Leaf Area Distribution Research Articles

The response of weed and crop species to shading: Which parameters explain weed impacts on crop production?

Crops compete with weeds for light, and choosing competitive crop species contributes to managing weeds. The objective was to identify which crop and weed parameters related to competition for light drive weed harmfulness for crop production. In a previous experiment, we measured parameters to characterize species potential plant morphology in unshaded conditions and species response to shading for a range of 60 crop and annual weed species. Here, we integrated the measured parameter values into an existing simulation model that uses an individual-based 3D representation of crop-weed canopies to predict weed dynamics and crop production from pedoclimate and cropping system information. The model, i.e. FlorSys, was used to run virtual experiments in seven French and Spanish regions, with 272 cropping systems varying in terms of crop rotations, herbicide use and tillage intensity etc. A series of statistical methods (RLQ, fourth corner analysis, Principal Component Analysis, Pearson correlation coefficients, analysis of variance) were used to identify the key weed and crop parameters that drive crop yield loss and other weed harmfulness indicators. The weed species that caused the highest yield loss had a large leaf area at emergence. When young, they presented a large specific leaf area and a uniform leaf area distribution along plant height. They were also taller per unit plant biomass and their populations were more homogeneous in terms of plant width. At later stages, harmful weed species presented a smaller interception area to herbicides, with thicker leaves located lower on the plant. When shaded, harmful weed species shifted their leaves upwards and decreased their plant width per unit biomass. Weed-suppressive crop species had a large specific leaf area, wider plants per unit biomass, and a uniform leaf area distribution along plant height. When shaded, they increased their plant height and width per unit biomass. There was a trade-off between parameters driving potential crop production and those minimizing weed-inflicted yield losses.

Changes in the vertical distribution of leaf area enhanced light interception efficiency in maize over generations of selection.

Breeders select for yield, thereby indirectly selecting for traits that contribute to it. We tested if breeding has affected a range of traits involved in plant architecture and light interception, via the analysis of a panel of 60 maize hybrids released from 1950 to 2015. This was based on novel traits calculated from reconstructions derived from a phenotyping platform. The contribution of these traits to light interception was assessed in virtual field canopies composed of 3D plant reconstructions, with a model tested in a real field. Two categories of traits had different contributions to genetic progress. (a) The vertical distribution of leaf area had a high heritability and showed a marked trend over generations of selection. Leaf area tended to be located at lower positions in the canopy, thereby improving light penetration and distribution in the canopy. This potentially increased the carbon availability to ears, via the amount of light absorbed by the intermediate canopy layer. (b) Neither the horizontal distribution of leaves in the relation to plant rows nor the response of light interception to plant density showed appreciable trends with generations. Hence, among many architectural traits, the vertical distribution of leaf area was the main indirect target of selection.

Functional Crown Architecture of Five Temperate Broadleaf Tree Species: Vertical Gradients in Leaf Morphology, Leaf Angle, and Leaf Area Density

The morphology, inclination, and spatial distribution of leaves in different parts of tree crowns are important determinants of the radiation, momentum, and gas exchange between the canopy and the atmosphere. However, it is not well known how these foliage-related traits vary among species differing in successional status. We measured leaf size, leaf mass area (LMA), leaf inclination (angle to the horizontal), leaf area density (LAD), total leaf area (leaf area index, LAI), and leaf area distribution across the crown in adult trees of five common, early to late-successional tree species (Betula pendula Roth, Quercus petraea (Matt.) Liebl., Carpinus betulus L., Tilia cordata Mill., and Fagus sylvatica L.) using different canopy access techniques and the harvest of foliated trees (29 trees in total). Leaf size increased continuously with crown depth in B. pendula and T. cordata but peaked at mid-crown in Q. petraea, C. betulus, and F. sylvatica to decrease toward the shade crown. By contrast, LMA and leaf angle decreased continuously with crown depth in all species, but the pattern of vertical change varied. The mid/late- and late-successional species had higher LAI, lower shade-leaf LMA, lower leaf angles (shade and sun crown), and higher LAD in the uppermost sun crown in comparison to early successional B. pendula. We assume that the most peripheral sun leaf layer is partly acting as a shield against excess radiation, with foliage properties depending on the structure of the shade crown. We conclude that the vertical change in leaf morphology, inclination, and spatial distribution in tree crowns is highly species specific, with partial dependence on the species’ position in succession.

