The contribution of phenotypic plasticity to complementary light capture in plant mixtures

Quantification of the Cumulative Shading Capacity in a Maize-Soybean Intercropping System Using an Unmanned Aerial Vehicle

In intercropping systems, higher crops block direct radiation, resulting in inevitable shading on the lower crops. Cumulative shading capacity (CSC), defined as the amount of direct radiation shaded by higher crops during a growth period, affects the light interception and radiation use efficiency of crops. Previous studies investigated the light interception and distribution of intercropping. However, how to directly quantify the CSC and its inter-row heterogeneity is still unclear. Considering the canopy height differences (Hms, obtained using an unmanned aerial vehicle) and solar position, we developed a shading capacity model (SCM) to quantify the shading on soybean in maize-soybean intercropping systems. Our results indicated that the southernmost row of soybean had the highest shading proportion, with variations observed among treatments composed of strip configurations and plant densities (ranging from 52.44% to 57.44%). The maximum overall CSC in our treatments reached 123.77 MJ m-2. There was a quantitative relationship between CSC and the soybean canopy height increment (y = 3.61 × 10-2×ln(x)+6.80 × 10-1, P < 0.001). Assuming that the growth status of maize and soybean was consistent under different planting directions and latitudes, we evaluated the effects of factors (i.e., canopy height difference, latitude, and planting direction) on shading to provide insights for optimizing intercropping planting patterns. The simulation showed that increasing canopy height differences and latitude led to increased shading, and the planting direction with the least shading was about 90° to 120° at the experimental site. The newly proposed SCM offers a quantitative approach for better understanding shading in intercropping systems.

Maize-legume intercropping achieves yield advantages by improving leaf functions and dry matter partition

Intercropping can obtain yield advantages, but the mechanism of yield advantages of maize-legume intercropping is still unclear. Then, we explored the effects of cropping systems and N input on yield advantages in a two-year experiment. Cropping systems included monoculture maize (Zea mays L.) (MM), monoculture soybean (Glycine max L. Merr.) (MS), monoculture peanut (Arachis hypogaea L.) (MP), maize-soybean substitutive relay intercropping (IMS), and maize-peanut substitutive strip intercropping (IMP). N input included without N (N0) and N addition (N1). Results showed that maize's leaf area index was 31.0% and 34.6% higher in IMS and IMP than in MM. The specific leaf weight and chlorophyll a (chl a) of maize were notably higher by 8.0% and 18.8% in IMS, 3.1%, and 18.6% in IMP compared with MM. Finally, N addition resulted in a higher thousand kernels weight of maize in IMS and IMP than that in MM. More dry matter accumulated and partitioned to the grain, maize's averaged partial land equivalent ratio and the net effect were 0.76 and 2.75 t ha-1 in IMS, 0.78 and 2.83 t ha-1 in IMP. The leaf area index and specific leaf weight of intercropped soybean were 16.8% and 26% higher than MS. Although soybean suffers from shade during coexistence, recovered growth strengthens leaf functional traits and increases dry matter accumulation. The averaged partial land equivalent ratio and the net effect of intercropped soybean were 0.76 and 0.47 t ha-1. The leaf area index and specific leaf weight of peanuts in IMP were 69.1% and 14.4% lower than in the MP. The chlorophyll a and chlorophyll b of peanut in MP were 17.0% and 24.4% higher than in IMP. A less dry matter was partitioned to the grain for intercropped peanut. The averaged pLER and NE of intercropped peanuts were 0.26 and -0.55 t ha-1. In conclusion, the strengthened leaf functional traits promote dry matter accumulation, maize-soybean relay intercropping obtained a win-win yield advantage, and maize-peanut strip intercropping achieved a trade-off yield advantage.

Increasing sustainability by intercropping legume crops with sugar beet under imposed water stress

The sustainable use of soil and water resources is a goal that should be pursued to attain food security. This investigation was implemented to compare the effects of three legume intercropping systems with sugar beet on (i) enhancing sugar beet yield under imposed water stress conditions, (ii) soil N contents, (iii) land and water use efficiencies, and (iv) farmers' net income. Two field experiments were carried out in the 2018/19 and 2019/20 seasons in the El‐Minia Governorate, Egypt. The treatments included the interaction between three irrigation treatments: required irrigation ((control, 100% ETc, RI) and two levels of imposed water stress (85% ETc (WS1) and 70% ETc (WS2)), and three intercropping systems: faba bean (FIS), chickpea (CIS) and lentil (LIS) intercropped with sugar beet. The results indicate that the application of implementing CIS and with RI attained higher average values of soil N content (SNC = 14.0 mg kg−1) and net income (NI = US$3,974 ha−1) than those obtained by sugar beet alone. Irrigation with WS1 and the implementation of CIS gave a value of SNC (12.3 mg kg−1) close to that obtained under sugar beet alone irrigated with RI. CIS irrigated with WS1 attained higher averaged values of land equivalent ratio (LER = 1.34), area time equivalent ratio (ATER = 1.28), land equivalent coefficient (LEC = 0.38), water equivalent ratio (WER = 1.12), negative value of change in water use (ΔWU < 0) and NI (US$3,602 ha−1) than those obtained under FIS or LIS irrigated with RI. In conclusion, implementing CIS and irrigation with RI can achieve the sustainable use of land and water. However, implementing CIS and irrigation with WS1 can realize soil improvement, conserve irrigation water and attain higher values of LER, ATER, LEC, WER, and NI than those obtained under FIS, LIS and sugar beet alone.

Comparative analyses of functional traits based on metabolome and economic traits variation of Bletilla striata: Contribution of intercropping

The intercropping practice has been regarded as a practical land-use selection to improve the management benefits of Bletilla striata plantations. The reports about the variety of economic and functional traits of Bletilla pseudobulb under intercropping systems were limited. The present study investigated the variation of economic and functional traits of Bletilla pseudobulb under different intercropping systems (the deep-rooted intercropping system: B. striata - Cyclocarya paliurus, CB; and the shallow-rooted intercropping system: B. striata - Phyllostachys edulis, PB). The functional traits were analyzed through non-targeted metabolomics based on GC-MS. The results indicated that the PB intercropping system significantly decreased the yield of Bletilla pseudobulb while significantly increasing the total phenol and flavonoids compared with the control (CK). However, there were no significant differences in all economic traits between CB and CK. The functional traits among CB, PB, and CK were separated and exhibited significant differences. Under different intercropping systems, B. striata may adopt different functional strategies in response to interspecific competition. The functional node metabolites (D-galactose, cellobiose, raffinose, D-fructose, maltose, and D-ribose) were up-regulated in CB, while the functional node metabolites (L-valine, L-leucine, L-isoleucine, methionine, L-lysine, serine, D-glucose, cellobiose, trehalose, maltose, D-ribose, palatinose, raffinose, xylobiose, L-rhamnose, melezitose, and maltotriose) were up-regulated in PB. The correlation between economic and functional traits depends on the degree of environmental stress. Artificial neural network models (ANNs) accurately predicted the variation in economic traits via the combination of functional node metabolites in PB. The correlation analysis of environmental factors indicated that Ns (including TN, NH₄ ⁺-, and NO₃ ^--), SRI (solar radiation intensity), and SOC were the main factors that affected the economic traits (yield, total phenol, and total flavonoids). TN, SRI, and SOC were the main factors affecting the functional traits of the Bletilla pseudobulb. These findings strengthen our understanding of the variation of economic and functional traits of Bletilla pseudobulb under intercropping and clarify the main limiting environmental factors under B. striata intercropping systems.

