How plant architecture affects light absorption and photosynthesis in tomato: towards an ideotype for plant architecture using a functional-structural plant model

The role of red and white light in optimizing growth and accumulation of plant specialized metabolites at two light intensities in medical cannabis (Cannabis sativa L.)

The cultivation of medical cannabis (Cannabis sativa L.) is expanding in controlled environments, driven by evolving governmental regulations for healthcare supply. Increasing inflorescence weight and plant specialized metabolite (PSM) concentrations is critical, alongside maintaining product consistency. Medical cannabis is grown under different spectra and photosynthetic photon flux densities (PPFD), the interaction between spectrum and PPFD on inflorescence weight and PSM attracts attention by both industrialists and scientists. Plants were grown in climate-controlled rooms without solar light, where four spectra were applied: two low-white spectra (7B-20G-73R/Narrow and 6B-19G-75R/2Peaks), and two high-white (15B-42G-43R/Narrow and 17B-40G-43R/Broad) spectra. The low-white spectra differed in red wavelength peaks (100% 660 nm, versus 50:50% of 640:660 nm), the high-white spectra differed in spectrum broadness. All four spectra were applied at 600 and 1200 μmol m-2 s-1. Irrespective of PPFD, white light with a dual red peak of 640 and 660 nm (6B-19G-75R/2Peaks) increased inflorescence weight, compared to white light with a single red peak of 660 nm (7B-20G-73R/Narrow) (tested at P = 0.1); this was associated with higher total plant dry matter production and a more open plant architecture, which likely enhanced light capture. At high PPFD, increasing white fraction and spectrum broadness (17B-40G-43R/Broad) produced similar inflorescence weights compared to white light with a dual red peak of 640 and 660 nm (6B-19G-75R/2Peaks). This was caused by an increase of both plant dry matter production and dry matter partitioning to the inflorescences. No spectrum or PPFD effects on cannabinoid concentrations were observed, although at high PPFD white light with a dual red peak of 640 and 660 nm (6B-19G-75R/2Peaks) increased terpenoid concentrations compared to the other spectra. At low PPFD, the combination of white light with 640 and 660 nm increased photosynthetic efficiency compared with white light with a single red peak of 660nm, indicating potential benefits in light use efficiency and promoting plant dry matter production. These results indicate that the interaction between spectrum and PPFD influences plant dry matter production. Dividing the light energy in the red waveband over both 640 and 660 nm equally shows potential in enhancing photosynthesis and plant dry matter production.

Three-Dimensional Leaf Edge Reconstruction Combining Two- and Three-Dimensional Approaches

Leaves, crucial for plant physiology, exhibit various morphological traits that meet diverse functional needs. Traditional leaf morphology quantification, largely 2-dimensional (2D), has not fully captured the 3-dimensional (3D) aspects of leaf function. Despite improvements in 3D data acquisition, accurately depicting leaf morphologies, particularly at the edges, is difficult. This study proposes a method for 3D leaf edge reconstruction, combining 2D image segmentation with curve-based 3D reconstruction. Utilizing deep-learning-based instance segmentation for 2D edge detection, structure from motion for estimation of camera positions and orientations, leaf correspondence identification for matching leaves among images, and curve-based 3D reconstruction for estimating 3D curve fragments, the method assembles 3D curve fragments into a leaf edge model through B-spline curve fitting. The method's performances were evaluated on both virtual and actual leaves, and the results indicated that small leaves and high camera noise pose greater challenges to reconstruction. We developed guidelines for setting a reliability threshold for curve fragments, considering factors occlusion, leaf size, the number of images, and camera error; the number of images had a lesser impact on this threshold compared to others. The method was effective for lobed leaves and leaves with fewer than 4 holes. However, challenges still existed when dealing with morphologies exhibiting highly local variations, such as serrations. This nondestructive approach to 3D leaf edge reconstruction marks an advancement in the quantitative analysis of plant morphology. It is a promising way to capture whole-plant architecture by combining 2D and 3D phenotyping approaches adapted to the target anatomical structures.

Gibberellin-mediated far-red light-induced leaf expansion in cucumber seedlings

Our experiments explored the effects of far-red (FR) light on cucumber (Cucumis sativus L. 'Zhongnong No. 26') seedling growth. Our results indicated that FR light significantly promoted the growth of cucumber seedlings. Specifically, it promoted the accumulation of shoot biomass and the elongation of internodes and leaves (except the first leaf at the bottom). Further analysis showed that FR light had no effect on the accumulation contents of abscisic acid (ABA) and auxin (IAA) in seedling leaves. Still, it significantly caused the increase of the gibberellin (GA3, GA4, and GA7) contents and the decrease of GA1 content, which suggested that the leaf expansion progress under FR light may be primarily related to GA. Therefore, the cucumber seedling leaf expansion response to GA was evaluated under different light sources. The exogenous spraying of different GA4/7 contents significantly promoted the leaf expansion of cucumber seedlings under white light, while the GA biosynthesis inhibitor paclobutrazol (PAC) significantly promoted the expression of GA hydrolytic genes (GA2ox2 and GA2ox4) and decreased the content of endogenous active GA, which inhibited the leaf expansion induced by FR light. As expected, the combination of exogenous GA4/7 and PAC restored the growth promotion effect of FR light on cucumber seedling leaves. It increased the contents of endogenous active GA (GA1, GA3, GA4, and GA7), and the expression trend in GA synthetic/hydrolytic-related genes was the opposite of that of PAC was applied alone. All of the above results indicated that FR light regulates leaf expansion progress in cucumber seedlings through GA.

The ORGAN SIZE (ORG) locus modulates both vegetative and reproductive gigantism in domesticated tomato

BACKGROUND AND AIMS

Gigantism is a key component of the domestication syndrome, a suite of traits that differentiates crops from their wild relatives. Allometric gigantism is strongly marked in horticultural crops, causing disproportionate increases in the size of edible parts such as stems, leaves or fruits. Tomato (Solanum lycopersicum) has attracted attention as a model for fruit gigantism, and many genes have been described controlling this trait. However, the genetic basis of a corresponding increase in size of vegetative organs contributing to isometric gigantism has remained relatively unexplored.

METHODS

Here, we identified a 0.4-Mb region on chromosome 7 in introgression lines (ILs) from the wild species Solanum pennellii in two different tomato genetic backgrounds (cv. 'M82' and cv. 'Micro-Tom') that controls vegetative and reproductive organ size in tomato. The locus, named ORGAN SIZE (ORG), was fine-mapped using genotype-by-sequencing. A survey of the literature revealed that ORG overlaps with previously mapped quantitative trait loci controlling tomato fruit weight during domestication.

KEY RESULTS

Alleles from the wild species led to lower cell number in different organs, which was partially compensated by greater cell expansion in leaves, but not in fruits. The result was a proportional reduction in leaf, flower and fruit size in the ILs harbouring the alleles from the wild species.

CONCLUSIONS

Our findings suggest that selection for large fruit during domestication also tends to select for increases in leaf size by influencing cell division. Since leaf size is relevant for both source-sink balance and crop adaptation to different environments, the discovery of ORG could allow fine-tuning of these parameters.

