Looking in the Wrong Direction for Higher-Yielding Crop Genotypes

The biocontrol paradox

Biocontrol agents can significantly reduce the growth and performance of individual invasive plants but often have limited success in controlling invasions. Here, we suggest that some biocontrol failures may be understood by distinguishing between individual plant performance and the performance of groups growing in monoculture. The success of a group growing in monoculture can be maximised if individual plants limit their allocation of limited resources to competition. However, individual performance can be maximised by acquiring resources at the expense of neighbouring plants. Enemies such as herbivores can reduce the dominance of individual plants and limit resource allocation to competition. Thus, biocontrol could have the unexpected effect of increasing the performance of groups of invaders.

Breeding in winter wheat (Triticum aestivum L.) can be further progressed by targeting previously neglected competitive traits

Breeders work to adapt winter wheat genotypes for high planting densities to pursue sustainable intensification and maximize canopy productivity. Although the effects of plant-plant competition at high planting density have been extensively reported, the quantitative relationship between competitiveness and plant performance remains unclear. In this study, we introduced a shoot competitiveness index (SCI) to quantify the competitiveness of genotypes and examined the dynamics of nine competitiveness-related traits in 200 winter wheat genotypes grown in heterogeneous canopies at two planting densities. Higher planting densities increased shoot length but reduced biomass, tiller numbers, and leaf mass per area (LMA), with trait plasticity showing at least 41% variation between genotypes. Surprisingly, genotypes with higher LMA at low density exhibited greater decreases under high density, challenging expectations from game theory. Regression analysis identified tiller number, LMA, and shoot length as key traits influencing performance under high density. Contrary to our hypothesis, early competitiveness did not guarantee sustained performance, revealing the dynamic nature of plant-plant competition. Our evaluation of breeding progress across the panel revealed a declining trend in SCI (R² = 0.61), aligning with the breeding objective of reducing plant height to reduce individual competitiveness and increase the plant-plant cooperation. The absence of historical trends in functional traits and their plasticities, such as tiller number and LMA, suggests their potential for designing ideal trait-plasticity for plant-plant cooperation and further crop improvement.

Uncovering the genetic basis of competitiveness and the potential for cooperation in plant groups

Crop productivity was transformed by incorporating dwarfing genes that made plants smaller and less competitive (more cooperative). Beyond such major shifts in plant size, however, it is not clear how much variation in competitiveness remains and how to find its genetic basis. We performed plant density experiments, using 484 lines of the Arabidopsis thaliana multi-parent advanced generation inter-cross population, to compare methods for mapping the genetic basis of plant competitiveness. We first found that a major dwarfing gene, the erecta allele, caused reduced competitiveness and higher group productivity. Then, measuring competitiveness more generally, we found: (i) extensive variation in generic measures of competitiveness that extended beyond the effects of the erecta allele; (ii) a novel genomic region underlying variation in competitiveness; and (iii) that some measures of competitiveness were more useful than others. Our results show how modern genomic resources, including multi-parent populations, could uncover hidden genes for more cooperative crop plants.

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.

The Birth and Death of Floral Organs in Cereal Crops

Florets of cereal crops are the basic reproductive organs that produce grains for food or feed. The birth of a floret progresses through meristem initiation and floral organ identity specification and maintenance. During these processes, both endogenous and external cues can trigger a premature floral organ death, leading to reproductive failure. Recent advances in different cereal crops have identified both conserved and distinct regulators governing the birth of a floret. However, the molecular underpinnings of floral death are just beginning to be understood. In this review, we first provide a general overview of the current findings in the field of floral development in major cereals and outline different forms of floral deaths, particularly in the Triticeae crops. We then highlight the importance of vascular patterning and photosynthesis in floral development and reproductive success and argue for an expanded knowledge of floral birth-death balance in the context of agroecology.

