute to the sustainable intensification of modern dairy goat farms.

Suggested Citation

  • Belanche, Alejandro & Martín-García, A. Ignacio & Fernández-Álvarez, Javier & Pleguezuelos, Javier & Mantecón, Ángel R. & Yáñez-Ruiz, David R., 2019. "Optimizing management of dairy goat farms through individual animal data interpretation: A case study of smart farming in Spain," Agricultural Systems, Elsevier, vol. 173(C), pages 27-38.
  • Handle: RePEc:eee:agisys:v:173:y:2019:i:c:p:27-38
    DOI: 10.1016/j.agsy.2019.02.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X17311319
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.agsy.2019.02.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Guimarães, Vinícius Pereira & Tedeschi, Luis Orlindo & Rodrigues, Marcelo Teixeira, 2009. "Development of a mathematical model to study the impacts of production and management policies on the herd dynamics and profitability of dairy goats," Agricultural Systems, Elsevier, vol. 101(3), pages 186-196, July.
    2. Riveiro, J.A. & Mantecón, A.R. & Álvarez, C.J. & Lavín, P., 2013. "A typological characterization of dairy Assaf breed sheep farms at NW of Spain based on structural factor," Agricultural Systems, Elsevier, vol. 120(C), pages 27-37.
    3. Wolfert, Sjaak & Ge, Lan & Verdouw, Cor & Bogaardt, Marc-Jeroen, 2017. "Big Data in Smart Farming – A review," Agricultural Systems, Elsevier, vol. 153(C), pages 69-80.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Elizabeth Ahikiriza & Joshua Wesana & Xavier Gellynck & Guido Van Huylenbroeck & Ludwig Lauwers, 2021. "Context Specificity and Time Dependency in Classifying Sub-Saharan Africa Dairy Cattle Farmers for Targeted Extension Farm Advice: The Case of Uganda," Agriculture, MDPI, vol. 11(9), pages 1-19, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hrosul, Viktoriia & Kruhlova, Olena & Kolesnyk, Alina, 2023. "Digitalization of the agricultural sector: the impact of ICT on the development of enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(4), December.
    2. Pigford, Ashlee-Ann E. & Hickey, Gordon M. & Klerkx, Laurens, 2018. "Beyond agricultural innovation systems? Exploring an agricultural innovation ecosystems approach for niche design and development in sustainability transitions," Agricultural Systems, Elsevier, vol. 164(C), pages 116-121.
    3. Hrosul, Viktoriia & Kruhlova, Olena & Kolesnyk, Alina, 2023. "Digitization of the Agricultural Sector: The Impact of ICT on the Development of Enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(4), January.
    4. Panos Constantinides & Ola Henfridsson & Geoffrey G. Parker, 2018. "Introduction—Platforms and Infrastructures in the Digital Age," Information Systems Research, INFORMS, vol. 29(2), pages 381-400, June.
    5. Divya Suresh & Abhishek Choudhury & Yinjia Zhang & Zhiying Zhao & Rajib Shaw, 2024. "The Role of Data-Driven Agritech Startups—The Case of India and Japan," Sustainability, MDPI, vol. 16(11), pages 1-17, May.
    6. Hidalgo, Francisco & Quiñones-Ruiz, Xiomara F. & Birkenberg, Athena & Daum, Thomas & Bosch, Christine & Hirsch, Patrick & Birner, Regina, 2023. "Digitalization, sustainability, and coffee. Opportunities and challenges for agricultural development," Agricultural Systems, Elsevier, vol. 208(C).
    7. Madhu Khanna & Shady S. Atallah & Saurajyoti Kar & Bijay Sharma & Linghui Wu & Chengzheng Yu & Girish Chowdhary & Chinmay Soman & Kaiyu Guan, 2022. "Digital transformation for a sustainable agriculture in the United States: Opportunities and challenges," Agricultural Economics, International Association of Agricultural Economists, vol. 53(6), pages 924-937, November.
    8. Víctor M. Albornoz & Lia C. Araneda & Rodrigo Ortega, 2022. "Planning and scheduling of selective harvest with management zones delineation," Annals of Operations Research, Springer, vol. 316(2), pages 873-890, September.
    9. Jingmei Gao & Zahid Sarwar, 2024. "How do firms create business value and dynamic capabilities by leveraging big data analytics management capability?," Information Technology and Management, Springer, vol. 25(3), pages 283-304, September.
    10. Shebanina, Olena & Burkovska, Anna & Petrenko, Vadym & Burkovska, Alla, 2023. "Economic planning at agricultural enterprises: Ukrainian experience of increasing the availability of data in the context of food security," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(4), December.
    11. Shen, Zhiyang & Wang, Songkai & Boussemart, Jean-Philippe & Hao, Yu, 2022. "Digital transition and green growth in Chinese agriculture," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    12. Salembier, Chloé & Segrestin, Blanche & Sinoir, Nicolas & Templier, Joseph & Weil, Benoît & Meynard, Jean-Marc, 2020. "Design of equipment for agroecology: Coupled innovation processes led by farmer-designers," Agricultural Systems, Elsevier, vol. 183(C).
    13. Pereira, Karine Vargas & Siluk, Julio Cezar Mairesse & Michelin, Cláudia de Freitas & Rigo, Paula Donaduzzi & Quiroga, Daniel Oscar & Manosso, Thayane Sviercoski, 2024. "Factors that impact on Brazilian rural producers’ decision-making: A systematic literature review," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 15(02), June.
    14. Norman Siebrecht, 2020. "Sustainable Agriculture and Its Implementation Gap—Overcoming Obstacles to Implementation," Sustainability, MDPI, vol. 12(9), pages 1-27, May.
    15. Ashfield, Austen & Mullan, Conall & Jack, Claire, 2020. "Encouraging farmer participation in agricultural education and training: A Northern Ireland perspective," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 9, November.
    16. Gackstetter, David & von Bloh, Malte & Hannus, Veronika & Meyer, Sebastian T. & Weisser, Wolfgang & Luksch, Claudia & Asseng, Senthold, 2023. "Autonomous field management – An enabler of sustainable future in agriculture," Agricultural Systems, Elsevier, vol. 206(C).
    17. Dixit, Krishna & Aashish, Kumar & Kumar Dwivedi, Amit, 2023. "Antecedents of smart farming adoption to mitigate the digital divide – extended innovation diffusion model," Technology in Society, Elsevier, vol. 75(C).
    18. Schnack, Alexander & Bartsch, Fabian & Osburg, Victoria-Sophie & Errmann, Amy, 2024. "Sustainable agricultural technologies of the future: Determination of adoption readiness for different consumer groups," Technological Forecasting and Social Change, Elsevier, vol. 208(C).
    19. Parra-López, Carlos & Reina-Usuga, Liliana & Carmona-Torres, Carmen & Sayadi, Samir & Klerkx, Laurens, 2021. "Digital transformation of the agrifood system: Quantifying the conditioning factors to inform policy planning in the olive sector," Land Use Policy, Elsevier, vol. 108(C).
    20. Wu, Haitao & Wang, Bingjie & Lu, Mingyue & Irfan, Muhammad & Miao, Xin & Luo, Shiyue & Hao, Yu, 2023. "The strategy to achieve zero‑carbon in agricultural sector: Does digitalization matter under the background of COP26 targets?," Energy Economics, Elsevier, vol. 126(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:173:y:2019:i:c:p:27-38. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.