The Spatial Distribution of the Needle Area of Planted Larix olgensis Trees

The spatial distribution of leaf area largely governs both the structure and function of a tree crown. Three sample trees were selected from a 16-year-old Larix olgensis plantation in the Maoershan Forest Farm, Heilongjiang Province, based on the average diameter at breast height in each plot. All needles from the branches in the nodal and internodal pseudowhorls within the crown were destructively sampled. The crown was divided into several segments in the vertical and horizontal directions, resulting in different sub-regions. The needle area (NA) in each sub-region was computed based on the needle mass per area (NMA). The vertical and horizontal distributions and their cumulative NA distributions were characterized using the Weibull distribution function and its cumulative form. A two-dimensional NA model was created by combining the two Weibull distribution functions of the vertical and horizontal distributions. The variation in the spatial distribution of the NA among the different crown directions is discussed, and the influence of competition from competitors on the spatial distribution of NA was analyzed. The results showed that the Weibull distribution function and its cumulative form performed well in describing the vertical and horizontal distributions and the cumulative distributions of the NA, which was generally concentrated upward within the crown. This phenomenon was most apparent in dense stands with strong competition. The center of the NA exhibited an inward shift in the horizontal direction within the crown but shifted outwards with an increase in competition. The cumulative vertical and horizontal distributions of the NA obviously varied with different crown directions, which was associated mainly with the light conditions. The two-dimensional NA patterns showed that the center of the NA generally shifted outward with an increase in the relative depth into the crown (RDINC), and that more concentrated and more skewed patterns usually occurred under increased competition. Different crown directions exhibited different two-dimensional NA patterns, but the core driver was the variable light condition caused by the competitors, particularly in closed stands.

Extraction of Leaf Biophysical Attributes Based on a Computer Graphic-based Algorithm Using Terrestrial Laser Scanning Data

Leaf attribute estimation is crucial for understanding photosynthesis, respiration, transpiration, and carbon and nutrient cycling in vegetation and evaluating the biological parameters of plants or forests. Terrestrial laser scanning (TLS) has the capability to provide detailed characterisations of individual trees at both the branch and leaf scales and to extract accurate structural parameters of stems and crowns. In this paper, we developed a computer graphic-based 3D point cloud segmentation approach for accurately and efficiently detecting tree leaves and their morphological features (i.e., leaf area and leaf angle distributions (leaf azimuthal angle and leaf inclination angle)) from single leaves. To this end, we adopted a sphere neighbourhood model with an adaptive radius to extract the central area points of individual leaves with different morphological structures and complex spatial distributions; meanwhile, four auxiliary criteria were defined to ensure the accuracy of the extracted central area points of individual leaf surfaces. Then, the density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to cluster the central area points of leaves and to obtain the centre point corresponding to each leaf surface. We also achieved segmentation of individual leaf blades using an advanced 3D watershed algorithm based on the extracted centre point of each leaf surface and two morphology-related parameters. Finally, the leaf attributes (leaf area and leaf angle distributions) were calculated and assessed by analysing the segmented single-leaf point cloud. To validate the final results, the actual leaf area, leaf inclination and azimuthal angle data of designated leaves on the experimental trees were manually measured during field activities. In addition, a sensitivity analysis investigated the effect of the parameters in our segmentation algorithm. The results demonstrated that the segmentation accuracy of Ehretia macrophylla (94.0%) was higher than that of crape myrtle (90.6%) and Fatsia japonica (88.8%). The segmentation accuracy of Fatsia japonica was the lowest of the three experimental trees. In addition, the single-leaf area estimation accuracy for Ehretia macrophylla (95.39%) was still the highest among the three experimental trees, and the single-leaf area estimation accuracy for crape myrtle (91.92%) was lower than that for Ehretia macrophylla (95.39%) and Fatsia japonica (92.48%). Third, the method proposed in this paper provided accurate leaf inclination and azimuthal angles for the three experimental trees (Ehretia macrophylla: leaf inclination angle: R 2 = 0.908, RMSE = 6.806° and leaf azimuth angle: R 2 = 0.981, RMSE = 7.680°; crape myrtle: leaf inclination angle: R 2 = 0.901, RMSE = 8.365° and leaf azimuth angle: R 2 = 0.938, RMSE = 7.573°; Fatsia japonica: leaf inclination angle: R 2 = 0.849, RMSE = 6.158° and leaf azimuth angle: R 2 = 0.947, RMSE = 3.946°). The results indicate that the proposed method is effective and operational for providing accurate, detailed information on single leaves and vegetation structure from scanned data. This capability facilitates improvements in applications such as the estimation of leaf area, leaf angle distribution and biomass.