The Influence of External Parameters on the Ripeness of Pumpkins

Growing pumpkins in controlled environments, such as greenhouses, has become increasingly important due to the potential to optimise yield and quality. However, achieving optimal environmental conditions for pumpkin cultivation requires precise monitoring and control, which can be facilitated by modern sensor technologies. The objective of this study was to determine the optimal placement of sensors to determine the influence of external parameters on the maturity of pumpkins. The greenhouse used in the study consisted of a plastic film for growing pumpkins. Five different sensors labeled from A1 to A5 measured the air temperature, humidity, soil temperature, soil humidity, and illumination at five different locations. We used two methods, error-based sensor placement and entropy-based sensor placement, to evaluate optimisation. We selected A3 sensor locations where the monitored data were close to the reference value, i.e., the average data of all measurement locations and parameters. Using this method, we selected sensor positions to monitor the influence of external parameters on the maturity of pumpkins. These methods enable the determination of optimal sensor locations to represent the entire facility environment and detect areas with significant environmental disparities. Our study provides an accurate measurement of the internal environment of a greenhouse and properly selects the base installation locations of sensors in the pumpkin greenhouse.

Leaf shape, planting density, and nitrogen application affect soybean yield by changing direct and diffuse light distribution in the canopy

When attempting to maximize the crop yield from field-grown soybean (Glycine max (L.) Merr.) by means of improving the light conditions for photosynthesis in the canopy, it is crucial to find the optimal planting density and nitrogen application rate. The soybean plants that were the subject of our experiment were cultivated in N-dense mutual pairs, and included two cultivars with different leaf shapes; one cultivar sported ovate leaves (O-type) and the other lanceolate leaves (L-type). We analyzed the results quantitatively to determine the amount of spatial variation in light distribution and photosynthetic efficiency across the canopy, and to gauge the effect of the experimental parameters on the yield as well as the photosynthetic light and nitrogen use efficiency of the crop. Results indicate that the different leaf shapes were responsible for significant disparities between the photosynthetic utilization of direct and diffuse light. As the nitrogen fertilizer rate and the planting density increased, the soybean plants responded by adjusting leaf morphology in order to maximize the canopy apparent photosynthetic light use efficiency, which in turn affected the leaf nitrogen distribution in the canopy. Despite the fact that the light interception rate of the canopy of the L-type cultivar was lower than that of the canopy of the O-type cultivar, we found its canopy apparent photosynthetic nitrogen and light use efficiency were higher. It was interesting to note, however, that the nitrogen and light use efficiency contributions associated with exposure to diffuse light were greater for the latter than for the former.

Crop/Plant Modeling Supports Plant Breeding: I. Optimization of Environmental Factors in Accelerating Crop Growth and Development for Speed Breeding

The environmental conditions in customered speed breeding practice are, to some extent, empirical and, thus, can be further optimized. Crop and plant models have been developed as powerful tools in predicting growth and development under various environments for extensive crop species. To improve speed breeding, crop models can be used to predict the phenotypes resulted from genotype by environment by management at the population level, while plant models can be used to examine 3-dimensional plant architectural development by microenvironments at the organ level. By justifying the simulations via numerous virtual trials using models in testing genotype × environment × management, an optimized combination of environmental factors in achieving desired plant phenotypes can be quickly determined. Artificial intelligence in assisting for optimization is also discussed. We admit that the appropriate modifications on modeling algorithms or adding new modules may be necessary in optimizing speed breeding for specific uses. Overall, this review demonstrates that crop and plant models are promising tools in providing the optimized combinations of environment factors in advancing crop growth and development for speed breeding.

The Importance of Using Realistic 3D Canopy Models to Calculate Light Interception in the Field

Quantifying canopy light interception provides insight into the effects of plant spacing, canopy structure, and leaf orientation on radiation distribution. This is essential for increasing crop yield and improving product quality. Canopy light interception can be quantified using 3-dimensional (3D) plant models and optical simulations. However, virtual 3D canopy models (VCMs) have often been used to quantify canopy light interception because realistic 3D canopy models (RCMs) are difficult to obtain in the field. This study aims to compare the differences in light interception between VCMs and RCM. A realistic 3D maize canopy model (RCM) was reconstructed over a large area of the field using an advanced unmanned aerial vehicle cross-circling oblique (CCO) route and the structure from motion-multi-view stereo method. Three types of VCMs (VCM-1, VCM-4, and VCM-8) were then created by replicating 1, 4, and 8 individual realistic plants constructed by CCO in the center of the corresponding RCM. The daily light interception per unit area (DLI), as computed for the 3 VCMs, exhibited marked deviation from the RCM, as evinced by the relative root mean square error (rRMSE) values of 20.22%, 17.38%, and 15.48%, respectively. Although this difference decreased as the number of plants used to replicate the virtual canopy increased, rRMSE of DLI for VCM-8 and RCM still reached 15.48%. It was also found that the difference in light interception between RCMs and VCMs was substantially smaller in the early stage (48 days after sowing [DAS]) than in the late stage (70 DAS). This study highlights the importance of using RCM when calculating light interception in the field, especially in the later growth stages of plants.

Branch angle and leaflet shape are associated with canopy coverage in soybean

Early canopy coverage is a desirable trait that is a major determinant of yield in soybean (Glycine max). Variation in traits comprising shoot architecture can influence canopy coverage, canopy light interception, canopy-level photosynthesis, and source-sink partitioning efficiency. However, little is known about the extent of phenotypic diversity of shoot architecture traits and their genetic control in soybean. Thus, we sought to understand the contribution of shoot architecture traits to canopy coverage and to determine the genetic control of these traits. We examined the natural variation for shoot architecture traits in a set of 399 diverse maturity group I soybean (SoyMGI) accessions to identify relationships between traits, and to identify loci that are associated with canopy coverage and shoot architecture traits. Canopy coverage was correlated with branch angle, number of branches, plant height, and leaf shape. Using previously collected 50K single nucleotide polymorphism data, we identified quantitative trait locus (QTL) associated with branch angle, number of branches, branch density, leaflet shape, days to flowering, maturity, plant height, number of nodes, and stem termination. In many cases, QTL intervals overlapped with previously described genes or QTL. We also found QTL associated with branch angle and leaflet shape located on chromosomes 19 and 4, respectively, and these QTL overlapped with QTL associated with canopy coverage, suggesting the importance of branch angle and leaflet shape in determining canopy coverage. Our results highlight the role individual architecture traits play in canopy coverage and contribute information on their genetic control that could help facilitate future efforts in their genetic manipulation.

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).

Consequences of intra-canopy and top LED lighting for uniformity of light distribution in a tomato crop

In the past decade, the potential of positioning LED lamps in between the canopy (intra-canopy) to enhance crop growth and yield has been explored in greenhouse cultivation. Changes in spatial heterogeneity of light absorption that come with the introduction of intra-canopy lighting have not been thoroughly explored. We calibrated and validated an existing functional structural plant model (FSPM), which combines plant morphology with a ray tracing model to estimate light absorption at leaflet level. This FSPM was used to visualize the light environment in a tomato crop illuminated with intra-canopy lighting, top lighting or a combination of both. Model validation of light absorption of individual leaves showed a good fit (R² = 0.93) between measured and modelled light absorption of the canopy. Canopy light distribution was then quantified and visualized in three voxel directions by means of average absorbed photosynthetic photon flux density (PPFD) and coefficient of variation (CV) within that voxel. Simulations showed that the variation coefficient within horizontal direction was higher for intra-canopy lighting than top lighting (CV=48% versus CV= 43%), while the combination of intra-canopy lighting and top lighting yielded the lowest CV (37%). Combined intra-canopy and top lighting (50/50%) had in all directions a more uniform light absorption than intra-canopy or top lighting alone. The variation was minimal when the ratio of PPFD from intra-canopy to top lighting was about 1, and increased when this ratio increased or decreased. Intra-canopy lighting resulted in 8% higher total light absorption than top lighting, while combining 50% intra-canopy lighting with 50% top lighting, increased light absorption by 4%. Variation in light distribution was further reduced when the intra-canopy LEDs were distributed over strings at four instead of two heights. When positioning LED lamps to illuminate a canopy both total light absorption and light distribution have to be considered.