Disentangling the Heterosis in Biomass Production and Radiation Use Efficiency in Maize: A Phytomer-Based 3D Modelling Approach

Maize (Zea mays L.) benefits from heterosis in-yield formation and photosynthetic efficiency through optimizing canopy structure and improving leaf photosynthesis. However, the role of canopy structure and photosynthetic capacity in determining heterosis in biomass production and radiation use efficiency has not been separately clarified. We developed a quantitative framework based on a phytomer-based three-dimensional canopy photosynthesis model and simulated light capture and canopy photosynthetic production in scenarios with and without heterosis in either canopy structure or leaf photosynthetic capacity. The accumulated above-ground biomass of Jingnongke728 was 39% and 31% higher than its male parent, Jing2416, and female parent, JingMC01, while accumulated photosynthetically active radiation was 23% and 14% higher, correspondingly, leading to an increase of 13% and 17% in radiation use efficiency. The increasing post-silking radiation use efficiency was mainly attributed to leaf photosynthetic improvement, while the dominant contributing factor differs for male and female parents for heterosis in post-silking yield formation. This quantitative framework illustrates the potential to identify the key traits related to yield and radiation use efficiency and helps breeders to make selections for higher yield and photosynthetic efficiency.

Leaf, plant, to canopy: A mechanistic study on aboveground plasticity and plant density within a maize-soybean intercrop system for the Midwest, USA

Plants have evolved to adapt to their neighbours through plastic trait responses. In intercrop systems, plant growth occurs at different spatial and temporal dimensions, creating a competitive light environment where aboveground plasticity may support complementarity in light-use efficiency, realizing yield gains per unit area compared with monoculture systems. Physiological and architectural plasticity including the consequences for light-use efficiency and yield in a maize-soybean solar corridor intercrop system was compared, empirically, with the standard monoculture systems of the Midwest, USA. The impact of reducing maize plant density on yield was investigated in the following year. Intercropped maize favoured physiological plasticity over architectural plasticity, which maintained harvest index (HI) but reduced light interception efficiency (ɛ_i ) and conversion efficiency (ɛ_c ). Intercropped soybean invested in both plasticity responses, which maintained ɛ_i , but HI and ɛ_c decreased. Reducing maize plant density within the solar corridor rows did not improve yields under monoculture and intercrop systems. Overall, the intercrop decreased land-use efficiency by 9%-19% and uncoordinated investment in aboveground plasticity by each crop under high maize plant density does not support complementarity in light-use efficiency. Nonetheless, the mechanistic understanding gained from this study may improve crop cultivars and intercrop designs for the Midwest to increase yield.

Design and Development of a Low-Cost UGV 3D Phenotyping Platform with Integrated LiDAR and Electric Slide Rail

Unmanned ground vehicles (UGV) have attracted much attention in crop phenotype monitoring due to their lightweight and flexibility. This paper describes a new UGV equipped with an electric slide rail and point cloud high-throughput acquisition and phenotype extraction system. The designed UGV is equipped with an autopilot system, a small electric slide rail, and Light Detection and Ranging (LiDAR) to achieve high-throughput, high-precision automatic crop point cloud acquisition and map building. The phenotype analysis system realized single plant segmentation and pipeline extraction of plant height and maximum crown width of the crop point cloud using the Random sampling consistency (RANSAC), Euclidean clustering, and k-means clustering algorithm. This phenotyping system was used to collect point cloud data and extract plant height and maximum crown width for 54 greenhouse-potted lettuce plants. The results showed that the correlation coefficient (R2) between the collected data and manual measurements were 0.97996 and 0.90975, respectively, while the root mean square error (RMSE) was 1.51 cm and 4.99 cm, respectively. At less than a tenth of the cost of the PlantEye F500, UGV achieves phenotypic data acquisition with less error and detects morphological trait differences between lettuce types. Thus, it could be suitable for actual 3D phenotypic measurements of greenhouse crops.

Consequences of interplant trait variation for canopy light absorption and photosynthesis

Plant-to-plant variation (interplant variation) may play an important role in determining individual plant and whole canopy performance, where interplant variation in architecture and photosynthesis traits has direct effects on light absorption and photosynthesis. We aimed to quantify the importance of observed interplant variation on both whole-plant and canopy light absorption and photosynthesis. Plant architecture was measured in two experiments with fruiting tomato crops (Solanum lycopersicum) grown in glasshouses in the Netherlands, in week 16 (Exp. 1) or week 19 (Exp. 2) after transplanting. Experiment 1 included four cultivars grown under three supplementary lighting treatments, and Experiment 2 included two different row orientations. Measured interplant variations of the architectural traits, namely, internode length, leaf area, petiole angle, and leaflet angle, as well as literature data on the interplant variation of the photosynthesis traits alpha, J max28, and V cmax28, were incorporated in a static functional-structural plant model (FSPM). The FSPM was used to analyze light absorption and net photosynthesis of whole plants in response to interplant variation in architectural and photosynthesis traits. Depending on the trait, introducing interplant variation in architecture and photosynthesis traits in a functional-structural plant model did not affect or negatively affected canopy light absorption and net photosynthesis compared with the reference model without interplant variation. Introducing interplant variation of architectural and photosynthesis traits in FSPM results in a more realistic simulation of variation of plants within a canopy. Furthermore, it can improve the accuracy of simulation of canopy light interception and photosynthesis although these effects at the canopy level are relatively small (<4% for light absorption and<7% for net photosynthesis).

Plastic response of leaf traits to N deficiency in field-grown maize

Nitrogen (N) utilization for crop production under N deficiency conditions is subject to a trade-off between maintaining specific leaf N content (SLN) important for radiation-use efficiency versus maintaining leaf area (LA) development, important for light capture. This paper aims to explore how maize deals with this trade-off through responses in SLN, LA and their underlying traits during the vegetative and reproductive growth stages. In a 10-year N fertilization trial in Jilin province, Northeast China, three N fertilizer levels have been maintained: N deficiency (N0), low N supply (N1) and high N supply (N2). We analysed data from years 8 and 10 of this experiment for two common hybrids. Under N deficiency, maize plants maintained LA and decreased SLN during vegetative stages, while both LA and SLN decreased comparably during reproductive stages. Canopy SLA (specific leaf area, cm² g^-1) decreased sharply during vegetative stages and slightly during reproductive stages, mainly because senesced leaves in the lower canopy had a higher SLA. In the vegetative stage, maize maintained LA at low N by maintaining leaf biomass (albeit hence having N content/mass) and slightly increasing SLA. These responses to N deficiency were stronger in maize hybrid XY335 than in ZD958. We conclude that the main strategy of maize to cope with low N is to maintain LA, mainly by increasing SLA throughout the plant but only during the vegetative growth phase.

