Diversity in Plant Breeding: A New Conceptual Framework

An allometry perspective on crops

Understanding trait-trait coordination is essential for successful plant breeding and crop modeling. Notably, plant size drives variation in morphological, physiological, and performance-related traits, as described by allometric laws in ecology. Yet, as allometric relationships have been limitedly studied in crops, how they influence and possibly limit crop performance remains unknown. Here, we review how an allometry perspective on crops gains insights into the phenotypic evolution during crop domestication, the breeding of varieties adapted to novel conditions, and the prediction of crop yields. As allometry is an active field of research, modeling and manipulating crop allometric relationships can help to develop more resilient and productive agricultural systems to face future challenges.

Impact of intraspecific genetic variation on interspecific competition: a theoretical case study of forage binary mixtures

Introduction

Increasing intraspecific genetic variation (IV) has been identified as a potential factor to improve productivity and stabilise botanical composition in plant communities. In grasslands systems, this could offer a lever to manage uncertainties of production and variability in the harvested species balance. However, little is known about the conditions to favour IV impact and the mechanisms at play.

Methods

The dependency of IV impact on traits holding it and environmental stressors were analysed using a spatially-explicit individual-based model (IBM) of grassland communities. Sixty-three binary mixtures were defined to reflect a gradient of functional divergence between species regarding light and nitrogen (N) acquisition. The growth and dynamics of these communities were simulated for one year with three possible IV levels under two environments contrasting in terms of soil N fertility.

Results and discussion

The model predicted a positive impact of moderate and high IV levels on maintaining the species balance over time, but no marked effects on mixture productivity. This stabilising effect increased at higher IV levels and under low soil N fertility. It also tended to be more pronounced in communities with intermediate functional divergence offering a significant overlap between light and N acquisition parameter values of both species. The major traits involved in the plant response to neighbours differed depending on the most contested resource, as indicated by the within-population selection of individuals with favourable N-related parameters under low N and light-related parameters under high N environments. The hypothesis that IV favours a complementarity of resource use between species was not supported. Rather, a greater spatial heterogeneity in competitive interactions was demonstrated, leading to a higher probability of growth and survival for individuals within the subordinate species. These results highlight the potential usefulness of IV to design forage mixtures with improved stability and resilience.

Harnessing monocrop breeding strategies for intercrops

Intercropping is considered advantageous for many reasons, including increased yield stability, nutritional value and the provision of various regulating ecosystem services. However, intercropping also introduces diverse competition effects between the mixing partners, which can negatively impact their agronomic performance. Therefore, selecting complementary intercropping partners is the key to realizing a well-mixed crop production. Several specialized intercrop breeding concepts have been proposed to support the development of complementary varieties, but their practical implementation still needs to be improved. To lower this adoption threshold, we explore the potential of introducing minor adaptations to commonly used monocrop breeding strategies as an initial stepping stone towards implementing dedicated intercrop breeding schemes. While we acknowledge that recurrent selection for reciprocal mixing abilities is likely a more effective breeding paradigm to obtain genetic progress for intercrops, a well-considered adaptation of monoculture breeding strategies is far less intrusive concerning the design of the breeding programme and allows for balancing genetic gain for both monocrop and intercrop performance. The main idea is to develop compatible variety combinations by improving the monocrop performance in the two breeding pools in parallel and testing for intercrop performance in the later stages of selection. We show that the optimal stage for switching from monocrop to intercrop testing should be adapted to the specificity of the crop and the heritability of the traits involved. However, the genetic correlation between the monocrop and intercrop trait performance is the primary driver of the intercrop breeding scheme optimization process.

Domestication and the evolution of crops: variable syndromes, complex genetic architectures, and ecological entanglements

Domestication can be considered a specialized mutualism in which a domesticator exerts control over the reproduction or propagation (fitness) of a domesticated species to gain resources or services. The evolution of crops by human-associated selection provides a powerful set of models to study recent evolutionary adaptations and their genetic bases. Moreover, the domestication and dispersal of crops such as rice, maize, and wheat during the Holocene transformed human social and political organization by serving as the key mechanism by which human societies fed themselves. Here we review major themes and identify emerging questions in three fundamental areas of crop domestication research: domestication phenotypes and syndromes, genetic architecture underlying crop evolution, and the ecology of domestication. Current insights on the domestication syndrome in crops largely come from research on cereal crops such as rice and maize, and recent work indicates distinct domestication phenotypes can arise from different domestication histories. While early studies on the genetics of domestication often identified single large-effect loci underlying major domestication traits, emerging evidence supports polygenic bases for many canonical traits such as shattering and plant architecture. Adaptation in human-constructed environments also influenced ecological traits in domesticates such as resource acquisition rates and interactions with other organisms such as root mycorrhizal fungi and pollinators. Understanding the ecological context of domestication will be key to developing resource-efficient crops and implementing more sustainable land management and cultivation practices.

Towards a practical threat assessment methodology for crop landraces

Crop landraces (LR), the traditional varieties of crops that have been maintained for millennia by repeated cycles of planting, harvesting, and selection, are genetically diverse compared to more modern varieties and provide one of the key components for crop improvement due to the ease of trait transfer within the crop species. However, LR diversity is increasingly threatened with genetic erosion and extinction by replacement with improved cultivars, lack of incentives for farmers to maintain traditional agricultural systems, and rising threats from climate change. Their active conservation is necessary to maintain this critical resource. However, as there are hundreds of thousands of LR and millions of LR populations for crops globally, active conservation is complex and resource-intensive. To assist in implementation, it is useful to be able to prioritise LR for conservation action and an obvious means of prioritisation is based on relative threat assessment. There have been several attempts to propose LR threat assessment methods, but none thus far has been widely accepted or applied. The aim of this paper is to present a novel, practical, standardised, and objective methodology for LR threat assessment derived from the widely applied IUCN Red Listing for wild species, involving the collation of time series information for LR population range, LR population trend, market, and farmer characteristics and LR context information. The collated information is compared to a set of threat criteria and an appropriate threat category is assigned to the LR when a threshold level is reached. The proposed methodology can be applied at national, regional, or global levels and any crop group.

