Breeding Beyond Monoculture: Putting the “Intercrop” Into Crops - Bourke, Peter M.; Evers, Jochem B.; Bijma, Piter; van Apeldoorn, Dirk F.; Smulders, Marinus J. M.; Kuyper, Thomas W.; Mommer, Liesje; Bonnema, Guusje (Frontiers in Plant Science, 2021)
Intercropping is both a well-established and yet novel agricultural practice, depending on one’s perspective. Such perspectives are principally governed by geographic location and whether monocultural practices predominate. Given the negative environmental effects of monoculture agriculture (loss of biodiversity, reliance on non-renewable inputs, soil degradation etc.), there has been a renewed interest in cropping systems that can reduce the impact of modern agriculture while maintaining (or even increasing) yields. Intercropping is one of the most promising practices in this regard, yet faces a multitude of challenges if it is to compete with and ultimately replace the prevailing monocultural norm. These challenges include the necessity for more complex agricultural designs in space and time, bespoke machinery and adapted crop cultivars. Plant breeding for monocultures has focussed on maximising yield in single-species stands, leading to highly productive yet specialised genotypes. However, indications suggest that these genotypes are not the best adapted to intercropping systems. Re-designing breeding programs to accommodate inter-specific interactions and compatibilities, with potentially multiple different intercropping partners, is certainly challenging, but recent technological advances offer novel solutions. We identify a number of such technology-driven directions, either ideotype-driven (i.e. “trait-based” breeding) or quantitative genetics-driven (i.e. “product-based” breeding). For ideotype breeding, plant growth modelling can help predict plant traits that affect both inter- and intra-specific interactions and their influence on crop performance. Quantitative breeding approaches on the other hand estimate breeding values of component crops without necessarily understanding the underlying mechanisms. We argue that a combined approach, for example integrating plant growth modelling with genomic-assisted selection and Indirect Genetic Effects may offer the best chance to bridge the gap between current monoculture breeding programs and the more integrated and diverse breeding programs of the future.