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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
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    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.

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