DEKR-SPrior: An Efficient Bottom-Up Keypoint Detection Model for Accurate Pod Phenotyping in Soybean

The pod and seed counts are important yield-related traits in soybean. High-precision soybean breeders face the major challenge of accurately phenotyping the number of pods and seeds in a high-throughput manner. Recent advances in artificial intelligence, especially deep learning (DL) models, have provided new avenues for high-throughput phenotyping of crop traits with increased precision. However, the available DL models are less effective for phenotyping pods that are densely packed and overlap in in situ soybean plants; thus, accurate phenotyping of the number of pods and seeds in soybean plant is an important challenge. To address this challenge, the present study proposed a bottom-up model, DEKR-SPrior (disentangled keypoint regression with structural prior), for in situ soybean pod phenotyping, which considers soybean pods and seeds analogous to human people and joints, respectively. In particular, we designed a novel structural prior (SPrior) module that utilizes cosine similarity to improve feature discrimination, which is important for differentiating closely located seeds from highly similar seeds. To further enhance the accuracy of pod location, we cropped full-sized images into smaller and high-resolution subimages for analysis. The results on our image datasets revealed that DEKR-SPrior outperformed multiple bottom-up models, viz., Lightweight-OpenPose, OpenPose, HigherHRNet, and DEKR, reducing the mean absolute error from 25.81 (in the original DEKR) to 21.11 (in the DEKR-SPrior) in pod phenotyping. This paper demonstrated the great potential of DEKR-SPrior for plant phenotyping, and we hope that DEKR-SPrior will help future plant phenotyping.

Reduced Root Cortical Tissue with an Increased Root Xylem Investment Is Associated with High Wheat Yields in Central China

Trait-based approaches are increasingly used to understand crop yield improvement, although they have not been widely applied to anatomical traits. Little is known about the relationships between root and leaf anatomy and yield in wheat. We selected 20 genotypes that have been widely planted in Luoyang, in the major wheat-producing area of China, to explore these relationships. A field study was performed to measure the yields and yield components of the genotypes. Root and leaf samples were collected at anthesis to measure the anatomical traits relevant to carbon allocation and water transport. Yield was negatively correlated with cross-sectional root cortex area, indicating that reduced root cortical tissue and therefore reduced carbon investment have contributed to yield improvement in this region. Yield was positively correlated with root xylem area, suggesting that a higher water transport capacity has also contributed to increased yields in this study. The area of the leaf veins did not significantly correlate with yield, showing that the high-yield genotypes did not have larger veins, but they may have had a conservative water use strategy, with tight regulation of water loss from the leaves. This study demonstrates that breeding for higher yields in this region has changed wheat's anatomical traits, reducing the roots' cortical tissue and increasing the roots' xylem investment.

Agroecological genetics of biomass allocation in wheat uncovers genotype interactions with canopy shade and plant size

How plants distribute biomass among organs influences resource acquisition, reproduction and plant-plant interactions, and is essential in understanding plant ecology, evolution, and yield production in agriculture. However, the genetic mechanisms regulating allocation responses to the environment are largely unknown. We studied recombinant lines of wheat (Triticum spp.) grown as single plants under sunlight and simulated canopy shade to investigate genotype-by-environment interactions in biomass allocation to the leaves, stems, spikes, and grains. Size-corrected mass fractions and allometric slopes were employed to dissect allocation responses to light limitation and plant size. Size adjustments revealed light-responsive alleles associated with adaptation to the crop environment. Combined with an allometric approach, we demonstrated that polymorphism in the DELLA protein is associated with the response to shade and size. While a gibberellin-sensitive allelic effect on stem allocation was amplified when plants were shaded, size-dependent effects of this allele drive allocation to reproduction, suggesting that the ontogenetic trajectory of the plant affects the consequences of shade responses for allocation. Our approach provides a basis for exploring the genetic determinants underlying investment strategies in the face of different resource constraints and will be useful in predicting social behaviours of individuals in a crop community.

Dynamic Phytomeric Growth Contributes to Local Adaptation in Barley

Vascular plants have segmented body axes with iterative nodes and internodes. Appropriate node initiation and internode elongation are fundamental to plant fitness and crop yield; however, how these events are spatiotemporally coordinated remains elusive. We show that in barley (Hordeum vulgare L.), selections during domestication have extended the apical meristematic phase to promote node initiation, but constrained subsequent internode elongation. In both vegetative and reproductive phases, internode elongation displays a dynamic proximal-distal gradient, and among subpopulations of domesticated barleys worldwide, node initiation and proximal internode elongation are associated with latitudinal and longitudinal gradients, respectively. Genetic and functional analyses suggest that, in addition to their converging roles in node initiation, flowering-time genes have been repurposed to specify the timing and duration of internode elongation. Our study provides an integrated view of barley node initiation and internode elongation and suggests that plant architecture should be recognized as a collection of dynamic phytomeric units in the context of crop adaptive evolution.