Morphological and physiological variation of soybean seedlings in response to shade

Soybean (Glycine max) is a legume species that is widely used in intercropping. Quantitative analyses of plasticity and genetic differences in soybean would improve the selection and breeding of soybean in intercropping. Here, we used data of 20 varieties from one year artificial shading experiment and one year intercropping experiment to characterize the morphological and physiological traits of soybean seedlings grown under shade and full sun light conditions. Our results showed that shade significantly decreased biomass, leaf area, stem diameter, fraction of dry mass in petiole, leaf mass per unit area, chlorophyll a/b ratio, net photosynthetic rate per unit area at PAR of 500 μmol m-2 s-1 and 1,200 μmol m-2 s-1 of soybean seedling, but significantly increased plant height, fraction of dry mass in stem and chlorophyll content. Light × variety interaction was significant for all measured traits, light effect contributed more than variety effect. The biomass of soybean seedlings was positively correlated with leaf area and stem diameter under both shade and full sunlight conditions, but not correlated with plant height and net photosynthetic rate. The top five (62.75% variation explained) most important explanatory variables of plasticity of biomass were that the plasticity of leaf area, leaf area ratio, leaflet area, plant height and chlorophyll content, whose total weight were 1, 0.9, 0.3, 0.2, 0.19, respectively. The plasticity of biomass was positively correlated with plasticity of leaf area and leaflet area but significant negative correlated with plasticity of plant height. The principal component one account for 42.45% variation explain. A cluster analysis further indicated that soybean cultivars were classified into three groups and cultivars; Jiandebaimaodou, Gongdou 2, and Guixia 3 with the maximum plasticity of biomass. These results suggest that for soybean seedlings grown under shade increasing the capacity for light interception by larger leaf area is more vital than light searching (plant height) and light conversion (photosynthetic rate).

Use of 3D modeling to refine predictions of canopy light utilization: A comparative study on canopy photosynthesis models with different dimensions

Canopy photosynthesis integrates leaf functional and structural traits in space and time and correlates positively with yield formation. Many models with different levels of architectural details ranging from zero-dimensional (0D) to three-dimensional (3D) have been developed to simulate canopy light interception and photosynthesis. Based on these models, a crop growth model can be used to assess crop yield in response to genetic improvement, optimized practices, and environmental change. However, to what extent do architectural details influence light interception, photosynthetic production, and grain yield remains unknown. Here, we show that a crop growth model with high-resolution upscaling approach in space reduces the departure of predicted yield from actual yield and refines the simulation of canopy photosynthetic production. We found crop yield predictions decreased by 12.0-48.5% with increasing the resolution of light simulation, suggesting that a crop growth model without architectural details may result in a considerable departure from the actual photosynthetic production. A dramatic difference in light interception and photosynthetic production of canopy between cultivars was captured by the proposed 3D model rather than the 0D, 1D, and 2D models. Furthermore, we found that the overestimation of crop yield by the 0D model is caused by the overestimation of canopy photosynthetically active radiation (PAR) interception and the RUE and that by the 1D and 2D model is caused by the overestimated canopy photosynthesis rate that is possibly related to higher predicted PAR and fraction of sunlit leaves. Overall, this study confirms the necessity of taking detailed architecture traits into consideration when evaluating the strategies of genetic improvement and canopy configuration in improving crop yield by crop modeling.

Active and adaptive plasticity in a changing climate

Better understanding of the mechanistic basis of plant plasticity will enhance efforts to breed crops resilient to predicted climate change. However, complexity in plasticity's conceptualisation and measurement may hinder fruitful crossover of concepts between disciplines that would enable such advances. We argue active adaptive plasticity is particularly important in shaping the fitness of wild plants, representing the first line of a plant's defence to environmental change. Here, we define how this concept may be applied to crop breeding, suggest appropriate approaches to measure it in crops, and propose a refocussing on active adaptive plasticity to enhance crop resilience. We also discuss how the same concept may have wider utility, such as in ex situ plant conservation and reintroductions.

Niche partitioning in nitrogen uptake among subtropical tree species enhances biomass production

Nitrogen (N) is a main nutrient limiting plant growth in most terrestrial ecosystems, but so far it remains unknown which role plant N uptake plays for the positive relationship between species richness and productivity. An in situ¹⁵N labeling experiment was carried out by planting four subtropical tree species (i.e., Koelreuteria bipinnata, Lithocarpus glaber, Cyclobalanopsis myrsinaefolia and Castanopsis eyrei) in pots, at richness levels 1, 2 and 4 species per pot. Plant N uptake preference for inorganic N form of NO₃^- to NH₄⁺ and organic N form of glycine, as well as biomass and plant functional traits was evaluated under different tree species richness level. Overall, pot biomass productivity increased with tree species richness. Biomass of the most productive species, K. bipinnata increased, but not at the expense of a decreased growth of the other species. In mixtures, the species shifted their preference for the inorganic N form, from NO₃^- to NH₄⁺ or vice versa. The uptake preference for glycine remained stable along the species richness gradient. Plant N uptake was well correlated with numerous functional traits, both aboveground, such as height and shoot diameter, and belowground, such as root diameter and root length. We conclude that increased ecosystem biomass production with tree species richness could be largely explained by niche partitioning in N uptake among tree species. Our findings highlight that niche partitioning for N uptake should be a possible important mechanism maintaining species diversity and ecosystem production in subtropical forests.

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.

iTRAQ-based proteomic analysis of heteromorphic leaves reveals eco-adaptability of Populus euphratica Oliv

BACKGROUND

Heterophylly is regard as adaptation to different environments in plant, and Populus euphratica is an important heterophyllous woody plant. However, information on its molecular mechanism in eco-adaptability remains obscure.

RESULTS

In this research, proteins were identified by isobaric tags for relative and absolute quantitation (iTRAQ) technology in lanceolate, ovate, and dentate broad-ovate leaves from adult P. euphratica trees, respectively. Besides, chlorophyll content, net photosynthetic rate, stomatal conductance, transpiration rate and peroxidase activity in these heteromorphic leaves were investigated. A total number of 2,689 proteins were detected in the heteromorphic leaves, of which 56, 73, and 222 differential abundance proteins (DAPs) were determined in ovate/lanceolate, dentate broad-ovate/lanceolate, and dentate broad-ovate/ovate comparison groups. Bioinformatics analysis suggested these altered proteins related to photosynthesis, stress tolerance, respiration and primary metabolism accumulated in dentate broad-ovate and ovate leaves, which were consistent with the results of physiological parameters and Real-time Quantitative PCR experiments.