Integrating GWAS, linkage mapping and gene expression analyses reveal the genetic control of first branch height in Brassica napus L

Rapeseed (Brassica napus L.) is a crucial oil crop cultivated worldwide. First branch height, an essential component of rapeseed plant architecture, has an important effect on yield and mechanized harvesting; however, the underlying genetic mechanism remains unclear. In this study, based on the 60K single nucleotide polymorphism array and a recombinant inbred lines population derived from M083 and 888-5, a total of 19 QTLs were detected in five environments, distributed on linkage groups A02, A09, A10, C06, and C07, which explained phenotypic variation ranging from 4.87 to 29.87%. Furthermore, 26 significant SNPs were discovered on Chr.A02 by genome-wide association study in a diversity panel of 324 re-sequencing accessions. The major QTL of the first branch height trait was co-located on Chr.A02 by integrating linkage mapping and association mapping. Eleven candidate genes were screened via allelic variation analysis, inter-subgenomic synteny analysis, and differential expression of genes in parental shoot apical meristem tissues. Among these genes, BnaA02g13010D, which encodes a TCP transcription factor, was confirmed as the target gene according to gene function annotation, haplotype analysis, and full-length gene sequencing, which revealed that TATA insertion/deletion in the promoter region was closely linked to significantly phenotypic differences BnaA02.TCP1 ^M083 overexpression resulted in decreased branch height and increased branch number in Arabidopsis. These results provide a genetic basis for first branch height and the ideal architecture of B. napus.

Initiation of aboveground organ primordia depends on combined action of auxin, ERECTA family genes, and PINOID

Leaves and flowers are produced by the shoot apical meristem (SAM) at a certain distance from its center, a process that requires the hormone auxin. The amount of auxin and the pattern of its distribution in the initiation zone determine the size and spatial arrangement of organ primordia. Auxin gradients in the SAM are formed by PIN-FORMED (PIN) auxin efflux carriers whose polar localization in the plasma membrane depends on the protein kinase PINOID (PID). Previous work determined that ERECTA (ER) family genes (ERfs) control initiation of leaves. ERfs are plasma membrane receptors that enable cell-to-cell communication by sensing extracellular small proteins from the EPIDERMAL PATTERNING FACTOR/EPF-LIKE (EPF/EPFL) family. Here, we investigated whether ERfs regulate initiation of organs by altering auxin distribution or signaling in Arabidopsis (Arabidopsis thaliana). Genetic and pharmacological data suggested that ERfs do not regulate organogenesis through PINs while transcriptomics data showed that ERfs do not alter primary transcriptional responses to auxin. Our results indicated that in the absence of ERf signaling the peripheral zone cells inefficiently initiate leaves in response to auxin signals and that increased accumulation of auxin in the er erecta-like1 (erl1) erl2 SAM can partially rescue organ initiation defects. We propose that both auxin and ERfs are essential for leaf initiation and that they have common downstream targets. Genetic data also indicated that the role of PID in initiation of cotyledons and leaves cannot be attributed solely to regulation of PIN polarity and PID is likely to have other functions in addition to regulation of auxin distribution.

QTL and candidate genes for heterophylly in soybean based on two populations of recombinant inbred lines

Heterophylly, the existence of different leaf shapes and sizes on the same plant, has been observed in many flowering plant species. Yet, the genetic characteristics and genetic basis of heterophylly in soybean remain unknown. Here, two populations of recombinant inbred lines (RILs) with distinctly different leaf shapes were used to identify loci controlling heterophylly in two environments. The ratio of apical leaf shape (LSUP) to basal leaf shape (LSDOWN) at the reproductive growth stage (RLS) was used as a parameter for classifying heterophylly. A total of eight QTL were detected for RLS between the two populations and four of them were stably identified in both environments. Among them, qRLS20 had the largest effect in the JS population, with a maximum LOD value of 46.9 explaining up to 47.2% of phenotypic variance. This locus was located in the same genomic region as the basal leaf shape QTL qLSDOWN20 on chromosome 20. The locus qRLS19 had the largest effect in the JJ population, with a maximum LOD value of 15.2 explaining up to 27.0% of phenotypic variance. This locus was located in the same genomic region as the apical leaf shape QTL qLSUP19 on chromosome 19. Four candidate genes for heterophylly were identified based on sequence differences among the three parents of the two mapping populations, RT-qPCR analysis, and gene functional annotation analysis. The QTL and candidate genes detected in this study lay a foundation for further understanding the genetic mechanism of heterophylly and are invaluable in marker-assisted breeding.

3dCAP-Wheat: An Open-Source Comprehensive Computational Framework Precisely Quantifies Wheat Foliar, Nonfoliar, and Canopy Photosynthesis

Canopy photosynthesis is the sum of photosynthesis of all above-ground photosynthetic tissues. Quantitative roles of nonfoliar tissues in canopy photosynthesis remain elusive due to methodology limitations. Here, we develop the first complete canopy photosynthesis model incorporating all above-ground photosynthetic tissues and validate this model on wheat with state-of-the-art gas exchange measurement facilities. The new model precisely predicts wheat canopy gas exchange rates at different growth stages, weather conditions, and canopy architectural perturbations. Using the model, we systematically study (1) the contribution of both foliar and nonfoliar tissues to wheat canopy photosynthesis and (2) the responses of wheat canopy photosynthesis to plant physiological and architectural changes. We found that (1) at tillering, heading, and milking stages, nonfoliar tissues can contribute ~4, ~32, and ~50% of daily gross canopy photosynthesis (A_cgross; ~2, ~15, and ~-13% of daily net canopy photosynthesis, A_cnet) and absorb ~6, ~42, and ~60% of total light, respectively; (2) under favorable condition, increasing spike photosynthetic activity, rather than enlarging spike size or awn size, can enhance canopy photosynthesis; (3) covariation in tissue respiratory rate and photosynthetic rate may be a major factor responsible for less than expected increase in daily A_cnet; and (4) in general, erect leaves, lower spike position, shorter plant height, and proper plant densities can benefit daily A_cnet. Overall, the model, together with the facilities for quantifying plant architecture and tissue gas exchange, provides an integrated platform to study canopy photosynthesis and support rational design of photosynthetically efficient wheat crops.

