Contrasting plant height can improve the control of rain-borne diseases in wheat cultivar mixture: modelling splash dispersal in 3-D canopies

Contrasting plant height can improve the control of rain-borne diseases in wheat cultivar... Abstract Background and Aims Growing cultivars differing by their disease resistance level together (cultivar mixtures) can reduce the propagation of diseases. Although architectural characteristics of cultivars are little considered in mixture design, they could have an effect on disease, in particular through spore dispersal by rain splash, which occurs over short distances. The objective of this work was to assess the impact of plant height of wheat cultivars in mixtures on splash dispersal of Zymoseptoria tritici, which causes septoria tritici leaf blotch. Methods We used a modelling approach involving an explicit description of canopy architecture and splash dispersal processes. The dispersal model computed raindrop interception by a virtual canopy as well as the production, transport and interception of splash droplets carrying inoculum. We designed 3-D virtual canopies composed of susceptible and resistant plants, according to field measurements at the flowering stage. In numerical experiments, we tested different heights of virtual cultivars making up binary mixtures to assess the influence of this architectural trait on dispersal patterns of spore-carrying droplets. Key Results Inoculum interception decreased exponentially with the height relative to the main inoculum source (lower diseased leaves of susceptible plants), and little inoculum was intercepted further than 40 cm above the inoculum source. Consequently, tall plants intercepted less inoculum than smaller ones. Plants with twice the standard height intercepted 33 % less inoculum than standard height plants. In cases when the height of suscpeptible plants was doubled, inoculum interception by resistant leaves was 40 % higher. This physical barrier to spore-carrying droplet trajectories reduced inoculum interception by tall susceptible plants and was modulated by plant height differences between cultivars of a binary mixture. Conclusions These results suggest that mixture effects on spore dispersal could be modulated by an adequate choice of architectural characteristics of cultivars. In particular, even small differences in plant height could reduce spore dispersal. Canopy architecture, plant height, splash dispersal, 3-D modelling, septoria tritici leaf blotch, wheat, cultivar mixtures, Triticum aestivum, Zymoseptoria tritici INTRODUCTION Plant diseases are a major threat to agricultural production, especially in a context of climatic uncertainty (Lamichhane et al., 2015; Savary et al., 2017). Disease management is mainly provided by the use of resistant cultivars and pesticides. However, some pathogens have high adaptive capacities. They can overcome cultivar resistance relatively quickly (de Vallavieille-Pope et al., 2012) and develop resistance to pesticides (Leroux and Walker, 2011). This is the case, for example, for Zymoseptoria tritici (Orton et al., 2011), which causes septoria tritici blotch (STB), a highly damaging wheat disease (Fones and Gurr, 2015) dispersed by rain splash (Huber et al., 2006) during its epidemic phase. In addition, in the case of STB, cultivar resistance is mostly partial (Brown et al., 2015). Cropping systems in industrialized countries have tended towards growing standardization in order to simplify crop management and improve yield. However, this standardization also led to a selective pressure on pathogens and a dependence to a large extent on farm inputs, including fungicides. Introducing diversity in cropping systems, for example using intercropping, can make it possible to improve the stability of production and to contribute to disease management (Boudreau, 2013) in a context of reduction or absence of fungicide use. Cultivar mixtures consist of growing different cultivars together in the same field. This cultural practice can provide a reduction of disease propagation if mixtures are adequately designed, in particular if chosen cultivars have contrasting levels of resistance to the targeted disease (Finckh and Wolfe, 2006; Gigot et al., 2014). Moreover, it makes it possible to grow cultivars having interesting qualities (e.g. grain quality, resistance to another disease) that are sometimes neglected because of their susceptibility to an important disease. In a cultivar mixture, major mechanisms involved in disease reduction are related to spore dispersal. Distance between susceptible plants is larger than in pure stands, thus reducing spore transfer from one susceptible plant to the other (density effect), particularly in the case of spore transfer by rain splash which occurs over short distances, typically a median distance of <1 m (Macdonald and McCartney, 1987). On the other hand, spores are intercepted by resistant plants which are not or little affected by disease, and part of the inoculum is therefore prevented from reaching susceptible plants (barrier effect). The reduction of disease propagation in cultivar mixture can be optimized by using an adequate proportion of resistant and susceptible cultivars within the mixture (Jeger et al., 1981; Garrett and Mundt, 1999; Xu and Ridout, 2000; Cox et al., 2004; Dai et al., 2012; Gigot et al., 2014). For example, Gigot et al. (2013) obtained reductions of STB severity up to 42 % in wheat cultivar mixtures containing 75 % of partially resistant plants and 25 % of susceptible plants. Cultivar mixtures used in mechanized agricultural systems are usually composed of cultivars with similar architecture (Wolfe, 1985), and cultivar architecture is seldom considered in the process of mixture design. However, canopy architecture has an impact on spore dispersal (Calonnec et al., 2008). This is particularly striking in the case of rain splash dispersal, which occurs over short distances. For example, experiments under controlled conditions have shown a relationship between canopy density and gradient shape (Yang et al., 1991; Madden and Boudreau, 1997; Schoeny et al., 2008). Moreover, plant height has been shown to be related to STB severity (Bahat, 1980; Arraiano et al., 2009). Taking advantage of intraspecific diversity in terms of plant architecture could be a way to enhance the reduction of disease propagation in cultivar mixtures. For example, growing together cultivars of contrasting height has provided disease reductions in the field (Jackson and Wennig, 1997; Zhu et al., 2005; Li et al., 2012; Vidal et al., 2017a). In the field, it is difficult to assess the direct impact of plant architecture on dispersal and to distinguish it from other mechanisms that have an impact on disease. Modelling approaches have been proved to be useful to investigate the impact of architecture on disease propagation in pure stands (Calonnec et al., 2008; Robert et al., 2008). The objective of this work was to assess the impact of plant architecture of wheat cultivars in mixtures on rain splash dispersal of Z. tritici. In order to investigate this question, we used a modelling approach involving an explicit description of canopy architecture and spatial spore dispersal processes. We simulated spore dispersal events occurring in mixtures of two cultivars, at the flowering stage. We tested different heights for virtual plants of the two cultivars comprising the mixtures in order to assess the impact of two factors on spore dispersal patterns within cultivar mixtures: canopy height and the difference in cultivar height. MODELLING APPROACH Splash dispersal events were simulated in wheat cultivar mixtures at the flowering stage. In the case of wheat, flowering is a critical stage in the epidemic as (1) disease keeps propagating upwards while the height of leaves remains fixed; and (2) no more healthy tissues are formed and global disease severity at the plant level increases. At this stage, plant organs have been fully developed and have reached their final location within the canopy, and top leaves, which have a critical importance in yield formation (Thomas et al., 1989), begin to be affected by disease progression. At this stage, the impact of cultivar mixture on disease propagation becomes visible (Gigot et al., 2013). Mixture design could have an impact on both canopy architecture and epidemic before flowering. We therefore based our case study on field measurements of architecture and disease measurements performed at the flowering stage, representing a snapshot of canopy architecture and location of inoculum sources at this critical stage. In order to study the impact of plant height of cultivars making up a binary mixture on splash dispersal, we simulated splash dispersal events in canopies including virtual plants with different insertion heights of leaves of each of the two cultivars: from the plant height that was observed in the field (typical wheat plant height, around 80 cm) to twice this height. Here we focused on individual dispersal events and not on the whole epidemic, in order to better understand mechanisms related to canopy architecture. Other studies have investigated the effect of cultivar mixtures on epidemics, and shown that mixture effects can be amplified by successive dispersal cycles (Gigot et al., 2014). Splash dispersal within the canopy In several dispersal models, canopy architecture is taken into account through integrated parameters such as porosity of crop density, thus considering plant canopy as a homogeneous medium. In the case of STB, vertical heterogeneity is an important point as spores travel from sporulating lesions, usually located on lower leaves, to younger and higher healthy leaves (Suffert and Sache, 2011; Suffert et al., 2011). Vertical heterogeneity of canopy structure has been considered previously in spore dispersal and disease modelling (Pielaat et al., 2002; Robert et al., 2008; Garin et al., 2014). In the case of a cultivar mixture, horizontal heterogeneity is also important as disease reduction mechanisms rely on the proximity of resistant and susceptible plants grown side by side. This type of heterogeneity, i.e. within-field spatial pattern, has already been considered previously, including in cultivar mixture models (Sapoukhina et al., 2010; Gigot et al., 2014). However, 3-D canopy heterogeneity is rarely considered in dispersal models. We used a model proposed by Saint-Jean et al. (2004) that explicitly describes splash dispersal processes in a 3-D canopy structure. The model was implemented in C++. Described mechanisms included (1) interception of incoming raindrops; (2) production of splash droplets; (3) droplet transport within the canopy; and (4) interception of splash droplets by elements of the canopy. The model used a Monte Carlo integration method (Binder and Heermann, 1992; Lafortune, 1996), involving sampling of incoming raindrop properties, sampling of splash droplet characteristics and computation of ballistic droplet trajectories. The model computed integrated variables describing dispersal indicators that were distributed throughout the canopy. Simulation of rain events was performed using 107 samples in the rain drop distribution for each rain event in order to reach standard errors <2 %. Raindrop diameters were distributed uniformly and ranged from 0.53 to 4.00 mm, corresponding to diameters commonly found in natural rains (Ulbrich, 1983). Rainfall is modelled here as a flux of raindrops and, because distribution was chosen as uniform, the rain intensity and its variation over time were not taken into account. Properties of splash droplets including Weibull distribution of diameters, and velocity as well as distribution of ejection angles were sampled as in Saint-Jean et al. (2004) based on experimental results obtained by Yang et al. (1991). In order to avoid border effects and to approach open field conditions, periodic boundary conditions were applied to mimic infinite canopy. Droplets that reached a virtual plot border were relocated on the opposite side, as explained in Gigot et al. (2014). A module was implemented in order to account for incorporation of inoculum produced by sporulating lesions in splash droplets. When a raindrop was intercepted by a diseased leaf element, the proportion