Feed/food competition; Food production; Human-edible protein; Land use; Multivariate analysis; Redundancy analysis; Environmental Engineering; Agronomy and Crop Science
Abstract :
[en] The increasing human population and demand for animal food products raise the issue of impacts of animal systems on food security caused by their use of human-edible feed and/or tillable land. The utility of replacing animal systems with potential food-crop systems needs to be assessed but is associated with many uncertainties. Some metrics analyse the contribution of current animal systems to food security, especially the dimension of food availability. These methods address feed conversion efficiency (i.e. total (‘gross’) or human-edible (‘net’)) or the efficiency of agricultural land use (i.e. total, permanent grassland, and tillable land) but never both simultaneously. The purpose of this study was to develop a new metric—‘net productivity’—to represent the performances of current animal systems more accurately by considering both the use of human-edible feed and agricultural land. Through a protein assessment, we analysed the ability of the existing and the new metrics to assess the performances of 111 dairy farms in Wallonia (Belgium). We found that net productivity was positively correlated with both metrics of feed conversion efficiency and negatively correlated with the three metrics of land use. To analyse the influence of farm characteristics, we grouped the farms into four clusters using k-means clustering based on these metrics of contribution to food security and then performed redundancy analysis to select the most influential farm characteristics aiming to highlight contrasted farm strategies. The highest net productivity was reached by an ‘intensive and net efficient’ farm strategy, which had intensive grass-based management, high milk production per cow, appropriate use of concentrates, and well-managed dairy followers (i.e. replacement heifers and calves). The newly developed metric of net productivity can be useful to quantify the contribution of dairy systems to food security by considering both the use of human-edible protein and agricultural land simultaneously.
Disciplines :
Animal production & animal husbandry
Author, co-author :
Battheu-Noirfalise, Caroline ; Université de Liège - ULiège > TERRA Research Centre ; Department Sustainability, Systems and Prospectives, Centre Wallon de Recherches Agronomiques, Libramont, Belgium
Mertens, Alexandre; Department Sustainability, Systems and Prospectives, Centre Wallon de Recherches Agronomiques, Libramont, Belgium
Froidmont, Eric; Department Sustainability, Systems and Prospectives, Centre Wallon de Recherches Agronomiques, Libramont, Belgium
Mathot, Michaël; Department Sustainability, Systems and Prospectives, Centre Wallon de Recherches Agronomiques, Libramont, Belgium
Rouillé, Benoit; IDELE, Service Productions Laitières, Paris, France
Stilmant, Didier; Department Sustainability, Systems and Prospectives, Centre Wallon de Recherches Agronomiques, Libramont, Belgium
Language :
English
Title :
Net productivity, a new metric to evaluate the contribution to food security of livestock systems: the case of specialised dairy farms
FRIA - Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture ERDF - European Regional Development Fund Ministère de l'Agriculture et de la Souveraineté alimentaire
Funding text :
The first author is a recipient of a Ph.D. grant financed by the Belgian ‘Fonds pour la formation à la Recherche dans l’Industrie et dans l’Agriculture’ (FRIA). Data came partly from the Interreg V project AUTOPROT, which is financed by the European Regional Development Fund (ERDF) and the Walloon region. The authors also thank the French Ministry of Agriculture and Food for funding the ERADAL project (#5710, CASDAR grant for Rural and Agricultural Development).The authors thank the Agricultural Economic Analysis Department (DAEA), the Walloon Breeders Association (AWE), and the Provincial Service for Information, Management, and Agricultural Vulgarisation (SPIGVA) for making their data available; anonymous reviewers for useful comments on an earlier version of the manuscript; and Marc Dufrène for statistical insight into multivariate analysis.
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