Genetic dissection of seed yield and yield-related traits in Brassica napus grown with contrasting nitrogen supplies

Oilseed rape (B. napus) is the main oil crop in China as well as in the world. Nitrogen (N) deficiency significantly reduces the seed yield of B. napus. However, a very few studies involved in the genetic mechanism of seed yield and SY-related traits of B. napus in response to N deficiency. In this study, plant height (PH), branch number per plant (BN), pod number per plant (PN), seed number per pod (SN), 1000-seed weight (SW), and seed yield per plant (SY) were investigated using a B. napus double haploid (BnaTNDH) population derived from a cross between cultivars "Tapidor" and "Ningyou7" grown at an optimal N (ON) and a low N (LN) supplies in three-year field trials. Great variations of SY and related traits were observed in BnaTNDH population under contrasting N supplies. A total of 106 and 110 significant quantitative trait loci (QTLs) were detected for six traits at ON and LN in three field trials, respectively. All of these significant QTLs for the same trait identified in two or three trials were integrated into 20 stable QTLs. A total of 50 consensus QTLs and 53 unique QTLs were obtained from 172 significant QTLs and 20 stable QTLs, including 35 ON-specific QTLs, 29 LN-specific QTLs and 39 constitutive QTLs detected at both ON and LN. cqA3l was integrated from four QTLs for PN, PH, SN, SY at LN, cqC9c was integrated from QTLs for BN, SY, PN at ON and LN. Both cqA3l and cqC9c were detected in three trials. In addition, a total of 194 epistatic interactions, inculding 15 pleiotropic epistatic interactions, were identified. Eight of the 15 pleiotropic epistatic interactions were detected to affect SY. This result may help to better understand the genetic mechanism of yield traits in response to low N and promote the breeding of N-efficient varieties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01281-0.

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.

Determination of the Optimal Orientation of Chinese Solar Greenhouses Using 3D Light Environment Simulations

With the continuous use of resources, solar energy is expected to be the most used sustainable energy. To improve the solar energy efficiency in Chinese Solar Greenhouses (CSG), the effect of CSG orientation on intercepted solar radiation was systematically studied. By using a 3D CSG model and a detailed crop canopy model, the light environment within CSG was optimized. Taking the most widely used Liao-Shen type Chinese solar greenhouse (CSG-LS) as the prototype, the simulation was fully verified. The intercepted solar radiation of the maintenance structures and crops was used as the evaluation index. The results showed that the highest amount of solar radiation intercepted by the maintenance structures occurred in the CSG orientations of 4–6° south to west (S-W) in 36.8° N and 38° N areas, 8–10° S-W in 41.8° N areas, and 2–4° south to east (S-E) in 43.6° N areas. The solar radiation intercepted by the crop canopy displayed the highest value at an orientation of 2–4° S-W in 36.8° N, 38° N, 43.6° N areas, and 4–6° S-W in the 41.8° N area. Furthermore, the proposed model could provide scientific guidance for greenhouse crop modelling.

Functional-Structural Plant Models Mission in Advancing Crop Science: Opportunities and Prospects

Functional-structural plant models (FSPMs) have been evolving for over 2 decades and their future development, to some extent, depends on the value of potential applications in crop science. To date, stabilizing crop production by identifying valuable traits for novel cultivars adapted to adverse environments is topical in crop science. Thus, this study will examine how FSPMs are able to address new challenges in crop science for sustainable crop production. FSPMs developed to simulate organogenesis, morphogenesis, and physiological activities under various environments and are amenable to downscale to the tissue, cellular, and molecular level or upscale to the whole plant and ecological level. In a modeling framework with independent and interactive modules, advanced algorithms provide morphophysiological details at various scales. FSPMs are shown to be able to: (i) provide crop ideotypes efficiently for optimizing the resource distribution and use for greater productivity and less disease risk, (ii) guide molecular design breeding via linking molecular basis to plant phenotypes as well as enrich crop models with an additional architectural dimension to assist breeding, and (iii) interact with plant phenotyping for molecular breeding in embracing three-dimensional (3D) architectural traits. This study illustrates that FSPMs have great prospects in speeding up precision breeding for specific environments due to the capacity for guiding and integrating ideotypes, phenotyping, molecular design, and linking molecular basis to target phenotypes. Consequently, the promising great applications of FSPMs in crop science will, in turn, accelerate their evolution and vice versa.

Current status and future challenges in implementing and upscaling vertical farming systems

Vertical farming can produce food in a climate-resilient manner, potentially emitting zero pesticides and fertilizers, and with lower land and water use than conventional agriculture. Vertical farming systems (VFS) can meet daily consumer demands for nutritious fresh products, forming a part of resilient food systems-particularly in and around densely populated areas. VFS currently produce a limited range of crops including fruits, vegetables and herbs, but successful implementation of vertical farming as part of mainstream agriculture will require improvements in profitability, energy efficiency, public policy and consumer acceptance. Here we discuss VFS as multi-layer indoor crop cultivation systems, exploring state-of-the-art vertical farming and future challenges in the fields of plant growth, product quality, automation, robotics, system control and environmental sustainability and how research and development, socio-economic and policy-related institutions must work together to ensure successful upscaling of VFS to future food systems.

Integrating terrestrial laser scanning with functional-structural plant models to investigate ecological and evolutionary processes of forest communities

BACKGROUND

Woody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional-structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs.

SCOPE

The potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers.

CONCLUSIONS

We conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.

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

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

Side effects of triazoles on treated crops

Triazolic fungicides are widely applied in crop production to protect plants against fungal pathogens. However, they may influence the biochemical processes in plants and other non-target species. This paper is aimed at the effect of triazoles (namely tebuconazole, cyproconazole, and penconazole) single/mixed applications on the phenolics production in tomato (Solanum lycopersicum L.) fruit peel, amount of chlorophyll a and b in tomato leaves as well as on basic plant growth parameters. For this purpose, cherry tomatoes were planted in the pot experiment and foliarly-treated weekly, with the same total triazoles dose of 3.52 μmol per plant (in mixtures of 1.71 or 1.17 μmol of each in two or three components, respectively). The treatments increased the weight of fruits in the 1st harvest about 43%, however, this effect was not observed in the next harvest. Increased oxidative stress in the triazoles presence was observed, based on the elevated production of antioxidant phenolics in the 1st harvest. Most alarming is the decrease of the weight of thin stems and foliage and the concentration of chlorophyll a (b) in leaves in all triazoles-treated variants. The non-target impacts on plant biochemical processes (related to the phenolics or chlorophylls production and functionality) were confirmed.

Turgor-time controls grass leaf elongation rate and duration under drought stress

The process of leaf elongation in grasses is characterized by the creation and transformation of distinct cell zones. The prevailing turgor pressure within these cells is one of the key drivers for the rate at which these cells divide, expand and differentiate, processes that are heavily impacted by drought stress. In this article, a turgor-driven growth model for grass leaf elongation is presented, which combines mechanistic growth from the basis of turgor pressure with the ontogeny of the leaf. Drought-induced reductions in leaf turgor pressure result in a simultaneous inhibition of both cell expansion and differentiation, lowering elongation rate but increasing elongation duration due to the slower transitioning of cells from the dividing and elongating zone to mature cells. Leaf elongation is, therefore, governed by the magnitude of, and time spent under, growth-enabling turgor pressure, a metric which we introduce as turgor-time. Turgor-time is able to normalize growth patterns in terms of varying water availability, similar to how thermal time is used to do so under varying temperatures. Moreover, additional inclusion of temperature dependencies within our model pioneers a novel concept enabling the general expression of growth regardless of water availability or temperature.

