A key issue in the debate on the contribution of organic agriculture to the future of world agriculture is whether organic agriculture can produce sufficient food to feed the world. Comparisons of organic and conventional yields play a central role in this debate. We therefore compiled and analyzed a meta-dataset of 362 published organic–conventional comparative crop yields. Our results show that organic yields of individual crops are on average 80% of conventional yields, but variation is substantial (standard devia- tion 21%). In our dataset, the organic yield gap significantly differed between crop groups and regions. The analysis gave some support to our hypothesis that the organic–conventional yield gap increases as conventional yields increase, but this relationship was only rather weak. The rationale behind this hypothesis is that when conventional yields are high and relatively close to the potential or water-limited level, nutrient stress must, as per definition of the potential or water-limited yield levels, be low and pests and diseases well controlled, which are conditions more difficult to attain in organic agriculture.
We discuss our findings in the context of the literature on this subject and address the issue of upscal- ing our results to higher system levels. Our analysis was at field and crop level. We hypothesize that due to challenges in the maintenance of nutrient availability in organic systems at crop rotation, farm and regional level, the average yield gap between conventional and organic systems may be larger than 20% at higher system levels. This relates in particular to the role of legumes in the rotation and the farm- ing system, and to the availability of (organic) manure at the farm and regional levels. Future research should therefore focus on assessing the relative performance of both types of agriculture at higher system levels, i.e. the farm, regional and global system levels, and should in that context pay particular attention to nutrient availability in both organic and conventional agriculture.
|2012.03.02||1.0||Raw Data File|