Dataset Information

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional-structural plant model.

ABSTRACT: There is increasing interest in evaluating the environmental effects on crop architectural traits and yield improvement. However, crop models describing the dynamic changes in canopy structure with environmental conditions and the complex interactions between canopy structure, light interception, and dry mass production are only gradually emerging. Using tomato (Solanum lycopersicum L.) as a model crop, a dynamic functional-structural plant model (FSPM) was constructed, parameterized, and evaluated to analyse the effects of temperature on architectural traits, which strongly influence canopy light interception and shoot dry mass. The FSPM predicted the organ growth, organ size, and shoot dry mass over time with high accuracy (>85%). Analyses of this FSPM showed that, in comparison with the reference canopy, shoot dry mass may be affected by leaf angle by as much as 20%, leaf curvature by up to 7%, the leaf length:width ratio by up to 5%, internode length by up to 9%, and curvature ratios and leaf arrangement by up to 6%. Tomato canopies at low temperature had higher canopy density and were more clumped due to higher leaf area and shorter internodes. Interestingly, dry mass production and light interception of the clumped canopy were more sensitive to changes in architectural traits. The complex interactions between architectural traits, canopy light interception, dry mass production, and environmental conditions can be studied by the dynamic FSPM, which may serve as a tool for designing a canopy structure which is 'ideal' in a given environment.

SUBMITTER: Chen TW

PROVIDER: S-EPMC4246178 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional-structural plant model.

Chen Tsu-Wei TW Nguyen Thi My Nguyet TM Kahlen Katrin K Stützel Hartmut H

Journal of experimental botany 20140902 22

There is increasing interest in evaluating the environmental effects on crop architectural traits and yield improvement. However, crop models describing the dynamic changes in canopy structure with environmental conditions and the complex interactions between canopy structure, light interception, and dry mass production are only gradually emerging. Using tomato (Solanum lycopersicum L.) as a model crop, a dynamic functional-structural plant model (FSPM) was constructed, parameterized, and evalua ...[more]

PMID: 25183746

Similar Datasets

Project description: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.

Project description:Canopy architecture determines the light distribution and light interception in the canopy. Reasonable shaping and pruning can optimize tree structure; maximize the utilization of land, space and light energy; and lay the foundation for achieving early fruiting, high yield, health and longevity. Due to the complexity of loquat canopy architecture and the multi-year period of tree growth, the variables needed for experiments in canopy type training are hardly accessible through field measurements. In this paper, we concentrated on exploring the relationship between branching angle and light interception using a three-dimensional (3D) canopy model in loquat (Eriobotrya japonica Lindl). First, detailed 3D models of loquat trees were built by integrating branch and organ models. Second, the morphological models of different loquat trees were constructed by interactive editing. Third, the 3D individual-tree modeling software LSTree integrated with the OpenGL shadow technique, a radiosity model and a modified rectangular hyperbola model was used to calculate the silhouette to total area ratio, the distribution of photosynthetically active radiation within canopies and the net photosynthetic rate, respectively. Finally, the influence of loquat tree organ organization on the light interception of the trees was analyzed with different parameters. If the single branch angle between the level 2 scaffold branch and trunk is approximately 15° and the angles among the level 2 scaffold branches range from 60 to 90°, then a better light distribution can be obtained. The results showed that the branching angle has a significant impact on light interception, which is useful for grower manipulation of trees, e.g., shoot bending (scaffold branch angle). Based on this conclusion, a reasonable tree structure was selected for intercepting light. This quantitative simulation and analytical method provides a new digital and visual method that can aid in the design of tree architecture.

