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Crop pollinator dependency for faba bean

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In this paper:

"Quantifying crop pollinator dependence and its heterogeneity using multi‐level meta‐analysis"

researchers Jacob Bishop and Shinichi Nakagawa focus on understanding the benefits of pollination to faba bean Vicia faba using a literature review and multi‐level meta‐analysis to estimate overall benefits of pollination to faba bean yield and to quantify variation in these benefits associated with different  factors such as plant genotype, growing environment.

Their overall estimate of pollination benefit to faba bean yield, expressed as the percentage yield reduction without pollination, is 32.9%. Based on the prediction intervals, which include the heterogeneity in pollination benefit, there is an 80% chance that pollination will increase yield of a faba bean crop.

Half of all heterogeneity in pollination dependence was due to differences between plant genotypes. The number of beans per plant showed similar pollination dependence to yield mass per plant while pod number and number of beans per pod underestimated yield benefits.

There was weak evidence to suggest pollination benefits vary between pollinator species, with honeybees showing a smaller yield increase.

They suggest that simplified experimental studies comparing yield of open‐pollinated and enclosed plants can provide reliable insights into pollination benefits across a large range of plant genotypes and landscapes.

Despite variability in pollination benefits due to various factors both inside and outside of grower control, there is a high likelihood that biotic pollination will increase faba bean yield.

They suggest that their findings support ecological intensification and specifically the management of pollinators to maximise pollination benefits to faba bean production.

Published in December 2020 in the Journal of Applied Ecology, the paper is open access

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The Leg Value project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727672.

European Union Legume Innovation Network