{"title":"Benchmarking sustainability performance in UK free-range laying hen flocks","authors":"L.E. Higham , I. Handel , L. Boden , D. Moran","doi":"10.1016/j.agsy.2024.104103","DOIUrl":null,"url":null,"abstract":"<div><h3>CONTEXT</h3><div>To equitably nourish the world's growing human population whilst halting further transgression of the planetary boundaries, there is a need to evaluate the relative performance of food and farming systems in terms of multiple and often competing food security, environmental, and ethical sustainability objectives.</div></div><div><h3>OBJECTIVE</h3><div>We aimed to benchmark the sustainability performance of 80 free-range laying hen flocks in England and Scotland, in production between 2016 and 2022, and to identify any common characteristics between the best performers to inform supply chain policy. Benchmarking was based on multi-criteria efficiency scores, incorporating six input and two output criteria covering human, animal, and environmental domains, including the neglected measures of animal welfare and antibiotic use.</div></div><div><h3>METHODS</h3><div>Data Envelope Analysis (DEA) was used to derive efficiency scores. Univariate and multivariate regression analyses were then applied to explore production factors that could be associated with the attainment of maximum efficiency.</div></div><div><h3>RESULTS AND CONCLUSIONS</h3><div>Approximately half of the flocks attained the maximum efficiency score, relative to their peers. Analysis of their component inputs and outputs demonstrated the favourable performance of the most efficient flocks across a broad array of criteria compared to inefficient flocks, indicating that some farms are successfully reconciling production and profitability with superior environmental, animal welfare, and antibiotic use performance. Univariate analysis and multivariate regression revealed no statistically significant predictors of efficiency at the level of <em>p</em> < 0.05, with unexplained variation in relative efficiency scores of the flocks of between 0.7 and 1.0, indicating a path of improvement amongst farmers with similar production systems and standards, potentially based on unmeasured human factors. However, univariate analysis revealed an association between laying hen breed and the attainment of efficiency at the level of <em>p</em> < 0.1, supporting the notion that breeds with balanced genetic merit will play an important role in food systems seeking to mitigate externalities of production.</div></div><div><h3>SIGNIFICANCE</h3><div>DEA allows multiple sustainability dimensions to be combined into a single performance metric to benchmark and compare production units. It offers a method for industry and government to identify potential leverage points to incentivise improved performance, and is a basis for better data collection in relation to both market and non-market (external) cost impacts of production, including animal welfare and antimicrobial use.</div></div>","PeriodicalId":7730,"journal":{"name":"Agricultural Systems","volume":"221 ","pages":"Article 104103"},"PeriodicalIF":6.1000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Agricultural Systems","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0308521X24002531","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
CONTEXT
To equitably nourish the world's growing human population whilst halting further transgression of the planetary boundaries, there is a need to evaluate the relative performance of food and farming systems in terms of multiple and often competing food security, environmental, and ethical sustainability objectives.
OBJECTIVE
We aimed to benchmark the sustainability performance of 80 free-range laying hen flocks in England and Scotland, in production between 2016 and 2022, and to identify any common characteristics between the best performers to inform supply chain policy. Benchmarking was based on multi-criteria efficiency scores, incorporating six input and two output criteria covering human, animal, and environmental domains, including the neglected measures of animal welfare and antibiotic use.
METHODS
Data Envelope Analysis (DEA) was used to derive efficiency scores. Univariate and multivariate regression analyses were then applied to explore production factors that could be associated with the attainment of maximum efficiency.
RESULTS AND CONCLUSIONS
Approximately half of the flocks attained the maximum efficiency score, relative to their peers. Analysis of their component inputs and outputs demonstrated the favourable performance of the most efficient flocks across a broad array of criteria compared to inefficient flocks, indicating that some farms are successfully reconciling production and profitability with superior environmental, animal welfare, and antibiotic use performance. Univariate analysis and multivariate regression revealed no statistically significant predictors of efficiency at the level of p < 0.05, with unexplained variation in relative efficiency scores of the flocks of between 0.7 and 1.0, indicating a path of improvement amongst farmers with similar production systems and standards, potentially based on unmeasured human factors. However, univariate analysis revealed an association between laying hen breed and the attainment of efficiency at the level of p < 0.1, supporting the notion that breeds with balanced genetic merit will play an important role in food systems seeking to mitigate externalities of production.
SIGNIFICANCE
DEA allows multiple sustainability dimensions to be combined into a single performance metric to benchmark and compare production units. It offers a method for industry and government to identify potential leverage points to incentivise improved performance, and is a basis for better data collection in relation to both market and non-market (external) cost impacts of production, including animal welfare and antimicrobial use.
期刊介绍:
Agricultural Systems is an international journal that deals with interactions - among the components of agricultural systems, among hierarchical levels of agricultural systems, between agricultural and other land use systems, and between agricultural systems and their natural, social and economic environments.
The scope includes the development and application of systems analysis methodologies in the following areas:
Systems approaches in the sustainable intensification of agriculture; pathways for sustainable intensification; crop-livestock integration; farm-level resource allocation; quantification of benefits and trade-offs at farm to landscape levels; integrative, participatory and dynamic modelling approaches for qualitative and quantitative assessments of agricultural systems and decision making;
The interactions between agricultural and non-agricultural landscapes; the multiple services of agricultural systems; food security and the environment;
Global change and adaptation science; transformational adaptations as driven by changes in climate, policy, values and attitudes influencing the design of farming systems;
Development and application of farming systems design tools and methods for impact, scenario and case study analysis; managing the complexities of dynamic agricultural systems; innovation systems and multi stakeholder arrangements that support or promote change and (or) inform policy decisions.