Modeling the Directional Clumping Index of Crop and Forest

The Clumping Index (Ω) was introduced to quantify the spatial distribution pattern of vegetation elements. It is crucial to improve the estimation accuracy of vital vegetation parameters, such as Leaf Area Index (LAI) and Gross Primary Production (GPP). Meanwhile, the parameterization of Ω is challenging partly due to the varying observations of canopy gaps from different view angles. Many previous studies have shown the increase of Ω with view zenith angle through samples of gap size distribution from in situ measurements. In contrast, remote sensing retrieval algorithms only assign a constant value for each biome type to roughly correct the clumping effect as a compromise between the accuracy and efficiency. In this paper, analytical models are proposed that estimate the directional clumping index (Ω(θ)) of crop and forest at canopy level. The angular variation trend and magnitude of crop Ω(θ) was analyzed within row structure where vegetation elements are randomly spaced along rows. The forest model predicts Ω(θ) with tree density, distribution pattern, crown shape, trunk size, and leaf area and angle distribution function. The models take into account the main directional characteristics of clumping index using easy-to-measure parameters. Test cases showed that Ω(θ) magnitude variation for black spruce forest was 102.3% of the hemispherical average clumping index ( Ω ˜ ), whereas the Larch forest had 48.7% variation, and row crop variation reached 32.4%. This study provided tools to assess Ω(θ) of discontinuous canopies.

Predicting models of leaf area for trees in Larix olgensis plantation.

Leaf area influences dry matter production of trees, as well as the growth of trees and forest stands. The accurate estimation of leaf area plays an important role in analyzing the growth of trees and forest stands. Based on data of 76 Larix olgensis trees in a plantation of Heilongjiang Province, predicting models of branch leaf area (BLA) and crown leaf area (CLA) were constructed, respectively. The results showed that a form of lnBLA=β1+(β2+b2)lnBD+(β3+b3)lnRDINC+β4lnDBH+β5lnHT/DBH+(β6+b6)lnCR was selected as the optimal BLA mixed-effect model with the considera-tion of tree-level random effects, composed of three random-effect on lnBD, lnRDINC and lnCR (βi represented model fixed parameters, bi represented model random-effect parameters, BD was branch diameter, RDINC was the relative depth into crown from tree apex, DBH was tree diameter at breast height, HT/DBH represented the ratio of tree height to DBH, and CR represented the ratio of crown length to tree height). The adjusted coefficient of determination (Ra2), residual mean squares error (RMSE), mean error (ME), mean absolute error (MAE) and precision estimation (P) of the optimal BLA mixed model were 0.90, 0.5477, -0.03, 0.24 and 91%, respectively, indicating the model had a good performance in predicting. The CLA was calculated by predicted values of all branches based on developed BLA model and the final form of CLA model was as follows: lnCLA=γ0+γ1lnDBH+γ2CR (γi, model parameters). Results of likelihood ratio test (P>0.05) showed that plot-level random effect had no influence on the model performance, which can be ignored. The CLA model got a good-fitting effect with R2 and RMSE being 0.87 and 0.3847, respectively. The CLA predicting model developed in this study could provide a good prediction of CLA for L. olgensis trees and provided a theoretical basis for the research on distribution of leaf area and photosynthesis.

