TY - JOUR
T1 - Assessment and analysis of yield gaps in pasture-based livestock systems
T2 - A review of methods
AU - Santos, Patricia Menezes
AU - van der Linden, Aart
AU - Martha, Geraldo Bueno
AU - Monteiro, Leonardo Amaral
AU - Marin, Fábio R.
AU - Mayberry, Dianne
AU - Nogueira, Sandra Furlan
AU - Bayma, Gustavo
AU - Caram, Nicolas
AU - van de Ven, Gerrie W.J.
AU - Sollenberger, Lynn
PY - 2025/5
Y1 - 2025/5
N2 - CONTEXT: Grazing landscapes cover a substantial portion of global agricultural land and are essential for the provision of ecosystem services, food security, and rural livelihoods. The yield gap concept highlights the potential for increased agricultural production through sustainable intensification by quantifying the difference between current yields and maximum achievable yields. Assessing yield gaps is crucial for targeting public and private interventions and investments in regions with the greatest potential for production increases. However, methods for assessing yield gaps vary, impacting their ability to identify underlying factors and assess yield risks consistently and accurately, particularly in pasture-based systems where interactions between plants and animals add complexity. OBJECTIVE: The objectives of this review were to provide an overview of methods used to assess and analyze yield gaps in pasture-based livestock production systems and to discuss how they may aid decision-making processes. METHODS: Review of literature. RESULTS AND CONCLUSIONS: Different approaches have been applied for yield gap analysis of pasture-based livestock production systems. For benchmarking, climate binning, frontier methods, and production system models approaches we provide a brief description, examples of applications, data requirements, and advantages and disadvantages. The selection of specific approaches depends on the research questions addressed, spatial scale of the study, data availability and computational processing capacity. Benchmarking approaches are commonly used by farmers to compare the performance of their enterprise to others with similar characteristics. The climate binning approach is applied to larger spatial scales for identifying regions where sustainable intensification technically could be an option. Frontier approaches provide insights on both technical and economic efficiencies. Methods based on production system models may be applied for different purposes, according to the characteristics of the models. In general, mathematical models currently used for yield gap analysis in pasture-based production systems rarely account for the effects of different grazing strategies, plant species proportion, pasture nutritive value and selective grazing by animals. SIGNIFICANCE: Methods for yield gap assessment and analysis in pasture-based systems can contribute knowledge and technical conditions to increase productivity and resource use efficiency from existing areas rather than expanding to new ones. This provides opportunities to meet the increasing demand for food while conserving land and natural resources. It is necessary to integrate technical insights from yield gap analysis into a broader social, economic, and political framework to support decision making by policy makers and farmers, highlighting the need for future research to improve the current methods.
AB - CONTEXT: Grazing landscapes cover a substantial portion of global agricultural land and are essential for the provision of ecosystem services, food security, and rural livelihoods. The yield gap concept highlights the potential for increased agricultural production through sustainable intensification by quantifying the difference between current yields and maximum achievable yields. Assessing yield gaps is crucial for targeting public and private interventions and investments in regions with the greatest potential for production increases. However, methods for assessing yield gaps vary, impacting their ability to identify underlying factors and assess yield risks consistently and accurately, particularly in pasture-based systems where interactions between plants and animals add complexity. OBJECTIVE: The objectives of this review were to provide an overview of methods used to assess and analyze yield gaps in pasture-based livestock production systems and to discuss how they may aid decision-making processes. METHODS: Review of literature. RESULTS AND CONCLUSIONS: Different approaches have been applied for yield gap analysis of pasture-based livestock production systems. For benchmarking, climate binning, frontier methods, and production system models approaches we provide a brief description, examples of applications, data requirements, and advantages and disadvantages. The selection of specific approaches depends on the research questions addressed, spatial scale of the study, data availability and computational processing capacity. Benchmarking approaches are commonly used by farmers to compare the performance of their enterprise to others with similar characteristics. The climate binning approach is applied to larger spatial scales for identifying regions where sustainable intensification technically could be an option. Frontier approaches provide insights on both technical and economic efficiencies. Methods based on production system models may be applied for different purposes, according to the characteristics of the models. In general, mathematical models currently used for yield gap analysis in pasture-based production systems rarely account for the effects of different grazing strategies, plant species proportion, pasture nutritive value and selective grazing by animals. SIGNIFICANCE: Methods for yield gap assessment and analysis in pasture-based systems can contribute knowledge and technical conditions to increase productivity and resource use efficiency from existing areas rather than expanding to new ones. This provides opportunities to meet the increasing demand for food while conserving land and natural resources. It is necessary to integrate technical insights from yield gap analysis into a broader social, economic, and political framework to support decision making by policy makers and farmers, highlighting the need for future research to improve the current methods.
KW - Cattle
KW - Grasslands
KW - Livestock production
KW - Models
KW - Ruminants
U2 - 10.1016/j.agsy.2025.104323
DO - 10.1016/j.agsy.2025.104323
M3 - Article
AN - SCOPUS:105001428517
SN - 0308-521X
VL - 226
JO - Agricultural Systems
JF - Agricultural Systems
M1 - 104323
ER -