OPT-ing out: Root-shoot dynamics are caused by local resource capture and biomass allocation, not optimal partitioning

Combining plant growth analysis with a simple model of local resource capture and biomass allocation applied to exemplary experimental data, showed that dynamic changes in allocation to roots when nutrients are scarce is caused by disparities in growth rates between roots and shoots. Whole-plant growth rates also change but are not caused by an adaptive allocation response. Allocation and whole-plant growth rate are interdependent, not independent, traits. Following a switch in nutrient availability or partial biomass removal, convergence of allocation and growth rate trajectories does not reflect goal-seeking behaviour, but the constraints imposed by finite resource availability. Optimal root-shoot allocations are unnecessary to maximise whole-plant growth rate. Similar growth rates are attainable with different allocations. Changes in allocation cannot maintain or restore a superior whole-plant growth rate. Roots and shoots do not have to be tightly coordinated but can operate semiautonomously, as their modular construction permits. These findings question the plausibility of the prevailing general explanation of plants' root-shoot allocation responses, 'optimal partitioning theory' (OPT). Local allocation models, not OPT, explain the origins of variability in root-shoot trade-offs in individuals, the allocation of biomass at global and ecosystem scales and inform selection for allocation plasticity in crop breeding.

Exploring the trade-off between individual fitness and community performance of wheat crops using simulated canopy shade

The genetic heritage of wheat (Triticum spp.) crops has been shaped by millions of years of predomestication natural selection, often driven by competition among individuals. However, genetic improvements in yield potential are thought to involve selection towards reduced competitiveness, thus enhancing adaptation to the crop environment. We investigated potential trade-offs between individual plant fitness and community performance using a population of introgression lines carrying chromosome segments of wild emmer (nondomesticated) in the background of an elite durum cultivar. We focused on light as a primary factor affecting plant-plant interactions and assessed morphological and biomass phenotypes of single plants grown in mixtures under sunlight and a simulated canopy shade, and the relevance of these phenotypes for the monoculture community in the field. We found that responses to canopy shade resemble responses to high density and contribute to both the individual and the community. Stepwise regressions suggested that grain number per spike and its persistence under shade are essential attributes of productive communities, advocating their use as a breeding target during early-generation selection. Overall, multiple phenotypes attained under shade could better explain community performance. Our novel, applicable, high-throughput set-up provides new prospects for studying and selecting single-plant phenotypes in a canopy-like environment.

Shade avoidance syndrome in soybean and ideotype toward shade tolerance

The shade avoidance syndrome (SAS) in soybean can have destructive effects on yield, as essential carbon resources reserved for yield are diverted to the petiole and stem for exaggerated elongation, resulting in lodging and susceptibility to disease. Despite numerous attempts to reduce the unfavorable impacts of SAS for the development of cultivars suitable for high-density planting or intercropping, the genetic bases and fundamental mechanisms of SAS remain largely unclear. The extensive research conducted in the model plant Arabidopsis provides a framework for understanding the SAS in soybean. Nevertheless, recent investigations suggest that the knowledge obtained from model Arabidopsis may not be applicable to all processes in soybean. Consequently, further efforts are required to identify the genetic regulators of SAS in soybean for molecular breeding of high-yield cultivars suitable for density farming. In this review, we present an overview of the recent developments in SAS studies in soybean and suggest an ideal planting architecture for shade-tolerant soybean intended for high-yield breeding.

Improved Field-Based Soybean Seed Counting and Localization with Feature Level Considered

Developing automated soybean seed counting tools will help automate yield prediction before harvesting and improving selection efficiency in breeding programs. An integrated approach for counting and localization is ideal for subsequent analysis. The traditional method of object counting is labor-intensive and error-prone and has low localization accuracy. To quantify soybean seed directly rather than sequentially, we propose a P2PNet-Soy method. Several strategies were considered to adjust the architecture and subsequent postprocessing to maximize model performance in seed counting and localization. First, unsupervised clustering was applied to merge closely located overcounts. Second, low-level features were included with high-level features to provide more information. Third, atrous convolution with different kernel sizes was applied to low- and high-level features to extract scale-invariant features to factor in soybean size variation. Fourth, channel and spatial attention effectively separated the foreground and background for easier soybean seed counting and localization. At last, the input image was added to these extracted features to improve model performance. Using 24 soybean accessions as experimental materials, we trained the model on field images of individual soybean plants obtained from one side and tested them on images obtained from the opposite side, with all the above strategies. The superiority of the proposed P2PNet-Soy in soybean seed counting and localization over the original P2PNet was confirmed by a reduction in the value of the mean absolute error, from 105.55 to 12.94. Furthermore, the trained model worked effectively on images obtained directly from the field without background interference.