Plant-soil synchrony in nutrient cycles: Learning from ecosystems to design sustainable agrosystems

Redesigning agrosystems to include more ecological regulations can help feed a growing human population, preserve soils for future productivity, limit dependency on synthetic fertilizers, and reduce agriculture contribution to global changes such as eutrophication and warming. However, guidelines for redesigning cropping systems from natural systems to make them more sustainable remain limited. Synthetizing the knowledge on biogeochemical cycles in natural ecosystems, we outline four ecological systems that synchronize the supply of soluble nutrients by soil biota with the fluctuating nutrient demand of plants. This synchrony limits deficiencies and excesses of soluble nutrients, which usually penalize both production and regulating services of agrosystems such as nutrient retention and soil carbon storage. In the ecological systems outlined, synchrony emerges from plant-soil and plant-plant interactions, eco-physiological processes, soil physicochemical processes, and the dynamics of various nutrient reservoirs, including soil organic matter, soil minerals, atmosphere, and a common market. We discuss the relative importance of these ecological systems in regulating nutrient cycles depending on the pedoclimatic context and on the functional diversity of plants and microbes. We offer ideas about how these systems could be stimulated within agrosystems to improve their sustainability. A review of the latest advances in agronomy shows that some of the practices suggested to promote synchrony (e.g., reduced tillage, rotation with perennial plant cover, crop diversification) have already been tested and shown to be effective in reducing nutrient losses, fertilizer use, and N2 O emissions and/or improving biomass production and soil carbon storage. Our framework also highlights new management strategies and defines the conditions for the success of these nature-based practices allowing for site-specific modifications. This new synthetized knowledge should help practitioners to improve the long-term productivity of agrosystems while reducing the negative impact of agriculture on the environment and the climate.

The genetic identity of neighboring plants in intraspecific mixtures modulates disease susceptibility of both wheat and rice

Mixing crop cultivars has long been considered as a way to control epidemics at the field level and is experiencing a revival of interest in agriculture. Yet, the ability of mixing to control pests is highly variable and often unpredictable in the field. Beyond classical diversity effects such as dispersal barrier generated by genotypic diversity, several understudied processes are involved. Among them is the recently discovered neighbor-modulated susceptibility (NMS), which depicts the phenomenon that susceptibility in a given plant is affected by the presence of another healthy neighboring plant. Despite the putative tremendous importance of NMS for crop science, its occurrence and quantitative contribution to modulating susceptibility in cultivated species remains unknown. Here, in both rice and wheat inoculated in greenhouse conditions with foliar fungal pathogens considered as major threats, using more than 200 pairs of intraspecific genotype mixtures, we experimentally demonstrate the occurrence of NMS in 11% of the mixtures grown in experimental conditions that precluded any epidemics. Thus, the susceptibility of these 2 major crops results from indirect effects originating from neighboring plants. Quite remarkably, the levels of susceptibility modulated by plant-plant interactions can reach those conferred by intrinsic basal immunity. These findings open new avenues to develop more sustainable agricultural practices by engineering less susceptible crop mixtures thanks to emergent but now predictable properties of mixtures.

Single-gene resolution of diversity-driven overyielding in plant genotype mixtures

In plant communities, diversity often increases productivity and functioning, but the specific underlying drivers are difficult to identify. Most ecological theories attribute positive diversity effects to complementary niches occupied by different species or genotypes. However, the specific nature of niche complementarity often remains unclear, including how it is expressed in terms of trait differences between plants. Here, we use a gene-centred approach to study positive diversity effects in mixtures of natural Arabidopsis thaliana genotypes. Using two orthogonal genetic mapping approaches, we find that between-plant allelic differences at the AtSUC8 locus are strongly associated with mixture overyielding. AtSUC8 encodes a proton-sucrose symporter and is expressed in root tissues. Genetic variation in AtSUC8 affects the biochemical activities of protein variants and natural variation at this locus is associated with different sensitivities of root growth to changes in substrate pH. We thus speculate that - in the particular case studied here - evolutionary divergence along an edaphic gradient resulted in the niche complementarity between genotypes that now drives overyielding in mixtures. Identifying genes important for ecosystem functioning may ultimately allow linking ecological processes to evolutionary drivers, help identify traits underlying positive diversity effects, and facilitate the development of high-performance crop variety mixtures.

A necessary considering factor for breeding: growth-defense tradeoff in plants

Crop diseases cause enormous yield losses and threaten global food security. Deployment of resistant cultivars can effectively control the disease and to minimize crop losses. However, high level of genetic immunity to disease was often accompanied by an undesired reduction in crop growth and yield. Recently, literatures have been rapidly emerged in understanding the mechanism of disease resistance and development genes in crop plants. To determine how and why the costs and the likely benefit of resistance genes caused in crop varieties, we re-summarized the present knowledge about the crosstalk between plant development and disease resistance caused by those genes that function as plasma membrane residents, MAPK cassette, nuclear envelope (NE) channels components and pleiotropic regulators. Considering the growth-defense tradeoffs on the basis of current advances, finally, we try to understand and suggest that a reasonable balancing strategies based on the interplay between immunity with growth should be considered to enhance immunity capacity without yield penalty in future crop breeding.

A major genetic locus in neighbours controls changes of gene expression and susceptibility in intraspecific rice mixtures

Reports indicate that intraspecific neighbours alter the physiology of focal plants, and with a few exceptions, their molecular responses to neighbours are unknown. Recently, changes in susceptibility to pathogen resulting from such interactions were demonstrated, a phenomenon called neighbour-modulated susceptibility (NMS). However, the genetics of NMS and the associated molecular responses are largely unexplored. Here, we analysed in rice the modification of biomass and susceptibility to the blast fungus pathogen in the Kitaake focal genotype in the presence of 280 different neighbours. Using genome-wide association studies, we identified the loci in the neighbour that determine the response in Kitaake. Using a targeted transcriptomic approach, we characterized the molecular responses in focal plants co-cultivated with various neighbours inducing a reduction in susceptibility. Our study demonstrates that NMS is controlled by one major locus in the rice genome of its neighbour. Furthermore, we show that this locus can be associated with characteristic patterns of gene expression in focal plant. Finally, we propose an hypothesis where Pi could play a role in explaining this case of NMS. Our study sheds light on how plants affect the physiology in their neighbourhood and opens perspectives for understanding plant-plant interactions.

The ecologically relevant genetics of plant-plant interactions

Interactions among plants have been long recognized as a major force driving plant community dynamics and crop yield. Surprisingly, our knowledge of the ecological genetics associated with variation of plant-plant interactions remains limited. In this opinion article by scientists from complementary disciplines, the international PLANTCOM network identified four timely questions to foster a better understanding of the mechanisms mediating plant assemblages. We propose that by identifying the key relationships among phenotypic traits involved in plant-plant interactions and the underlying adaptive genetic and molecular pathways, while considering environmental fluctuations at diverse spatial and time scales, we can improve predictions of genotype-by-genotype-by-environment interactions and modeling of productive and stable plant assemblages in wild habitats and crop fields.

