Laurent Lescop
email: laurent.lescop@nantes.archi.fr

Lydia Zotkina
email: lidiazotkina@gmail.com

Catherine Cretin
email: catherine.cretin@culture.gouv.fr

PARAMETRIC METHODS TO VISUALIZE AN EXCEPTIONAL PARIETAL SCULPTURE. The revelations of the Poisson engraving

Keywords: Archeology, Grasshopper, Parametric, Parietal, Engraving Anthropocene,

come

Parametrics methods to visualize an exceptional parietal sculpture.The revelations of the Poisson engraving

Archeological background

While the neighbouring Abri Lartet was discovered in 1863 by É. Lartet and H. Christy, it took nearly thirty years, i. e. 1892, before Paul Girod and his collaborator with Elie Massénat discovered and searched the Abri du Poisson, which was probably entirely hidden by sedimentary deposits (Girod 1906). He called it "Gorge d'Enfer B" (meaning the Hell Pit) and recognized an Aurignacian level under 1m50 of stones of various sizes. This "Aurignacian formation" consists of a continuous whole of 0m80 where it is impossible to trace divisions. So there is a great homogeneity in the deposit. However, its section seems to contradict it, as D. Peyrony has already pointed out, since we can see a zonation in its horizon. It is important to note that at that time excavations were not carried out: workers were employed to collect the pieces and observations on the archaeological layers were often second-hand. Similarly, the limestone blocks were not examined for possible ornamentation (Peyrony 1952). After Dr. Girod's visit, several excavations followed one another, including those of Gabriel (or François) Galou, around 1898. The manager of a restaurant called Le Paradis, located nearby Fort de Tayac, resumed excavations in front of the shelter. Above the vault, it meets a row of hearths dug in the scree ground, associated with split-base bone points, awls, smoothers, pierced teeth, "all types of flint of the Aurignacian...". [START_REF] Peyrony | Les Abris Lartet et du Poisson à Gorge d'Enfer (Dordogne)[END_REF] and a muskox skull studied by E. Harlé, from Bordeaux (Harlé 1901). Except for this last piece, there is no publication of the results of his excavations. The fish sculpture was therefore discovered twenty years after the first excavations in the shelter. D. Peyrony's intervention allowed, on December 9 th of the same year 1912, to interrupt the cut-out work on the sculpture. On December 11th, the locks were placed on the screened entrance door (Delluc 1997). This is how "this work of art could only be preserved in place if it was of real scientific value only in the context and environment in which it was designed and executed" [START_REF] Peyrony | Les Abris Lartet et du Poisson à Gorge d'Enfer (Dordogne)[END_REF]. Also in the same year, D. Peyrony discovered several engraved and painted blocks in the excavation backfill, one of them bearing a deer design (Peyrony 1952). He had the shelter classified as a Historic Monument on the 23rd of March 1913. He also expropriated the land for the benefit of the State and closed the shelter with a wall. On August the 6th 1913, Henri Breuil came to trace the figure of the fish (Breuil 1960, p. 118). He did not publish it until 1927 (referenced as Breuil and Saint-Perier 1927, fig. 1;Figure 15-a, p. 25). At that time, on the ceiling of the shelter were identified the following motifs: the fish, the relief under the fish's head, the series of seven vertical lines, the small cups and the two rings on the fish, the unintelligible engraved lines, some decorated blocks and fragments detached from the vault (without knowing what D. Peyrony's criteria of discrimination between these two categories were), which are both engraved and painted. In 1917, D. Peyrony undertook protective work at l'Abri du Poisson (Fish Shelter), clearing the shelter and building the fence wall and began archaeological excavations in the Lartet Shelter. He excavated the Abri du Poisson in 1918, where he was able to distinguish five sedimentary groups, including two archaeological levels, an Aurignacian level I with split-based bone points and a Gravettien level with Noailles burins, separated by a sterile level [START_REF] Peyrony | Les Abris Lartet et du Poisson à Gorge d'Enfer (Dordogne)[END_REF]. His observations therefore contradict P. Girod's conclusions.