The relationship between leaf and ecosystem CO2 exchanges in a maize field

The relationship between leaf photosynthetic rate (A) in a vegetation canopy and the net ecosystem CO2 exchange (NEE) over an entire ecosystem is not well understood. The aim of the present study is to assess the coordinated changes in NEE derived with eddy covariance, A measured in leaf cuvette, and their associations in a rainfed maize field. The light response-curves were estimated for the carbon assimilation rate at both the leaf and ecosystem scales. NEE and A synchronically changed throughout the day and were greater around noon and persisted longer during rapid growth periods. The leaf A had a similar pattern of daytime changes in the top, middle, and bottom leaves. Only severe leaf ageing led to a significant decline in the maximum efficiency of photosystem II (PSII) photochemistry. The greater maximum NEE was associated with a higher ecosystem quantum yield. NEE was positively and significantly correlated with the leaf A averaged based on the vertical distribution of leaf area. The finding highlights the feasibility of assessing NEE by leaf CO2 exchange because of most of experimental data obtained with leaf cuvette methods; and also implies that simultaneously enhancing leaf photosynthetic rate, electron transport rate, net carbon assimilation at whole ecosystem might play a critical role for the enhancement of crop productivity.

Spatial variation in specific leaf area and horizontal distribution of leaf area in juvenile western larch (Larix occidentalis Nutt.)

Models were developed to predict spatial distribution of specific leaf area (SLA) and horizontal distribution of leaf area for western larch. Cardinal branch direction significantly influenced both SLA and horizontal leaf area distributions. Leaf area, specific leaf area (SLA), and their spatial distribution in the crown are important indicators of biological response to changes in growing conditions including light and water availability. Western larch (Larix occidentalis Nutt.) is a deciduous coniferous pioneer species in the U.S. Inland Northwest known for its rapid growth, high-quality wood, and ecological importance. Analysis with nonlinear models revealed that SLA and horizontal leaf area distributions differ between cardinal quadrants of juvenile western larch crowns. SLA was significantly higher in the more illuminated, southern side of the crown, and leaf area peaked closer to the stem in the southwest quadrant. Similar to other conifers, horizontal distributions of foliage in western larch also shifted further outward towards the branch tips with increasing depth in the crown. Models developed for horizontal distribution of leaf area and spatial distribution of specific leaf area for western larch may be extended by future researchers to predict its response to environmental variables or management practices.

Neighbor and Height Effects on Crown Properties Associated with the Uniform-Stress Principle of Stem Formation

According to the uniform-stress principle of stem formation, the amount of leaf area a tree carries and the leverage it exerts on the stem determine the stem dimensions. Within an even-aged monoculture, the leaf area per tree and the leverage placed on the stem are functions of tree density and tree height. The uniform-stress principle presents the means to translate density effects on crown characteristics into stem dimensions and total standing volume. This approach is truly a top-down method of simulating growth tree and stand growth because leaf area and other crown properties must be determined before stem size and taper can be calculated. Each crown property influences either the sail area or the leverage placed on the stem, but the degree to which a specific crown property affects these parameters changes with stand density and height. Leverage is the more complicated of the two variables, being a function of the height to the base of the live crown and the vertical distribution of leaf area. The purpose of this brief review is to summarize the effects of stand density on the height to the base of the live tree and the vertical distribution of leaf area and the various ways these variables have been quantified.