Diversity matters in wheat mixtures: A genomic survey of the impact of genetic diversity on the performance of 12 way durum wheat mixtures grown in two contrasted and controlled environments

In ecology, an increase in genetic diversity within a community in natural ecosystems increases its productivity, while in evolutionary biology, kinship selection predicts that relatedness on social traits improves fitness. Varietal mixtures, where different genotypes are grown together, show contrasting results, especially for grain yield where both positive and negative effects of mixtures have been reported. To understand the effect of diversity on field performance, we grew 96 independent mixtures each composed with 12 durum wheat (Triticum turgidum ssp. durum Thell.) inbred lines, under two contrasting environmental conditions for water availability. Using dense genotyping, we imputed allelic frequencies and a genetic diversity index on more than 96000 loci for each mixture. We then analyzed the effect of genetic diversity on agronomic performance using a genome-wide approach. We explored the stress gradient hypothesis, which proposes that the greater the unfavourable conditions, the more beneficial the effect of diversity on mixture performance. We found that diversity on average had a negative effect on yield and its components while it was beneficial on grain weight. There was little support for the stress gradient theory. We discuss how to use genomic data to improve the assembly of varietal mixtures.

Nitrogen availability and plant-plant interactions drive leaf silicon concentration in wheat genotypes

Estimating plasticity of leaf silicon (Si) in response to abiotic and biotic factors underpins our comprehension of plant defences and stress resistance in natural and agroecosystems. However, how nitrogen (N) addition and intraspecific plant-plant interactions affect Si concentration remains unclear.We grew 19 durum wheat genotypes (Triticum turgidum ssp. durum) in pots, either alone or in intra- or intergenotypic cultures of two individuals, and with or without N. Above-ground biomass, plant height and leaf [Si] were quantified at the beginning of the flowering stage.Nitrogen addition decreased leaf [Si] for most genotypes, proportionally to the biomass increase. Si plasticity to plant-plant interactions varied significantly among genotypes, with both increases and decreases in leaf [Si] when mixed with a neighbour, regardless of the mixture type (intra-/intergenotype). Besides, increased leaf [Si] in response to plant-plant interactions was associated with increased plant height.Our results suggest the occurrence of both facilitation and competition for Si uptake from the rhizosphere in wheat mixtures. Future research should identify which leaf and root traits characterise facilitating neighbours for Si acquisition. We also show that Si could be involved in height gain in response to intraspecific competition, possibly for increasing light capture. This important finding opens up new research directions on Si and plant-plant interactions in both natural ecosystems and agroecosystems. More generally, our results stress the need to explore leaf Si plasticity in responses to both abiotic and biotic factors to understand plant stress resistance. Read the free Plain Language Summary for this article on the Journal blog.

Linking quantitative genetics with community-level performance: Are there operational models for plant breeding?

Plant breeding is focused on the genotype and population levels while targeting effects at higher levels of biodiversity, from crop covers to agroecosystems. Making predictions across nested levels of biodiversity is therefore a major challenge for the development of intercropping practices. New prediction tools and concepts are required to design breeding strategies with desirable outcomes at the crop community level. We reviewed theoretical advances in the field of evolutionary ecology to identify potentially operational ways of predicting the effects of artificial selection on community-level performances. We identified three main types of approaches differing in the way they model interspecific indirect genetic effects (IIGEs) at the community level: (1) The community heritability approach estimates the variance for IIGE induced by a focal species at the community level; (2) the joint phenotype approach quantifies genetic constraints between direct genetic effects and IIGE for a set of interacting species; (3) the community-trait genetic gradient approach decomposes the IIGE for a focal species across a multivariate set of its functional traits. We discuss the potential operational capacities of these approaches and stress that each is a special case of a general multitrait and multispecies selection index. Choosing one therefore involves assumptions and goals regarding the breeding target and strategy. Obtaining reliable quantitative, community-level predictions at the genetic level is constrained by the size and complexity of the experimental designs usually required. Breeding strategies should instead be compared using theoretically informed qualitative predictions. The need to estimate genetic covariances between traits measured both within and among species (for IIGE) is another obstacle, as the two are not determined by the exact same biological processes. We suggest future research directions and strategies to overcome these limits. Our synthesis offers an integrative theoretical framework for breeders interested in the genetic improvement of crop communities but also for scientists interested in the genetic bases of plant community functioning.

Biodiversity-based cropping systems: A long-term perspective is necessary

Biodiversity-based cropping systems are an interesting option to address the many challenges that agriculture faces. However, benefits of these systems should not obscure the fact that creating biodiversity-based cropping systems represents a major change for farmers. To address this challenge, we argue that designing biodiversity-based cropping systems requires transforming ecological concepts into technical opportunities. Indeed, integrating ecological concepts such as plant-soil feedback and plant functional traits more strongly into cropping system design offers promising opportunities for the provision of ecosystem services, such as pest and disease control, crop production (including crop yield stability), climate regulation and regulation of soil quality. Accordingly, we demonstrate that designing biodiversity-based cropping systems requires considering not only the short term but also the long term. This would ensure that the expected ecosystem services have enough time to build up and provide their full effects, that the cropping systems are resilient and that they avoid the limitations of short-term assessments, which do not sufficiently consider multi-year effects. Considering long-term consequences of system change - induced by biodiversity - is essential to identify potential trade-offs between ecosystem services, as well as agricultural obstacles to and mechanisms of change. Including farmers and other food-chain actors in cropping system design would help find acceptable compromises that consider not only the provision of ecosystem services, but also other dimensions related to economic viability, workload or the technical feasibility of crops, which are identified as major obstacles to crop diversification. This strategy represents an exciting research front for the development of agroecological cropping systems.

Moving towards the ecological intensification of tree plantations

The growing demand for timber and the boom in massive tree-planting programs could mean the spreading of mismanaged tree plantations worldwide. Here, we apply the concept of ecological intensification to forestry systems as a viable biodiversity-focused strategy that could be critical to develop productive, yet sustainable, tree plantations. Tree plantations can be highly productive if tree species are properly combined to complement their ecological functions. Simultaneously considering soil biodiversity and animal-mediated biocontrol will be critical to minimize the reliance on external inputs. Integrating genetic, functional, and demographic diversity across heterogeneous landscapes should improve resilience under climate change. Designing ecologically intensified plantations will mean breaking the timber productivity versus conservation dichotomy and assuring the maintenance of key ecosystem services at safe levels.

How Could the Use of Crop Wild Relatives in Breeding Increase the Adaptation of Crops to Marginal Environments?

Alongside the use of fertilizer and chemical control of weeds, pests, and diseases modern breeding has been very successful in generating cultivars that have increased agricultural production several fold in favorable environments. These typically homogeneous cultivars (either homozygous inbreds or hybrids derived from inbred parents) are bred under optimal field conditions and perform well when there is sufficient water and nutrients. However, such optimal conditions are rare globally; indeed, a large proportion of arable land could be considered marginal for agricultural production. Marginal agricultural land typically has poor fertility and/or shallow soil depth, is subject to soil erosion, and often occurs in semi-arid or saline environments. Moreover, these marginal environments are expected to expand with ongoing climate change and progressive degradation of soil and water resources globally. Crop wild relatives (CWRs), most often used in breeding as sources of biotic resistance, often also possess traits adapting them to marginal environments. Wild progenitors have been selected over the course of their evolutionary history to maintain their fitness under a diverse range of stresses. Conversely, modern breeding for broad adaptation has reduced genetic diversity and increased genetic vulnerability to biotic and abiotic challenges. There is potential to exploit genetic heterogeneity, as opposed to genetic uniformity, in breeding for the utilization of marginal lands. This review discusses the adaptive traits that could improve the performance of cultivars in marginal environments and breeding strategies to deploy them.