of droplets carrying spores was equal to the proportion of sporulating lesion area of the leaf. For example, half the droplets generated by a splash event on a leaf with 50 % of sporulating area carried spores. Canopy structure and inoculum location at the flowering stage Architectural models can provide a realistic representation of canopy structure (Godin, 2000). These models can be used to compute physical variables such as interception of rain (Bussière et al., 2002), spray (Dorr et al., 2014) or light (Chelle and Andrieu, 2007). They have been used to investigate properties of complex canopies as in the case of pea–wheat intercropping (Barillot et al., 2012). Virtual 3-D canopies were designed based on field data collected at the flowering stage during a field experiment conducted at the INRA experimental station in Grignon (France) in 2016 (Vidal et al., 2017a). A mixture was constituted with two standard height cultivars, including 25 % of susceptible plants (‘Sogood’) and 75 % of partially resistant plants (‘Maxwell’). This proportion corresponds to a mixture design that provided STB reductions under field conditions (Gigot et al., 2013). At the flowering stage, leaf and internode dimensions, as well as leaf curvature were measured on 30 main stems per cultivar grown in a pure stand. Leaf and internode dimensions were also measured on 15 main stems per cultivar in mixtures. The density of tillers with ears was recorded in 3 sections of rows of 1 m length each, in each treatment. Tiller density was of 475 tillers m–2 in the cultivar mixture. Susceptible plants accounted for 33 % of ears in the mixture. The proportion of sporulating area was measured at leaf level in each treatment, on 18 main stems of each cultivar in mixtures. At the flowering stage, average disease severity was 1.7 % (s.e. 0.9) on leaf 4 (from the top) and 17.3 % (s.e. 5.0) on leaf 5 for the resistant plants, and 8.9 % (s.e. 3.0) on leaf 4 and 51.6 % (s.e. 6.8) on leaf 5 for the susceptible plants. Main stems were reconstructed using Adel-Wheat (Fournier et al., 2003) to combine metamer dimension and leaf curvature. Each stem had the dimensions of one of the plants measured in the field. Leaf curvature was sampled from a database of measured curvatures, for each cultivar and leaf layer. Leaf azimuth was attributed automatically in Adel-Wheat. Main stems were then assembled to constitute canopies according to the measured tiller density of each cultivar in each mixture. Plants were organized in rows and plant order was sampled to simulate a random arrangement of the two cultivars. Virtual canopies had a ground area of 1 m2. Plants were described under the form of cylinders (stems and ears), triangles and quadrilaterals (leaves). A proportion of sporulating area was attributed to each leaf element. For each virtual stem, a severity profile (proportion of sporulating area on each leaf of the stem) was sampled from profiles measured on field stems, depending on cultivar. For a determined treatment, replicates were generated by modifying the seed used for random sampling in the process of canopy design. We assessed the impact of the variability of the input canopy on simulation results. The different stochastic aspects involved in canopy design were assessed: variability profiles in leaf area, leaf curvature and severity profiles as well as the organization of cultivars within the mixture. In order to quantify these aspects, we ran simulations for four canopies (four different sampling patterns) for each of four chosen treatments. Numerical experiments In order to study the impact of plant height of cultivars in a two-component mixture, leaf insertion heights of plants comprising a mixture were modified in each type of mixture. Changes in plant height involved only differences in leaf insertion height. All tested canopies had a constant leaf area index (LAI) of 4.7 m2 of leaves per m2 of ground. Leaf dimensions and curvature remained unchanged; sporulating area remained on leaves but their height was modified according to leaf insertion height. Relative height was defined as a proportion of plant height of the reference canopy. Four cases were tested: (1) a susceptible and a resistant cultivar, both with short plant height; (2) a tall susceptible cultivar with a shorter resistant cultivar; (3) a short susceptible cultivar with a taller resistant cultivar; and (4) increased height of both cultivars. Short height corresponded to the typical height of a wheat plant (around 80 cm) while tall plant height corresponded to double the standard height, which is representative of the cultivated diversity available for plant height within wheat cultivars (some landrace wheat cultivars reach 160 cm in height). The vertical distribution of leaf area differed greatly depending on the size of plants comprising the mixtures (Fig. 1). Plant height affected the position of the inoculum sources, mainly constituted of lower diseased leaves of susceptible plants. Sporulating lesions were present only on leaves 4 and 5. In the case of short plants, these leaves were located mostly at a height up to 30 cm above the ground, while they reached 55 cm in the case of the tall susceptible cultivar. Canopies with contrasting plant height were made up of two layers of leaves: one lower layer to which the short cultivar was confined and one upper layer occupied exclusively by leaves of the tall cultivar. The layers are constituted of resistant and susceptible leaves. Fig. 1. View largeDownload slide Vertical distribution of leaf area (m2 m–2 of ground) as a function of height within virtual 3-D canopies, in mixtures of two cultivars with contrasting canopy structure. Healthy leaves correspond to leaves 1–3 (from the top, leaf 1 is the highest leaf or flag leaf). Diseased leaves correspond to leaves 4 and 5 that had sporulating lesions. Virtual 3-D canopies were designed by combining measurements of leaf curvature and organ dimensions obtained from a field experiment. The s.e. error of the vertical distribution of leaf area ranged from 1.23 × 10–3 to 1.67 × 10–10 (m2 m–2 of ground). Fig. 1. View largeDownload slide Vertical distribution of leaf area (m2 m–2 of ground) as a function of height within virtual 3-D canopies, in mixtures of two cultivars with contrasting canopy structure. Healthy leaves correspond to leaves 1–3 (from the top, leaf 1 is the highest leaf or flag leaf). Diseased leaves correspond to leaves 4 and 5 that had sporulating lesions. Virtual 3-D canopies were designed by combining measurements of leaf curvature and organ dimensions obtained from a field experiment. The s.e. error of the vertical distribution of leaf area ranged from 1.23 × 10–3 to 1.67 × 10–10 (m2 m–2 of ground). RESULTS Detailed characteristics of four contrasting cases We first present here the detailed characteristics of four canopies with contrasting structures, representing the diversity of explored canopy structure, i.e. (1) plants with similar size either short (reference case, relative height = 1) or tall (relative height = 2) and (2) plants with contrasting size with either the resistant or the susceptible cultivar having twice the height of the other cultivar of the mixture. For these key cases, four replicate canopies were generated for each treatment. Standard errors on intercepted drops ranged from 0.08 to 0.66 % of total raindrops per m2 of leaf. For intercepted spore-carrying droplets, the standard errors ranged from 0 to 1.3 per 100 raindrops and per m2 of leaf. Variability of intercepted spore-carrying droplets was related to (1) the arrangement of plants within the canopy and (2) the sampling of severity profiles. Fixing severity to its mean value for each leaf level and sampling four replicates of plant arrangements led to standard errors of at most 1.03 per 100 raindrops and per m2 of leaf. On the other hand, four replicate samplings of severity profiles for the same plant arrangement led to standard errors of at most 0.97 spore-carrying droplets per 100 raindrops and per m2 of leaf. When susceptible plants were taller than the resistant plants, they intercepted many more raindrops than when they were shorter than resistant plants (Fig. 2A). Indeed, when plants of different heights were present in the mixtures, many leaves of the tallest plants were located above those of the short plants, thus providing a shelter from the rain. Fewer raindrops were intercepted by lower diseased leaves of susceptible plants, thus limiting the amount of splash droplets carrying spores being formed in this type of canopy. This is consistent with the small number of spore-carrying droplets intercepted by lower leaves in this case (Fig. 2B). However, more spore-carrying droplets were intercepted by upper leaves when short susceptible plants were grown with tall resistant plants. Short susceptible plants were located at the bottom of the canopy with very few resistant leaves. Thus, the barrier effect was low and most spore-carrying droplets were intercepted by susceptible plants. Mixture design including tall susceptible plants led to lower interception of spore-carrying droplets by upper leaves of susceptible plants. Indeed, top leaves of susceptible plants were far from the source of inoculum and resistant leaves provided a barrier effect. Fig. 2. View largeDownload slide Dispersal patterns simulated in virtual 3-D canopies in cultivar mixtures with contrasting canopy structure. Drop interception (A) was expressed as a proportion of total raindrops per m2 of leaves. Inoculum interception (B) was expressed as the number of spore-carrying droplets per incoming raindrop and per m2 of leaves. Diseased leaves of susceptible plants constituted most of the inoculum source and corresponded to lower leaves (leaf 4 and 5). Error bars correspond to the s.e. obtained with four simulations for each treatment. Fig. 2. View largeDownload slide Dispersal patterns simulated in virtual 3-D canopies in cultivar mixtures with contrasting canopy structure. Drop interception (A) was expressed as a proportion of total raindrops per m2 of leaves. Inoculum interception (B) was expressed as the number of spore-carrying droplets per incoming raindrop and per m2 of leaves. Diseased leaves of susceptible plants constituted most of the inoculum source and corresponded to lower leaves (leaf 4 and 5). Error bars correspond to the s.e. obtained with four simulations for each treatment. Changes in virtual canopy height in the cultivar mixture had no impact on the distribution of incident raindrops between cultivars. The number of raindrops intercepted on diseased leaves of the susceptible cultivar did not change with canopy height because the LAI above diseased leaves remained constant (results not shown). The number of spore-carrying droplets intercepted by both cultivars decreased similarly with canopy height, from 1.5 spore-carrying droplets per 100 raindrops and per m2 of leaves for standard height to 1.0 spore-carrying droplets when the height was doubled considering resistant plants, and from 1.2 to 0.8 spore-carrying droplets considering susceptible plants (Fig. 3). This was related to a larger distance between leaves, in particular between diseased leaves and top leaves, when canopy height was large (height effect). Fig. 3. View largeDownload slide Simulated inoculum interception by resistant and susceptible virtual plants in a cultivar mixture as a function of relative canopy height. Each point corresponds to one simulation with a determined canopy height. The reference was a homogeneous cultivar mixture at the flowering stage, including a susceptible and a resistant cultivar, both of standard plant height (approx. 80 cm, relative height = 1). Canopy height is expressed as a proportion of the reference canopy height. Fig. 3. View largeDownload slide Simulated inoculum interception by resistant and susceptible virtual plants in a cultivar mixture as a function of relative canopy height. Each point corresponds to one simulation with a determined canopy height. The reference was a homogeneous cultivar mixture at the flowering stage, including a susceptible and a resistant cultivar, both of standard plant height (approx. 