In 1973, Max Sarradet noticed a horse engraved on the ceiling engravings (Sarradet 1975). Taking an interest for the first time in the presence of colour on the fish sculpture and on the ceiling, A. Roussot spotted a black negative hand in December 1975, in the company of C. Archambault (Rigaud 1976, Roussot 1981, 1984a-b). After having found some of the Peyrony blocks preserved at the Musée des Eyzies (Delluc 1978a), Brigitte et Gilles Delluc began in 1983 a technological study of the engravings and sculptures on the ceiling of the Fish Shelter and a number of blocks [START_REF] Rigaud | Abri du Poisson[END_REF], Delluc 1991). They interpreted one of the engraved signs of the large collapsed block as a vulva and found a fingerprint sign on another of the blocks preserved in situ. They also tried to map the ceiling, grouping the different reliefs, cracks, calcined areas, flakes in the process of disbonding, engraved lines, red paint plates and rings.

No archaeological work took place after 1918, with the exception of the rock art survey operation of B. and G. Delluc in 1983. Only conservation work, for which we will have to specify the nature in the future, is carried out on an ad hoc basis. Among them is the microbiological monitoring of LRMH (Touron et al., 2008(Touron et al., -2009)). The Fish Shelter was visited as part of our PCR on 4 July 2013 (Cretin et al. 2013, pp. 54-60 and p. 135) and assessed the good potential of information held by the site, on the ceiling, on the blocks or in its sedimentary deposit. Finally, a preliminary study, in September 2016, by Lydia V. Zotkina, determines the good potential for techno-traceological information of the ceiling as well as the possibility of discriminating between anthropic traces and subsequent alterations. In fact, it is possible to consider new representations (Zotkina and Cleyet-Merle 2017), this is what will now be presented.

The 3D survey

The first objectives of digitizing the shelter are to estimate the volume of the shelter and to provide a support for the surveys and inventory of the works, the shelter ceiling and the collapsed block that rests on a separate surface. This allows more accurate 3D models to be integrated, if possible into the entire shelter model, otherwise on a sector, ceiling, block etc. The objects identified as interesting are the carved fish, the rings (N = 8 to 11), the collapsed block. The 3D also makes it possible to locate stratigraphic surveys and test hypotheses concerning the geometry of the fill and the collapsed block reassembly on the shelter ceiling. For the shelter, 119 photos in JPG, CR2 and TIFF formats were taken and a first model obtained 880,923 aligned points, a dense cloud of 53,883,473 points and a mesh size of 58,725 faces. In this first geometry the hidden parts are missing. It should be noted that shooting in the shelter is particularly uncomfortable, that it is very difficult to compose light to help photogrammetry and that areas are so narrow that it is difficult to slip someone with a camera in.

The representation of a fish is exceptional in parietal art, both in France and around the world. There are only about ten of them in total. The engraving described here is dated 25,000 years ago and it seems to be the oldest ever found. The figure is very realistic, the fish is as if caught in the motion. The size of the sculpture is 1.05 metres, which represents a plausible real dimension. Realistic details give precise indications of the species and the period during which the fish was caught. He was probably fished in the nearby Vézère river. The details that can be noted are the curved jaw that indicates that it is a Bécard type salmon. The lower jaw is curved in a hook shape, which indicates that it is a male fish and that it was caught after spawning, i. e. the period of egg fertilization. There are 7 lines above the fish that have been interpreted as the representation of the dorsal fin, but it is generally accepted that it is morphologically inconsistent. However, separation from the body can give way to other interpretations. The photogrammetric survey used here was carried out in 2019 following a previous series of surveys that did not give good results. A series of 99 photos were taken at 6032x4032 resolution with a Nikon D750, an exposure time of 1/100 seconds and the focal length at F/14, the focal length being 60mm. The flash was not used. The calculation in MetaShape yielded 3,669,909 vertices and 7,332,415 faces. So it's a very high resolution model.By resolution we can indicate that the engraving area is 0.46 m², which represents 460,000 mm². Considering that we have 7,332,415 faces at the end of the calculation, that is 16 faces per square millimetre. The risk in photogrammetry is always to be at the scale of the grain of the rock, which disrupts the modelling by creating a kind of noise where there is detail. It goes without saying that despite everything, the model will be simplified to carry out the experiments that will follow.