Kin and Non-Kin Connected Plants Benefit More Than Disconnected Kin and Non-Kin Plants under Nutrient-Competitive Environments

In the natural environment, plants grow and interact with both conspecific and heterospecific neighbours under different environmental conditions. In this study, we tested whether Chenopodium quinoa Willd genotypes differ in growth performance when grown with kin and non-kin under nutrient limitation in pot partitioning treatments. Biomass accumulation, allocation, organ efficiency, and specific leaf area were measured at the end of the experiment. Response variables were differentially impacted by kinship, fertility, and barrier. Total dry mass, shoot dry mass, and root and stem allocation were greater for plants grown with kin in connected pots than with non-kin in connected pots across the nutrient treatments. Kin connected and disconnected plants had a greater specific root length, specific stem length, and average leaf mass than non-kin connected and disconnected plants. Non-kin connected and disconnected plants had greater LAR and SLA than kin connected and disconnected plants under low- and high-nutrient treatments. Plants always grew better in the presence of their kin than non-kin. These results conclude that quinoa plant production benefits from planting closely related individuals under both high- and low-nutrient conditions.

Kin selection theory and the design of cooperative crops

In agriculture and plant breeding, plant traits may be favoured because they benefit neighbouring plants and ultimately increase total crop yield. This idea of promoting cooperation among crop plants has existed almost as long as W.D. Hamilton's inclusive fitness (kin selection) theory, the leading framework for explaining cooperation in biology. However, kin selection thinking has not been adequately applied to the idea of cooperative crops. Here, I give an overview of modern kin selection theory and consider how it explains three key strategies for designing cooperative crops: (1) selection for a less-competitive plant type (a 'communal ideotype'); (2) group-level selection for yield; and (3) exploiting naturally selected cooperation. The first two strategies, using artificial selection, have been successful in the past but suffer from limitations that could hinder future progress. Instead, I propose an alternative strategy and a new 'colonial ideotype' that exploits past natural selection for cooperation among the modules (e.g., branches or stems) of individual plants. More generally, I suggest that Hamiltonian agriculture-a kin selection view of agriculture and plant breeding-transforms our understanding of how to improve crops of the future.

Explaining pre-emptive acclimation by linking information to plant phenotype

We review mechanisms for pre-emptive acclimation in plants and propose a conceptual model linking developmental and evolutionary ecology with the acquisition of information through sensing of cues and signals. The idea is that plants acquire much of the information in the environment not from individual cues and signals but instead from their joint multivariate properties such as correlations. If molecular signalling has evolved to extract such information, the joint multivariate properties of the environment must be encoded in the genome, epigenome, and phenome. We contend that multivariate complexity explains why extrapolating from experiments done in artificial contexts into natural or agricultural systems almost never works for characters under complex environmental regulation: biased relationships among the state variables in both time and space create a mismatch between the evolutionary history reflected in the genotype and the artificial growing conditions in which the phenotype is expressed. Our model can generate testable hypotheses bridging levels of organization. We describe the model and its theoretical bases, and discuss its implications. We illustrate the hypotheses that can be derived from the model in two cases of pre-emptive acclimation based on correlations in the environment: the shade avoidance response and acclimation to drought.

Bottom-up redistribution of biomass optimizes energy allocation, water use and yield formation in dryland wheat improvement

BACKGROUND

Modern wheat cultivars have been developed having distinct advantages in many aspects under drought stress, such as plasticity in biomass allocation and root system architecture. A better understanding of the biomass allocation mechanisms that enable modern wheat to achieve higher yields and yield-based water use efficiency (WUE_g ) is essential for implementing best management strategies and identifying phenotypic traits for cultivar improvement. We systematically investigated the biomass allocation, morphological and physiological characteristics of three ploidy wheat genotypes under 80% and 50% field water-holding capacity (FC) conditions. Some crucial traits were also assessed in a complementary field experiment.