CONCLUSION

This research demonstrated the mechanism of the differential abundance proteins in providing an optimal strategy of resource utilization and survival for P. euphratica, that could offer clues for further investigations into eco-adaptability of heterophyllous woody plants.

Analyzing the Impact of Greenhouse Planting Strategy and Plant Architecture on Tomato Plant Physiology and Estimated Dry Matter

Determine the level of significance of planting strategy and plant architecture and how they affect plant physiology and dry matter accumulation within greenhouses is essential to actual greenhouse plant management and breeding. We thus analyzed four planting strategies (plant spacing, furrow distance, row orientation, planting pattern) and eight different plant architectural traits (internode length, leaf azimuth angle, leaf elevation angle, leaf length, leaflet curve, leaflet elevation, leaflet number/area ratio, leaflet length/width ratio) with the same plant leaf area using a formerly developed functional-structural model for a Chinese Liaoshen-solar greenhouse and tomato plant, which used to simulate the plant physiology of light interception, temperature, stomatal conductance, photosynthesis, and dry matter. Our study led to the conclusion that the planting strategies have a more significant impact overall on plant radiation, temperature, photosynthesis, and dry matter compared to plant architecture changes. According to our findings, increasing the plant spacing will have the most significant impact to increase light interception. E-W orientation has better total light interception but yet weaker light uniformity. Changes in planting patterns have limited influence on the overall canopy physiology. Increasing the plant leaflet area by leaflet N/A ratio from what we could observe for a rose the total dry matter by 6.6%, which is significantly better than all the other plant architecture traits. An ideal tomato plant architecture which combined all the above optimal architectural traits was also designed to provide guidance on phenotypic traits selection of breeding process. The combined analysis approach described herein established the causal relationship between investigated traits, which could directly apply to provide management and breeding insights on other plant species with different solar greenhouse structures.

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.

Diversity increases yield but reduces harvest index in crop mixtures

Resource allocation to reproduction is a critical trait for plant fitness^1,2. This trait, called harvest index in the agricultural context^3-5, determines how plant biomass is converted to seed yield and consequently financial revenue from numerous major staple crops. While plant diversity has been demonstrated to increase plant biomass^6-8, plant diversity effects on seed yield of crops are ambiguous⁹ and dependent on the production syndrome¹⁰. This discrepancy might be explained through changes in the proportion of resources invested in reproduction in response to changes in plant diversity, namely through changes in species interactions and microenvironmental conditions^11-14. Here, we show that increasing crop plant diversity from monocultures over two- to four-species mixtures increased annual primary productivity, resulting in overall higher plant biomass and, to a lesser extent, higher seed yield in mixtures compared with monocultures. The difference between the two responses to diversity was due to a reduced harvest index of the eight tested crop species in mixtures, possibly because their common cultivars have been bred for maximum performance in monoculture. While crop diversification provides a sustainable measure of agricultural intensification¹⁵, the use of currently available cultivars may compromise larger gains in seed yield. We therefore advocate regional breeding programmes for crop varieties to be used in mixtures that should exploit complementarity¹⁶ among crop species.

Estimating the contribution of plant traits to light partitioning in simultaneous maize/soybean intercropping

Spatial configuration and plant phenotypic plasticity contribute to increased light capture in relay intercropping, but there is little information on whether these factors also increase light capture in simultaneous intercropping. We developed and validated a three-dimensional functional-structural plant model to simulate light capture in maize and soybean sole crops and intercrop scenarios, using species traits observed in sole crops and intercrops. The intercrop maize phenotype had 2% greater light capture than the sole crop phenotype in a pure stand. The soybean intercrop phenotype had 5-10% lower light capture than the sole crop phenotype in a pure stand. The intercrop configuration increased the light capture of maize by 29% and reduced the light capture of soybean by 42%, compared with the light capture expected from sole crops. However, intercrop configuration only marginally affected total light capture by the intercrop system (+1%). Testing of individual soybean plant traits revealed that plasticity in leaf dimensions was the main reason for differences in light capture by soybean in simulated sole crops and intercrops. The results of this study illustrate a major shift of light capture from shorter species (soybean) to the taller component (maize) in a simultaneous strip intercrop. Plastic plant traits modulate this overall effect, but only marginally.

Enhanced light interception and light use efficiency explain overyielding in young tree communities

Diverse plant communities are often more productive than mono-specific ones. Several possible mechanisms underlie this phenomenon but their relative importance remains unknown. Here we investigated whether light interception alone or in combination with light use efficiency (LUE) of dominant and subordinate species explained greater productivity of mixtures relative to monocultures (i.e. overyielding) in 108 young experimental tree communities. We found mixed-species communities that intercepted more light than their corresponding monocultures had 84% probability of overyielding. Enhanced LUE, which arose via several pathways, also mattered: the probability of overyielding was 71% when, in a mixture, species with higher 'inherent' LUE (i.e. LUE in monoculture) intercepted more light than species with lower LUE; 94% when dominant species increased their LUE in mixture; and 79% when subordinate species increased their LUE. Our results suggest that greater light interception and greater LUE, generated by inter and intraspecific variation, together drive overyielding in mixed-species forests.

Simulating the effects of water limitation on plant biomass using a 3D functional-structural plant model of shoot and root driven by soil hydraulics

BACKGROUND AND AIMS

Improved modelling of carbon assimilation and plant growth to low soil moisture requires evaluation of underlying mechanisms in the soil, roots, and shoots. The feedback between plants and their local environment throughout the whole spectrum soil-root-shoot-environment is crucial to accurately describe and evaluate the impact of environmental changes on plant development. This study presents a 3D functional structural plant model, in which shoot and root growth are driven by radiative transfer, photosynthesis, and soil hydrodynamics through different parameterisation schemes relating soil water deficit and carbon assimilation. The new coupled model is used to evaluate the impact of soil moisture availability on plant productivity for two different groups of flowering plants under different spatial configurations.

METHODS

In order to address different aspects of plant development due to limited soil water availability, a 3D FSP model including root, shoot, and soil was constructed by linking three different well-stablished models of airborne plant, root architecture, and reactive transport in the soil. Different parameterisation schemes were used in order to integrate photosynthetic rate with root water uptake within the coupled model. The behaviour of the model was assessed on how the growth of two different types of plants, i.e. monocot and dicot, is impacted by soil water deficit under different competitive conditions: isolated (no competition), intra, and interspecific competition.