Procedural interpretation

Experiments now becoming established [START_REF] Lescop | Gavrinis, The raising of digital stones[END_REF]) using deviance analysis have shown their effectiveness in highlighting details that are difficult to detect with the naked eye. The method does not have the effectiveness of revolving lights to determine the chronology of the engravings, but is nevertheless effective for a detailed exploration of the topography. However, the examples identified [START_REF] Sanz | A simple methodology for recording petroglyphs using low-cost digital image correlation photogrammetry and consumer-grade digital cameras[END_REF] for example) work only on depth and as far as possible on fairly flat geometries. Our project here is to be able to control the slightest adjustment concerning the position of the reference plane, the number of gradients and their representation. In a second step, we will add another information that seems to us fundamental to understand the geometry of the engravings, it is the slope. The slope can provide information about the carving process by indicating the angle of attack, the use of the right or left hand, the hardness of the tool and the continuity effects. To design the parametric model for interpreting the engraving of the Fish, we will use the Grasshopper software. Grasshopper is a development environment associated with Rhino software and, more recently, Autodesk Revit architecture software under the name Dynamo. Grasshopper is not the only parametric development environment, but over the years, since its creation in 2007, it has acquired a reputation that ensures an active community of developers and many examples that can be used as training materials. Grasshopper falls into the category of visual programming languages with applications in architecture and engineering, but also in art, our proposal is also to introduce it in archaeology. To develop our process, we started by creating several resolutions of the basic model: a resolution at 7000 polygons, then 70,000, then 700,000. The 7 million polygon model proved too heavy to use. Depth analysis is rather simple to set up. First, it is a matter of extracting all the coordinates of all the points of the mesh. From this list, only the (z) values, the heights, are considered. From this collection of values, we determine the domain, i.e. the lowest value and the highest value, which gives us both extremes. The last step consists in constructing a gradient between the extreme values. However, in the context of archaeological analysis, it may be interesting to filter values and play with low and high values to highlight details. In this case, a Slider is created that will allow to vary the high and low reference planes. The details will therefore appear more finely and at the same time, we will have precise information on the thickness of the slice for further analysis.

The figuration of the depths gives interesting interpretive elements, among other things, the continuity levels of the figures, however the highlighting of the tracings remains rather weak. This will be corrected by slope analysis. The slope analysis is slightly more complex and interesting. It can be done either by drawing the contour lines, but the density of the lines can end up interfering with the reading, or by color gradient, which we will present here. The slope calculation will work a bit like a grazing light lamp by revealing the orientations of each polygon to a reference vector, by default the vector (z) pointing upwards. There are many ways to build a Grasshopper definition for this type of calculation, we will present here a simple setup. Each polygon's normal must be taken and each angle compared with the vector (z). From there several solutions, for instance, work in radians that can be converted into percentages or translate the angles into degrees. Then, just limit the domain of study and display the results using a gradient. Finally, the volume must be coloured with the results obtained. In the following examples, the choice was made to use a black and white gradient. The angles were then filtered. For the first image, only angles between 0 and 40°with (z) were selected. We can see that all the details come out more accurately than with the depth map. It is then necessary to distinguish as anthropogenic or not these lines and traces that appear.

Figure 10. Slopes definition with different vector orientation, top, orientation (z) it gives fine details of the engraving relative depths, middle, orientation (x), it emphases the 7 stripes above the fish, down, orientation (y) gives details on the fish's belly.

The second image is taken with the vector (x) as reference and an angle filtering between 45 and 145°. The result is close to a grazing light without being generated by drop shadows. In this image, the 7 lines above the fish's body appear very clearly, while only 6 are visible to the naked eye. Other details also come to mind. Finally, the third image is referenced with the vector (y) and with an angle filtering between 40 and 145. Here again, the grazing lighting effect works very well, without drop shadows and other details further enrich the analysis.

Conclusion

The method briefly presented here is under development in order to obtain ever finer results. The simplicity of the set-up allows the researcher, even if he is not a Grasshopper expert, to be able to vary the settings, to choose the appropriate type of presentation of the results and to always have control over the values handled. The researcher knows at any time what depth he is analyzing or what angle is being visualized.Other investigations can be carried out using the same model, such as cross-sections on the tracings or the length of the ridges, which can give an idea of the time required to complete the figure. The sections on the plots associated with the analysis of the angles according to a selected vector give indications on the tool used, whether it is held with the right or left hand and the angle of attack of this tool.The risk is always to confuse an anthropogenic trace of a natural surface accident (Lescop 2018). Traceology makes it possible to solve these questions. In our approach, we defend the position that no technique is orphan and that their diversity makes it possible to approach the understanding of the subjects as well as possible. However, the method presented here has the advantage of allowing a relatively fast investigation, accuracy according to the geometry quality and allowing to work with other recording techniques.