Seasonal Efficiency of Supplemental LED Lighting on Growth and Photomorphogenesis of Sweet Basil

For decisions on supplemental lighting a quantitative knowledge of the plants' responses to light under varying conditions is fundamental. In this study, we developed light dose-response curves of growth and morphological traits for Ocimum basilicum L. and examined the effects of light color (blue, red, and white plus far-red) and natural environment (season) on these curves. Four greenhouse experiments were conducted throughout the year to determine the efficiencies of the light regimes on growth and their effects on plant morphology. A special aspect was the photosynthetic efficiency of far-red light. Linear and monomolecular relationships were found for the relationships between plant traits and supplemental light dose. Traits related to biomass productivity increased linearly with light dose whereas some morphological characters showed a saturation behavior. Red light and white plus far-red light were more efficient in plant dry weight production than blue light, and the plants adapted differently to the light qualities: higher biomass under red light was related to a plant architecture more favorable for light capture, i.e., taller plants and bigger leaves. White plus far-red light, on the other hand, increased leaf mass per area (LMA) and light use efficiency (LUE). Blue light resulted in lowest plant light interception and LUE. Considering photosynthetic effects of near-infrared light (PPFD800, 400-800 nm) instead of photosynthetic photon flux density (PPFD700, 400-700 nm) led to strongly reduced efficiencies. Traits related to photosynthesis such as dry weight, LMA and LUE were particularly affected by PPFD800. There were no interactions between the efficiencies of the different light colors and the seasons. Efficiencies of all light regimes were significantly lower during summer compared to spring and winter. Higher dry weight production during summer compared to winter and spring were a consequence of increased light interception rather than changes in LUE. The observed differences in seasonal efficiencies were directly linked to the amount of natural light present as indicated by changes in the ratio of supplemental to natural light.

Dissecting the Genotypic Variation of Growth Responses to Far-Red Radiation in Tomato

The recent development of light-emitting diodes (LEDs) and their application in modern horticulture stimulated studies demonstrating that additional far-red (FR) radiation (700-800 nm) increases plant dry mass. This effect of FR has been explained by improved photosynthesis and/or plant architecture. However, the genotypic variation in this response is largely unknown. Here, we aim to explore and explain the genotypic variation in growth responses to additional FR. We expected the genotypic variation in the responses of plant dry mass to additional FR. Further, we hypothesized that a significant improvement of both net assimilation rate (NAR) and leaf area ratio (LAR) is responsible for a strong dry mass increase under additional FR, while some genotypes respond only marginally or even negatively in NAR or LAR under FR, thus resulting in a weak FR effect on plant dry mass. To test these hypotheses, we grew 33 different tomato genotypes for 21 days with 0, 25, or 100 μmol m^-2 s^-1 of FR added to a common white + red LED background lighting of 150 μmol m^-2 s^-1. Genotypes responded similarly with respect to plant height, stem dry mass, and shoot:root ratio; i.e., they all increased with increasing FR. However, the response of total plant dry mass varied among genotypes. We categorized the genotypes into three groups (strongly, moderately, and weakly responding groups) based on their relative response in total plant dry mass to FR. Growth component analysis revealed that the strongly responding genotypes increased strongly in NAR rather than LAR. The weakly responding genotypes, however, showed a substantial increase in LAR but not NAR. The increase in LAR was due to the increase in specific leaf area. Leaf mass fraction, which is the other component of LAR, decreased with FR and did not differ between groups. In conclusion, tomato genotypes that increased strongly in NAR in response to FR were able to achieve a more substantial increase in dry mass than did other genotypes. This is the first study to explain the differences in growth responses of a large number of tomato genotypes toward FR in their light environment.

LED Lighting Strategies Affect Physiology and Resilience to Pathogens and Pests in Eggplant (Solanum melongena L.)

Over the last decade, LED lighting has gained considerable interest as an energy-efficient supplemental light source in greenhouse horticulture that can change rapidly in intensity and spectral composition. Spectral composition not only affects crop physiology but may also affect the biology of pathogens, pests, and their natural enemies, both directly and indirectly through an impact on induced plant resistance. In this study, we investigated the effects of light spectrum against a background of sunlight on growth and development of Solanum melongena. These effects were related to the spectral effects on the establishment of populations of the predatory mite Amblyseius swirskii and plant resilience against the biotrophic fungus powdery mildew, the necrotrophic fungus botrytis, and the herbivorous arthropod Western flower thrips. The effects of a reduced red/far-red (R:FR) ratio were studied under two ratios of red to blue light. Far-red light either was supplied additionally to the photosynthetic photon flux density (PPFD) or partially replaced PPFD, while maintaining total photon flux density (PFD). Effects of white light or additional UV-B light on plant resilience was tested, compared to the reference (5% blue, 5% green, and 90% red light). Plant biomass in the vegetative phase increased when additional far-red light was supplied. Stem length increased with far-red, irrespective of PPFD and the percentage of blue light. In the generative phase, total shoot biomass and fruit fresh weights were higher under additional far-red light, followed by the treatments where far-red partly replaced PPFD. Far-red light increased biomass partitioning into the fruits, at the expense of the leaves. There were no differences in population growth of A. swirskii mites between light treatments, nor did light treatment have an effect on the vertical distribution of these predatory mites in the plants. The treatments with additional far-red light reduced the infection rate of powdery mildew, but increased botrytis infection. These differences might be due to the plant defenses acting against these pathogens evolving from two different regulatory pathways. These results show that positive effects of altered spectral compositions on physiological responses were only moderately compensated by increased susceptibility to fungal pathogens, which offers perspective for a sustainable greenhouse horticulture.

Supplemental LED Lighting Effectively Enhances the Yield and Quality of Greenhouse Truss Tomato Production: Results of a Meta-Analysis

Intensive growing systems used for greenhouse tomato production, together with light interception by cladding materials or other devices, may induce intracanopy mutual shading and create suboptimal environmental conditions for plant growth. There are a large number of published peer-reviewed studies assessing the effects of supplemental light-emitting diode (LED) lighting on improving light distribution in plant canopies, increasing crop yields and producing qualitative traits. However, the research results are often contradictory, as the lighting parameters (e.g., photoperiod, intensity, and quality) and environmental conditions vary among conducted experiments. This research presents a global overview of supplemental LED lighting applications for greenhouse tomato production deepened by a meta-analysis aimed at answering the following research question: does supplemental LED lighting enhance the yield and qualitative traits of greenhouse truss tomato production? The meta-analysis was based on the differences among independent groups by comparing a control value (featuring either background solar light or solar + HPS light) with a treatment value (solar + supplemental LED light or solar + HPS + supplemental LED light, respectively) and included 31 published papers and 100 total observations. The meta-analysis results revealed the statistically significant positive effects (p-value < 0.001) of supplemental LED lighting on enhancing the yield (+40%), soluble solid (+6%) and ascorbic acid (+11%) contents, leaf chlorophyll content (+31%), photosynthetic capacity (+50%), and leaf area (+9%) compared to the control conditions. In contrast, supplemental LED lighting did not show a statistically significant effect on the leaf stomatal conductance (p-value = 0.171). In conclusion, in addition to some partial inconsistencies among the considered studies, the present research enables us to assert that supplemental LED lighting ameliorates the quantitative and qualitative aspects of greenhouse tomato production.

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.