A research agenda for scaling up agroecology in European countries

A profound transformation of agricultural production methods has become unavoidable due to the increase in the world's population, and environmental and climatic challenges. Agroecology is now recognized as a challenging model for agricultural systems, promoting their diversification and adaptation to environmental and socio-economic contexts, with consequences for the entire agri-food system and the development of rural and urban areas. Through a prospective exercise performed at a large interdisciplinary institute, INRAE, a research agenda for agroecology was built that filled a gap through its ambition and interdisciplinarity. It concerned six topics. For genetics, there is a need to study genetic aspects of complex systems (e.g., mixtures of genotypes) and to develop breeding methods for them. For landscapes, challenges lie in effects of heterogeneity at multiple scales, in multifunctionality and in the design of agroecological landscapes. Agricultural equipment and digital technologies show high potential for monitoring dynamics of agroecosystems. For modeling, challenges include approaches to complexity, consideration of spatial and temporal dimensions and representation of the cascade from cropping practices to ecosystem services. The agroecological transition of farms calls for modeling and observational approaches as well as for creating new design methods. Integration of agroecology into food systems raises the issues of product specificity, consumer behavior and organization of markets, standards and public policies. In addition, transversal priorities were identified: (i) generating sets of biological data, through research and participatory mechanisms, that are appropriate for designing agroecological systems and (ii) collecting and using coherent sets of data to enable assessment of vulnerability, resilience and risk in order to evaluate the performance of agroecological systems and to contribute to scaling up. The main lessons learned from this collective exercise can be useful for the entire scientific community engaged in research into agroecology.

Shift in beneficial interactions during crop evolution

Plant domestication can be viewed as a form of co-evolved interspecific mutualism between humans and crops for the benefit of the two partners. Here, we ask how this plant-human mutualism has, in turn, impacted beneficial interactions within crop species, between crop species, and between crops and their associated microbial partners. We focus on beneficial interactions resulting from three main mechanisms that can be promoted by manipulating genetic diversity in agrosystems: niche partitioning, facilitation, and kin selection. We show that a combination of factors has impacted either directly or indirectly plant-plant interactions during domestication and breeding, with a trend toward reduced benefits arising from niche partitioning and facilitation. Such factors include marked decrease of molecular and functional diversity of crops and other organisms present in the agroecosystem, mass selection, and increased use of chemical inputs. For example, the latter has likely contributed to the relaxation of selection pressures on nutrient-mobilizing traits such as those associated to root exudation and plant nutrient exchanges via microbial partners. In contrast, we show that beneficial interactions arising from kin selection have likely been promoted since the advent of modern breeding. We highlight several issues that need further investigation such as whether crop phenotypic plasticity has evolved and could trigger beneficial interactions in crops, and whether human-mediated selection has impacted cooperation via kin recognition. Finally, we discuss how plant breeding and agricultural practices can help promoting beneficial interactions within and between species in the context of agroecology where the mobilization of diversity and complexity of crop interactions is viewed as a keystone of agroecosystem sustainability.

Coupling genetic structure analysis and ecological-niche modeling in Kersting’s groundnut in West Africa

Orphan legume crops play an important role in smallholder farmers’ food systems. Though less documented, they have the potential to contribute to adequate nutrition in vulnerable communities. Unfortunately, data are scarce about the potential of those crops to withstand current and future climate variations. Using Macrotyloma geocarpum as an example, we used ecological niche modeling to explore the role of ecology on the current and future distributions of genetic populations of Kersting’s groundnut. Our findings showed that: (1) the models had good predictive power, indicating that M. geocarpum’s distribution was correlated with both climatic and soil layers; (2) identity and similarity tests revealed that the two genetic groups have identical and similar environmental niches; (3) by integrating the genetic information in niche modeling, niches projections show divergence in the response of the species and genetic populations to ongoing climate change. This study highlights the importance of incorporating genetic data into Ecological Niche Modeling (ENM) approaches to obtain a finer information of species’ future distribution, and explores the implications for agricultural adaptation, with a particular focus on identifying priority actions in orphan crops conservation and breeding.

Harnessing the Potential of Wheat-Pea Species Mixtures: Evaluation of Multifunctional Performance and Wheat Diversity

Species mixtures and heterogeneous crop populations are two promising approaches for diversified ecological cropping systems with increased resilience and reduced dependency on external inputs. Inter- and intraspecific diversity were evaluated in combination using 15 wheat (Triticum aestivum) entries, including line cultivars and heterogeneous populations (HPs), from central Europe and Hungary and one winter pea cultivar under organic conditions. Monocultures and wheat mixtures were evaluated multi-functionally for yield, quality, land use efficiency, crop protection, and wheat entry traits. Mixtures increased cereal grain quality, weed suppression, resource use efficiency, yield gain, and reduced lodging. Effects were stronger in 2018/19, which were characterized by dry and nutrient-poor conditions than in 2019/20 when nutrient levels were higher. Wheat entries varied considerably in protein content and yield in both mixtures and monocultures. Under higher nutrient availability, entry-based variation was reduced in both systems, and peas were suppressed. Because of low disease pressure, the wheat entries varied little in terms of disease protection services, and mixture effects on the disease were low. The multi-criteria framework identified stability of yield, yield gains, and quality under high environmental variability of mixtures as clear agronomic advantages with HPs being considerably more stable than line cultivars. Some line cultivars outperformed the HPs in either protein content or yield across environments but not both simultaneously. Trait analysis revealed a possible link between harvest index and reduced competition in mixtures, which can increase yield performance in specific line cultivars. System cultivar interactions were generally very low and highly dependent on environmental conditions. We conclude that while cultivar breeding for mixtures can be successful in monocultures, high environmental variation highlights the necessity of evaluating cultivars in mixtures. In addition, use of intraspecific diversity within interspecific mixed cropping systems can be a valuable addition to further improve mixture performance and its stability under increasing environmental stresses due to climate change.

A Comprehensive Approach to Evaluate Durum Wheat-Faba Bean Mixed Crop Performance

Plant breeding for intercropping is lagging because most varieties currently available in the market are selected for sole cropping systems. The present study analyzed the response of durum wheat (12 varieties) and faba bean (3 varieties) in pure and mixed cropping. Field trials were conducted in 2019 and 2020. The performance of each variety in mixed and pure cropping was evaluated using both univariate and multivariate analyses of the grain yield and land equivalent ratio (LER). For durum wheat, grain protein content was also evaluated. Durum wheat varieties were characterized by good performance in both years, whereas faba bean varieties were more affected by the growing season, suggesting that much breeding effort is warranted to improve the latter as a pure and mixed crop. Moreover, the relative performance of all varieties was affected by their combination in mixed cropping, as evaluated based on the ratio (LERratio) between LER for wheat (LERw) and LER for faba bean (LERfb). To further evaluate the overall performance of wheat and faba bean in mixed cropping, total yield, LERtotal (LERw + LERfb), and ln(LERratio) were subjected to principal component and cluster analyses. The first principal component combined the total yield and LERtotal in a single index of the overall performance of each mixed crop combination. The second principal component, based on ln(LERratio), highlighted the relative performance of varieties in each mixed crop combination. The proposed multivariate approach can be applied in the breeding programs for intercropping to identify variety combinations based on crop performance and the relative importance of the proportion of cereal and legume grains in the total harvest.

From cultivar mixtures to allelic mixtures: opposite effects of allelic richness between genotypes and genotype richness in wheat

Agroecosystem diversification through increased crop genetic diversity could provide multiple services such as improved disease control or increased productivity. However, we still poorly understand how genetic diversity affects agronomic performance. We grew 179 inbred lines of durum wheat in pure stands and in 202 binary mixtures in field conditions. We then tested the effect of allelic richness between genotypes and genotype richness on grain yield and Septoria tritici blotch disease. Allelic richness was tested at 19K single nucleotide polymorphisms distributed along the durum wheat genome. Both genotype richness and allelic richness could be equal to 1 or 2. Mixtures were overall more productive and less diseased than their pure stand components. Yet, we identified one locus at which allelic richness between genotypes was associated with increased disease severity and decreased grain yield. The effect of allelic richness at this locus was stronger than the effect of genotype richness on grain yield (-7.6% vs +5.7%). Our results suggest that positive effects of crop diversity can be reversed by unfavourable allelic associations. This highlights the need to integrate genomic data into crop diversification strategies. More generally, investigating plant-plant interactions at the genomic level is promising to better understand biodiversity-ecosystem functioning relationships.

Supply Chain Perspectives on Breeding for Legume-Cereal Intercrops

Compared to sole crops, intercropping-especially of legumes and cereals-has great potential to improve crop yield and resource use efficiency, and can provide many other ecosystem services. However, the beneficial effects of intercrops are often greatly dependent on the end use as well as the specific species and genotypes being co-cultivated. In addition, intercropping imposes added complexity at different levels of the supply chain. While the need for developing crop genotypes for intercropping has long been recognized, most cultivars on the market are optimized for sole cropping and may not necessarily perform well in intercrops. This paper aims to place breeding targets for intercrop-adapted genotypes in a supply chain perspective. Three case studies of legumes and cereals intercropped for human consumption are used to identify desirable intercrop traits for actors across the supply chains, many of which are not targeted by traditional breeding for sole crops, including certain seed attributes, and some of which do not fit traditional breeding schemes, such as breeding for synchronized maturity and species synergies. Incorporating these traits into intercrop breeding could significantly reduce complexity along the supply chain. It is concluded that the widespread adoption and integration of intercrops will only be successful through the inclusion and collaboration of all supply chain actors, the application of breeding approaches that take into account the complexity of intercrop supply chains, and the implementation of diversification strategies in every process from field to fork.

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

Intercropping of two or more species on the same piece of land can enhance biodiversity and resource use efficiency in agriculture. Traditionally, intercropping systems have been developed and improved by empirical methods within a specific local context. To support the development of promising intercropping systems, the individual species that are part of an intercrop can be subjected to breeding. Breeding for intercropping aims at resource foraging traits of the admixed species to maximize niche complementarity, niche facilitation, and intercrop performance. The breeding process can be facilitated by modeling tools that simulate the outcome of the combination of different species' (or genotypes') traits for growth and yield development, reducing the need of extensive field testing. Here, we revisit the challenges associated with breeding for intercropping, and give an outlook on applying crop growth models to assist breeding for intercropping. We conclude that crop growth models can assist breeding for intercropping, provided that (i) they incorporate the relevant plant features and mechanisms driving interspecific plant-plant interactions; (ii) they are based on model parameters that are closely linked to the traits that breeders would select for; and (iii) model calibration and validation is done with field data measured in intercrops. Minimalist crop growth models are more likely to incorporate the above elements than comprehensive but parameter-intensive crop growth models. Their lower complexity and reduced parameter requirement facilitate the exploration of mechanisms at play and fulfil the model requirements for calibration of the appropriate crop growth models.

'Systems approach' plant breeding illustrated by trees

The linkage in new and creative ways of existing plant breeding methods responsive to different global trends and values provides a 'systems approach' to address a broad set of global production challenges more effectively. Here, we illustrate such an approach through its application to trees, chosen because of their extensive diversity in features, uses, users, production contexts, and domestication pathways. We coin the resulting strategy 'tree diversity breeding' and consider it with reference to trends and values related to participation, environment, biotechnology, and markets as examples. Features of the approach for trees are applicable to plant breeding more widely, as we seek to address complex problems through strategic biodiversity use.

Whole-plant phenotypic engineering: moving beyond ratios for multi-objective optimization of nutrient use efficiency

Nutrient use efficiency (NUE) is typically measured as the ratio of yield to soil nutrient availability but ignores contributions of underlying plant traits. Relevant plant traits can be grouped as root acquisition efficiency, shoot radiation use efficiency, and plant metabolic efficiency. The intentional integration of these traits will lead to synergistic improvements of NUE. Recent progress in trait-focused research includes phenotyping root nutrient uptake rates and respiration, engineering reduced photorespiration, and identification of nutrient assimilation pathways. Traits need to be conceptualized in agricultural systems contexts to improve synchrony of plant demand and soil supply of nutrients, including consideration of crop mixtures. Use of simulation modeling and multi-objective optimization will allow accelerating NUE gains beyond selection for a single ratio.

A genome‐wide analysis suggests pleiotropic effects of Green Revolution genes on shade avoidance in wheat

A classic example of phenotypic plasticity in plants is the suit of phenotypic responses induced by a change in the ratio of red to far-red light (R∶FR) as a result of shading, also known as the shade avoidance syndrome (SAS). While the adaptive consequences of this syndrome have been extensively discussed in natural ecosystems, how SAS varies within crop populations and how SAS evolved during crop domestication and breeding remain poorly known. In this study, we grew a panel of 180 durum wheat (Triticum turgidum ssp. durum) genotypes spanning diversity from wild, early domesticated, and elite genetic compartments under two light treatments: low R:FR light (shaded treatment) and high R:FR light (unshaded treatment). We first quantified the genetic variability of SAS, here measured as a change in plant height at the seedling stage. We then dissected the genetic basis of this variation through genome-wide association mapping. Genotypes grown in shaded conditions were taller than those grown under unshaded conditions. Interaction between light quality and genotype did not affect plant height. We found six QTLs affecting plant height. Three significantly interacted with light quality among which the well-known Rht1 gene introgressed in elite germplasm during the Green Revolution. Interestingly at three loci, short genotypes systematically expressed reduced SAS, suggesting a positive genetic correlation between plant height and plant height plasticity. Overall, our study sheds light on the evolutionary history of crops and illustrates the relevance of genetic approaches to tackle agricultural challenges.