Figure 1 .

 1 Figure 1. Location of the Abri du Poisson, Manaurie, 44.9445457,0.9930259.

Figure 2 .

 2 Figure 2. Abri du Poisson, photogrammetry of the main facade + volume of the shelter, Cretin, Lescop, Camille Medjkouh Boulain 2017.

Figure 3 .

 3 Figure 3. Interpretations of the fish figure in bas-relief, by H. Breuil (a), D. Peyrony (b), and A.Leroi-Gourhan (diagrams in l'Atlas des grottes ornées, 1984, p. 156).

Figure 4 .

 4 Figure 4. Photogrammetry of fish engraving, photo Zotkina, 3D Zotkina and Lescop.

Figure 5 .

 5 Figure 5. Deviance map and slopes, ill. Lescop.

Figure 6 .

 6 Figure 6. Grasshopper definition for depth.

Figure 7 .

 7 Figure 7. Result for depth map with 2 filtering, above with the total bounding box, below with two closer values, more details appear.

Figure 8 .

 8 Figure 8. Depth map with contour lines.

Figure 9 .

 9 Figure 9. Grasshopper defintion for slopes visualization.

Figure 11 .

 11 Figure 11. Depth analysis, color version, workspace in Grasshopper.

L. LESCOP, L. ZOTKINA AND C. CRETIN


Alexandre Boyer

Sonia Ben Dhia

Low-Cost Broadband Electronic Coupler for Estimation of Radiated Emission of Integrated Circuits in TEM Cell

published or not. The documents may come

Abstract-TEM cell is a well-known method for the qualification of radiated electromagnetic emission from integrated circuits. Combined with a 180° hybrid coupler, it provides a simple method for quantifying radiated emission. However, typical transformer or coupled line-based hybrid couplers have limited bandwidth which cannot cover the full frequency range required by integrated circuit emission tests (150 kHz to 1 GHz). This paper presents the design and the validation of a low-cost broadband electronic version of a 180° hybrid coupler dedicated to the estimation of radiation emission from TEM cell measurements. The proposed prototype is able to cover a large frequency range (from DC to 1 GHz) with a sufficient sensitivity and dynamic range for radiated emission tests in TEM cell. The cost of the presented coupler is very reasonable as it is entirely based on commercial opamps.

Index Terms-Integrated Circuit, TEM cell, radiated emission measurement

I. INTRODUCTION

EM cell method, known also as IEC61967-2 [START_REF]Integrated Circuits -Measurement of Electromagnetic Emissions, 150 kHz to 1 GHz -Part 2: Measurement of Radiated Emissions -TEM Cell and Wideband TEM Cell Method[END_REF], is a popular test for the characterization of the radiated emission (RE) of integrated circuits (IC) due to its compact size and its good sensitivity compared to other RE test facilities (e.g. open area test site or anechoic chamber). The typical set-up of TEM cell RE measurement is presented in Fig. 1.a. The TEM cell is a rectangular stripline structure whose dimensions have been defined to ensure 50 Ω matching and transverse electromagnetic (TEM) mode propagation up to 1.2 GHz. Any small powered device placed within the cell excites its TEM mode and induces a voltage on both terminals, which is usually measured by a spectrum analyser.

Actually, the relationship between the measured voltage and RE, for example in free space far-field conditions, is not straightforward. If the excitation source is electrically small and placed at the cell center (z = 0), RE can be estimated according to the method described in [START_REF] Wilson | On Correlating TEM Cell and OATS Emission Measurements[END_REF], which is illustrated in Fig. 1.b. The excitation source (here the IC under test) can be expanded into equivalent electric and magnetic dipole moments PY and MX whose RE is easily calculable. They contribute respectively to electric (E) and magnetic-field (H) A. Boyer, S. Ben Dhia are with LAAS-CNRS, 7 avenue du colonel Roche, F-31077 Toulouse Cedex 4, France (e-mail: alexandre.boyer@laas.fr, sonia.ben.dhia@laas.fr). 2), where k0 is the propagation constant, ZC the TEM cell characteristic impedance and h the distance between the IC under test and the TEM cell septum.