KEY RESULTS

The model proved to be capable of simulating carbon assimilation and plant development under different growing settings including isolated monocots and dicots, intra, and interspecific competition. The model predicted that (1) soil water availability has a larger impact on photosynthesis than on carbon allocation; (2) soil water deficit has an impact on root and shoot biomass production by up to 90 % for monocots and 50 % for dicots; and (3) the improved dicot biomass production in interspecific competition was highly related to root depth and plant transpiration.

CONCLUSIONS

An integrated model of 3D shoot architecture and biomass development with a 3D root system representation, including light limitation and water uptake considering soil hydraulics, was presented. Plant-plant competition and regulation on stomatal conductance to drought were able to be predicted by the model. In the cases evaluated here, water limitation impacted plant growth almost 10 times more than the light environment.

Resource-use efficiency drives overyielding via enhanced complementarity

Overyielding, the primary metric for assessing biodiversity effects on ecosystem functions, is often partitioned into "complementarity" and "selection" components, but this reveals nothing about the role of increased resource use, resource-use efficiency, or trait plasticity. We obtained multiple overyielding values by comparing productivity in a five-species mixture to expected values from its component monocultures at a) six levels of nitrogen addition (spanning 0-500 kg N ha^-1 year^-1) and b) across four seasons. We also measured light, water, and nitrogen use, resource-use efficiency, and three functional traits-leaf nitrogen content, specific leaf area, and leaf area ratio-n mixtures and monocultures. We found strong evidence for non-transgressive overyielding. This was strongest in spring, with mixture productivity exceeding expected values by 20 kg dry matter ha^-1 day^-1. Peak overyielding was driven by enhanced complementarity, with the two non-N₂-fixing forb species far exceeding expected productivity in mixtures. Peak overyielding also coincided with higher water use in the mixture than for any monoculture, and enhanced mixture-resource-use efficiency. There was only weak evidence that trait plasticity influenced overyielding or resource use. Our findings suggest that when complementarity drives overyielding in grassland mixtures, and this is made possible both by increased water use and enhanced efficiency in water, nitrogen, and light use. Our results also suggest that mixtures offer a viable compromise between productivity, resource-use efficiency, and reduced environmental impacts (i.e., nitrate leaching) from intensive agriculture.

Spatiotemporal Resolved Leaf Angle Establishment Improves Rice Grain Yield via Controlling Population Density

Leaf angle is mainly determined by the lamina joint (LJ) and contributes to ideal crop architecture for high yield. Here, we dissected five successive stages with distinct cytological features of LJs spanning organogenesis to leaf angle formation and obtained the underlying stage-specific mRNAs and small RNAs, which well explained the cytological dynamics during LJ organogenesis and leaf angle plasticity. Combining the gene coexpression correlation with high-throughput promoter analysis, we identified a set of transcription factors (TFs) determining the stage- and/or cytological structure-specific profiles. The functional studies of these TFs demonstrated that cytological dynamics determined leaf angle and that the knockout rice of these TFs with erect leaves significantly enhanced yield by maintaining the proper tiller number under dense planting. This work revealed the high-resolution mechanisms of how the cytological dynamics of LJ determined leaf erectness and served as a valuable resource to remodel rice architecture for high yield by controlling population density.

Genetic richness affects trait variation but not community productivity in a tree diversity experiment

Biodiversity-ecosystem functioning experiments found that productivity generally increases with species richness, but less is known about effects of within-species genetic richness and potential interactions between the two. While functional differences between species can explain species richness effects, empirical evidence regarding functional differences between genotypes within species and potential consequences for productivity is largely lacking. We therefore measured within- and among-species variation in functional traits and growth and determined stand-level tree biomass in a large forest experiment factorially manipulating species and genetic richness in subtropical China. Within-species variation across genetic seed families, in addition to variation across species, explained a substantial amount of trait variation. Furthermore, trait responses to species and genetic richness varied significantly within and between species. Multivariate trait variation was larger among individuals from species mixtures than those from species monocultures, but similar among individuals from genetically diverse vs genetically uniform monocultures. Correspondingly, species but not genetic richness had a positive effect on stand-level tree biomass. We argue that identifying functional diversity within and among species in forest communities is necessary to separate effects of species and genetic diversity on tree growth and community productivity.

Ameliorated light conditions increase the P uptake capability of soybean in a relay-strip intercropping system by altering root morphology and physiology in the areas with low solar radiation

Belowground interspecific facilitation and complementarity contribute to the phosphorus (P) uptake advantages in the cereal-legume intercropping system. However, the root morphological and physiological plasticity and, subsequently, the P uptake capability response to light conditions in intercropping systems remain unclear. Soybean was grown under two levels of P application rates in sole and intercropping systems (maize/soybean relay strip intercropping) from 2016 to 2018 in Renshou, southwest of China. As a supplement to the field experiment, soybean was also grown in L-S (simulating the light conditions of sole cropping in the field: light first and then shading) and S-L (simulating the light conditions of intercropping in the field: shading first and then light) light conditions with two levels of P application in 2018 in a pot experiment. After maize harvest (approximately 3/4 of the soybean growth period), light capture in intercropping was higher than sole (ameliorated light conditions in intercropping system), which resulted in an advantage of P uptake in intercropped soybean. Both low P supply and more light capture increased the total root length and root APase activity. The genes GmEXPB2 (which is associated with root growth) and GmACP1 (which is associated with exudation of APase) were highly expressed in plants that captured more light under both P-sufficient and P-deficient conditions. Additionally, more light capture increased the production of lateral roots and the proportion of in the upper 15 cm soil layer roots at the reproductive stage in the field. Across the field and pot experiments, increased root morphological and physiological plasticity were associated with lower P concentrations in the leaves and greater allocation of photosynthates to roots as sucrose. It is suggested that ameliorated light conditions can regulate soybean root growth plasticity and, consequently, P uptake in maize/soybean relay strip intercropping systems, especially in the areas with low solar radiation.

The potential of corn-soybean intercropping to improve the soil health status and biomass production in cool climate boreal ecosystems

Intercropping (IC) is a promising approach used to improve soil health and sustainable crop production. However, it is unknown whether IC improve the soil health status and biomass productivity of crops cultivated in podzols under cool climate in boreal ecosystems. Two silage corn and three forage soybean genotypes were cultivated either as inter or monocrop (MC) treatments in a randomized complete block design. IC resulted in 28% increase in total forage production (FP). A reduction in rhizosphere soil pH (RS-pH) was observed in the IC treatments. Conversely, the rhizosphere soil acid phosphatase (RS-APase) activity was significantly higher (26-46%) in the IC treatments and occurred concomitant with a significant increase in available phosphorus (RS-Pavailable) (26-74%) in the rhizosphere. Furthermore, IC enhanced the active microbial composition and strong positive correlations were observed between RS-Pavailable, RS-APase, microbial biomass and FP; while RS-pH was negatively correlated with FP, RS-APase and RS-Pavailable. These findings suggested silage corn intercropped with forage soybean could be a viable approach to enhance FP through improved active microbial community structure, RS-APase activity and RS-Pavailable when cultivated on podzols in cool climate boreal ecosystem.