Plastic tree crowns contribute to small-scale heterogeneity in virgin beech forests—An individual-based modeling approach

Old-growth beech (Fagus sylvatica L.) forests in Europe show a structural heterogeneity, which distinguish from managed ones. Recent investigations revealed that facilitative belowground interactions might counteract aboveground competition for light. However, the exact interaction of these mechanisms is unclear. We developed the BEEchPlasticity (BEEP) model to investigate whether the mere focus on the aboveground competition for canopy space with subsequent modeling of the light transmittance through the forest canopy suffices to reproduce the observed structural attributes. The BEEP model is individual-based, and explicitly describes the plasticity of tree crowns in a three-dimensional space through a geometric approach. This conceptual design allows tracing neighborhood effects to the forest stand level.We ran 10 simulation experiments with 1000 time steps on a simulation area of 0.5öha. We analyzed the emerging spatial point patterns, gap dynamics as well as distributions of tree age, tree height, tree crown projection area, and tree diameter. By applying various indices that revealed the emergent horizontal and vertical forest structure, we were able to show a strong mutual link between beech crown plasticity and forest heterogeneity. The crown plasticity enabled the trees to close small gaps, which resulted in a highly dynamic tree regeneration, which in turn led to a small-scale heterogeneous forest structure. We found that, over long periods, crown centroids of canopy trees taller than 20öm were more regularly distributed than stem foot points. Absolute crown displacements were greater than reported from beech stands in North-Germany and the Sudetes in the Czech Republic. This indicates a need to restrain the model crown growth in order to recognize tree architecture and stability. We could simulate an increasing forest structural heterogeneity. Starting with a structural homogeneous layer of tree saplings, we showed that forest structures similar to those in unmanaged beech forests took several tree generations or approximately 700 time steps to emerge. We recommend enhancing this model approach with spatial explicit modeling of the leaf-area distribution, which has already been done for single beech trees.

Verification of a One-Dimensional Model of $$\hbox {CO}_{2}$$ CO 2 Atmospheric Transport Inside and Above a Forest Canopy Using Observations at the Norunda Research Station

A model of (Formula presented.) atmospheric transport in vegetated canopies is tested against measurements of the flow, as well as (Formula presented.) concentrations at the Norunda research station located inside a mixed pine–spruce forest. We present the results of simulations of wind-speed profiles and (Formula presented.) concentrations inside and above the forest canopy with a one-dimensional model of profiles of the turbulent diffusion coefficient above the canopy accounting for the influence of the roughness sub-layer on turbulent mixing according to Harman and Finnigan (Boundary-Layer Meteorol 129:323–351, 2008; hereafter HF08). Different modelling approaches are used to define the turbulent exchange coefficients for momentum and concentration inside the canopy: (1) the modified HF08 theory—numerical solution of the momentum and concentration equations with a non-constant distribution of leaf area per unit volume; (2) empirical parametrization of the turbulent diffusion coefficient using empirical data concerning the vertical profiles of the Lagrangian time scale and root-mean-square deviation of the vertical velocity component. For neutral, daytime conditions, the second-order turbulence model is also used. The flexibility of the empirical model enables the best fit of the simulated (Formula presented.) concentrations inside the canopy to the observations, with the results of simulations for daytime conditions inside the canopy layer only successful provided the respiration fluxes are properly considered. The application of the developed model for radiocarbon atmospheric transport released in the form of (Formula presented.) is presented and discussed. (Less)