80 cm, relative height = 1). Canopy height is expressed as a proportion of the reference canopy height. Increasing the height of the resistant plants decreased the number of raindrops intercepted by susceptible leaves (Fig. 4A). Leaves from tall resistant plants were located above susceptible leaves and intercepted incoming raindrops before the latter, thus providing a rain shelter (called here the ‘umbrella effect’). The LAI located above susceptible lower leaves changed from 2.42 for standard height to 3.73 for doubled resistant plant height. However, this had little impact on the number of raindrops intercepted by diseased leaves of susceptible plants which were located at the bottom of the canopy. Bottom leaves thus intercepted a small number of raindrops (from 1.4 to 1.1 % of total incoming raindrops), as a high leaf area of the canopy was located above these leaves, independently of resistant plant height. Raindrop interception by the resistant cultivar increased slightly with resistant plant height, from 55 % (standard height) to 65 % (doubling of standard height) of incoming raindrops. Resistant leaves accounted for 71 % of the leaf area of the mixture and intercepted many raindrops independently of their height. The number of new raindrops intercepted due to taller resistant plant height was therefore relatively small in proportion. Fig. 4. View largeDownload slide Simulated raindrop and inoculum interception by resistant and susceptible virtual plants in a cultivar mixture as a function of virtual plant height of each cultivar making up the mixture. Each point corresponds to one simulation with a determined height of virtual plants of one of the cultivars making up the mixture. The reference was a homogeneous cultivar mixture with a resistant and a susceptible cultivar, both of standard plant height (approx. 80 cm), at the flowering stage. Plant height is expressed as a proportion of the reference plant height. In (A) and (C), the size of the resistant cultivar varies, while the size of the susceptible cultivar is fixed with two different heights: reference height (solid line) or twice the reference height (dotted line). In (B) and (D), the size of the susceptible cultivar varies, while the size of the resistant cultivar is fixed with two different heights (solid line: reference height, dotted line: twice the reference height). Fig. 4. View largeDownload slide Simulated raindrop and inoculum interception by resistant and susceptible virtual plants in a cultivar mixture as a function of virtual plant height of each cultivar making up the mixture. Each point corresponds to one simulation with a determined height of virtual plants of one of the cultivars making up the mixture. The reference was a homogeneous cultivar mixture with a resistant and a susceptible cultivar, both of standard plant height (approx. 80 cm), at the flowering stage. Plant height is expressed as a proportion of the reference plant height. In (A) and (C), the size of the resistant cultivar varies, while the size of the susceptible cultivar is fixed with two different heights: reference height (solid line) or twice the reference height (dotted line). In (B) and (D), the size of the susceptible cultivar varies, while the size of the resistant cultivar is fixed with two different heights (solid line: reference height, dotted line: twice the reference height). Increasing the height of the susceptible cultivar strongly increased interception of raindrops by susceptible leaves, from 16 % (standard height) to 25 % (double standard height) of incoming raindrops (Fig. 4B). When susceptible plants were taller, their leaves were higher in the canopy and more exposed to incoming raindrops. The interception of raindrops by lower diseased leaves, which produced spore-carrying droplets, also increased, from 1.4 % for standard height to 2.6 % of total raindrops. Indeed, LAI above diseased susceptible leaves was reduced to 1.03 when susceptible plant height was doubled, compared with 2.42 for standard height. The interception of raindrops by resistant leaves decreased slightly, from 55 to 48 % of total raindrops. Susceptible plants accounted for a small proportion of 29 % of canopy leaf area in the mixture and therefore provided a small umbrella effect. Increasing the height of the resistant cultivar reduced inoculum interception by the resistant plants from 1.5 to 0.8 spore-carrying droplets of inoculum per raindrop and per m2 of leaves. This reduction was related to the increase of distance to the main inoculum source (lower leaves of susceptible plants) due to increased plant height and was called here the ‘height effect’. Simultaneously, inoculum interception by the susceptible cultivar increased from 1.2 to 1.6 spore-carrying droplets per raindrop and per m2 of leaves (Fig. 4C). When the resistant cultivar was taller, fewer resistant leaves were present at the height of short susceptible plants, representing a leaf area of 0.19 m2 m–2 with doubled plant height compared with 1.65 m2 m–2 for standard height. Interception of spores by resistant leaves, which provided protection of susceptible leaves (called the ‘barrier effect’), was thus reduced when resistant plant height increased, from 1.5 for normal plant height to 0.8 spore-carrying droplets of inoculum per raindrop and per m2 of leaves for doubled resistant plant height. Increasing the height of the susceptible cultivar decreased inoculum interception by the susceptible cultivar from 1.2 to 0.8 spore-carrying droplets per raindrop and per m2 of leaves, while increasing inoculum interception by the resistant cultivar from 1.5 to 2.1 spore-carrying droplets per raindrop and per m2 of leaves (Fig. 4D). This resulted from two main effects. First, the distance between leaves of the susceptible cultivar and the diseased leaves, which constituted the main source of inoculum, increased (height effect). Secondly, more resistant leaves were present at the same height as lower leaves of the susceptible cultivar when susceptible plants were taller, corresponding to an LAI of 2.37 when susceptible plant height was doubled compared with 1.65 m2 m–2 for standard height, thus providing an efficient barrier effect. With sporulating lesion areas located on lower leaves, the barrier effect was thus at a maximum with a tall susceptible cultivar and a short resistant cultivar. Effects of canopy structure on dispersal The number of raindrops intercepted by a determined leaf layer strongly depended on the amount of leaf area located above it (Fig. 5). By analogy with light interception and Beer–Lambert’s law (Sinoquet and Bonhomme, 1991), an exponential relationship fitted well to the simulation results. This implies that a difference of ‘LAI located above a determined leaf layer’ had more impact on raindrop interception by leaves located at the top of the canopy than on leaves located at the bottom of the canopy. According to the variance analysis, the highly significant relationship between intercepted raindrops and LAI distribution depended on leaf number and cultivar (P < 2.2 × 10−16), but not on the height of cultivars within the mixture (P = 1). The number of raindrops intercepted by lower leaves varied only slightly when the height of cultivars comprising the mixture was modified. Modifications in plant height mainly affected the distribution of leaf area above these leaves. However, raindrop interception by leaves 3 and upwards strongly varied depending on plant height within the mixture. The effect of LAI located above a determined leaf layer (umbrella effect) was thus higher for top leaves. The impact of the ‘umbrella effect’ on inoculum dispersal could therefore be higher if sporulating lesions were present on these leaves, which could occur later in the epidemic. Fig. 5. View largeDownload slide Simulated distribution of raindrop interception within cultivar mixture canopies as a function of vertical position of leaf levels within the canopy. Leaf area index (LAI) corresponds to leaf area per m2 of ground. This graph shows the percentage of total incoming raindrops intercepted per leaf area, by a determined leaf layer as a function of leaf area located above the leaf layer. Points correspond to simulations involving changes in cultivar height within each treatment but with unchanged LAI. Each point corresponds to one leaf layer of one cultivar in one simulation. Leaf 1 (L1) corresponds to the top leaf or flag leaf. The lines correspond to a fitted model. The dotted line corresponds to a fitted model: log(drops) = 14.0 − 0.5 × LAIa (R2 = 0.79), where ‘drops’ corresponds to the number of intercepted raindrops per leaf area and ‘LAIa’ the canopy LAI located above the concerned leaf layer. The solid line is an inverse function: 1/drops = 3.72 + 5.12 × LAIa (R2 = 0.92). Fig. 5. View largeDownload slide Simulated distribution of raindrop interception within cultivar mixture canopies as a function of vertical position of leaf levels within the canopy. Leaf area index (LAI) corresponds to leaf area per m2 of ground. This graph shows the percentage of total incoming raindrops intercepted per leaf area, by a determined leaf layer as a function of leaf area located above the leaf layer. Points correspond to simulations involving changes in cultivar height within each treatment but with unchanged LAI. Each point corresponds to one leaf layer of one cultivar in one simulation. Leaf 1 (L1) corresponds to the top leaf or flag leaf. The lines correspond to a fitted model. The dotted line corresponds to a fitted model: log(drops) = 14.0 − 0.5 × LAIa (R2 = 0.79), where ‘drops’ corresponds to the number of intercepted raindrops per leaf area and ‘LAIa’ the canopy LAI located above the concerned leaf layer. The solid line is an inverse function: 1/drops = 3.72 + 5.12 × LAIa (R2 = 0.92). The number of spore-carrying droplets intercepted by a determined leaf layer strongly depended on the distance between this leaf layer and the main source of inoculum (Fig. 6) constituted by lower diseased leaves of the susceptible cultivar. Considering a positive distance above the inoculum source, the amount of intercepted inoculum increased exponentially when the distance to the inoculum source decreased. This relationship depended on cultivar (P = 0.035) and on the height of the cultivars within the mixture (P = 0.0001) but not on leaf number (P = 0.24). This was consistent with the relationship between plant height and inoculum interception (height effect) mentioned previously (Figs 2–4). The number of spore-carrying droplets intercepted by leaves higher than 40 cm above the inoculum source was very small on the whole. This suggests that even small increases in plant height could have a non-negligible effect on the interception of spore-carrying droplets. Fig. 6. View largeDownload slide Simulated vertical distribution of inoculum interception within cultivar mixture canopies as a function of the distance to the main inoculum source. The graph shows the amount of inoculum intercepted per leaf area, by a determined leaf layer as a function of height difference with the main inoculum source (leaves 4 and 5 of the susceptible cultivar). Points correspond to simulations involving changes in cultivar height within mixtures with unchanged leaf area index. Each point corresponds to one leaf layer of one cultivar in one simulation. Leaf 1 (L1) corresponds to the top leaf or flag leaf. The curve corresponds to a model fitted for positive distances to the inoculum source: log(intCD) = 25.5 − 7.9 × (dInoc + 1.5) (R2 = 0.84) with ‘intCD’ the number of intercepted contaminated droplets per raindrop and per m2 of leaves and ‘dInoc’ the distance (height) to the inoculum source. Fig. 6. View largeDownload slide Simulated vertical distribution of inoculum interception within cultivar mixture canopies as a function of the distance to the main inoculum source. The graph shows the amount of inoculum intercepted per leaf area, by a determined leaf layer as a function of height difference with the main inoculum source (leaves 4 and 5 of the susceptible cultivar). Points correspond to simulations involving changes in cultivar height within mixtures with unchanged leaf area index. Each point corresponds to one leaf layer of one cultivar in one simulation. Leaf 1 (L1) corresponds to the top leaf or flag leaf. The curve corresponds to a model fitted for positive distances to the