Crop Phenomics: Current Status and Perspectives

Reliable, automatic, multifunctional, and high-throughput phenotypic technologies are increasingly considered important tools for rapid advancement of genetic gain in breeding programs. With the rapid development in high-throughput phenotyping technologies, research in this area is entering a new era called 'phenomics.' The crop phenotyping community not only needs to build a multi-domain, multi-level, and multi-scale crop phenotyping big database, but also to research technical systems for phenotypic traits identification and develop bioinformatics technologies for information extraction from the overwhelming amounts of omics data. Here, we provide an overview of crop phenomics research, focusing on two parts, from phenotypic data collection through various sensors to phenomics analysis. Finally, we discussed the challenges and prospective of crop phenomics in order to provide suggestions to develop new methods of mining genes associated with important agronomic traits, and propose new intelligent solutions for precision breeding.

A generic individual-based model can predict yield, nitrogen content, and species abundance in experimental grassland communities

Functional-structural plant models are increasingly being used to analyse relationships between plant functioning and the topological and spatial organisation of their modular structure. In this study, the performance of an individual-based model accounting for the the architecture and population dynamics of forage legumes in multi-species grasslands was assessed. Morphogenetic shoot and root parameters were calibrated for seven widely used species. Other model parameters concerning C and N metabolism were obtained from the literature. The model was evaluated using a series of independent experiments combining the seven species in binary mixtures that were subject to regular defoliation. For all the species, the model could accurately simulate phytomer demography, leaf area dynamics, and root growth under conditions of weak competition. In addition, the plastic changes induced by competition for light and N in terms of plant development, leaf area, N uptake, and total plant biomass were correctly predicted. The different species displayed contrasting sensitivities to defoliation, and the model was able to predict the superior ability of creeping species to sustain regular defoliation. As a result of competition and management, the balance between species changed over time and was strongly dependent on the pair of species used. The model proved able to capture these differences in community dynamics. Overall, the results demonstrate that integrating the individual components of population dynamics in a process-based model can provide good predictive capacity regarding mixtures of cultivated species.

Understanding and optimizing species mixtures using functional-structural plant modelling

Plant species mixtures improve productivity over monocultures by exploiting species complementarities for resource capture in time and space. Complementarity results in part from competition avoidance responses that maximize resource capture and growth of individual plants. Individual organs accommodate to local resource levels, e.g. with regard to nitrogen content and photosynthetic capacity or by size (e.g. shade avoidance). As a result, the resource acquisition in time and space is improved and performance of the community as a whole is increased. Modelling is needed to unravel the primary drivers and subsequent dynamics of complementary growth responses in mixtures. Here, we advocate using functional-structural plant (FSP) modelling to analyse the functioning of plant mixtures. In FSP modelling, crop performance is a result of the behaviour of the individual plants interacting through competitive and complementary resource acquisition. FSP models can integrate the interactions between structural and physiological plant responses to the local resource availability and strength of competition, which drive resource capture and growth of individuals in species mixtures. FSP models have the potential to accelerate mixed-species plant research, and thus support the development of knowledge that is needed to promote the use of mixtures towards sustainably increasing crop yields at acceptable input levels.

Interactions Between Light Intensity and Phosphorus Nutrition Affect the P Uptake Capacity of Maize and Soybean Seedling in a Low Light Intensity Area

To capture more nutrients, root systems of maize (Zea mays L.) and soybean (Glycine max L.) exhibit morphological and physiological plasticity to a localized supply of phosphorus (P). However, the mechanisms of the interaction between light intensity and P affecting root morphological and physiological alterations remain unclear. In the present study, the regulation of P uptake capacity of maize and soybean by light intensity and localized P supply was investigated in a low solar radiation area. The plants were grown under continual and disrupted light conditions with homogeneous and heterogeneous P supply. Light capture of maize and soybean increased under the disrupted light condition. Plant dry weight and P uptake were increased by more light capture, particularly when plants were grown in soil with heterogeneous P supply. Similarly, both localized P supply and disrupted light treatment increased the production of fine roots and specific root length in maize. Both homogeneous P supply and disrupted light treatment increased the malate and citrate exudation in the root of soybean. Across all of the experimental treatments, high root morphological plasticity of maize and root physiological plasticity of soybean were associated with lower P concentrations in leaves and greater sucrose concentrations in roots. It is suggested that the carbon (C), exceeded shoot growth capabilities and was transferred to roots as sucrose, which may serve as both a nutritional signal and a C-substrate for root morphological and physiological changes.

Ecological interactions shape the adaptive value of plant defence: Herbivore attack versus competition for light

Plants defend themselves against diverse communities of herbivorous insects. This requires an investment of limited resources, for which plants also compete with neighbours. The consequences of an investment in defence are determined by the metabolic costs of defence as well as indirect or ecological costs through interactions with other organisms. These ecological costs have a potentially strong impact on the evolution of defensive traits, but have proven to be difficult to quantify.We aimed to quantify the relative impact of the direct and indirect or ecological costs and benefits of an investment in plant defence in relation to herbivory and intergenotypic competition for light. Additionally, we evaluated how the benefits of plant defence balance its costs in the context of herbivory and intergenotypic competition.To this end, we utilised a functional-structural plant (FSP) model of Brassica nigra that simulates plant growth and development, morphogenesis, herbivory and plant defence. In the model, a simulated investment in defences affected plant growth by competing with other plant organs for resources and affected the level and distribution of herbivore damage.Our results show that the ecological costs of intergenotypic competition for light are highly detrimental to the fitness of defended plants, as it amplifies the size difference between defended and undefended plants. This leads to herbivore damage counteracting the effects of intergenotypic competition under the assumption that herbivore damage scales with plant size. Additionally, we show that plant defence relies on reducing herbivore damage rather than the dispersion of herbivore damage, which is only beneficial under high levels of herbivore damage.We conclude that the adaptive value of plant defence is highly dependent on ecological interactions and is predominantly determined by the outcome of competition for light. plain language summary is available for this article.

Scale dependence of the diversity-stability relationship in a temperate grassland

A positive relationship between biodiversity and ecosystem stability has been reported in many ecosystems; however, it has yet to be determined whether and how spatial scale affects this relationship. Here, for the first time, we assessed the effects of alpha, beta and gamma diversity on ecosystem stability and the scale dependence of the slope of the diversity-stability relationship.By employing a long-term (33 years) dataset from a temperate grassland, northern China, we calculated the all possible spatial scales with the complete combination from the basic 1-m² plots.Species richness was positively associated with ecosystem stability through species asynchrony and overyielding at all spatial scales (1, 2, 3, 4 and 5 m²). Both alpha and beta diversity were positively associated with gamma stability.Moreover, the slope of the diversity-area relationship was significantly higher than that of the stability-area relationship, resulting in a decline of the slope of the diversity-stability relationship with increasing area.Synthesis. With the positive species diversity effect on ecosystem stability from small to large spatial scales, our findings demonstrate the need to maintain a high biodiversity and biotic heterogeneity as insurance against the risks incurred by ecosystems in the face of global environmental changes.