Project description:Light is a key driver of forest biodiversity and functioning. Light regimes beneath tree canopies are mainly driven by the solar angle, topography, and vegetation structure, whose three-dimensional complexity creates heterogeneous light conditions that are challenging to quantify, especially across large areas. Remotely sensed canopy structure data from airborne laser scanning (ALS) provide outstanding opportunities for advancement in this respect. We used ALS point clouds and a digital terrain model to produce hemispherical photographs from which we derived indices of nondirectional diffuse skylight and direct sunlight reaching the understory. We validated our approach by comparing the performance of these indices, as well as canopy closure (CCl) and canopy cover (CCo), for explaining the light conditions experienced by forest plant communities, as indicated by the Landolt indicator values for light (L light) from 43 vegetation surveys along an elevational gradient. We applied variation partitioning to analyze how the independent and joint statistical effects of light, macroclimate, and soil on the spatial variation in plant species composition (i.e., turnover, Simpson dissimilarity, ? SIM) depend on light approximation methodology. Diffuse light explained L light best, followed by direct light, CCl and CCo (R2 = .31, .23, .22, and .22, respectively). The combination of diffuse and direct light improved the model performance for ? SIM compared with CCl and CCo (R2 = .30, .27 and .24, respectively). The independent effect of macroclimate on ? SIM dropped from an R 2 of .15 to .10 when diffuse light and direct light were included. The ALS methods presented here outperform conventional approximations of below-canopy light conditions, which can now efficiently be quantified along entire horizontal and vertical forest gradients, even in topographically complex environments such as mountains. The effect of macroclimate on forest plant communities is prone to be overestimated if local light regimes and associated microclimates are not accurately accounted for.

Project description:This study examined the acclimation to temperature of two globally invasive species Iris pseudacorus and Lythrum salicaria, which share the same habitat type but differ in morphology. Iris pseudacorus has long vertical leaves, allowing light penetration through the canopy, while L. salicaria has stems with small horizontal leaves, creating significant self-shading. We aimed to build a physiological understanding of how these two species respond to different growth temperatures with regard to growth and gas exchange-related traits over the canopy. Growth and gas exchange-related traits in response to low (15 °C) and high (25 °C) growth temperature regimes were compared. Plants were grown in growth chambers, and light response curves were measured with infrared gas analysers after 23-33 days at three leaf positions on each plant, following the vertical light gradient through the canopy. After 37 days of growth, above-ground biomass, photosynthetic pigments and leaf N concentration were determined. The maximum photosynthesis rate was lower in lower leaf positions but did not differ significantly between temperatures. Iris pseudacorus photosynthesis decreased with decreasing leaf position, more so than L. salicaria. This was explained by decreasing N and chlorophyll concentrations towards the leaf base in I. pseudacorus, while pigment concentrations increased towards the lower canopy in L. salicaria. Biomass, shoot height and specific leaf area increased with temperature, more so in I. pseudacorus than in L. salicaria. Light response curves revealed that L. salicaria had a higher degree of shade acclimation than I. pseudacorus, probably due to self-shading in L. salicaria. High temperature decreased C assimilation at the bottom of the canopy in L. salicaria, while C assimilation in I. pseudacorus was less affected by temperature. As vegetative growth and flowering was stimulated by temperature, the invasive potential of these species is predicted to increase under global warming.

Project description:The need for the olive farm modernization have encouraged the research of more efficient crop management strategies through cross-breeding programs to release new olive cultivars more suitable for mechanization and use in intensive orchards, with high quality production and resistance to biotic and abiotic stresses. The advancement of breeding programs are hampered by the lack of efficient phenotyping methods to quickly and accurately acquire crop traits such as morphological attributes (tree vigor and vegetative growth habits), which are key to identify desirable genotypes as early as possible. In this context, an UAV-based high-throughput system for olive breeding program applications was developed to extract tree traits in large-scale phenotyping studies under field conditions. The system consisted of UAV-flight configurations, in terms of flight altitude and image overlaps, and a novel, automatic, and accurate object-based image analysis (OBIA) algorithm based on point clouds, which was evaluated in two experimental trials in the framework of a table olive breeding program, with the aim to determine the earliest date for suitable quantifying of tree architectural traits. Two training systems (intensive and hedgerow) were evaluated at two very early stages of tree growth: 15 and 27 months after planting. Digital Terrain Models (DTMs) were automatically and accurately generated by the algorithm as well as every olive tree identified, independently of the training system and tree age. The architectural traits, specially tree height and crown area, were estimated with high accuracy in the second flight campaign, i.e. 27 months after planting. Differences in the quality of 3D crown reconstruction were found for the growth patterns derived from each training system. These key phenotyping traits could be used in several olive breeding programs, as well as to address some agronomical goals. In addition, this system is cost and time optimized, so that requested architectural traits could be provided in the same day as UAV flights. This high-throughput system may solve the actual bottleneck of plant phenotyping of "linking genotype and phenotype," considered a major challenge for crop research in the 21st century, and bring forward the crucial time of decision making for breeders.

Dataset Information

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional-structural plant model.

Publications

Quantification of the effects of architectural traits on dry mass production and light interception of tomato canopy under different temperature regimes using a dynamic functional-structural plant model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets