Environmental efficiency of alternative dairy systems: a productive efficiency approach.
Agriculture across the globe needs to produce "more with less." Productivity should be increased in a sustainable manner so that the environment is not further degraded, management practices are both socially acceptable and economically favorable, and future generations are not disadvantaged. The objective of this paper was to compare the environmental efficiency of 2 divergent strains of Holstein-Friesian cows across 2 contrasting dairy management systems (grazing and nongrazing) over multiple years and so expose any genetic × environment (G × E) interaction. The models were an extension of the traditional efficiency analysis to account for undesirable outputs (pollutants), and estimate efficiency measures that allow for the asymmetric treatment of desirable outputs (i.e., milk production) and undesirable outputs. Two types of models were estimated, one considering production inputs (land, nitrogen fertilizers, feed, and cows) and the other not, thus allowing the assessment of the effect of inputs by comparing efficiency values and rankings between models. Each model type had 2 versions, one including 2 types of pollutants (greenhouse gas emissions, nitrogen surplus) and the other 3 (greenhouse gas emissions, nitrogen surplus, and phosphorus surplus). Significant differences were found between efficiency scores among the systems. Results indicated no G × E interaction; however, even though the select genetic merit herd consuming a diet with a higher proportion of concentrated feeds was most efficient in the majority of models, cows of the same genetic merit on higher forage diets could be just as efficient. Efficiency scores for the low forage groups were less variable from year to year, which reflected the uniformity of purchased concentrate feeds. The results also indicate that inputs play an important role in the measurement of environmental efficiency of dairy systems and that animal health variables (incidence of udder health disorders and body condition score) have a significant effect on the environmental efficiency of each dairy system. We conclude that traditional narrow measures of performance may not always distinguish dairy farming systems best fitted to future requirements.
Land Economy and Environment Group, Scotland's Rural College (SRUC), King's Buildings, West Mains Road, Edinburgh, EH9 3JG, United Kingdom.
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L
Toma
Future Farming Systems Group, SRUC, Hestan House, The Crichton Business Park, Dumfries, DG1 4TA, United Kingdom. Electronic address: maggie.march@sruc.ac.uk.
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M
March
Future Farming Systems Group, SRUC, King's Buildings, West Mains Road, Edinburgh, EH9 3JG, United Kingdom.
A W
AW
Stott
Future Farming Systems Group, SRUC, Hestan House, The Crichton Business Park, Dumfries, DG1 4TA, United Kingdom.
D J
DJ
Roberts
D000383:Agriculture; D000821:Animal Feed; D000818:Animals; D058572:Carbon Footprint; D002417:Cattle / Q000502:physiology*; D003247:Conservation of Natural Resources; D003612:Dairying / Q000379:methods*; D004032:Diet / Q000662:veterinary; D004777:Environment; D004787:Environmental Pollution; D005260:Female; D005308:Fertilizers; D005838:Genotype; D017752:Greenhouse Effect; D007774:Lactation; D008892:Milk; D009584:Nitrogen; D010758:Phosphorus; D013223:Statistics as Topic / Q000379:methods
D005308:Fertilizers; D010758:Phosphorus; D009584:Nitrogen
environmental efficiency; experimental dairy farm; nonparametric data envelopment analysis