RESULTS

The diploid and tetraploid genotypes were found to allocate more biomass to the root system, especially roots in the topsoil under drought stress. Our data illustrated that lower WUE_g and yield of these old genotypes were due to excessive investment in the root system, which was associated with severely restricted canopy development. Modern hexaploid genotypes were found to allocate smaller biomass to roots and larger biomass to shoots. This not only ensured the necessary water uptake, but also allowed the plant to distribute more assimilates and limited water to the shoots. Therefore, the hexaploid genotypes have evolved a stable plant canopy structure to optimize WUE_g and grain yield.

CONCLUSION

This study demonstrated that the biomass shift from below ground to above ground or a more balanced root:shoot ratio tended to optimize water use and yield of the modern cultivars. This discovery provides potential guidance for future dryland wheat breeding and sustainable management strategies. © 2021 Her Majesty the Queen in Right of Canada Journal of The Science of Food and Agriculture © 2021 Society of Chemical Industry. Reproduced with the permission of the Minister of Agriculture and Agri-Food Canada.

Soybean Yield Formation Physiology - A Foundation for Precision Breeding Based Improvement

The continued improvement of crop yield is a fundamental driver in agriculture and is the goal of both plant breeders and researchers. Plant breeders have been remarkably successful in improving crop yield, as demonstrated by the continued release of varieties with improved yield potential. This has largely been accomplished through performance-based selection, without specific knowledge of the molecular mechanisms underpinning these improvements. Insight into molecular mechanisms has been provided by plant molecular, genetic, and biochemical research through elucidation of the function of genes and pathways that underlie many of the physiological processes that contribute to yield potential. Despite this knowledge, the impact of most genes and pathways on yield components have not been tested in key crops or in a field environment for yield assessment. This gap is difficult to bridge, but field-based physiological knowledge offers a starting point for leveraging molecular targets to successfully apply precision breeding technologies such as genome editing. A better understanding of both the molecular mechanisms underlying crop yield physiology and yield limiting processes under field conditions is essential for elucidating which combinations of favorable alleles are required for yield improvement. Consequently, one goal in plant biology should be to more fully integrate crop physiology, breeding, genetics, and molecular knowledge to identify impactful precision breeding targets for relevant yield traits. The foundation for this is an understanding of yield formation physiology. Here, using soybean as an example, we provide a top-down review of yield physiology, starting with the fact that yield is derived from a population of plants growing together in a community. We review yield and yield-related components to provide a basic overview of yield physiology, synthesizing these concepts to highlight how such knowledge can be leveraged for soybean improvement. Using genome editing as an example, we discuss why multiple disciplines must be brought together to fully realize the promise of precision breeding-based crop improvement.

Meristem transitions and plant architecture-learning from domestication for crop breeding

Genetic networks that regulate meristem transitions were recurrent targets of selection during crop domestication and allow fine-tuning of plant architecture for improved crop productivity.

Evolutionary and ecological perspectives on the wheat phenotype

Technologies, from molecular genetics to precision agriculture, are outpacing theory, which is becoming a bottleneck for crop improvement. Here, we outline theoretical insights on the wheat phenotype from the perspective of three evolutionary and ecologically important relations-mother-offspring, plant-insect and plant-plant. The correlation between yield and grain number has been misinterpreted as cause-and-effect; an evolutionary perspective shows a striking similarity between crop and fishes. Both respond to environmental variation through offspring number; seed and egg size are conserved. The offspring of annual plants and semelparous fishes, lacking parental care, are subject to mother-offspring conflict and stabilizing selection. Labile reserve carbohydrates do not fit the current model of wheat yield; they can stabilize grain size, but involve trade-offs with root growth and grain number, and are at best neutral for yield. Shifting the focus from the carbon balance to an ecological role, we suggest that labile carbohydrates may disrupt aphid osmoregulation, and thus contribute to wheat agronomic adaptation. The tight association between high yield and low competitive ability justifies the view of crop yield as a population attribute whereby the behaviour of the plant becomes subordinated within that of the population, with implications for genotyping, phenotyping and plant breeding.