Effect of Drought on Bean Yield Is Mediated by Intraspecific Variation in Crop Mixtures

Increasing plant diversity in agricultural systems provides promising solutions for sustainably increasing crop yield. It remains unclear; however, how plant-plant interactions in diverse systems are mediated by plant genetic variation. We conducted a greenhouse experiment in which we grew three varieties of common beans with three companion plant species (chickpeas, sorghum, and sunflower) in different combinations (crop mixtures, bean cultivar mixtures, and monocultures), with and without drought stress. We hypothesized that under drought stress, the effect of companion plant species on bean yield would be mediated by the drought tolerance potential of the species. We further hypothesized that this effect would vary across different bean cultivars. Overall, we show that the effect of companion plant species on bean yield was not influenced by drought stress; instead, it was dependent on the identity of the bean variety. This could partially be explained by variation in growth rate between bean varieties, where the fastest growing variety recorded the highest yield increase in plant mixtures. The effect of companion plant species on chickpea biomass, however, was potentially influenced by chickpea drought tolerance potential; chickpea biomass was recorded to be higher in plant mixtures than in its monoculture under drought conditions. Our study highlights that to develop plant mixtures, it is not only important to consider the functional traits of the interacting plant species, but also those of the different plant varieties. We further suggest that stress tolerance can be a useful trait for initial selection of plant varieties when developing crop mixtures.

Multivariate Analysis of Agronomic Traits in M4 Generation of Aromatic Rice Lines

<b>Background and Objective:</b> Developing rice (<i>Oryza sativa</i> L.) varieties with increased yield potential has been a major concern for genetic improvement. This study aimed to evaluate aromatic rice lines and the relationship among their twelve agronomic traits using heatmap Pearson correlation and multivariate analysis to identify high yield lines using grain yield as a marker-trait. <b>Materials and Methods:</b> Twelve aromatic rice genotypes (eleven mutant lines and one control) were evaluated in the M<sub>4</sub> generation. The experiment was conducted at Tana Toraja regency following Randomized Complete Block Design (RCBD) with two replications. <b>Results:</b> The darker and lighter colour scale produced by heatmap revealed contrasting nature of genotypes. A significant positive correlation observed for yield was the number of fertile grains and grain weight per panicle, while a negative correlation was days to flowering. The first four components account for 83.46% of the total cumulative variation. Cluster analysis grouped 11 lines and one control into three clusters. <b>Conclusion:</b> The results concluded that the PB-A.5.3.45 line could be used for hybridization programs to develop high-yielding mutant-derived aromatic rice varieties for further improvement.

Plant Breeding for Intercropping in Temperate Field Crop Systems: A Review

Monoculture cropping systems currently dominate temperate agroecosystems. However, intercropping can provide valuable benefits, including greater yield stability, increased total productivity, and resilience in the face of pest and disease outbreaks. Plant breeding efforts in temperate field crops are largely focused on monoculture production, but as intercropping becomes more widespread, there is a need for cultivars adapted to these cropping systems. Cultivar development for intercropping systems requires a systems approach, from the decision to breed for intercropping systems through the final stages of variety testing and release. Design of a breeding scheme should include information about species variation for performance in intercropping, presence of genotype × management interaction, observation of key traits conferring success in intercropping systems, and the specificity of intercropping performance. Together this information can help to identify an optimal selection scheme. Agronomic and ecological knowledge are critical in the design of selection schemes in cropping systems with greater complexity, and interaction with other researchers and key stakeholders inform breeding decisions throughout the process. This review explores the above considerations through three case studies: (1) forage mixtures, (2) perennial groundcover systems (PGC), and (3) soybean-pennycress intercropping. We provide an overview of each cropping system, identify relevant considerations for plant breeding efforts, describe previous breeding focused on the cropping system, examine the extent to which proposed theoretical approaches have been implemented in breeding programs, and identify areas for future development.

Population Structure of a Worldwide Phytophthora palmivora Collection Suggests Lack of Host Specificity and Reduced Genetic Diversity in South America and the Caribbean

Phytophthora palmivora (Butler) is a highly destructive plant pathogen that infects tropical hosts worldwide, many of which are economically important crops. Despite the broad host range and wide distribution, the pathogen has displayed a considerable amount of variation in morphological characters, including virulence. However, the genetic variability at a global level, which is critical to understand the center of origin and the potential pathway(s) of introduction, was unclear. Here, we mapped the genetic variation of P. palmivora using isolates representing four regions, 15 countries, and 14 host species. We designed a large set of simple sequence repeat markers from the P. palmivora genome and picked 17 selectively neutral markers to screen 98 P. palmivora isolates. We found that P. palmivora populations from our collection generally did not cluster according to host; rather, some isolates from North America were generally distinct from all other populations. Isolates from South America and the Caribbean clustered and appeared to share ancestry with isolates from Asia. Populations from North America and Asia were the most genetically diverse, while the South American and Caribbean populations exhibited similar reduced genetic diversity. The isolates collected in various plantations in Colombia did not show host or geographic specificity. Our study brought a further understanding of this important plant pathogen, although the determination for hypothesized source of origin, spread, and evolution would need further sampling. The genomic resources developed in this study would facilitate further studies on P. palmivora diagnostics and management.

The Genomic Architecture of Competitive Response of Arabidopsis thaliana Is Highly Flexible Among Plurispecific Neighborhoods

Plants are daily challenged by multiple abiotic and biotic stresses. A major biotic constraint corresponds to competition with other plant species. Although plants simultaneously interact with multiple neighboring species throughout their life cycle, there is still very limited information about the genetics of the competitive response in the context of plurispecific interactions. Using a local mapping population of Arabidopsis thaliana, we set up a genome wide association study (GWAS) to estimate the extent of genetic variation of competitive response in 12 plant species assemblages, based on three competitor species (Poa annua, Stellaria media, and Veronica arvensis). Based on five phenotypic traits, we detected strong crossing reaction norms not only between the three bispecific neighborhoods but also among the plurispecific neighborhoods. The genetic architecture of competitive response was highly dependent on the identity and the relative abundance of the neighboring species. In addition, most of the enriched biological processes underlying competitive responses largely differ among neighborhoods. While the RNA related processes might confer a broad range response toolkit for multiple traits in diverse neighborhoods, some processes, such as signaling and transport, might play a specific role in particular assemblages. Altogether, our results suggest that plants can integrate and respond to different species assemblages depending on the identity and number of each neighboring species, through a large range of candidate genes associated with diverse and unexpected processes leading to developmental and stress responses.

Cultivate biodiversity to harvest food security and sustainability

A confluence of discoveries in ecology and agriculture suggests that biodiversity can help address the sustainability problems facing modern intensive agriculture. Here we explore several questions related to this possibility. Can increases in national crop diversity help increase the stability and security of national food systems? Can practices based on greater crop biodiversity produce yields that compete with those obtained through the long-standing, high-input monoculture model? What are the appropriate levels and combinations of crops to be used? We highlight recent research that suggests it is time to begin unlocking the agricultural potential of biodiversity - from the level of crop genetic diversity to species diversity - and to do so on spatial scales from individual fields to nations. Recent research suggests that the biodiversification of agriculture may lead to greater and more stable yields, decrease land clearing, and lower the use of harmful agrochemicals.

Genome features of common vetch (Vicia sativa) in natural habitats

Wild plants are often tolerant to biotic and abiotic stresses in their natural environments, whereas domesticated plants such as crops frequently lack such resilience. This difference is thought to be due to the high levels of genome heterozygosity in wild plant populations and the low levels of heterozygosity in domesticated crop species. In this study, common vetch (Vicia sativa) was used as a model to examine this hypothesis. The common vetch genome (2n = 14) was estimated as 1.8 Gb in size. Genome sequencing produced a reference assembly that spanned 1.5 Gb, from which 31,146 genes were predicted. Using this sequence as a reference, 24,118 single nucleotide polymorphisms were discovered in 1243 plants from 12 natural common vetch populations in Japan. Common vetch genomes exhibited high heterozygosity at the population level, with lower levels of heterozygosity observed at specific genome regions. Such patterns of heterozygosity are thought to be essential for adaptation to different environments. The resources generated in this study will provide insights into de novo domestication of wild plants and agricultural enhancement.

Functional-Structural Plant Modeling Highlights How Diversity in Leaf Dimensions and Tillering Capability Could Promote the Efficiency of Wheat Cultivar Mixtures

Increasing the cultivated diversity has been identified as a major leverage for the agroecological transition as it can help improve the resilience of low input cropping systems. For wheat, which is the most cultivated crop worldwide in terms of harvested area, the use of cultivar mixtures is spreading in several countries, but studies have seldom focused on establishing mixing rules based on plant architecture. Yet, the aerial architecture of plants and the overall canopy structure are critical for field performance as they greatly influence light interception, plant interactions and yield. The very high number of trait combinations in wheat mixtures makes it difficult to conduct experimentations on this issue, which is why a modeling approach appears to be an appropriate solution. In this study, we used WALTer, a functional structural plant model (FSPM), to simulate wheat cultivar mixtures and try to better understand how differences between cultivars in key traits of the aerial architecture influence mixture performance. We simulated balanced binary mixtures of cultivars differing for different critical plant traits: final height, leaf dimensions, leaf insertion angle and tillering capability. Our study highlights the impact of the leaf dimensions and the tillering capability on the performance of the simulated mixtures, which suggests that traits impacting the plants' leaf area index (LAI) have more influence on the performance of the stand than traits impacting the arrangement of the leaves. Our results show that the performance of mixtures is very variable depending on the values of the explored architectural traits. In particular, the best performances were achieved by mixing cultivars with different leaf dimensions and different tillering capability, which is in agreement with numerous studies linking the diversity of functional traits in plant communities to their productivity. However, some of the worst performances were also achieved by mixing varieties differing in their aerial architecture, which suggests that diversity is not a sufficient criterion to design efficient mixtures. Overall, these results highlight the importance of simulation-based explorations for establishing assembly rules to design efficient mixtures.

Pea Breeding for Intercropping With Cereals: Variation for Competitive Ability and Associated Traits, and Assessment of Phenotypic and Genomic Selection Strategies

Mixed stand (MS) cropping of pea with small-grain cereals can produce more productive and environment-friendly grain crops relative to pure stand (PS) crops but may require selection to alleviate the pea competitive disadvantage. This study aimed to assess the pea variation for competitive ability and its associated traits and the efficiency of four phenotypic or genomic selection strategies. A set of 138 semi-leafless, semi-dwarf pea lines belonging to six recombinant inbred line populations and six parent lines were genotyped using genotyping-by-sequencing and grown in PS and in MS simultaneously with one barley and one bread wheat cultivar in two autumn-sown trials in Northern Italy. Cereal companions were selected in a preliminary study that highlighted the paucity of cultivars with sufficient earliness for association. Pea was severely outcompeted in both years albeit with variation for pea proportion ranging from nearly complete suppression (<3%) to values approaching a balanced mixture. Greater pea proportion in MS was associated with greater total yield of the mixture (r ≥ 0.46). The genetic correlation for pea yield across MS and PS conditions slightly exceeded 0.40 in both years. Later onset of flowering and taller plant height at flowering onset displayed a definite correlation with pea yield in MS (r ≥ 0.46) but not in PS, whereas tolerance to ascochyta blight exhibited the opposite pattern. Comparisons of phenotypic selection strategies within or across populations based on predicted or actual yield gains for independent years indicated an efficiency of 52-64% for indirect selection based on pea yield in PS relative to pea yield selection in MS. The efficiency of an indirect selection index including onset of flowering, plant height, and grain yield in PS was comparable to that of pea yield selection in MS. A genome-wide association study based on 5,909 SNP markers revealed the substantial diversity of genomic areas associated with pea yield in MS and PS. Genomic selection for pea yield in MS displayed an efficiency close to that of phenotypic selection for pea yield in MS, and nearly two-fold greater efficiency when also taking into account its shorter selection cycle and smaller evaluation cost.

Breeding Alfalfa (Medicago sativa L.) in Mixture with Grasses

Cultivation of forage mixtures offers several advantages over monocultures, but forage legumes like alfalfa (Medicago sativa L.) are mostly bred in pure stands. Our goal was to assess the extent of accession-by-cultivation system interaction when alfalfa plants are grown in pure stands or in an easily adaptable nursery system together with their companion grasses, thereby determining the system most suitable for selection in mixture. Spaced plants of 50 alfalfa accessions were grown on bare soil as control treatment (CONV), in a sown sward of short growing lawn cultivars of tall fescue (Festuca arundinacea Schreb.) and red fescue (F. rubra L.) (LAWN), and in a sown sward of taller forage cultivars of the same species (FORA). Accession-by-cultivation system interaction variances were large for growth habit but small for vigor. Phenotypic correlation coefficients (rp) among the cultivation systems were high for vigor, whereby LAWN was somewhat more predictive for FORA (rp, FORA−LAWN = 0.83) than CONV (rp, FORA−CONV = 0.77). Observed accession-by-genotype interactions can be used pro or contra necessity for selection in mixture. However, the LAWN cultivation system might be a good compromise for practical breeding, allowing to account for given competition effects among species and to easily assess traits in the nursery.

Ecological and evolutionary approaches to improving crop variety mixtures

Variety mixtures can provide a range of benefits for both the crop and the environment. Their utility for the suppression of pathogens, especially in small grain crops, is well established and has seen some remarkable successes. However, despite decades of academic interest in the topic, commercial efforts to develop, release and promote variety mixtures remain peripheral to normal breeding activities. Here we argue that this is because simple but general design principles that allow for the optimization of multiple mixture benefits are currently lacking. We therefore review the practical and conceptual challenges inherent in the development of variety mixtures, and discuss common approaches to overcome these. We further consider three domains in which they might be particularly beneficial: pathogen resistance, yield stability and yield enhancement. We demonstrate that combining evolutionary and ecological concepts with data typically available from breeding and variety testing programmes could make mixture development easier and more economic. Identifying synergies between the breeding for monocultures and mixtures may even be key to the widespread adoption of mixtures-to the profit of breeders, farmers and society as a whole.

Multi-Species Genomics-Enabled Selection for Improving Agroecosystems Across Space and Time

Plant breeding has been central to global increases in crop yields. Breeding deserves praise for helping to establish better food security, but also shares the responsibility of unintended consequences. Much work has been done describing alternative agricultural systems that seek to alleviate these externalities, however, breeding methods and breeding programs have largely not focused on these systems. Here we explore breeding and selection strategies that better align with these more diverse spatial and temporal agricultural systems.

Perennial groundcovers: an emerging technology for soil conservation and the sustainable intensification of agriculture

Integrating perennial groundcovers (PGC) — sometimes referred to as living mulches or perennial cover crops — into annual cash-crop systems could address root causes of bare-soil practices that lead to negative impacts on soil and water quality. Perennial groundcovers bring otherwise absent functional traits — namely perenniality — into cash-crop systems to preserve soil and regenerate water, carbon, and nutrient cycles. However, if not optimized, they can also cause competitive interactions and yield loss. When designing PGC systems, the goal is to maximize complementarity — spatial and temporal separation of growth and resource acquisition — between PGC and cash crops through both breeding and management. Traits of interest include complementary root and shoot systems, reduced shade avoidance response in the cash-crop, and PGC summer dormancy. Successful deployment of PGC systems could increase both productivity and profitability by improving water- and nutrient-use-efficiency, improving weed and pest control, and creating additional value-added opportunities like stover harvest. Many scientific questions about the inherent interactions at the cell, plant, and ecosystem levels in PGC systems are waiting to be explored. Their answers could enable innovation and refinement of PGC system design for multiple geographies, crops, and food systems, creating a practical and scalable pathway towards resiliency, crop diversification, and sustainable intensification in agriculture.

Trait Diversity of Pulse Species Predicts Agroecosystem Properties Trade-Offs

Crop diversity management in agriculture is a fundamental principle of agroecology and a powerful way to promote resilient and sustainable production systems. Pulses are especially relevant for diversification issues. Yet, the specific diversity of legumes is poorly represented in most cropping systems. We used the trait-based approach to quantify the functional diversity of 30 pulses varieties, belonging to 10 species, grown under common field conditions. Our aim was to test relationships between traits, yield, and supporting agroecosystem properties. Our experimental results highlighted trade-offs between agroecosystem properties supported by different combinations of traits. Also, results demonstrated the relevance of leaf nitrogen content (LNC), leaf area ratio (LAR), and reproductive phenology to predict most of the trade-offs observed between agroecosystem properties. A comparison with a previous analysis based on literature data collected in diverse agronomic situations suggested that some traits are more plastic than others and therefore contribute differently to frame legumes diversity depending on the conditions of observation. Present results suggested that the implementation of such trait-based approach would rapidly benefit the selection of species/varieties for specific targeted agroecosystem services provisioning under specific (environmental or management) conditions.

Modeling Illustrates That Genomic Selection Provides New Opportunities for Intercrop Breeding

Intercrop breeding programs using genomic selection can produce faster genetic gain than intercrop breeding programs using phenotypic selection. Intercropping is an agricultural practice in which two or more component crops are grown together. It can lead to enhanced soil structure and fertility, improved weed suppression, and better control of pests and diseases. Especially in subsistence agriculture, intercropping has great potential to optimize farming and increase profitability. However, breeding for intercrop varieties is complex as it requires simultaneous improvement of two or more component crops that combine well in the field. We hypothesize that genomic selection can significantly simplify and accelerate the process of breeding crops for intercropping. Therefore, we used stochastic simulation to compare four different intercrop breeding programs implementing genomic selection and an intercrop breeding program entirely based on phenotypic selection. We assumed three different levels of genetic correlation between monocrop grain yield and intercrop grain yield to investigate how the different breeding strategies are impacted by this factor. We found that all four simulated breeding programs using genomic selection produced significantly more intercrop genetic gain than the phenotypic selection program regardless of the genetic correlation with monocrop yield. We suggest a genomic selection strategy which combines monocrop and intercrop trait information to predict general intercropping ability to increase selection accuracy in the early stages of a breeding program and to minimize the generation interval.

Breeding Beyond Monoculture: Putting the "Intercrop" Into Crops

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 focused on maximizing yield in single-species stands, leading to highly productive yet specialized 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 modeling can help predict plant traits that affect both inter- and intraspecific 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 modeling 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.

Towards intercrop ideotypes: non-random trait assembly can promote overyielding and stability of species proportion in simulated legume-based mixtures

BACKGROUNDS AND AIMS

A major challenge when supporting the development of intercropping systems remains the design of efficient species mixtures. The ecological processes that sustain overyielding of legume-based mixtures compared to pure crops are well known, but their links to plant traits remain to be unravelled. A common assumption is that enhancing trait divergence among species for resource acquisition when assembling plant mixtures should increase species complementarity and improve community performance.

METHODS

The Virtual Grassland model was used to assess how divergence in trait values between species on four physiological functions (namely light and mineral N acquisition, temporal development, and C-N use efficiency) affected overyielding and mixture stability in legume-based binary mixtures. A first step allowed us to identify the model parameters that were most important to interspecies competition. A second step involved testing the impact of convergent and divergent parameter (or trait) values between species on virtual mixture performance.

RESULTS

Maximal overyielding was achieved in cases where trait values were divergent for the physiological functions controlling N acquisition and temporal development but convergent for light interception. It was also found that trait divergence should not affect competitive abilities of legume and non-legumes at random. Indeed, random trait combinations frequently led to reduced mixture yields when compared to a perfectly convergent neutral model. Combinations with the highest overyielding also tended to be associated with mixture instability and decreasing legume biomass proportion. Achieving both high overyielding and mixture stability was only found to be possible under low or moderate N levels, using combinations of traits adapted to each environment.

CONCLUSIONS

No simple assembly rule based on trait divergence could be confirmed. Plant models able to infer plant-plant interactions can be helpful for the identification of major interaction traits and the definition of ideotypes adapted to a targeted intercropping system.