A generic individual-based model to simulate morphogenesis, C-N acquisition and population dynamics in contrasting forage legumes

Background and Aims

Individual-based models (IBMs) are promising tools to disentangle plant interactions in multi-species grasslands and foster innovative species mixtures. This study describes an IBM dealing with the morphogenesis, growth and C-N acquisition of forage legumes that integrates plastic responses from functional-structural plant models.

Methods

A generic model was developed to account for herbaceous legume species with contrasting above- and below-ground morphogenetic syndromes and to integrate the responses of plants to light, water and N. Through coupling with a radiative transfer model and a three-dimensional virtual soil, the model allows dynamic resolution of competition for multiple resources at individual plant level within a plant community. The behaviour of the model was assessed on a range of monospecific stands grown along gradients of light, water and N availability.

Key Results

The model proved able to capture the diversity of morphologies encountered among the forage legumes. The main density-dependent features known about even-age plant populations were correctly anticipated. The model predicted (1) the 'reciprocal yield' law relating average plant mass to density, (2) a self-thinning pattern close to that measured for herbaceous species and (3) consistent changes in the size structure of plant populations with time and pedo-climatic conditions. In addition, plastic changes in the partitioning of dry matter, the N acquisition mode and in the architecture of shoots and roots emerged from the integration of plant responses to their local environment. This resulted in taller plants and thinner roots when competition was dominated by light, and shorter plants with relatively more developed root systems when competition was dominated by soil resources.

Conclusions

A population dynamic model considering growth and morphogenesis responses to multiple resources heterogeneously distributed in the environment was presented. It should allow scaling plant-plant interactions from individual to community levels without the inconvenience of average plant models.

A 3-D functional-structural grapevine model that couples the dynamics of water transport with leaf gas exchange

Background and Aims

Predicting both plant water status and leaf gas exchange under various environmental conditions is essential for anticipating the effects of climate change on plant growth and productivity. This study developed a functional-structural grapevine model which combines a mechanistic understanding of stomatal function and photosynthesis at the leaf level (i.e. extended Farqhuhar-von Caemmerer-Berry model) and the dynamics of water transport from soil to individual leaves (i.e. Tardieu-Davies model).

Methods

The model included novel features that account for the effects of xylem embolism (fPLC) on leaf hydraulic conductance and residual stomatal conductance (g0), variable root and leaf hydraulic conductance, and the microclimate of individual organs. The model was calibrated with detailed datasets of leaf photosynthesis, leaf water potential, xylem sap abscisic acid (ABA) concentration and hourly whole-plant transpiration observed within a soil drying period, and validated with independent datasets of whole-plant transpiration under both well-watered and water-stressed conditions.

Key Results

The model well captured the effects of radiation, temperature, CO2 and vapour pressure deficit on leaf photosynthesis, transpiration, stomatal conductance and leaf water potential, and correctly reproduced the diurnal pattern and decline of water flux within the soil drying period. In silico analyses revealed that decreases in g0 with increasing fPLC were essential to avoid unrealistic drops in leaf water potential under severe water stress. Additionally, by varying the hydraulic conductance along the pathway (e.g. root and leaves) and changing the sensitivity of stomatal conductance to ABA and leaf water potential, the model can produce different water use behaviours (i.e. iso- and anisohydric).

Conclusions

The robust performance of this model allows for modelling climate effects from individual plants to fields, and for modelling plants with complex, non-homogenous canopies. In addition, the model provides a basis for future modelling efforts aimed at describing the physiology and growth of individual organs in relation to water status.

Elucidating the interaction between light competition and herbivore feeding patterns using functional-structural plant modelling

Background and Aims

Plants usually compete with neighbouring plants for resources such as light as well as defend themselves against herbivorous insects. This requires investment of limiting resources, resulting in optimal resource distribution patterns and trade-offs between growth- and defence-related traits. A plant's competitive success is determined by the spatial distribution of its resources in the canopy. The spatial distribution of herbivory in the canopy in turn differs between herbivore species as the level of herbivore specialization determines their response to the distribution of resources and defences in the canopy. Here, we investigated to what extent competition for light affects plant susceptibility to herbivores with different feeding preferences.

Methods

To quantify interactions between herbivory and competition, we developed and evaluated a 3-D spatially explicit functional-structural plant model for Brassica nigra that mechanistically simulates competition in a dynamic light environment, and also explicitly models leaf area removal by herbivores with different feeding preferences. With this novel approach, we can quantitatively explore the extent to which herbivore feeding location and light competition interact in their effect on plant performance.

Key Results

Our results indicate that there is indeed a strong interaction between levels of plant-plant competition and herbivore feeding preference. When plants did not compete, herbivory had relatively small effects irrespective of feeding preference. Conversely, when plants competed, herbivores with a preference for young leaves had a strong negative effect on the competitiveness and subsequent performance of the plant, whereas herbivores with a preference for old leaves did not.

Conclusions

Our study predicts how plant susceptibility to herbivory depends on the composition of the herbivore community and the level of plant competition, and highlights the importance of considering the full range of dynamics in plant-plant-herbivore interactions.

Designing oil palm architectural ideotypes for optimal light interception and carbon assimilation through a sensitivity analysis of leaf traits

Background and Aims

Enhancement of light harvesting in annual crops has successfully led to yield increases since the green revolution. Such an improvement has mainly been achieved by selecting plants with optimal canopy architecture for specific agronomic practices. For perennials such as oil palm, breeding programmes were focused more on fruit yield, but now aim at exploring more complex traits. The aim of the present study is to investigate potential improvements in light interception and carbon assimilation in the study case of oil palm, by manipulating leaf traits and proposing architectural ideotypes.

Methods

Sensitivity analyses (Morris method and metamodel) were performed on a functional-structural plant model recently developed for oil palm which takes into account genetic variability, in order to virtually assess the impact of plant architecture on light interception efficiency and potential carbon acquisition.

Key Results

The most sensitive parameters found over plant development were those related to leaf area (rachis length, number of leaflets, leaflet morphology), although fine attributes related to leaf geometry showed increasing influence when the canopy became closed. In adult stands, optimized carbon assimilation was estimated on plants with a leaf area index between 3.2 and 5.5 m2 m-2 (corresponding to usual agronomic conditions), with erect leaves, short rachis and petiole, and high number of leaflets on the rachis. Four architectural ideotypes for carbon assimilation are proposed based on specific combinations of organ dimensions and arrangement that limit mutual shading and optimize light distribution within the plant crown.

Conclusions

A rapid set-up of leaf area is critical at young age to optimize light interception and subsequently carbon acquisition. At the adult stage, optimization of carbon assimilation could be achieved through specific combinations of architectural traits. The proposition of multiple morphotypes with comparable level of carbon assimilation opens the way to further investigate ideotypes carrying an optimal trade-off between carbon assimilation, plant transpiration and biomass partitioning.

Computational botany: advancing plant science through functional–structural plant modelling

The need to integrate the ever-expanding body of knowledge in the plant sciences has led to the development of sophisticated modelling approaches. This special issue focuses on functional–structural plant (FSP) models, which are the result of cross-fertilization between the domains of plant science, computer science and mathematics. FSP models simulate growth and morphology of individual plants that interact with their environment, from which complex plant community properties emerge. FSP models can be used for a broad range of research questions across disciplines related to plant science. This special issue presents the latest developments in FSP modelling, including the novel incorporation of plant ecophysiological concepts and the application of FSP models to address new scientific questions. Additionally, it illustrates the breadth of model evaluation approaches that are performed. FSP modelling is a very active domain of plant research which brings together a wide range of scientific disciplines. It offers the opportunity to address questions in complex plant systems that cannot be addressed by empirical approaches alone, including questions on fundamental concepts related to plant development such as regulation of morphogenesis, as well as on applied concepts such as the relationship between crop performance and plant competition for resources.

Temporal Differentiation of Crop Growth as One of the Drivers of Intercropping Yield Advantage

Intercropping studies usually focus on yield advantage and interspecific interactions but few quantify temporal niche differentiation and its relationship with intercropping yield advantage. A field experiment conducted in northwest China in 2013 and 2014 examined four intercropping systems (oilseed rape/maize, oilseed rape/soybean, potato/maize, and soybean/potato) and the corresponding monocultures. Total dry matter data collected every 20 d after maize emergence were fitted to logistic models to investigate the temporal dynamics of crop growth and interspecific interactions. All four intercropping systems showed significant yield advantages. Temporal niche complementarity between intercropped species was due to differences in sowing and harvesting dates or the time taken to reach maximum daily growth rate or both. Interspecific interactions between intercropped species amplified temporal niche differentiation as indicated by postponement of the time taken to reach maximum daily growth rate of late-maturing crops (i.e. 21 to 41 days in maize associated with oilseed rape or potato). Growth trajectories of intercropped maize or soybean recovered after the oilseed rape harvest to the same values as in their monoculture on a per plant basis. Amplified niche differentiation between crop species depends on the identity of neighboring species whose relative growth rate is crucial in determining the differentiation.

What plant functional traits can reduce nitrous oxide emissions from intensively managed grasslands?

Plant species exert a dominant control over the nitrogen (N) cycle of natural and managed grasslands. Although in intensively managed systems that receive large external N inputs the emission of the potent greenhouse gas nitrous oxide (N₂ O) is a crucial component of this cycle, a mechanistic relationship between plant species and N₂ O emissions has not yet been established. Here we use a plant functional trait approach to study the relation between plant species strategies and N₂ O emissions from soils. Compared to species with conservative strategies, species with acquisitive strategies have higher N uptake when there is ample N in the soil, but also trigger N mineralization when soil N is limiting. Therefore, we hypothesized that (1) compared to conservative species, species with acquisitive traits reduce N₂ O emissions after a high N addition; and (2) species with conservative traits have lower N₂ O emissions than acquisitive plants if there is no high N addition. This was tested in a greenhouse experiment using monocultures of six grass species with differing above- and below-ground traits, growing across a gradient of soil N availability. We found that acquisitive species reduced N₂ O emissions at all levels of N availability, produced higher biomass and showed larger N uptake. As such, acquisitive species had 87% lower N₂ O emissions per unit of N uptake than conservative species (p < .05). Structural equation modelling revealed that specific leaf area and root length density were key traits regulating the effects of plants on N₂ O emission and biomass productivity. These results provide the first framework to understand the mechanisms through which plants modulate N₂ O emissions, pointing the way to develop productive grasslands that contribute optimally to climate change mitigation.

Leaf-GP: an open and automated software application for measuring growth phenotypes for arabidopsis and wheat

BACKGROUND

Plants demonstrate dynamic growth phenotypes that are determined by genetic and environmental factors. Phenotypic analysis of growth features over time is a key approach to understand how plants interact with environmental change as well as respond to different treatments. Although the importance of measuring dynamic growth traits is widely recognised, available open software tools are limited in terms of batch image processing, multiple traits analyses, software usability and cross-referencing results between experiments, making automated phenotypic analysis problematic.

RESULTS

Here, we present Leaf-GP (Growth Phenotypes), an easy-to-use and open software application that can be executed on different computing platforms. To facilitate diverse scientific communities, we provide three software versions, including a graphic user interface (GUI) for personal computer (PC) users, a command-line interface for high-performance computer (HPC) users, and a well-commented interactive Jupyter Notebook (also known as the iPython Notebook) for computational biologists and computer scientists. The software is capable of extracting multiple growth traits automatically from large image datasets. We have utilised it in Arabidopsis thaliana and wheat (Triticum aestivum) growth studies at the Norwich Research Park (NRP, UK). By quantifying a number of growth phenotypes over time, we have identified diverse plant growth patterns between different genotypes under several experimental conditions. As Leaf-GP has been evaluated with noisy image series acquired by different imaging devices (e.g. smartphones and digital cameras) and still produced reliable biological outputs, we therefore believe that our automated analysis workflow and customised computer vision based feature extraction software implementation can facilitate a broader plant research community for their growth and development studies. Furthermore, because we implemented Leaf-GP based on open Python-based computer vision, image analysis and machine learning libraries, we believe that our software not only can contribute to biological research, but also demonstrates how to utilise existing open numeric and scientific libraries (e.g. Scikit-image, OpenCV, SciPy and Scikit-learn) to build sound plant phenomics analytic solutions, in a efficient and effective way.

CONCLUSIONS

Leaf-GP is a sophisticated software application that provides three approaches to quantify growth phenotypes from large image series. We demonstrate its usefulness and high accuracy based on two biological applications: (1) the quantification of growth traits for Arabidopsis genotypes under two temperature conditions; and (2) measuring wheat growth in the glasshouse over time. The software is easy-to-use and cross-platform, which can be executed on Mac OS, Windows and HPC, with open Python-based scientific libraries preinstalled. Our work presents the advancement of how to integrate computer vision, image analysis, machine learning and software engineering in plant phenomics software implementation. To serve the plant research community, our modulated source code, detailed comments, executables (.exe for Windows; .app for Mac), and experimental results are freely available at https://github.com/Crop-Phenomics-Group/Leaf-GP/releases.