𝑉 1 = 1 2 (𝑃 𝑌 + 𝑗𝑘 0 𝑀 𝑋 ) 𝑍 𝐶 ℎ = 1 2 (𝑉 𝐸 + 𝑉 𝐻 ) (1)
𝑉 2 = 1 2 (𝑃 𝑌 -𝑗𝑘 0 𝑀 𝑋 ) 𝑍 𝐶 ℎ = 1 2 (𝑉 𝐸 -𝑉 𝐻 ) (2)
Measuring the voltages VE and VH is essential to extract the equivalent electric and magnetic dipole moments. From these figures, not only the RE due to the IC in far-field, but also in

Low-Cost Broadband Electronic Coupler for Estimation of Radiated Emission of Integrated Circuits in TEM Cell

A. Boyer, S. Ben Dhia T near-field regions, can be accurately estimated. A typical experimental method to extract VE and VH relies on the use of a 180° hybrid coupler as presented in [START_REF] Kasturi | Quantifying Electric and Magnetic Field Coupling from Integrated Circuits with TEM Cell Measurements[END_REF], [START_REF] Blecic | Improved Estimation of Radiated Fields of Unintentional Radiators by Correction of the Impedance Mismatch Between a Transverse Electromagnetic Cell and a Hybrid Coupler[END_REF] for example. The method is illustrated in Fig. 1b. Depending on the frequency range, they are based on transformers, coupled transmission lines or waveguides. However, they never cover the full frequency range required by IEC61967 (150 kHz to 1 GHz), since they usually cover one or two decades of frequency. Moreover, they are expensive devices whose typical costs exceed several hundreds of euros. Surprisingly, in spite of its simplicity, no solution based on active devices has been proposed, certainly because of the required frequency and sensitivity constraints. However, low-cost high-frequency opamps are available whose frequency and noise characteristics comply with TEM cell test requirements. The purpose of this letter is to present the design and the characterization of a wideband home-made electronic coupler dedicated to the estimation of radiated emission of ICs from TEM cell measurements. Compared to conventional 180° hybrid couplers, the proposed coupler covers a large frequency range (from DC to 1 GHz) which complies with IEC61967 requirements at a reasonable price.

II. ELECTRONIC COUPLER DESIGN

The proposed coupler is a basic adder and substractor circuit based on the AD8000 op-amp from Analog Devices [5]. This high-speed current feedback amplifier is dedicated to IF/RF gain stage or high-resolution video graphic applications. With a small-signal bandwidth of 1.5 GHz, a high slew rate of 4100 V/µs, a low input voltage noise (1.6 nV/√Hz above 100 kHz), a low distortion (spurious-free dynamic range of 62 dBc at 50 MHz) and an excellent stability, it is a good candidate for the processing of voltage measured at TEM cell terminals.

A home-made prototype has been designed on a two-layer printed-circuit board (PCB). The PCB has not been mounted within a shielded cabinet. The overall cost of the design and fabrication of one prototype is 90 €, which makes it an affordable measurement device. The electrical schematic of the proposed coupler is presented in Fig. 2. Although its principle is simple, a careful design is required. The length of PCB traces must be limited and keep symmetrical to reduce parasitic output capacitance which may compromise stability and limit phase error. IEC61967-2 standard requires a voltage standing wave ratio (VSWR) less than 1.5:1, i.e. an input reflection coefficient less than -14 dB. SMA coaxial connectors are mounted at input and output terminals. The input impedance of the coupler must be controlled to ensure sufficient 50 Ω matching, because of the capacitive behaviour of the op-amp inputs (typically 3.6 pF).

The choice of resistors is a compromise between stability, gain flatness and minimization of noise. In this design, identical 330 Ω resistors are used so that the overall gain of the coupler is equal to 1. The output noise is estimated to 17 nV/√Hz above 100 kHz, i.e. -5 dBµV with 1 kHz RBW receiver, which is equivalent to noise floor of typical spectrum analyser. As the gain of the input stage of the coupler is equal to 2 and the maximum output voltage swing of the op-amp is 2V, the largest measurable signal at the input is equal to 1 V. The dynamic range between the largest and lowest harmonics of the input signal is limited by the distortion introduced by Fig. 2. Schematic of the proposed electronic coupler the op-amp. Below 100 MHz, the dynamic range exceeds 50 dB. As typical IC emission levels seldom exceed 50 dBµV, the dynamic range and the noise of the proposed electronic coupler comply with the requirements of the TEM cell measurement. This coupler has also other advantages compared to transformer or stripline-based hybrid couplers: it provides an excellent isolation between output terminals and there is no coupling loss between input and output. Moreover, the gain can be adjusted and increased, but it results in a reduced cut-off frequency.

