Identification of species traits enhancing yield in wheat-faba bean intercropping: development and sensitivity analysis of a minimalist mixture model

Abstract

Aim Cereal-legume intercropping can result in yield gains compared to monocrops. We aim to identify the combination of crop traits and management practices that confer a yield advantage in strip intercropping. Methods We developed a novel, parameter-sparse process-based crop growth model (Minimalist Mixture Model, M3) that can simulate strip intercrops under well-watered but nitrogen limited growth conditions. It was calibrated and validated for spring wheat (Triticum aestivum) and spring faba bean (Vicia faba) grown as monocrops and intercrops, and used to identify the most suitable trait combinations in these intercrops via sensitivity analyses. Results The land equivalent ratio of intercrops was greater than one over a wide range of nitrogen fertilizer levels, but transgressive overyielding, with total yield in the intercrop greater than that of either sole crop, was only obtained at intermediate nitrogen applications. We ranked the local sensitivities of the individual yields of wheat and faba bean of the whole intercrop under various nitrogen input levels to various crop traits. Conclusions The total intercrop yield can be improved by selecting specific traits related to phenology of both species, as well as light use efficiency of faba bean and, under high nitrogen applications, of wheat. Changes in height-related crop traits affected individual yields of species in intercrops but not the total intercrop yield.

Application of Crop Growth Models to Assist Breeding for Intercropping: Opportunities and Challenges

“…A more promising approach is developing dedicated minimalist crop growth models incorporating the plant characteristics and traits that are particularly important for the outcome of the intercrop. While even in these models some parameters cannot be immediately linked to traits for breeding, most of these minimalist crop growth models include parameters that either are true breeding traits important in an intercrop context, or could be easily linked to them; e.g., specific leaf area and plant height (Gou et al, 2017;Berghuijs et al, 2020;Tan et al, 2020). These are good candidates to be included in models to assist breeders.…”

“…For example, if maximizing the total intercrop community (seed) yield is the most important goal, then crop height of the component species might be less important. But if instead the individual yields of the component species matter most, then the crop height of the individual intercrop components is an important trait to consider (Berghuijs et al, 2020).…”

“…These models also facilitate model adjustment to various species or variety combinations grown in an intercrop under different conditions (Van der Werf et al, 2007). Minimalist crop models have been recently developed for strip intercrops of wheat and maize (Gou et al, 2017;Liu et al, 2017;Tan et al, 2020) or wheat and faba bean grown under nitrogen-limited conditions (Berghuijs et al, 2020).…”

“…The STICS model provides additional examples for crop related parameters that can account for the competitive ability and how it changes in intercrops: minimum and maximum root and biomass growth rates and species specific nitrogen dilution functions derived from theoretical optimum nitrogen contents in the admixed target species (Brisson et al, 2003;Corre-Hellou et al, 2009). Finally, in minimalist models, the following crop related parameters describing inter-specific competition have been used: minimum and maximum plant heights, relative growth rate, specific leaf area, RUE, nitrogen demand and dilution functions (Gou et al, 2017;Berghuijs et al, 2020;Tan et al, 2020).…”

Supply Chain Perspectives on Breeding for Legume–Cereal Intercrops

“…Recent advances in breeding tools and approaches highlight the growing interest in their potential use for intercrop breeding. Application of Function-Structural Plant Models (FSPM) and process-based minimalistic models could significantly reduce the complexity of intercrop breeding, and minimize the need for experimental evaluation of multiple crop genotype combinations and spatial designs ( Berghuijs et al, 2020 ; Blanc et al, 2021 ; Bourke et al, 2021 ). While simulation has shown the utility of genomic selection for intercrop breeding ( Bančič et al, 2021 ), using both phenotypic and genomic selection tools is strongly recommended ( Annicchiarico et al, 2021 ; Wolfe et al, 2021 ).…”