Cherry Tomato Production in Intelligent Greenhouses-Sensors and AI for Control of Climate, Irrigation, Crop Yield, and Quality

Greenhouses and indoor farming systems play an important role in providing fresh and nutritious food for the growing global population. Farms are becoming larger and greenhouse growers need to make complex decisions to maximize production and minimize resource use while meeting market requirements. However, highly skilled labor is increasingly lacking in the greenhouse sector. Moreover, extreme events such as the COVID-19 pandemic, can make farms temporarily less accessible. This highlights the need for more autonomous and remote-control strategies for greenhouse production. This paper describes and analyzes the results of the second “Autonomous Greenhouse Challenge”. In this challenge, an experiment was conducted in six high-tech greenhouse compartments during a period of six months of cherry tomato growing. The primary goal of the greenhouse operation was to maximize net profit, by controlling the greenhouse climate and crop with AI techniques. Five international teams with backgrounds in AI and horticulture were challenged in a competition to operate their own compartment remotely. They developed intelligent algorithms and use sensor data to determine climate setpoints and crop management strategy. All AI supported teams outperformed a human-operated greenhouse that served as reference. From the results obtained by the teams and from the analysis of the different climate-crop strategies, it was possible to detect challenges and opportunities for the future implementation of remote-control systems in greenhouse production.

Genome-wide mapping and prediction of plant architecture in a sorghum nested association mapping population

Modifying plant architecture is often necessary for yield improvement and climate adaptation, but we lack understanding of the genotype-phenotype map for plant morphology in sorghum. Here, we use a nested association mapping (NAM) population that captures global allelic diversity of sorghum to characterize the genetics of leaf erectness, leaf width (at two stages), and stem diameter. Recombinant inbred lines (n = 2200) were phenotyped in multiple environments (35,200 observations) and joint linkage mapping was performed with ∼93,000 markers. Fifty-four QTL of small to large effect were identified for trait BLUPs (9-16 per trait) each explaining 0.4-4% of variation across the NAM population. While some of these QTL colocalize with sorghum homologs of grass genes (e.g., those involved in transcriptional regulation of hormone synthesis [rice SPINDLY] and transcriptional regulation of development [rice Ideal plant architecture1]), most QTL did not colocalize with an a priori candidate gene (92%). Genomic prediction accuracy was generally high in five-fold cross-validation (0.65-0.83), and varied from low to high in leave-one-family-out cross-validation (0.04-0.61). The findings provide a foundation to identify the molecular basis of architecture variation in sorghum and establish genomic-enabled breeding for improved plant architecture.

High-density QTL mapping of leaf-related traits and chlorophyll content in three soybean RIL populations

BACKGROUND

Leaf size and shape, which affect light capture, and chlorophyll content are important factors affecting photosynthetic efficiency. Genetic variation of these components significantly affects yield potential and seed quality. Identification of the genetic basis for these traits and the relationship between them is of great practical significance for achieving ideal plant architecture and high photosynthetic efficiency for improved yield.

RESULTS

Here, we undertook a large-scale linkage mapping study using three mapping populations to determine the genetic interplay between soybean leaf-related traits and chlorophyll content across two environments. Correlation analysis revealed a significant negative correlation between leaf size and shape, while both traits were positively correlated with chlorophyll content. This phenotypic relationship was verified across the three mapping populations as determined by principal component analysis, suggesting that these traits are under the control of complex and interrelated genetic components. The QTLs for leaf-related traits and chlorophyll are partly shared, which further supports the close genetic relationship between the two traits. The largest-effect major loci, q20, was stably identified across all population and environments and harbored the narrow leaflet gene Gm-JAG1 (Ln/ln), which is a key regulator of leaflet shape in soybean.

CONCLUSION

Our results uncover several major QTLs (q4-1, q4-2, q11, q13, q18 and q20) and its candidate genes specific or common to leaf-related traits and chlorophyll, and also show a complex epistatic interaction between the two traits. The SNP markers closely linked to these valuable QTLs could be used for molecular design breeding with improved plant architecture, photosynthetic capacity and even yield.

Insights on SNP types, detection methods and their utilization in Brassica species: Recent progress and future perspectives

The genus Brassica, family Brassicaceae (Cruciferae), comprises many important species of oil crops, vegetables and medicinal plants including B. rapa, B. oleracea, B. nigra, B. napus, B. juncea, B. carinata. Genomic researches in Brassica species is constrained by polyploidization, mainly due to its complicated genomic structure. However, rapid development of methods for detecting single nucleotide polymorphisms (SNP), such as next generation sequencing and SNP microarray, has accelerated release of reference Brassica species genomes as well as discovery of large numbers and genome-wide SNPs, thus intensifying forward genetics in this genus. In this review, we summarize biological characteristics, classification and various methods for detecting SNPs, focusing on high-throughput techniques. Moreover, we describe the pivotal roles of SNPs in genetic diversity, linkage map construction and QTL mapping, comparative genomics, linkage disequilibrium and genome-wide association studies. These insights are expected to deepen our understanding and guide further advancements in Brassica species research.

Quantifying the importance of a realistic tomato (Solanum lycopersicum) leaflet shape for 3-D light modelling

BACKGROUND AND AIMS

Leaflet shapes of tomato plants (Solanum lycopersicum) have been reduced to simple geometric shapes in previous functional-structural plant models (FSPMs) in order to facilitate measurements and reduce the time required to reconstruct the plant virtually. The level of error that such simplifications introduce remains unaddressed. This study therefore aims to quantify the modelling error associated with simplifying leaflet shapes.

METHODS

Realistic shapes were implemented in a static tomato FSPM based on leaflet scans, and simulation results were compared to simple geometric shapes used in previous tomato FSPMs in terms of light absorption and gross photosynthesis, for both a single plant and a glasshouse scenario.

KEY RESULTS

The effect of simplifying leaflet shapes in FSPMs leads to small but significant differences in light absorption, alterations of canopy light conditions and differences in photosynthesis. The magnitude of these differences depends on both the type of leaflet shape simplification used and the canopy shape and density. Incorporation of realistic shapes requires a small increase in initial measurement and modelling work to establish a shape database and comes at the cost of a slight increase in computation time.

CONCLUSIONS

Our findings indicate that the error associated with leaflet shape simplification is small, but often unpredictable, and is affected by plant structure but also lamp placement, which is often a primary optimization goal of these static models. Assessment of the cost-benefit of realistic shape inclusion shows relatively little drawbacks for a decrease in model uncertainty.

Quantification of light interception within image-based 3-D reconstruction of sole and intercropped canopies over the entire growth season

BACKGROUND AND AIMS

Light interception is closely related to canopy architecture. Few studies based on multi-view photography have been conducted in a field environment, particularly studies that link 3-D plant architecture with a radiation model to quantify the dynamic canopy light interception. In this study, we combined realistic 3-D plant architecture with a radiation model to quantify and evaluate the effect of differences in planting patterns and row orientations on canopy light interception.

METHODS

The 3-D architectures of maize and soybean plants were reconstructed for sole crops and intercrops based on multi-view images obtained at five growth dates in the field. We evaluated the accuracy of the calculated leaf length, maximum leaf width, plant height and leaf area according to the measured data. The light distribution within the 3-D plant canopy was calculated with a 3-D radiation model. Finally, we evaluated canopy light interception in different row orientations.

KEY RESULTS

There was good agreement between the measured and calculated phenotypic traits, with an R2 >0.97. The light distribution was more uniform for intercropped maize and more concentrated for sole maize. At the maize silking stage, 85 % of radiation was intercepted by approx. 55 % of the upper canopy region for maize and by approx. 33 % of the upper canopy region for soybean. There was no significant difference in daily light interception between the different row orientations for the entire intercropping and sole systems. However, for intercropped maize, near east-west orientations showed approx. 19 % higher daily light interception than near south-north orientations. For intercropped soybean, daily light interception showed the opposite trend. It was approx. 49 % higher for near south-north orientations than for near east-west orientations.