III. EXPERIMENTAL CHARACTERIZATION

The performances of the designed prototype have been characterized. In order to prevent external interference issues, all the tests have been made in a Faraday cage. The reflection coefficients of both inputs have been measured, as shown in Fig. 3. They are less than -20 dB except between 800 MHz and 1.2 GHz, but they do not exceed the -14 dB requirement.

The noise introduced by the coupler has been characterized by measuring the noise floor of the spectrum analyser (Keysight N9341C) with and without the electronic coupler. Without the coupler, with a resolution bandwidth of 1 kHz, the noise floor of the spectrum analyser is -5 dBµV. With the coupler, it rises about 4 dB. If we suppose that the noise voltages produced by the spectrum analyser and the coupler are gaussian and uncorrelated, the amplitude of the noise introduced by the coupler can be estimated to -3.3 dBµV, which is acceptable for typical TEM cell emission measurements.

Correct sum and difference operations requires a small gain and phase differences between both signal channels. It depends on the design symmetry. The gain difference between signal channels is less than 2 dB up to 1 GHz, while the phase difference is less than 20°. Fig. 4 illustrates the frequency response of the sum and difference channel. The -6 dB cut-off frequency is reached at 1.01 GHz and 1.1 GHz. The gain is constant from DC to 100 MHz and varies in the range 100 Fig. 3. Characterization of the reflection coefficient of coupler inputs MHz to 1000 MHz, according to the choice of resistor values and an optional compensation output capacitor. Only a compromise between gain flatness and bandwidth can be found. However, the gain fluctuation can be characterized for calibration purpose.

IV. VALIDATION CASE

In order to validate the results delivered by our electronic coupler, the E and H field coupling induced voltages VE and VH are measured with a spectrum analyser (Keysight N9341C). The device under test is a 75 mm long 50 Ω microstrip line excited by a 10 MHz square signal with 4 ns transition time and a duty cycle of 50 %. The line ends are terminated by either 50 Ω load, shorted or opened. Depending on the line loading, electric, magnetic field, or both fields are predominant in nearfield region. For comparison purpose, measurements are also performed with a commercial 180° hybrid coupler (model ET Industries J-053-180) whose bandwidth is 500 MHz to 3000 MHz. Finally, measurement results are compared with the predicted values of VE and VH. The prediction relies on (3) and (4) [START_REF] Boyer | Basis of Electromagnetic Compatibility of Integrated Circuits[END_REF], which gives the electric and magnetic field coupling due to the equivalent electric and magnetic dipole moments PY and MX of the line which is supposed electrically short.

𝑉 𝐸 (𝑓) = 𝑃 𝑌 (𝑓) 𝑍 𝐶 ℎ = 𝑗2𝜋𝑓𝑐 𝑙𝑖𝑛𝑒 𝑙𝑖𝑛𝑒 (𝑓) 𝑍 𝐶 𝑙 𝑙𝑖𝑛𝑒 ℎ 𝑙𝑖𝑛𝑒 ℎ (3) 𝑉 𝐻 (𝑓) = 𝑗 2𝜋𝑓 𝑐 0 𝑀 𝑋 (𝑓) 𝑍 𝐶 ℎ = 𝑗 2𝜋𝑓 𝑐 0 𝐼 𝑙𝑖𝑛𝑒 (𝑓) 𝑍 𝐶 𝑙 𝑙𝑖𝑛𝑒 ℎ 𝑙𝑖𝑛𝑒 ℎ (4)
where f is the frequency, lline and hline are the length and the height of the microstrip line, cline its per-unit-length capacitance, and Vline and Iline the measured excitation voltage and current of the line. A Scilab script was developed to compute VE and VH voltages. The model was previously validated by comparing simulation results with S-parameter measurements between the line under test and the TEM cell. A good agreement was observed up to 1 GHz.

Initially, the line under test is terminated by a 50 Ω load. Measurement and simulation results of VE and VH voltages are compared in Fig. 5. For readability, only the envelop of emission spectra are plotted, which presents the maximum values taken by the spectrum. The measurements done with the proposed coupler fit with simulation, proving the validity of the measurements done with the proposed coupler up to 1 GHz. They also fit with the measurement done with the commercial 180° hybrid coupler in the range 500 MHz to 1 GHz.

Two other configurations are tested: either the line under test end is opened to enhance E field and limit H field generation, or the line under test end is shorted to enhance H field and limit E field generation. Measurement and simulation results of VE and VH voltages are compared in Fig. 6. In the top figure, the line under test is shorted and the E field coupling induced voltage is captured. In low frequency, as long as the line is electrically small, the voltage VE remains negligible as shown by the measurement done with the proposed electronic coupler and the simulation, which are in good agreement. In this situation, results provided by the commercial coupler are false up to 300 MHz since it is used outside its nominal frequency range. Above 500 MHz, measurements made with both couplers are also in agreement. Fig. 6 (bottom) presents similar results for the voltage VH when the end of the line is opened. The induced voltage due to magnetic field coupling remains negligible in low frequency. Measurements with the proposed electronic coupler are in good agreement with the simulation results, and with the measurement results obtained with the commercial 180° hybrid coupler between 500 MHz and 1 GHz.

V. CONCLUSION

In this letter, an electronic version of a 180° hybrid coupler has been designed in order to separate the contributions of electric and magnetic field coupling in emission measurement of ICs in TEM cell. This type of measurement is essential to estimate the radiated emission of ICs not only in far-field but also in near-field conditions. Compared to typical transformer or coupled line-based hybrid coupler, the proposed coupler relies on low-cost off-the-shelf op-amps. It covers all the frequency range required by the emission standard test IEC61967-2 (150 kHz to 1 GHz), without any excessive degradation of noise floor of the measurement receiver.

Fig. 1 .

 1 Fig. 1. a. Typical IC radiated emission measurement set-up; b. Extraction of the electric and magnetic-field coupling induced voltages coupling induced voltages in TEM cell, noted VE and VH. The TEM cell termination voltages, V1 and V2, are then obtained according to (1) and (2), where k0 is the propagation constant, ZC the TEM cell characteristic impedance and h the distance between the IC under test and the TEM cell septum.

Fig. 4 .Fig. 5 .

 45 Fig. 4. Characterization of the gain of the sum and difference channels

Fig. 6 .

 6 Fig. 6. Comparison between measurements with the proposed electronic coupler, a commercial 180° hybrid coupler and simulation of: (a) Line under test terminated by a short. E-field coupling induced voltage VE, (b) Line under test opened at its end. H-field coupling induced voltage VH


Martin John Barbetti
email: martin.barbetti@uwa.edu.au

Ian Pritchard

Jay-Ram Ram Lamichhane

Jean-Noël Aubertot

David Camilo

Corrales Munoz

Ming Pei

Tanveer N Khan

David Camilo Corrales

Ming Pei You

Challenges with Managing Disease Complexes during Application of Different Measures Against Foliar Diseases of Field Pea

Keywords: Pisum sativum, Ascochyta blight, Didymella pinodes, Phoma, Peronospora, Septoria, time of sowing, stand density

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

between pathogen species involved in the Ascochtya blight complex. In particular, D. pinodes can be favored and rendered dominant by management decisions in a given location or region. For example, in the mid-1960's in Canada, D. pinodes became the dominant species on field pea seed after the introduction of resistance to A. pisi [START_REF] Tivoli | Comparison of the epidemiology of Ascochyta blights on grain legumes[END_REF]. In Western Australia, the pathogen population associated with the Ascochyta blight has been dynamic across time and geographic location (Tran et al. 2014a), to the extent that P. koolunga can be even more virulent than D. pinodes and P. pinodella on stems and more virulent than D. pinodes on leaves of field pea [START_REF] Tran | Relative host resistance to black spot disease in field pea (Pisum sativum) is determined by individual pathogens[END_REF].

Significant yield losses from Ascochyta blight are widely reported, and while they can be large, they vary depending upon environmental conditions and cropping systems. Examples of such variation include the following: France, where in 7 years out of 10, Ascochyta blight reduced yield by 20% [START_REF] Maufras | L'anthracnose[END_REF]; in Canada, where average yield losses approximate 10%, but with losses of >50% in some situations [START_REF] Xue | Effects of timings of inoculation with Mycosphaerella pinodes on yield and seed infection of field pea[END_REF]; and in Australia, where yield losses ≥10% occurred annually [START_REF] Bretag | The epidemiology and control of Ascochyta blight in field peas: a review[END_REF]) but severe losses >50% have been reported (Salam et al. 2011c;[START_REF] Khan | Mycosphaerella pinodes and its management in field pea: challenges and opportunities[END_REF].