No neighbour-induced increase in root growth of soybean and sunflower in mesh-divider experiments after controlling for nutrient concentration and soil volume

Root competition is a key factor determining plant performance, community structure and ecosystem productivity. To adequately estimate the extent of root proliferation of plants in response to neighbours independently of nutrient availability, one should use a set-up that can simultaneously control for both nutrient concentration and soil volume at plant individual level. With a mesh-divider design, which was suggested as a promising solution for this problem, we conducted two intraspecific root competition experiments: one with soybean (Glycine max) and the other with sunflower (Helianthus annuus). We found no response of root growth or biomass allocation to intraspecific neighbours, i.e. an 'ideal free distribution' (IFD) norm, in soybean; and even a reduced growth as a negative response in sunflower. These responses are all inconsistent with the hypothesis that plants should produce more roots even at the expense of reduced fitness in response to neighbours, i.e. root over-proliferation. Our results suggest that neighbour-induced root over-proliferation is not a ubiquitous feature in plants. By integrating the findings with results from other soybean studies, we conclude that for some species this response could be a genotype-dependent response as a result of natural or artificial selection, or a context-dependent response so that plants can switch from root over-proliferation to IFD depending on the environment of competition. We also critically discuss whether the mesh-divider design is an ideal solution for root competition experiments.

Turning plant interactions upside down: Light signals from below matter

Plants grow in dense stands receive light signals of varying strength from all directions. Plant responses to light signals from below should be considered in light‐mediated plant interactions, as their consequences for plant performance differ among ecological and agricultural settings. Where to perceive, how to integrate and what type of responses can be induced by light signals from below are major questions that need to be solved to expand our understanding of light‐mediated plant interactions.

Light signalling shapes plant-plant interactions in dense canopies

Plants growing at high densities interact via a multitude of pathways. Here, we provide an overview of mechanisms and functional consequences of plant architectural responses initiated by light cues that occur in dense vegetation. We will review the current state of knowledge about shade avoidance, as well as its possible applications. On an individual level, plants perceive neighbour-associated changes in light quality and quantity mainly with phytochromes for red and far-red light and cryptochromes and phototropins for blue light. Downstream of these photoreceptors, elaborate signalling and integration takes place with the PHYTOCHROME INTERACTING FACTORS, several hormones and other regulators. This signalling leads to the shade avoidance responses, consisting of hyponasty, stem and petiole elongation, apical dominance and life cycle adjustments. Architectural changes of the individual plant have consequences for the plant community, affecting canopy structure, species composition and population fitness. In this context, we highlight the ecological, evolutionary and agricultural importance of shade avoidance.

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.

Seeking Crops with Balanced Parts for the Ideal Whole

Crop domestication and breeding considerably increased productivity over centuries but unconsciously lowered 'selfish plant behavior' or individual plant fitness. Paradoxically, enhancing individual plant fitness is mistakenly equated with crop improvement. Because agriculture relies on community performance, embracing an agroecological genetics and genomics viewpoint might maximize communal yield by matching crop genotypes to target environments.

The Genomes of the Allohexaploid Echinochloa crus-galli and Its Progenitors Provide Insights into Polyploidization-Driven Adaptation

The hexaploid species Echinochloa crus-galli is one of the most detrimental weeds in crop fields, especially in rice paddies. Its evolutionary history is similar to that of bread wheat, arising through polyploidization after hybridization between a tetraploid and a diploid species. In this study, we generated and analyzed high-quality genome sequences of diploid (E. haploclada), tetraploid (E. oryzicola), and hexaploid (E. crus-galli) Echinochloa species. Gene family analysis showed a significant loss of disease-resistance genes such as those encoding NB-ARC domain-containing proteins during Echinochloa polyploidization, contrary to their significant expansionduring wheat polyploidization, suggesting that natural selection might favor reduced investment in resistance in this weed to maximize its growth and reproduction. In contrast to the asymmetric patterns of genome evolution observed in wheat and other crops, no significant differences in selection pressure were detected between the subgenomes in E. oryzicola and E. crus-galli. In addition, distinctive differences in subgenome transcriptome dynamics during hexaploidization were observed between E. crus-galli and bread wheat. Collectively, our study documents genomic mechanisms underlying the adaptation of a major agricultural weed during polyploidization. The genomic and transcriptomic resources of three Echinochloa species and new insights into the polyploidization-driven adaptive evolution would be useful for future breeding cereal crops.