Semi-direct tree reconstruction using terrestrial LiDAR point cloud data

A new method was developed for reconstructing the geometric structure of large plants such as trees at the leaf-scale by utilizing terrestrial LiDAR data. The primary goal of the work was to develop a feasible means for accurately and rapidly reconstructing or “digitizing” entire trees in order to specify the position, orientation, and size of every leaf in digital tree models that provide geometric inputs for high-resolution biophysical models or analyses. As with any optical measurement technique, a primary challenge is accurately accounting for plant matter that is occluded from view of the sensor. The present method is termed “semi-direct” because it uses a triangulation procedure to approximately directly reconstruct as many leaves as possible that are in view of the scanner. For plant matter obstructed from view, a statistical backfilling procedure was used to add additional leaves such that the three-dimensional distribution of leaf area and orientation of the reconstructed plant matched that of the actual plant on average. In a best case scenario such as when leaf density is low, nearly all leaf area is directly reconstructed from the scan and the branch and clumping structure is preserved within the reconstruction. In the worst case scenario such as when the leaf density is very high and nearly all leaves are occluded from view of the scanner, only a small fraction of leaves can be directly reconstructed, but at a minimum the distribution of leaf area and the leaf angle distribution across the reconstructed plant will be consistent with that of the actual plant. Unlike many other approaches, the present method does not rely on the woody matter of the plant to provide a skeleton for reconstruction, and can be used in dense plants where little woody matter is visible from the scanner.

A three-dimensional model of solar radiation transfer in a non-uniform plant canopy

A three-dimensional (3D) model of solar radiation transfer in a non-uniform plant canopy was developed. It is based on radiative transfer equations and a so-called turbid medium assumption. The model takes into account the multiple scattering contributions of plant elements in radiation fluxes. These enable more accurate descriptions of plant canopy reflectance and transmission in different spectral bands. The model was applied to assess the effects of plant canopy heterogeneity on solar radiation transmission and to quantify the difference in a radiation transfer between photosynthetically active radiation PAR (=0.39-0.72 μm) and near infrared solar radiation NIR (Δλ = 0.72-3.00 μm). Comparisons of the radiative transfer fluxes simulated by the 3D model within a plant canopy consisted of sparsely planted fruit trees (plant area index, PAI - 0.96 m2 m-2) with radiation fluxes simulated by a one-dimensional (1D) approach, assumed horizontal homogeneity of plant and leaf area distributions, showed that, for sunny weather conditions with a high solar elevation angle, an application of a simplified 1D approach can result in an underestimation of transmitted solar radiation by about 22% for PAR, and by about 26% for NIR.

Multi-temporal fine-scale modelling of Larix decidua forest plots using terrestrial LiDAR and hemispherical photographs

Fine-scale architectural tree models serve as an effective representation of three-dimensional plant material distributions. They can help to quantify wood volume and biomass, to estimate leaf area distributions on a detailed scale, and can be exploited for physically based modelling approaches. If architectural tree models can be derived for multiple acquisition dates, they permit the detailed investigation of phenological effects. Although promising approaches for the generation of architectural tree/forest models from terrestrial LiDAR data are available, they are often non-trivial and their application to forest plots is often difficult. This is restricting the flexibility of these reconstruction approaches especially for multi-temporal analyses. In this paper, forest models of two Larix decidua forest plots are reconstructed by making use of terrestrial LiDAR data and digital hemispherical photographs (DHP). Recent modelling strategies are enhanced and developed further in order to improve the robustness and usability of the architectural tree model reconstruction process.Raw point cloud data are directly used as input to solve both tree delineation and tree reconstruction in a single processing pipeline. This includes terrain filtering, intensity filtering, and trunk extraction. These steps are followed by a hierarchical and iterative multi-tree branch and twig reconstruction. Based on multi-temporal DHPs, various foliage states are documented. These DHPs and the reconstructed branching architectures are used to flexibly generate and update multi-temporal 3D models of foliage. In order to quantify the modelling performance with respect to various forest characteristics, a test setup based on simulated forest and acquisition geometries is build up. It can be shown, that typical sources of error in the tree reconstruction process are minimized by the proposed approach. It is possible to estimate wood volume distributions, trunk tapering and leaf area distributions with an error of only 10–14%. Except for strongly overlapping tree crowns, the overall accuracy of the single tree delineation in interlinked tree crowns is higher than 80%. Considering these error margins, we apply the modelling strategy to two forest plots and derive architectural models for three dates during the growing season. Using DHPs as reference data, it can be shown, that the estimated gap fraction values derived from the generated models show an error of only 10–15%.