inoculum source: log(intCD) = 25.5 − 7.9 × (dInoc + 1.5) (R2 = 0.84) with ‘intCD’ the number of intercepted contaminated droplets per raindrop and per m2 of leaves and ‘dInoc’ the distance (height) to the inoculum source. DISCUSSION Three main effects were identified when varying plant height in a cultivar mixture: (1) leaves provided shelter from raindrops to leaves located below them (‘umbrella effect’); (2) interception of spore-carrying droplets decreased with plant height (‘height effect’); and (3) resistant leaves located close to diseased leaves of the susceptible cultivar (main source of inoculum) intercepted splash droplets carrying spores, which thus protected susceptible leaves (‘barrier effect’). These effects are discussed below. Umbrella effect The number of raindrops intercepted by a given leaf layer decreased exponentially with the increase of LAI above this leaf layer, i.e. the vertical position of leaves within the canopy (Fig. 5). This result was consistent with Calder’s work (1996), where the raindrop interception of the lower layer of a canopy was expressed as a decreasing exponential function of the projected leaf area of the upper layer. However, an inverse function fitted better (RMSE of 0.043) the decrease of intercepted raindrops with the increase of LAI compared with the exponential model (RMSE of 0.049). In mixtures of plants with similar height (Fig. 3), the distribution of raindrop interception was independent of canopy height (not shown). However, modifying the height of cultivars comprising a mixture independently led to a modification of raindrop interception patterns (Fig. 4A, B), related to a rearrangement of leaves and modifications of the vertical distribution of leaf area. On the whole, the ‘umbrella effect’ was relatively small considering diseased leaves that, for our simulations, were located in the lower part of the canopy. Indeed, the major impact of modification of the vertical distribution of leaf area was observed for leaves located higher in the canopy. The umbrella effect thus might be emphasized in the case when upper leaves (for example leaf 3) were affected by disease, which could occur later in the epidemic or in the case of a higher inoculum pressure. The impact of LAI distribution on raindrop distribution within the canopy, and therefore on umbrella effect, could be modulated by ground cover that is also related to other architectural traits of wheat plants (Abichou, 2016). For example, planophile leaves (close to a horizontal position) could lead to a higher ground cover compared with erectophile leaves (close to a vertical position), for a similar LAI. Differences in space foraging of cultivars, for example distance between tillers or tiller inclinations, could also have an impact on ground cover. Height effect Plant height determined the distance between the source of inoculum and upper leaves. A relationship between plant size and inoculum interception was observed in different simulations (Figs 3 and 4) and was confirmed when considering the whole set of simulations (Fig. 6). These simulation results are consistent with classical splash dispersal patterns (Shaw, 1987; Pietravalle et al., 2001; Pielaat et al., 2002). For a given inoculum and LAI conditions, a tall plant intercepted less inoculum than a short plant. This observation is consistent with the association of tall plant height with reduced STB severity observed by several authors (Bahat, 1980; Arraiano et al., 2009). Indeed, splash dispersal occurs over limited distances (Walklate et al., 1989), and splash droplets are not able to reach the highest leaves (a few spore-carrying droplets travelled further than 40 cm from the source). Rainfall was modelled here by using a uniform distribution of raindrop diameter. However, natural rainfalls follow more complex distributions such as lognormal distribution that could vary in time and be dependent on the rain intensity (Uijlenhoet and Stricker, 1999; Testud et al., 2001; Uijlenhoet et al., 2003). By using the assumption of a uniform distribution, we misestimated the proportion of the small raindrops, but the smallest drops do not contribute much to splash dispersal because of lower kinetic energy. On the other hand, uniform distribution overestimated larger raindrops and therefore emphasized splash dispersal to longer distances. Moreover, plant height also contributed to determining canopy density which has an impact on interception of splash droplets carrying spores (e.g. Yang and Madden, 1993; Madden and Boudreau, 1997; Schoeny et al., 2008). Resistant plants had a higher leaf area density when they were shorter, and thus intercepted more splash droplets and therefore more inoculum. In the case of cultivar mixtures, plant height thus contributed to the capacity of each cultivar to intercept inoculum. A short resistant cultivar thus provided a high barrier effect and a tall susceptible cultivar intercepted less inoculum. Barrier effect The barrier effect is often mentioned as an important effect leading to disease reduction in cultivar mixtures (Finckh and Wolfe, 2006; Vidal et al., 2017b). Our results suggest that the barrier effect can be modulated by canopy structure, and in particular by the vertical arrangement of resistant and susceptible leaves. The barrier effect occurred when resistant leaves were present at the same height as the source of inoculum, consisting here of the lower leaves of the susceptible cultivar. For example, there was very little barrier effect in mixtures including a tall resistant cultivar and a short susceptible cultivar, as few resistant leaves were located at the height of the inoculum on the susceptible cultivar (Fig. 4D). In contrast, the barrier effect was higher when susceptible and resistant plants were of similar height, and even higher when susceptible plants were taller than resistant plants (Figs 3 and 4D). In mixtures of cultivars with similar architecture, the barrier effect is often modulated through the proportion of resistant plants (Gigot et al., 2014). However, our results suggest that these effects could be amplified by differences in height between cultivars, in particular in the case of a taller susceptible cultivar (Fig. 4). These differences could lead to canopies composed of layers of different leaf area density with different proportions of resistant leaves. A mixture composed of a short resistant cultivar and a taller susceptible cultivar would thus lead to a dense lower layer containing many resistant leaves that could provide a high barrier effect. In contrast, the upper part of the canopy would be less dense and upper leaves would be protected both by the increased distance to the inoculum source (height effect) and by the presence of resistant leaves in the lower part of the canopy (barrier effect). Effects of the canopy architecture of cultivar mixtures on inoculum dispersal by rain splash The arrangement of resistant and susceptible plants and leaves within cultivar mixtures contributes to the reduction of disease propagation through effects on spore dispersal (Finckh and Wolfe, 2006). The barrier effect and density effect have been studied previously (Chin and Wolfe, 1984). These effects can be modulated through mixture design. In general, effects are larger when the mixture is homogeneous (e.g. chessboard design), while they tend to be lower when cultivars are arranged in different rows or blocks (Gigot et al., 2014). Here, we considered effects of plant architecture on rain splash dispersal that could have an impact on disease propagation within cultivar mixtures. We showed that the barrier effect could be modulated by the height of the cultivars making up the mixture. We described an effect of plant height that is important in the case of splash-dispersed diseases, due to short dispersal distances. This effect is similar to the ‘escape’ concept (Arraiano et al., 2009), excluding here the dynamic aspect of stem extension. Height effect could also be related to a vertical equivalent of the ‘density effect’ as it involves an increased distance between sporulating lesions (here confined to the lower leaves, mainly on susceptible plants) and healthy susceptible leaves (here mainly top leaves). Finally, we mentioned the possible importance of the vertical distribution of leaf area within the canopy (called here the umbrella effect), that could lead to a reduction of raindrop interception by diseased leaves, in later stages of the epidemic or in the case of more severe epidemics. Growing a tall susceptible cultivar together with a short resistant cultivar appears to be an interesting option. Besides effects on dispersal (Fig. 4) that were mentioned previously, this configuration could also be favourable in terms of microclimate. In this type of canopy structure, upper leaves would be in a low-density layer of the canopy, which could provide a dryer microclimate (related to increased air circulation), less favourable for pathogen development. This was observed in a field experiment when growing a tall susceptible and a short resistant rice cultivar together led to a reduced leaf moisture and reduced panicle blast disease severity on the susceptible cultivar (Zhu et al., 2005). In the case of STB, only partially resistant cultivars are available. An intense interception of spores by resistant leaves can thus result in new lesions on resistant plants. Canopy structure leading to a moderate interception of inoculum by resistant plants, such as in the case of taller homogeneous canopies, might also be of interest. Canopies with large differences in height between cultivars can be difficult to handle in mechanized agriculture, especially for harvest. However, our results suggest that effects on dispersal can be obtained even with limited differences in height (Fig. 4). Moreover, other architectural traits could have an impact on dispersal and would deserve further investigation (e.g. traits involving space foraging by plants such as leaf curvature, distance between axes, etc.). Finally, we considered here a single spore dispersal event in each canopy. In the case of polycyclic epidemics, several dispersal events occur and small protection effects can be amplified as the epidemic progresses. If we take into account the latent period of STB (from 270 to 500 °Cd; Lovell et al., 2004) and natural conditions occurring in the Paris area, the number of complete successive pathogen generations during a wheat post-heading period (roughly from late May to early June) is expected to be below ten. This means that, as shown by Gigot et al. (2014; Fig. 5) for the first successive generations, an increase of the protective effect is strongly expected to be observed under usual field conditions. CONCLUSION We described several mechanisms that have an impact on inoculum dispersal by rain splash and could favour the reduction of disease propagation in cultivar mixtures. Our results emphasized in particular the contribution of cultivar height contrast to mixture effects. Leaf area distribution within the canopy had an impact on raindrop interception patterns. The number of raindrops intercepted by a determined leaf layer depended on the amount of leaf area located above this leaf layer (umbrella effect). The barrier effect occurred when resistant leaves were present at the same height as the source of inoculum (here the lower leaves of the susceptible cultivar). Tall plants intercepted fewer spores than short plants due to the larger distance between lower leaves with sporulating lesions and upper leaves (height effect). The barrier effect was modulated by height distribution of cultivars in a mixture. The highest barrier effects were obtained by growing together a short resistant cultivar and a tall susceptible cultivar. In this case, upper leaves of the susceptible cultivar were also protected due to their larger distance from the inoculum source (height effect). These results suggest that considering cultivar architecture in mixture design could enhance mixture effects on foliar splash-dispersed diseases. ACKNOWLEDGEMENTS We thank the ABIES doctoral school for T.V.’s PhD grant and the Wheatamix project financed by the French National Research Agency (ANR-13-AGRO-0008, www6.inra.fr/wheatamix/) for financial support. We are grateful to Mariem Abichou, Bruno Andrieu, Romain Barillot and Camille Chambon for their help with the reconstruction of 3-D canopies using Adel-Wheat. LITERATURE CITED Abichou M . 2016 . 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Contrasting plant height can improve the control of rain-borne diseases in wheat cultivar mixture: modelling splash dispersal in 3-D canopies

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Abstract

Abstract Background and Aims Growing cultivars differing by their disease resistance level together (cultivar mixtures) can reduce the propagation of diseases. Although architectural characteristics of cultivars are little considered in mixture design, they could have an effect on disease, in particular through spore dispersal by rain splash, which occurs over short distances. The objective of this work was to assess the impact of plant height of wheat cultivars in mixtures on splash dispersal of Zymoseptoria tritici, which causes septoria tritici leaf blotch. Methods We used a modelling approach involving an explicit description of canopy architecture and splash dispersal processes. The dispersal model computed raindrop interception by a virtual canopy as well as the production, transport and interception of splash droplets carrying inoculum. We designed 3-D virtual canopies composed of susceptible and resistant plants, according to field measurements at the flowering stage. In numerical experiments, we tested different heights of virtual cultivars making up binary mixtures to assess the influence of this architectural trait on dispersal patterns of spore-carrying droplets. Key Results Inoculum interception decreased exponentially with the height relative to the main inoculum source (lower diseased leaves of susceptible plants), and little inoculum was intercepted further than 40 cm above the inoculum source. Consequently, tall plants intercepted less inoculum than smaller ones. Plants with twice the standard height intercepted 33 % less inoculum than standard height plants. In cases when the height of suscpeptible plants was doubled, inoculum interception by resistant leaves was 40 % higher. This physical barrier to spore-carrying droplet trajectories reduced inoculum interception by tall susceptible plants and was modulated by plant height differences between cultivars of a binary mixture. Conclusions These results suggest that mixture effects on spore dispersal could be modulated by an adequate choice of architectural characteristics of cultivars. In particular, even small differences in plant height could reduce spore dispersal. Canopy architecture, plant height, splash dispersal, 3-D modelling, septoria tritici leaf blotch, wheat, cultivar mixtures, Triticum aestivum, Zymoseptoria tritici INTRODUCTION Plant diseases are a major threat to agricultural production, especially in a context of climatic uncertainty (Lamichhane et al., 2015; Savary et al., 2017). Disease management is mainly provided by the use of resistant cultivars and pesticides. However, some pathogens have high adaptive capacities. They can overcome cultivar resistance relatively quickly (de Vallavieille-Pope et al., 2012) and develop resistance to pesticides (Leroux and Walker, 2011). This is the case, for example, for Zymoseptoria tritici (Orton et al., 2011), which causes septoria tritici blotch (STB), a highly damaging wheat disease (Fones and Gurr, 2015) dispersed by rain splash (Huber et al., 2006) during its epidemic phase. In addition, in the case of STB, cultivar resistance is mostly partial (Brown et al., 2015). Cropping systems in industrialized countries have tended towards growing standardization in order to simplify crop management and improve yield. However, this standardization also led to a selective pressure on pathogens and a dependence to a large extent on farm inputs, including fungicides. Introducing diversity in cropping systems, for example using intercropping, can make it possible to improve the stability of production and to contribute to disease management (Boudreau, 2013) in a context of reduction or absence of fungicide use. Cultivar mixtures consist of growing different cultivars together in the same field. This cultural practice can provide a reduction of disease propagation if mixtures are adequately designed, in particular if chosen cultivars have contrasting levels of resistance to the targeted disease (Finckh and Wolfe, 2006; Gigot et al., 2014). Moreover, it makes it possible to grow cultivars having interesting qualities (e.g. grain quality, resistance to another disease) that are sometimes neglected because of their susceptibility to an important disease. In a cultivar mixture, major mechanisms involved in disease reduction are related to spore dispersal. Distance between susceptible plants is larger than in pure stands, thus reducing spore transfer from one susceptible plant to the other (density effect), particularly in the case of spore transfer by rain splash which occurs over short distances, typically a median distance of <1 m (Macdonald and McCartney, 1987). On the other hand, spores are intercepted by resistant plants which are not or little affected by disease, and part of the inoculum is therefore prevented from reaching susceptible plants (barrier effect). The reduction of disease propagation in cultivar mixture can be optimized by using an adequate proportion of resistant and susceptible cultivars within the mixture (Jeger et al., 1981; Garrett and Mundt, 1999; Xu and Ridout, 2000; Cox et al., 2004; Dai et al., 2012; Gigot et al., 2014). For example, Gigot et al. (2013) obtained reductions of STB severity up to 42 % in wheat cultivar mixtures containing 75 % of partially resistant plants and 25 % of susceptible plants. Cultivar mixtures used in mechanized agricultural systems are usually composed of cultivars with similar architecture (Wolfe, 1985), and cultivar architecture is seldom considered in the process of mixture design. However, canopy architecture has an impact on spore dispersal (Calonnec et al., 2008). This is particularly striking in the case of rain splash dispersal, which occurs over short distances. For example, experiments under controlled conditions have shown a relationship between canopy density and gradient shape (Yang et al., 1991; Madden and Boudreau, 1997; Schoeny et al., 2008). Moreover, plant height has been shown to be related to STB severity (Bahat, 1980; Arraiano et al., 2009). Taking advantage of intraspecific diversity in terms of plant architecture could be a way to enhance the reduction of disease propagation in cultivar mixtures. For example, growing together cultivars of contrasting height has provided disease reductions in the field (Jackson and Wennig, 1997; Zhu et al., 2005; Li et al., 2012; Vidal et al., 2017a). In the field, it is difficult to assess the direct impact of plant architecture on dispersal and to distinguish it from other mechanisms that have an impact on disease. Modelling approaches have been proved to be useful to investigate the impact of architecture on disease propagation in pure stands (Calonnec et al., 2008; Robert et al., 2008). The objective of this work was to assess the impact of plant architecture of wheat cultivars in mixtures on rain splash dispersal of Z. tritici. In order to investigate this question, we used a modelling approach involving an explicit description of canopy architecture and spatial spore dispersal processes. We simulated spore dispersal events occurring in mixtures of two cultivars, at the flowering stage. We tested different heights for virtual plants of the two cultivars comprising the mixtures in order to assess the impact of two factors on spore dispersal patterns within cultivar mixtures: canopy height and the difference in cultivar height. MODELLING APPROACH Splash dispersal events were simulated in wheat cultivar mixtures at the flowering stage. In the case of wheat, flowering is a critical stage in the epidemic as (1) disease keeps propagating upwards while the height of leaves remains fixed; and (2) no more healthy tissues are formed and global disease severity at the plant level increases. At this stage, plant organs have been fully developed and have reached their final location within the canopy, and top leaves, which have a critical importance in yield formation (Thomas et al., 1989), begin to be affected by disease progression. At this stage, the impact of cultivar mixture on disease propagation becomes visible (Gigot et al., 2013). Mixture design could have an impact on both canopy architecture and epidemic before flowering. We therefore based our case study on field measurements of architecture and disease measurements performed at the flowering stage, representing a snapshot of canopy architecture and location of inoculum sources at this critical stage. In order to study the impact of plant height of cultivars making up a binary mixture on splash dispersal, we simulated splash dispersal events in canopies including virtual plants with different insertion heights of leaves of each of the two cultivars: from the plant height that was observed in the field (typical wheat plant height, around 80 cm) to twice this height. Here we focused on individual dispersal events and not on the whole epidemic, in order to better understand mechanisms related to canopy architecture. Other studies have investigated the effect of cultivar mixtures on epidemics, and shown that mixture effects can be amplified by successive dispersal cycles (Gigot et al., 2014). Splash dispersal within the canopy In several dispersal models, canopy architecture is taken into account through integrated parameters such as porosity of crop density, thus considering plant canopy as a homogeneous medium. In the case of STB, vertical heterogeneity is an important point as spores travel from sporulating lesions, usually located on lower leaves, to younger and higher healthy leaves (Suffert and Sache, 2011; Suffert et al., 2011). Vertical heterogeneity of canopy structure has been considered previously in spore dispersal and disease modelling (Pielaat et al., 2002; Robert et al., 2008; Garin et al., 2014). In the case of a cultivar mixture, horizontal heterogeneity is also important as disease reduction mechanisms rely on the proximity of resistant and susceptible plants grown side by side. This type of heterogeneity, i.e. within-field spatial pattern, has already been considered previously, including in cultivar mixture models (Sapoukhina et al., 2010; Gigot et al., 2014). However, 3-D canopy heterogeneity is rarely considered in dispersal models. We used a model proposed by Saint-Jean et al. (2004) that explicitly describes splash dispersal processes in a 3-D canopy structure. The model was implemented in C++. Described mechanisms included (1) interception of incoming raindrops; (2) production of splash droplets; (3) droplet transport within the canopy; and (4) interception of splash droplets by elements of the canopy. The model used a Monte Carlo integration method (Binder and Heermann, 1992; Lafortune, 1996), involving sampling of incoming raindrop properties, sampling of splash droplet characteristics and computation of ballistic droplet trajectories. The model computed integrated variables describing dispersal indicators that were distributed throughout the canopy. Simulation of rain events was performed using 107 samples in the rain drop distribution for each rain event in order to reach standard errors <2 %. Raindrop diameters were distributed uniformly and ranged from 0.53 to 4.00 mm, corresponding to diameters commonly found in natural rains (Ulbrich, 1983). Rainfall is modelled here as a flux of raindrops and, because distribution was chosen as uniform, the rain intensity and its variation over time were not taken into account. Properties of splash droplets including Weibull distribution of diameters, and velocity as well as distribution of ejection angles were sampled as in Saint-Jean et al. (2004) based on experimental results obtained by Yang et al. (1991). In order to avoid border effects and to approach open field conditions, periodic boundary conditions were applied to mimic infinite canopy. Droplets that reached a virtual plot border were relocated on the opposite side, as explained in Gigot et al. (2014). A module was implemented in order to account for incorporation of inoculum produced by sporulating lesions in splash droplets. When a raindrop was intercepted by a diseased leaf element, the proportion of droplets carrying spores was equal to the proportion of sporulating lesion area of the leaf. For example, half the droplets generated by a splash event on a leaf with 50 % of sporulating area carried spores. Canopy structure and inoculum location at the flowering stage Architectural models can provide a realistic representation of canopy structure (Godin, 2000). These models can be used to compute physical variables such as interception of rain (Bussière et al., 2002), spray (Dorr et al., 2014) or light (Chelle and Andrieu, 2007). They have been used to investigate properties of complex canopies as in the case of pea–wheat intercropping (Barillot et al., 2012). Virtual 3-D canopies were designed based on field data collected at the flowering stage during a field experiment conducted at the INRA experimental station in Grignon (France) in 2016 (Vidal et al., 2017a). A mixture was constituted with two standard height cultivars, including 25 % of susceptible plants (‘Sogood’) and 75 % of partially resistant plants (‘Maxwell’). This proportion corresponds to a mixture design that provided STB reductions under field conditions (Gigot et al., 2013). At the flowering stage, leaf and internode dimensions, as well as leaf curvature were measured on 30 main stems per cultivar grown in a pure stand. Leaf and internode dimensions were also measured on 15 main stems per cultivar in mixtures. The density of tillers with ears was recorded in 3 sections of rows of 1 m length each, in each treatment. Tiller density was of 475 tillers m–2 in the cultivar mixture. Susceptible plants accounted for 33 % of ears in the mixture. The proportion of sporulating area was measured at leaf level in each treatment, on 18 main stems of each cultivar in mixtures. At the flowering stage, average disease severity was 1.7 % (s.e. 0.9) on leaf 4 (from the top) and 17.3 % (s.e. 5.0) on leaf 5 for the resistant plants, and 8.9 % (s.e. 3.0) on leaf 4 and 51.6 % (s.e. 6.8) on leaf 5 for the susceptible plants. Main stems were reconstructed using Adel-Wheat (Fournier et al., 2003) to combine metamer dimension and leaf curvature. Each stem had the dimensions of one of the plants measured in the field. Leaf curvature was sampled from a database of measured curvatures, for each cultivar and leaf layer. Leaf azimuth was attributed automatically in Adel-Wheat. Main stems were then assembled to constitute canopies according to the measured tiller density of each cultivar in each mixture. Plants were organized in rows and plant order was sampled to simulate a random arrangement of the two cultivars. Virtual canopies had a ground area of 1 m2. Plants were described under the form of cylinders (stems and ears), triangles and quadrilaterals (leaves). A proportion of sporulating area was attributed to each leaf element. For each virtual stem, a severity profile (proportion of sporulating area on each leaf of the stem) was sampled from profiles measured on field stems, depending on cultivar. For a determined treatment, replicates were generated by modifying the seed used for random sampling in the process of canopy design. We assessed the impact of the variability of the input canopy on simulation results. The different stochastic aspects involved in canopy design were assessed: variability profiles in leaf area, leaf curvature and severity profiles as well as the organization of cultivars within the mixture. In order to quantify these aspects, we ran simulations for four canopies (four different sampling patterns) for each of four chosen treatments. Numerical experiments In order to study the impact of plant height of cultivars in a two-component mixture, leaf insertion heights of plants comprising a mixture were modified in each type of mixture. Changes in plant height involved only differences in leaf insertion height. All tested canopies had a constant leaf area index (LAI) of 4.7 m2 of leaves per m2 of ground. Leaf dimensions and curvature remained unchanged; sporulating area remained on leaves but their height was modified according to leaf insertion height. Relative height was defined as a proportion of plant height of the reference canopy. Four cases were tested: (1) a susceptible and a resistant cultivar, both with short plant height; (2) a tall susceptible cultivar with a shorter resistant cultivar; (3) a short susceptible cultivar with a taller resistant cultivar; and (4) increased height of both cultivars. Short height corresponded to the typical height of a wheat plant (around 80 cm) while tall plant height corresponded to double the standard height, which is representative of the cultivated diversity available for plant height within wheat cultivars (some landrace wheat cultivars reach 160 cm in height). The vertical distribution of leaf area differed greatly depending on the size of plants comprising the mixtures (Fig. 1). Plant height affected the position of the inoculum sources, mainly constituted of lower diseased leaves of susceptible plants. Sporulating lesions were present only on leaves 4 and 5. In the case of short plants, these leaves were located mostly at a height up to 30 cm above the ground, while they reached 55 cm in the case of the tall susceptible cultivar. Canopies with contrasting plant height were made up of two layers of leaves: one lower layer to which the short cultivar was confined and one upper layer occupied exclusively by leaves of the tall cultivar. The layers are constituted of resistant and susceptible leaves. Fig. 1. View largeDownload slide Vertical distribution of leaf area (m2 m–2 of ground) as a function of height within virtual 3-D canopies, in mixtures of two cultivars with contrasting canopy structure. Healthy leaves correspond to leaves 1–3 (from the top, leaf 1 is the highest leaf or flag leaf). Diseased leaves correspond to leaves 4 and 5 that had sporulating lesions. Virtual 3-D canopies were designed by combining measurements of leaf curvature and organ dimensions obtained from a field experiment. The s.e. error of the vertical distribution of leaf area ranged from 1.23 × 10–3 to 1.67 × 10–10 (m2 m–2 of ground). Fig. 1. View largeDownload slide Vertical distribution of leaf area (m2 m–2 of ground) as a function of height within virtual 3-D canopies, in mixtures of two cultivars with contrasting canopy structure. Healthy leaves correspond to leaves 1–3 (from the top, leaf 1 is the highest leaf or flag leaf). Diseased leaves correspond to leaves 4 and 5 that had sporulating lesions. Virtual 3-D canopies were designed by combining measurements of leaf curvature and organ dimensions obtained from a field experiment. The s.e. error of the vertical distribution of leaf area ranged from 1.23 × 10–3 to 1.67 × 10–10 (m2 m–2 of ground). RESULTS Detailed characteristics of four contrasting cases We first present here the detailed characteristics of four canopies with contrasting structures, representing the diversity of explored canopy structure, i.e. (1) plants with similar size either short (reference case, relative height = 1) or tall (relative height = 2) and (2) plants with contrasting size with either the resistant or the susceptible cultivar having twice the height of the other cultivar of the mixture. For these key cases, four replicate canopies were generated for each treatment. Standard errors on intercepted drops ranged from 0.08 to 0.66 % of total raindrops per m2 of leaf. For intercepted spore-carrying droplets, the standard errors ranged from 0 to 1.3 per 100 raindrops and per m2 of leaf. Variability of intercepted spore-carrying droplets was related to (1) the arrangement of plants within the canopy and (2) the sampling of severity profiles. Fixing severity to its mean value for each leaf level and sampling four replicates of plant arrangements led to standard errors of at most 1.03 per 100 raindrops and per m2 of leaf. On the other hand, four replicate samplings of severity profiles for the same plant arrangement led to standard errors of at most 0.97 spore-carrying droplets per 100 raindrops and per m2 of leaf. When susceptible plants were taller than the resistant plants, they intercepted many more raindrops than when they were shorter than resistant plants (Fig. 2A). Indeed, when plants of different heights were present in the mixtures, many leaves of the tallest plants were located above those of the short plants, thus providing a shelter from the rain. Fewer raindrops were intercepted by lower diseased leaves of susceptible plants, thus limiting the amount of splash droplets carrying spores being formed in this type of canopy. This is consistent with the small number of spore-carrying droplets intercepted by lower leaves in this case (Fig. 2B). However, more spore-carrying droplets were intercepted by upper leaves when short susceptible plants were grown with tall resistant plants. Short susceptible plants were located at the bottom of the canopy with very few resistant leaves. Thus, the barrier effect was low and most spore-carrying droplets were intercepted by susceptible plants. Mixture design including tall susceptible plants led to lower interception of spore-carrying droplets by upper leaves of susceptible plants. Indeed, top leaves of susceptible plants were far from the source of inoculum and resistant leaves provided a barrier effect. Fig. 2. View largeDownload slide Dispersal patterns simulated in virtual 3-D canopies in cultivar mixtures with contrasting canopy structure. Drop interception (A) was expressed as a proportion of total raindrops per m2 of leaves. Inoculum interception (B) was expressed as the number of spore-carrying droplets per incoming raindrop and per m2 of leaves. Diseased leaves of susceptible plants constituted most of the inoculum source and corresponded to lower leaves (leaf 4 and 5). Error bars correspond to the s.e. obtained with four simulations for each treatment. Fig. 2. View largeDownload slide Dispersal patterns simulated in virtual 3-D canopies in cultivar mixtures with contrasting canopy structure. Drop interception (A) was expressed as a proportion of total raindrops per m2 of leaves. Inoculum interception (B) was expressed as the number of spore-carrying droplets per incoming raindrop and per m2 of leaves. Diseased leaves of susceptible plants constituted most of the inoculum source and corresponded to lower leaves (leaf 4 and 5). Error bars correspond to the s.e. obtained with four simulations for each treatment. Changes in virtual canopy height in the cultivar mixture had no impact on the distribution of incident raindrops between cultivars. The number of raindrops intercepted on diseased leaves of the susceptible cultivar did not change with canopy height because the LAI above diseased leaves remained constant (results not shown). The number of spore-carrying droplets intercepted by both cultivars decreased similarly with canopy height, from 1.5 spore-carrying droplets per 100 raindrops and per m2 of leaves for standard height to 1.0 spore-carrying droplets when the height was doubled considering resistant plants, and from 1.2 to 0.8 spore-carrying droplets considering susceptible plants (Fig. 3). This was related to a larger distance between leaves, in particular between diseased leaves and top leaves, when canopy height was large (height effect). Fig. 3. View largeDownload slide Simulated inoculum interception by resistant and susceptible virtual plants in a cultivar mixture as a function of relative canopy height. Each point corresponds to one simulation with a determined canopy height. The reference was a homogeneous cultivar mixture at the flowering stage, including a susceptible and a resistant cultivar, both of standard plant height (approx. 80 cm, relative height = 1). Canopy height is expressed as a proportion of the reference canopy height. Fig. 3. View largeDownload slide Simulated inoculum interception by resistant and susceptible virtual plants in a cultivar mixture as a function of relative canopy height. Each point corresponds to one simulation with a determined canopy height. The reference was a homogeneous cultivar mixture at the flowering stage, including a susceptible and a resistant cultivar, both of standard plant height (approx. 80 cm, relative height = 1). Canopy height is expressed as a proportion of the reference canopy height. Increasing the height of the resistant plants decreased the number of raindrops intercepted by susceptible leaves (Fig. 4A). Leaves from tall resistant plants were located above susceptible leaves and intercepted incoming raindrops before the latter, thus providing a rain shelter (called here the ‘umbrella effect’). The LAI located above susceptible lower leaves changed from 2.42 for standard height to 3.73 for doubled resistant plant height. However, this had little impact on the number of raindrops intercepted by diseased leaves of susceptible plants which were located at the bottom of the canopy. Bottom leaves thus intercepted a small number of raindrops (from 1.4 to 1.1 % of total incoming raindrops), as a high leaf area of the canopy was located above these leaves, independently of resistant plant height. Raindrop interception by the resistant cultivar increased slightly with resistant plant height, from 55 % (standard height) to 65 % (doubling of standard height) of incoming raindrops. Resistant leaves accounted for 71 % of the leaf area of the mixture and intercepted many raindrops independently of their height. The number of new raindrops intercepted due to taller resistant plant height was therefore relatively small in proportion. Fig. 4. View largeDownload slide Simulated raindrop and inoculum interception by resistant and susceptible virtual plants in a cultivar mixture as a function of virtual plant height of each cultivar making up the mixture. Each point corresponds to one simulation with a determined height of virtual plants of one of the cultivars making up the mixture. The reference was a homogeneous cultivar mixture with a resistant and a susceptible cultivar, both of standard plant height (approx. 80 cm), at the flowering stage. Plant height is expressed as a proportion of the reference plant height. In (A) and (C), the size of the resistant cultivar varies, while the size of the susceptible cultivar is fixed with two different heights: reference height (solid line) or twice the reference height (dotted line). In (B) and (D), the size of the susceptible cultivar varies, while the size of the resistant cultivar is fixed with two different heights (solid line: reference height, dotted line: twice the reference height). Fig. 4. View largeDownload slide Simulated raindrop and inoculum interception by resistant and susceptible virtual plants in a cultivar mixture as a function of virtual plant height of each cultivar making up the mixture. Each point corresponds to one simulation with a determined height of virtual plants of one of the cultivars making up the mixture. The reference was a homogeneous cultivar mixture with a resistant and a susceptible cultivar, both of standard plant height (approx. 80 cm), at the flowering stage. Plant height is expressed as a proportion of the reference plant height. In (A) and (C), the size of the resistant cultivar varies, while the size of the susceptible cultivar is fixed with two different heights: reference height (solid line) or twice the reference height (dotted line). In (B) and (D), the size of the susceptible cultivar varies, while the size of the resistant cultivar is fixed with two different heights (solid line: reference height, dotted line: twice the reference height). Increasing the height of the susceptible cultivar strongly increased interception of raindrops by susceptible leaves, from 16 % (standard height) to 25 % (double standard height) of incoming raindrops (Fig. 4B). When susceptible plants were taller, their leaves were higher in the canopy and more exposed to incoming raindrops. The interception of raindrops by lower diseased leaves, which produced spore-carrying droplets, also increased, from 1.4 % for standard height to 2.6 % of total raindrops. Indeed, LAI above diseased susceptible leaves was reduced to 1.03 when susceptible plant height was doubled, compared with 2.42 for standard height. The interception of raindrops by resistant leaves decreased slightly, from 55 to 48 % of total raindrops. Susceptible plants accounted for a small proportion of 29 % of canopy leaf area in the mixture and therefore provided a small umbrella effect. Increasing the height of the resistant cultivar reduced inoculum interception by the resistant plants from 1.5 to 0.8 spore-carrying droplets of inoculum per raindrop and per m2 of leaves. This reduction was related to the increase of distance to the main inoculum source (lower leaves of susceptible plants) due to increased plant height and was called here the ‘height effect’. Simultaneously, inoculum interception by the susceptible cultivar increased from 1.2 to 1.6 spore-carrying droplets per raindrop and per m2 of leaves (Fig. 4C). When the resistant cultivar was taller, fewer resistant leaves were present at the height of short susceptible plants, representing a leaf area of 0.19 m2 m–2 with doubled plant height compared with 1.65 m2 m–2 for standard height. Interception of spores by resistant leaves, which provided protection of susceptible leaves (called the ‘barrier effect’), was thus reduced when resistant plant height increased, from 1.5 for normal plant height to 0.8 spore-carrying droplets of inoculum per raindrop and per m2 of leaves for doubled resistant plant height. Increasing the height of the susceptible cultivar decreased inoculum interception by the susceptible cultivar from 1.2 to 0.8 spore-carrying droplets per raindrop and per m2 of leaves, while increasing inoculum interception by the resistant cultivar from 1.5 to 2.1 spore-carrying droplets per raindrop and per m2 of leaves (Fig. 4D). This resulted from two main effects. First, the distance between leaves of the susceptible cultivar and the diseased leaves, which constituted the main source of inoculum, increased (height effect). Secondly, more resistant leaves were present at the same height as lower leaves of the susceptible cultivar when susceptible plants were taller, corresponding to an LAI of 2.37 when susceptible plant height was doubled compared with 1.65 m2 m–2 for standard height, thus providing an efficient barrier effect. With sporulating lesion areas located on lower leaves, the barrier effect was thus at a maximum with a tall susceptible cultivar and a short resistant cultivar. Effects of canopy structure on dispersal The number of raindrops intercepted by a determined leaf layer strongly depended on the amount of leaf area located above it (Fig. 5). By analogy with light interception and Beer–Lambert’s law (Sinoquet and Bonhomme, 1991), an exponential relationship fitted well to the simulation results. This implies that a difference of ‘LAI located above a determined leaf layer’ had more impact on raindrop interception by leaves located at the top of the canopy than on leaves located at the bottom of the canopy. According to the variance analysis, the highly significant relationship between intercepted raindrops and LAI distribution depended on leaf number and cultivar (P < 2.2 × 10−16), but not on the height of cultivars within the mixture (P = 1). The number of raindrops intercepted by lower leaves varied only slightly when the height of cultivars comprising the mixture was modified. Modifications in plant height mainly affected the distribution of leaf area above these leaves. However, raindrop interception by leaves 3 and upwards strongly varied depending on plant height within the mixture. The effect of LAI located above a determined leaf layer (umbrella effect) was thus higher for top leaves. The impact of the ‘umbrella effect’ on inoculum dispersal could therefore be higher if sporulating lesions were present on these leaves, which could occur later in the epidemic. Fig. 5. View largeDownload slide Simulated distribution of raindrop interception within cultivar mixture canopies as a function of vertical position of leaf levels within the canopy. Leaf area index (LAI) corresponds to leaf area per m2 of ground. This graph shows the percentage of total incoming raindrops intercepted per leaf area, by a determined leaf layer as a function of leaf area located above the leaf layer. Points correspond to simulations involving changes in cultivar height within each treatment but with unchanged LAI. Each point corresponds to one leaf layer of one cultivar in one simulation. Leaf 1 (L1) corresponds to the top leaf or flag leaf. The lines correspond to a fitted model. The dotted line corresponds to a fitted model: log(drops) = 14.0 − 0.5 × LAIa (R2 = 0.79), where ‘drops’ corresponds to the number of intercepted raindrops per leaf area and ‘LAIa’ the canopy LAI located above the concerned leaf layer. The solid line is an inverse function: 1/drops = 3.72 + 5.12 × LAIa (R2 = 0.92). Fig. 5. View largeDownload slide Simulated distribution of raindrop interception within cultivar mixture canopies as a function of vertical position of leaf levels within the canopy. Leaf area index (LAI) corresponds to leaf area per m2 of ground. This graph shows the percentage of total incoming raindrops intercepted per leaf area, by a determined leaf layer as a function of leaf area located above the leaf layer. Points correspond to simulations involving changes in cultivar height within each treatment but with unchanged LAI. Each point corresponds to one leaf layer of one cultivar in one simulation. Leaf 1 (L1) corresponds to the top leaf or flag leaf. The lines correspond to a fitted model. The dotted line corresponds to a fitted model: log(drops) = 14.0 − 0.5 × LAIa (R2 = 0.79), where ‘drops’ corresponds to the number of intercepted raindrops per leaf area and ‘LAIa’ the canopy LAI located above the concerned leaf layer. The solid line is an inverse function: 1/drops = 3.72 + 5.12 × LAIa (R2 = 0.92). The number of spore-carrying droplets intercepted by a determined leaf layer strongly depended on the distance between this leaf layer and the main source of inoculum (Fig. 6) constituted by lower diseased leaves of the susceptible cultivar. Considering a positive distance above the inoculum source, the amount of intercepted inoculum increased exponentially when the distance to the inoculum source decreased. This relationship depended on cultivar (P = 0.035) and on the height of the cultivars within the mixture (P = 0.0001) but not on leaf number (P = 0.24). This was consistent with the relationship between plant height and inoculum interception (height effect) mentioned previously (Figs 2–4). The number of spore-carrying droplets intercepted by leaves higher than 40 cm above the inoculum source was very small on the whole. This suggests that even small increases in plant height could have a non-negligible effect on the interception of spore-carrying droplets. Fig. 6. View largeDownload slide Simulated vertical distribution of inoculum interception within cultivar mixture canopies as a function of the distance to the main inoculum source. The graph shows the amount of inoculum intercepted per leaf area, by a determined leaf layer as a function of height difference with the main inoculum source (leaves 4 and 5 of the susceptible cultivar). Points correspond to simulations involving changes in cultivar height within mixtures with unchanged leaf area index. Each point corresponds to one leaf layer of one cultivar in one simulation. Leaf 1 (L1) corresponds to the top leaf or flag leaf. The curve corresponds to a model fitted for positive distances to the inoculum source: log(intCD) = 25.5 − 7.9 × (dInoc + 1.5) (R2 = 0.84) with ‘intCD’ the number of intercepted contaminated droplets per raindrop and per m2 of leaves and ‘dInoc’ the distance (height) to the inoculum source. Fig. 6. View largeDownload slide Simulated vertical distribution of inoculum interception within cultivar mixture canopies as a function of the distance to the main inoculum source. The graph shows the amount of inoculum intercepted per leaf area, by a determined leaf layer as a function of height difference with the main inoculum source (leaves 4 and 5 of the susceptible cultivar). Points correspond to simulations involving changes in cultivar height within mixtures with unchanged leaf area index. Each point corresponds to one leaf layer of one cultivar in one simulation. Leaf 1 (L1) corresponds to the top leaf or flag leaf. The curve corresponds to a model fitted for positive distances to the inoculum source: log(intCD) = 25.5 − 7.9 × (dInoc + 1.5) (R2 = 0.84) with ‘intCD’ the number of intercepted contaminated droplets per raindrop and per m2 of leaves and ‘dInoc’ the distance (height) to the inoculum source. DISCUSSION Three main effects were identified when varying plant height in a cultivar mixture: (1) leaves provided shelter from raindrops to leaves located below them (‘umbrella effect’); (2) interception of spore-carrying droplets decreased with plant height (‘height effect’); and (3) resistant leaves located close to diseased leaves of the susceptible cultivar (main source of inoculum) intercepted splash droplets carrying spores, which thus protected susceptible leaves (‘barrier effect’). These effects are discussed below. Umbrella effect The number of raindrops intercepted by a given leaf layer decreased exponentially with the increase of LAI above this leaf layer, i.e. the vertical position of leaves within the canopy (Fig. 5). This result was consistent with Calder’s work (1996), where the raindrop interception of the lower layer of a canopy was expressed as a decreasing exponential function of the projected leaf area of the upper layer. However, an inverse function fitted better (RMSE of 0.043) the decrease of intercepted raindrops with the increase of LAI compared with the exponential model (RMSE of 0.049). In mixtures of plants with similar height (Fig. 3), the distribution of raindrop interception was independent of canopy height (not shown). However, modifying the height of cultivars comprising a mixture independently led to a modification of raindrop interception patterns (Fig. 4A, B), related to a rearrangement of leaves and modifications of the vertical distribution of leaf area. On the whole, the ‘umbrella effect’ was relatively small considering diseased leaves that, for our simulations, were located in the lower part of the canopy. Indeed, the major impact of modification of the vertical distribution of leaf area was observed for leaves located higher in the canopy. The umbrella effect thus might be emphasized in the case when upper leaves (for example leaf 3) were affected by disease, which could occur later in the epidemic or in the case of a higher inoculum pressure. The impact of LAI distribution on raindrop distribution within the canopy, and therefore on umbrella effect, could be modulated by ground cover that is also related to other architectural traits of wheat plants (Abichou, 2016). For example, planophile leaves (close to a horizontal position) could lead to a higher ground cover compared with erectophile leaves (close to a vertical position), for a similar LAI. Differences in space foraging of cultivars, for example distance between tillers or tiller inclinations, could also have an impact on ground cover. Height effect Plant height determined the distance between the source of inoculum and upper leaves. A relationship between plant size and inoculum interception was observed in different simulations (Figs 3 and 4) and was confirmed when considering the whole set of simulations (Fig. 6). These simulation results are consistent with classical splash dispersal patterns (Shaw, 1987; Pietravalle et al., 2001; Pielaat et al., 2002). For a given inoculum and LAI conditions, a tall plant intercepted less inoculum than a short plant. This observation is consistent with the association of tall plant height with reduced STB severity observed by several authors (Bahat, 1980; Arraiano et al., 2009). Indeed, splash dispersal occurs over limited distances (Walklate et al., 1989), and splash droplets are not able to reach the highest leaves (a few spore-carrying droplets travelled further than 40 cm from the source). Rainfall was modelled here by using a uniform distribution of raindrop diameter. However, natural rainfalls follow more complex distributions such as lognormal distribution that could vary in time and be dependent on the rain intensity (Uijlenhoet and Stricker, 1999; Testud et al., 2001; Uijlenhoet et al., 2003). By using the assumption of a uniform distribution, we misestimated the proportion of the small raindrops, but the smallest drops do not contribute much to splash dispersal because of lower kinetic energy. On the other hand, uniform distribution overestimated larger raindrops and therefore emphasized splash dispersal to longer distances. Moreover, plant height also contributed to determining canopy density which has an impact on interception of splash droplets carrying spores (e.g. Yang and Madden, 1993; Madden and Boudreau, 1997; Schoeny et al., 2008). Resistant plants had a higher leaf area density when they were shorter, and thus intercepted more splash droplets and therefore more inoculum. In the case of cultivar mixtures, plant height thus contributed to the capacity of each cultivar to intercept inoculum. A short resistant cultivar thus provided a high barrier effect and a tall susceptible cultivar intercepted less inoculum. Barrier effect The barrier effect is often mentioned as an important effect leading to disease reduction in cultivar mixtures (Finckh and Wolfe, 2006; Vidal et al., 2017b). Our results suggest that the barrier effect can be modulated by canopy structure, and in particular by the vertical arrangement of resistant and susceptible leaves. The barrier effect occurred when resistant leaves were present at the same height as the source of inoculum, consisting here of the lower leaves of the susceptible cultivar. For example, there was very little barrier effect in mixtures including a tall resistant cultivar and a short susceptible cultivar, as few resistant leaves were located at the height of the inoculum on the susceptible cultivar (Fig. 4D). In contrast, the barrier effect was higher when susceptible and resistant plants were of similar height, and even higher when susceptible plants were taller than resistant plants (Figs 3 and 4D). In mixtures of cultivars with similar architecture, the barrier effect is often modulated through the proportion of resistant plants (Gigot et al., 2014). However, our results suggest that these effects could be amplified by differences in height between cultivars, in particular in the case of a taller susceptible cultivar (Fig. 4). These differences could lead to canopies composed of layers of different leaf area density with different proportions of resistant leaves. A mixture composed of a short resistant cultivar and a taller susceptible cultivar would thus lead to a dense lower layer containing many resistant leaves that could provide a high barrier effect. In contrast, the upper part of the canopy would be less dense and upper leaves would be protected both by the increased distance to the inoculum source (height effect) and by the presence of resistant leaves in the lower part of the canopy (barrier effect). Effects of the canopy architecture of cultivar mixtures on inoculum dispersal by rain splash The arrangement of resistant and susceptible plants and leaves within cultivar mixtures contributes to the reduction of disease propagation through effects on spore dispersal (Finckh and Wolfe, 2006). The barrier effect and density effect have been studied previously (Chin and Wolfe, 1984). These effects can be modulated through mixture design. In general, effects are larger when the mixture is homogeneous (e.g. chessboard design), while they tend to be lower when cultivars are arranged in different rows or blocks (Gigot et al., 2014). Here, we considered effects of plant architecture on rain splash dispersal that could have an impact on disease propagation within cultivar mixtures. We showed that the barrier effect could be modulated by the height of the cultivars making up the mixture. We described an effect of plant height that is important in the case of splash-dispersed diseases, due to short dispersal distances. This effect is similar to the ‘escape’ concept (Arraiano et al., 2009), excluding here the dynamic aspect of stem extension. Height effect could also be related to a vertical equivalent of the ‘density effect’ as it involves an increased distance between sporulating lesions (here confined to the lower leaves, mainly on susceptible plants) and healthy susceptible leaves (here mainly top leaves). Finally, we mentioned the possible importance of the vertical distribution of leaf area within the canopy (called here the umbrella effect), that could lead to a reduction of raindrop interception by diseased leaves, in later stages of the epidemic or in the case of more severe epidemics. Growing a tall susceptible cultivar together with a short resistant cultivar appears to be an interesting option. Besides effects on dispersal (Fig. 4) that were mentioned previously, this configuration could also be favourable in terms of microclimate. In this type of canopy structure, upper leaves would be in a low-density layer of the canopy, which could provide a dryer microclimate (related to increased air circulation), less favourable for pathogen development. This was observed in a field experiment when growing a tall susceptible and a short resistant rice cultivar together led to a reduced leaf moisture and reduced panicle blast disease severity on the susceptible cultivar (Zhu et al., 2005). In the case of STB, only partially resistant cultivars are available. An intense interception of spores by resistant leaves can thus result in new lesions on resistant plants. Canopy structure leading to a moderate interception of inoculum by resistant plants, such as in the case of taller homogeneous canopies, might also be of interest. Canopies with large differences in height between cultivars can be difficult to handle in mechanized agriculture, especially for harvest. However, our results suggest that effects on dispersal can be obtained even with limited differences in height (Fig. 4). Moreover, other architectural traits could have an impact on dispersal and would deserve further investigation (e.g. traits involving space foraging by plants such as leaf curvature, distance between axes, etc.). Finally, we considered here a single spore dispersal event in each canopy. In the case of polycyclic epidemics, several dispersal events occur and small protection effects can be amplified as the epidemic progresses. If we take into account the latent period of STB (from 270 to 500 °Cd; Lovell et al., 2004) and natural conditions occurring in the Paris area, the number of complete successive pathogen generations during a wheat post-heading period (roughly from late May to early June) is expected to be below ten. This means that, as shown by Gigot et al. (2014; Fig. 5) for the first successive generations, an increase of the protective effect is strongly expected to be observed under usual field conditions. CONCLUSION We described several mechanisms that have an impact on inoculum dispersal by rain splash and could favour the reduction of disease propagation in cultivar mixtures. Our results emphasized in particular the contribution of cultivar height contrast to mixture effects. Leaf area distribution within the canopy had an impact on raindrop interception patterns. The number of raindrops intercepted by a determined leaf layer depended on the amount of leaf area located above this leaf layer (umbrella effect). The barrier effect occurred when resistant leaves were present at the same height as the source of inoculum (here the lower leaves of the susceptible cultivar). Tall plants intercepted fewer spores than short plants due to the larger distance between lower leaves with sporulating lesions and upper leaves (height effect). The barrier effect was modulated by height distribution of cultivars in a mixture. The highest barrier effects were obtained by growing together a short resistant cultivar and a tall susceptible cultivar. In this case, upper leaves of the susceptible cultivar were also protected due to their larger distance from the inoculum source (height effect). 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Annals of BotanyOxford University Press

Published: Mar 20, 2018

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