Making sense of Integrated Pest Management (IPM) in the light of evolution

Integrated Pest Management (IPM) is a holistic approach to combat pests (including herbivores, pathogens, and weeds) using a combination of preventive and curative actions, and only applying synthetic pesticides when there is an urgent need. Just as the recent recognition that an evolutionary perspective is useful in medicine to understand and predict interactions between hosts, diseases, and medical treatments, we argue that it is crucial to integrate an evolutionary framework in IPM to develop efficient and reliable crop protection strategies that do not lead to resistance development in herbivores, pathogens, and weeds. Such a framework would not only delay resistance evolution in pests, but also optimize each element of the management and increase the synergies between them. Here, we outline key areas within IPM that would especially benefit from a thorough evolutionary understanding. In addition, we discuss the difficulties and advantages of enhancing communication among research communities rooted in different biological disciplines and between researchers and society. Furthermore, we present suggestions that could advance implementation of evolutionary principles in IPM and thus contribute to the development of sustainable agriculture that is resilient to current and emerging pests.

The case for improving crop carbon sink strength or plasticity for a CO2-rich future

Atmospheric CO₂ concentration [CO₂] has increased from 260 to 280μmolmol^-1 (level during crop domestication up to the industrial revolution) to currently 400 and will reach 550μmolmol^-1 by 2050. C3 crops are expected to benefit from elevated [CO₂] (e-CO₂) thanks to photosynthesis responsiveness to [CO₂] but this may require greater sink capacity. We review recent literature on crop e-CO₂ responses, related source-sink interactions, how abiotic stresses potentially interact, and prospects to improve e-CO₂ response via breeding or genetic engineering. Several lines of evidence suggest that e-CO₂ responsiveness is related either to sink intrinsic capacity or adaptive plasticity, for example, involving enhanced branching. Wild relatives and old cultivars mostly showed lower photosynthetic rates, less downward acclimation of photosynthesis to e-CO₂ and responded strongly to e-CO₂ due to greater phenotypic plasticity. While reverting to such archaic traits would be an inappropriate strategy for breeding, we argue that substantial enhancement of vegetative sink vigor, inflorescence size and/or number and root sinks will be necessary to fully benefit from e-CO₂. Potential ideotype features based on enhanced sinks are discussed. The generic 'feast-famine' sugar signaling pathway may be suited to engineer sink strength tissue-specifically and stage-specifically and help validate ideotype concepts. Finally, we argue that models better accounting for acclimation to e-CO₂ are needed to predict which trait combinations should be targeted by breeders for a CO₂-rich world.

Engineering Improved Photosynthesis in the Era of Synthetic Biology

Much attention has been given to the enhancement of photosynthesis as a strategy for the optimization of crop productivity. As traditional plant breeding is most likely reaching a plateau, there is a timely need to accelerate improvements in photosynthetic efficiency by means of novel tools and biotechnological solutions. The emerging field of synthetic biology offers the potential for building completely novel pathways in predictable directions and, thus, addresses the global requirements for higher yields expected to occur in the 21st century. Here, we discuss recent advances and current challenges of engineering improved photosynthesis in the era of synthetic biology toward optimized utilization of solar energy and carbon sources to optimize the production of food, fiber, and fuel.

Photosynthesis in the fleeting shadows: an overlooked opportunity for increasing crop productivity?

Photosynthesis measurements are traditionally taken under steady-state conditions; however, leaves in crop fields experience frequent fluctuations in light and take time to respond. This slow response reduces the efficiency of carbon assimilation. Transitions from low to high light require photosynthetic induction, including the activation of Rubisco and the opening of stomata, whereas transitions from high to low light require the relaxation of dissipative energy processes, collectively known as non-photochemical quenching (NPQ). Previous attempts to assess the impact of these delays on net carbon assimilation have used simplified models of crop canopies, limiting the accuracy of predictions. Here, we use ray tracing to predict the spatial and temporal dynamics of lighting for a rendered mature Glycine max (soybean) canopy to review the relative importance of these delays on net cumulative assimilation over the course of both a sunny and a cloudy summer day. Combined limitations result in a 13% reduction in crop carbon assimilation on both sunny and cloudy days, with induction being more important on cloudy than on sunny days. Genetic variation in NPQ relaxation rates and photosynthetic induction in parental lines of a soybean nested association mapping (NAM) population was assessed. Short-term NPQ relaxation (<30 min) showed little variation across the NAM lines, but substantial variation was found in the speeds of photosynthetic induction, attributable to Rubisco activation. Over the course of a sunny and an intermittently cloudy day these would translate to substantial differences in total crop carbon assimilation. These findings suggest an unexplored potential for breeding improved photosynthetic potential in our major crops.