Rapid, high-resolution measurement of leaf area and leaf orientation using terrestrial LiDAR scanning data

The rapid evolution of high performance computing technology has allowed for the development of extremely detailed models of the urban and natural environment. Although models can now represent sub-meter-scale variability in environmental geometry, model users are often unable to specify the geometry of real domains at this scale given available measurements. An emerging technology in this field has been the use of terrestrial LiDAR scanning data to rapidly measure the three-dimensional geometry of trees, such as the distribution of leaf area. However, current LiDAR methods suffer from the limitation that they require detailed knowledge of leaf orientation in order to translate projected leaf area into actual leaf area. Common methods for measuring leaf orientation are often tedious or inaccurate, which places constraints on the LiDAR measurement technique. This work presents a new method to simultaneously measure leaf orientation and leaf area within an arbitrarily defined volume using terrestrial LiDAR data. The novelty of the method lies in the direct measurement of the fraction of projected leaf area G from the LiDAR data which is required to relate projected leaf area to total leaf area, and in the new way in which radiation transfer theory is used to calculate leaf area from the LiDAR data. The method was validated by comparing LiDAR-measured leaf area to (1) ‘synthetic’ or computer-generated LiDAR data where the exact area was known, and (2) direct measurements of leaf area in the field using destructive sampling. Overall, agreement between the LiDAR and reference measurements was very good, showing a normalized root-mean-squared-error of about 15% for the synthetic tests, and 13% in the field.

Elevated CO2 alters distribution of nodal leaf area and enhances nitrogen uptake contributing to yield increase of soybean cultivars grown in Mollisols.

Understanding how elevated CO2 affects dynamics of nodal leaf growth and N assimilation is crucial for the construction of high-yielding canopy via breeding and N management to cope with the future climate change. Two soybean cultivars were grown in two Mollisols differing in soil organic carbon (SOC), and exposed to ambient CO2 (380 ppm) or elevated CO2 (580 ppm) throughout the growth stages. Elevated CO2 induced 4–5 more nodes, and nearly doubled the number of branches. Leaf area duration at the upper nodes from R5 to R6 was 4.3-fold greater and that on branches 2.4-fold higher under elevated CO2 than ambient CO2, irrespective of cultivar and soil type. As a result, elevated CO2 markedly increased the number of pods and seeds at these corresponding positions. The yield response to elevated CO2 varied between the cultivars but not soils. The cultivar-specific response was likely attributed to N content per unit leaf area, the capacity of C sink in seeds and N assimilation. Elevated CO2 did not change protein concentration in seeds of either cultivar. These results indicate that elevated CO2 increases leaf area towards the upper nodes and branches which in turn contributes yield increase.

