Do genomic innovations enable an economic and environmental win-win in dairy production?. (May 2020)

• Record Type: Journal Article
• Authors: Worden, David; Hailu, Getu
• Is Part Of: Agricultural systems. Volume 181(2020)
• Publication Date: 2020-05
• Subjects: Genomics -- Dairy economics -- Technology adoption -- Innovation -- Feed efficiency -- Food security -- Productivity growth -- Greenhouse gas emissions; Agricultural systems -- Periodicals; Agriculture -- Environmental aspects -- Periodicals; 338.16
• DOI: 10.1016/j.agsy.2020.102807
• Languages: English
• ISSNs: 0308-521X

Abstract

Abstract: Meeting global food demand and achieving environmental sustainability remain key challenges for the future, particularly given continued population growth, rising incomes, shifting dietary preferences, and global climate change. We examine the ex ante economic and environmental benefits of the adoption of genomic technologies to selectively breed dairy cattle for improved feed efficiency and reduced methane emissions. We use a farm-level representative dynamic multi-year enterprise budgeting stochastic simulation and optimization model to examine the effect of on-farm adoption. First, we find positive financial benefits to producers from a reduction in feed costs and environmental benefits to society from a reduction in methane emissions. Second, we find that the economic and environmental benefits depend on the predictive accuracy of genomic selection. Lower accuracies may lead to negative net financial returns, limiting widespread adoption of the technology. While these results are specific to a feed efficiency trait on a representative dairy farm in Ontario, Canada, they highlight potential benefits and challenges associated with selecting for novel traits using emerging biotechnologies. Highlights: Genomic selection for feed efficiency can be profitable for dairy operations However, there is significant variation and a high risk of a negative return Low predictive accuracy and overlapping phenotypic feed ranges lead to higher risk The value of delaying adoption is low but may limit advances in predictive accuracy