CONCLUSIONS

The accurate reconstruction of 3-D plants grown in the field based on multi-view images provides the possibility for high-throughput 3-D phenotyping in the field and allows a better understanding of the relationship between canopy architecture and the light environment.

Two decades of functional-structural plant modelling: now addressing fundamental questions in systems biology and predictive ecology

BACKGROUND

Functional-structural plant models (FSPMs) explore and integrate relationships between a plant's structure and processes that underlie its growth and development. In the last 20 years, scientists interested in functional-structural plant modelling have expanded greatly the range of topics covered and now handle dynamical models of growth and development occurring from the microscopic scale, and involving cell division in plant meristems, to the macroscopic scales of whole plants and plant communities.

SCOPE

The FSPM approach occupies a central position in plant science; it is at the crossroads of fundamental questions in systems biology and predictive ecology. This special issue of Annals of Botany features selected papers on critical areas covered by FSPMs and examples of comprehensive models that are used to solve theoretical and applied questions, ranging from developmental biology to plant phenotyping and management of plants for agronomic purposes. Altogether, they offer an opportunity to assess the progress, gaps and bottlenecks along the research path originally foreseen for FSPMs two decades ago. This review also allows discussion of current challenges of FSPMs regarding (1) integration of multidisciplinary knowledge, (2) methods for handling complex models, (3) standards to achieve interoperability and greater genericity and (4) understanding of plant functioning across scales.

CONCLUSIONS

This approach has demonstrated considerable progress, but has yet to reach its full potential in terms of integration and heuristic knowledge production. The research agenda of functional-structural plant modellers in the coming years should place a greater emphasis on explaining robust emergent patterns, and on the causes of possible deviation from it. Modelling such patterns could indeed fuel both generic integration across scales and transdisciplinary transfer. In particular, it could be beneficial to emergent fields of research such as model-assisted phenotyping and predictive ecology in managed ecosystems.

Parameter estimation for functional-structural plant models when data are scarce: using multiple patterns for rejecting unsuitable parameter sets

BACKGROUND AND AIMS

Functional-structural plant (FSP) models provide insights into the complex interactions between plant architecture and underlying developmental mechanisms. However, parameter estimation of FSP models remains challenging. We therefore used pattern-oriented modelling (POM) to test whether parameterization of FSP models can be made more efficient, systematic and powerful. With POM, a set of weak patterns is used to determine uncertain parameter values, instead of measuring them in experiments or observations, which often is infeasible.

METHODS

We used an existing FSP model of avocado (Persea americana 'Hass') and tested whether POM parameterization would converge to an existing manual parameterization. The model was run for 10 000 parameter sets and model outputs were compared with verification patterns. Each verification pattern served as a filter for rejecting unrealistic parameter sets. The model was then validated by running it with the surviving parameter sets that passed all filters and then comparing their pooled model outputs with additional validation patterns that were not used for parameterization.

KEY RESULTS

POM calibration led to 22 surviving parameter sets. Within these sets, most individual parameters varied over a large range. One of the resulting sets was similar to the manually parameterized set. Using the entire suite of surviving parameter sets, the model successfully predicted all validation patterns. However, two of the surviving parameter sets could not make the model predict all validation patterns.

CONCLUSIONS

Our findings suggest strong interactions among model parameters and their corresponding processes, respectively. Using all surviving parameter sets takes these interactions into account fully, thereby improving model performance regarding validation and model output uncertainty. We conclude that POM calibration allows FSP models to be developed in a timely manner without having to rely on field or laboratory experiments, or on cumbersome manual parameterization. POM also increases the predictive power of FSP models.

Light response of photosynthesis and stomatal conductance of rose leaves in the canopy profile: the effect of lighting on the adaxial and the abaxial sides

We investigated the light response of leaf photosynthesis, stomatal conductance and optical properties in rose plants grown in a glasshouse with bending technique. Leaves were lighted from the adaxial or the abaxial side during measurements, performed in four positions in the upright and bent shoots: top leaves, middle leaves, bottom leaves, and bent shoot leaves. Moreover, the effect of the irradiation on the adaxial or abaxial leaf side on whole canopy photosynthesis was estimated through model simulation. No significant differences were found in light transmission, reflection and absorption of leaves and in photosynthesis light response curves among the four positions. In all the leaf positions, light absorption, stomatal conductance and photosynthesis were higher when leaves were lighted from the adaxial compared with the abaxial side. The model showed that a substantial part of the light absorbed by the crop originated from light reflected from the greenhouse floor, and thus the abaxial leaf properties have impact on whole crop light absorbance and photosynthesis. Simulations were performed for crops with leaf area index (LAI) 1, 2 and 3. Simulation at LAI 1 showed the highest reduction of simulated crop photosynthesis considering abaxial properties; however, to a lesser extent photosynthesis was also reduced at LAI 2 and 3. The overall results showed that the model may be helpful in designing crop systems for improved light utilisation by changing lamp position or level of leaf bending and pruning.

Substantial differences occur between canopy and ambient climate: Quantification of interactions in a greenhouse-canopy system

Organ temperature and variation therein plays a key role in plant functioning and its responses to e.g. climate change. There is a strong feedback between organ, especially leaf, temperature and the climate within the canopy (canopy climate), which in turn interacts with the climate outside the canopy (ambient climate). For greenhouses, the determinants of this interplay and how they drive differences between canopy and ambient climate are poorly understood. Yet, as many experiments on both regular greenhouse crops and field crops are done in greenhouses, this is crucial to know. Therefore, we designed an experiment to quantify the differences between ambient and canopy climate and leaf temperature. A path analysis was performed to quantify the interactions between components of the greenhouse canopy-climate system. We found that with high radiation the canopy climate can be up to 5°C cooler than the ambient climate, while for cloudy days this was only 2°C. Canopy relative humidity (RH) was up to 25% higher compared to ambient RH. We showed that radiation is very important for these climate differences, but that this effect could be partly counteracted by turning off supplementary light (i.e. due to its indirect effects e.g. changing light distribution). Leaf temperature was substantially different, both higher and lower, from the canopy air temperature. This difference was determined by leaf area index (LAI), temperature of the heating pipe and the use of supplementary light, which all strongly influence radiation, either shortwave or thermal radiation. The difference between leaf and ambient air temperature could be decreased by decreasing the LAI or increasing the temperature of the heating pipe.

Leaf shape is a predictor of fruit quality and cultivar performance in tomato

Commercial tomato (Solanum lycopersicum) is one of the most widely grown vegetable crops worldwide. Heirloom tomatoes retain extensive genetic diversity and a considerable range of fruit quality and leaf morphological traits. Here the role of leaf morphology was investigated for its impact on fruit quality. Heirloom cultivars were grown in field conditions, and BRIX by yield (BY) and other traits were measured over a 14-wk period. The complex relationships among these morphological and physiological traits were evaluated using partial least-squares path modeling, and a consensus model was developed. Photosynthesis contributed strongly to vegetative biomass and sugar content of fruits but had a negative impact on yield. Conversely leaf shape, specifically rounder leaves, had a strong positive impact on both fruit sugar content and yield. Cultivars such as Stupice and Glacier, with very round leaves, had the highest performance in both fruit sugar and yield. Our model accurately predicted BY for two commercial cultivars using leaf shape data as input. This study revealed the importance of leaf shape to fruit quality in tomato, with rounder leaves having significantly improved fruit quality. This correlation was maintained across a range of diverse genetic backgrounds and shows the importance of leaf morphology in tomato crop improvement.

Dorsoventral photosynthetic asymmetry of tobacco leaves in response to direct and diffuse light

Plants can change leaf forms, adjusting light conditions on their adaxial and abaxial surfaces, to adapt to light environments and enhance their light use efficiencies. The difference between photosynthesis on the two leaf sides (dorsoventral asymmetry) is an important factor that affects light use efficiency. However, photosynthetic dorsoventral asymmetry is rarely compared under direct and diffuse light conditions. To estimate the impacts of recently reported alterations in direct and diffuse light in the sky radiation on plant carbon assimilation, variations in morphology between the two leaf sides in tobacco (Nicotiana tabacum L.) were investigated, and the dorsoventral responses of photosynthesis to illuminating directions were compared in direct and diffuse light. Dorsoventral asymmetry was reflected in stomatal densities, anatomic structures, and photochemical traits, which caused markedly different photosynthetic rates as well as stomatal conductances both in direct and diffuse light. However, the degree of photosynthetic asymmetry was weakened in diffuse light. The diffuse light caused a greater stomatal conductance on the abaxial side than direct light, which resulted in reduced photosynthetic asymmetry. In addition, the photosynthetic dorsoventral asymmetry could be affected by the photosynthetic photon flux density. These results contribute to understanding the dorsoventral regulation of photosynthesis in bifacial leaves, and provide a reference for breeding to cope with the increase in the proportion of diffuse light in the future.

Phyllotaxis: is the golden angle optimal for light capture?

Phyllotactic patterns are some of the most conspicuous in nature. To create these patterns plants must control the divergence angle between the appearance of successive organs, sometimes to within a fraction of a degree. The most common angle is the Fibonacci or golden angle, and its prevalence has led to the hypothesis that it has been selected by evolution as optimal for plants with respect to some fitness benefits, such as light capture. We explore arguments for and against this idea with computer models. We have used both idealized and scanned leaves from Arabidopsis thaliana and Cardamine hirsuta to measure the overlapping leaf area of simulated plants after varying parameters such as leaf shape, incident light angles, and other leaf traits. We find that other angles generated by Fibonacci-like series found in nature are equally optimal for light capture, and therefore should be under similar evolutionary pressure. Our findings suggest that the iterative mechanism for organ positioning itself is a more likely target for evolutionary pressure, rather than a specific divergence angle, and our model demonstrates that the heteroblastic progression of leaf shape in A. thaliana can provide a potential fitness benefit via light capture.

UVA Radiation Is Beneficial for Yield and Quality of Indoor Cultivated Lettuce

Understanding the wavelength dependence of plant responses is essential for optimizing production and quality of indoor plant cultivation. UVA is the main component of solar UV radiation, but its role on plant growth is poorly understood. Here, two experiments were conducted to examine whether UVA supplementation is beneficial for indoor plant cultivation. Lettuce (Lactuca sativa L. cv. "Klee") was grown under mixed blue, red, and far-red light with photon flux density of 237 μmol m-2 s-1 in the growth room; photoperiod was 16 h. In the first experiment, three UVA intensities with peak wavelengths at 365 nm were used: 10 (UVA-10), 20 (UVA-20), and 30 (UVA-30) μmol m-2 s-1, respectively. In the second experiment, 10 μmol m-2 s-1 UVA radiation were given for 5 (UVA-5d), 10 (UVA-10d), and 15 (UVA-15d) days before harvest on day 15, respectively. Compared with control (no UVA), shoot dry weight was increased by 27%, 29%, and 15% in the UVA-10, UVA-20, and UVA-30 treatments, respectively, which correlated with 31% (UVA-10), 32% (UVA-20), and 14% (UVA-30) larger leaf area. Shoot dry weight under the treatments of UVA-5d, UVA-10d, and UVA-15d was increased by 18%, 32%, and 30%, respectively, and leaf area was increased by 15%-26%. For both experiments, UVA radiation substantially enhanced secondary metabolites accumulation, e.g. anthocyanin and ascorbic acid contents were increased by 17%-49% and 47%-80%, respectively. Moreover, plants grown under the UVA-30 treatment were stressed, as indicated by lipid peroxidation and lower maximum quantum efficiency of photosystem II photochemistry (Fv/Fm). We conclude that UVA supplementation not only stimulates biomass production in controlled environments, but also enhances secondary metabolite accumulation.

Tailoring parameter distributions to specific germplasm: impact on crop model-based ideotyping

Crop models are increasingly used to identify promising ideotypes for given environmental and management conditions. However, uncertainty must be properly managed to maximize the in vivo realizability of ideotypes. We focused on the impact of adopting germplasm-specific distributions while exploring potential combinations of traits. A field experiment was conducted on 43 Italian rice varieties representative of the Italian rice germplasm, where the following traits were measured: light extinction coefficient, radiation use efficiency, specific leaf area at emergence and tillering. Data were used to derive germplasm-specific distributions, which were used to re-run a previous modelling experiment aimed at identifying optimal combinations of plant trait values. The analysis, performed using the rice model WARM and sensitivity analysis techniques, was conducted under current conditions and climate change scenarios. Results revealed that the adoption of germplasm-specific distributions may markedly affect ideotyping, especially for the identification of most promising traits. A re-ranking of some of the most relevant parameters was observed (radiation use efficiency shifted from 4th to 1st), without clear relationships between changes in rankings and differences in distributions for single traits. Ideotype profiles (i.e., values of the ideotype traits) were instead more consistent, although differences in trait values were found.

Integrating Morphological and Physiological Responses of Tomato Plants to Light Quality to the Crop Level by 3D Modeling

Next to its intensity, the spectral composition of light is one of the most important factors affecting plant growth and morphology. The introduction of light emitting diodes (LEDs) offers perspectives to design optimal light spectra for plant production systems. However, knowledge on the effects of light quality on physiological plant processes is still limited. The aim of this study is to determine the effects of six light qualities on growth and plant architecture of young tomato plants, and to upscale these effects to the crop level using a multispectral, functional-structural plant model. Young tomato plants were grown under 210 μmol m-2 s-1 blue, green, amber, red, white or red/blue (92%/8%) LED light with a low intensity of sunlight as background. Plants grown under blue light were shorter and developed smaller leaves which were obliquely oriented upward. Leaves grown under blue light contained the highest levels of light harvesting pigments, but when exposed to blue light only, they had the lowest rate of leaf photosynthesis. However, when exposed to white light these leaves had the highest rate of photosynthesis. Under green light, tomato plants were taller and leaves were nearly horizontally oriented, with a high specific leaf area. The open plant structure combined with a high light transmission and reflection at the leaf level allowed green light to penetrate deeper into the canopy. Plants grown under red, amber and white light were comparable with respect to height, leaf area and biomass production. The 3D model simulations indicated that the observed changes in plant architecture had a significant impact on light absorbance at the leaf and crop level. The combination of plant architecture and spectrum dependent photosynthesis was found to result in the highest rate of crop photosynthesis under red light in plants initially grown under green light. These results suggest that dynamic light spectra may offer perspectives to increase growth and production in high value production systems such as greenhouse horticulture and vertical farming.