Influence of a Young Pinus radiata Canopy on Aerial Spray Drift

Abstract. An experiment was undertaken to test the hypothesis that AGDISP, a mechanistic model that simulates the landing position of droplets aerially released for pesticide application, overestimates downwind airborne spray concentrations by not accounting for the turbulence generated within the canopy sublayer. AGDISP is used by pesticide regulators in many parts of the world to quantify exposure from aerial pesticide spraying as part of an assessment of risks to public health and the environment. Using a novel design, airborne spray drift was measured in a 3.2 m high radiata pine plantation, 65 m downwind from the aerial spray flight line, using a small circular sampling array. The spray sampling array consisted of a central 10 m high mast plus a set of 16 secondary masts distributed evenly around a circle with a radius of 5 m from the central mast. All spray applications were made with a Bell Jet Ranger using a spray mix of water plus a fluorescent tracer and a droplet spectrum with a volume median diameter of 101 µm. A single treatment comprised six passes along the flight line, and there were 28 replications. Airborne spray was sampled with both rotorods and artificial foliage placed at four heights on the central mast, ranging from approximately half canopy height to 3 times canopy height. The secondary towers sampled airborne spray using the same collectors placed at just above canopy height and at half canopy height. Other measurements included leaf area distribution, prevailing meteorological conditions, and turbulence using sonic anemometers. Backscatter LiDAR was used in an attempt to quantify the height and density of the spray cloud in the vicinity of the central mast. Rotorod and artificial foliage deposition values were highly correlated, giving confidence in the sampling approach. Neither wind speed nor release height had a significant effect on airborne spray flux in the 0 to 10 m zone, but results were complicated by a spurious negative correlation between wind speed and spray release height. The lack of dependence of deposition on wind speed in this experiment is surprising but is explained both by the variance in the data as well as the physics of small droplet movement in the atmosphere. At the individual sample level, measurements of airborne spray using either rotorods or artificial foliage were poorly correlated with AGDISP predictions. However, when data were averaged across replications, there was a very strong correlation between measurements and AGDISP data, even though in absolute terms, and as hypothesized, AGDISP significantly overpredicted the quantity of airborne spray. As indicated from a comparison with measured deposition, the backscatter LiDAR appeared effective in describing the spray cloud profile, and it suggested a total spray cloud profile that was more complex than the AGDISP model prediction. Keywords: Aerial application, AGDISP, Canopy deposition, Pesticides, Spray drift.

A mechanical study on the mitigation of lodging in edible canna

Because edible canna is approximately 3-m tall in its latter growth stage, strong winds such as by typhoons can induce plant lodging and cause severe damage to it. To improve our previous estimations that the 1-m dwarfing of a plant mitigated 10–20% by strong wind (external force) and 50% by own weight (internal force), respectively, we re-examined these parameters in relation to rhizome yield for field-grown plants. From early middle growth stage (July–August) of edible canna, the perpendicularly projected area of above-ground biomass increased rapidly due to rapid shoot elongation. After the middle growth stage (September), the stock base radius increased and shoot inclination angle decreased until the latter growth stage (November) gradually, indicating a disturbed architecture and easy lodging. Throughout the growth period, we observed no radial, directional difference in the leaf area distribution. Increase in the distance between the ground surface and the center of gravity of shoot weight and decrease in the shoot inclination increased the components of the internal force. The easiness to fall down (percentage own-weight invasion moment) of plant became maximal in the latter growth stage. We conclude that approximately 50-cm dwarfing of the plant with minimal loss of rhizome yield (as low as approximately 20%) and the maintenance of lodging tolerance is optimal. In such a situation, both external and internal forces are mitigated by approximately 30%.

Phenotypic plasticity to altered apical bud temperature in Cucumis sativus: more leaves‐smaller leaves and vice versa

Many studies investigated temperature effects on leaf initiation and expansion by relating these processes to air temperature or the temperature of a specific organ (e.g. leaf temperature). In reality plant temperature is hardly ever equal to air temperature or spatially uniform. Apical bud temperature (Tbud ), for example, may greatly differ from the temperature of the rest of the plant (Tplant ) dependent on the environment. Recent research in Cucumis sativus showed that Tbud influences leaf initiation independent of Tplant . These findings trigger the question if such spatial temperature differences also influence leaf expansion and plant phenotype. In a 28 day study, we maintained temperature differences between Tbud and Tplant ranging from -7 to +8 °C using a custom-made bud temperature control system. Leaf expansion did not only depend on leaf temperature but also on the difference between bud and leaf temperature. Differences between Tbud and Tplant considerably influenced vertical leaf area distribution over the shoot: increasing Tbud beyond Tplant resulted in more and smaller leaves, while decreasing Tbud below Tplant resulted in less and larger leaves. The trade-off between leaf number and leaf area resulted in phenotypic alterations that cannot be predicted, for example, by crop models, when assuming plant temperature uniformity.