Even the extent of severe yield losses vary, ranging from 30-75% for Australia, France and Canada [START_REF] Xue | Effects of timings of inoculation with Mycosphaerella pinodes on yield and seed infection of field pea[END_REF][START_REF] Roger | Effects of temperature and moisture on disease and fruit body development of Mycosphaerella pinodes on pea (Pisum sativum)[END_REF][START_REF] Kaiser | Foliar diseases of cool season food legumes and their control[END_REF][START_REF] Bretag | Foliar diseases caused by fungi[END_REF][START_REF] Mcdonald | Effects of crop rotation, residue retention and sowing time on the incidence and survival of Ascochyta blight and its effect on grain yield of field peas (Pisum sativum L.)[END_REF]. In Western Australia, Ascochyta blight is considered the overriding reason limiting the area sown to field pea (Salam et al. 2011a,b,c;[START_REF] Khan | Mycosphaerella pinodes and its management in field pea: challenges and opportunities[END_REF].

Unfortunately, Ascochyta blight remains extremely difficult to manage, mainly due to a paucity of effective host plant resistance, and a lack of cost-effective fungicide sprays, and even multiple fungicide spray applications throughout much of the growing season may still not provide effective management, as is the case in Western Australia (Salam et al. 2011c; [START_REF] Khan | Mycosphaerella pinodes and its management in field pea: challenges and opportunities[END_REF]. In Australia, where the disease is particularly devastating [START_REF] Salam | Blackspot Manager" for understanding blackspot of peas and Ascochyta blight management. Lupin and Pulse Updates[END_REF], while there can be small differences in susceptibility between varieties, there remains a lack of effective resistance in commercial cultivars [START_REF] Bretag | The epidemiology and control of Ascochyta blight in field peas: a review[END_REF][START_REF] Khan | Mycosphaerella pinodes and its management in field pea: challenges and opportunities[END_REF]Tran et al. 2014b[START_REF] Tran | Relative host resistance to black spot disease in field pea (Pisum sativum) is determined by individual pathogens[END_REF]. This has meant that management of Ascochyta blight predominantly continues to rely on cultural options. Such cultural management options involve two main approaches.

Firstly, minimising inoculum carry-over and survival of inoculum on crop residues and in soil, such as by crop rotation [START_REF] Khan | Mycosphaerella pinodes and its management in field pea: challenges and opportunities[END_REF]. Secondly, reducing infection of the crop from airborne inoculum arising from infested residues, such as by attempting to avoid the main ascospore showers [START_REF] Mcdonald | Effects of crop rotation, residue retention and sowing time on the incidence and survival of Ascochyta blight and its effect on grain yield of field peas (Pisum sativum L.)[END_REF][START_REF] Khan | Mycosphaerella pinodes and its management in field pea: challenges and opportunities[END_REF]. For example, in Australia, delaying sowing of field pea crops is widely utilized to ensure major ascospore showers precede field pea crop germination (Salam et al. 2011a,b,c), despite such an approach is not always an option in other countries, for example, in Canada due to the short season there. Even where delayed sowing it is an option for reducing Ascochyta blight, such an approach can incur unsustainable yield penalties from end-of-season moisture stress (Salam et al. 2011a,b,c;[START_REF] Khan | Mycosphaerella pinodes and its management in field pea: challenges and opportunities[END_REF]. Other cultural management possibilities include lower planting densities to attempt to reduce both humidity (moisture) in the canopy and/or plant-to-plant spread of the disease.

Other foliar diseases outside of the Ascochyta blight complex can also be significant. First, downy mildew is also considered an important disease worldwide [START_REF] Biddle | Compendium of pea diseases and pests (2nd edn)[END_REF][START_REF] Kraft | Foliar Diseases of Local or Minor Imortance In 'Compendium of pea diseases and pests (2nd edn)[END_REF], including in Australia [START_REF] Barbetti | Diseases of peas[END_REF][START_REF] Davidson | Screening field pea germplasm for resistance to downy mildew (Peronospora viciae) and powdery mildew (Erysiphe pisi)[END_REF]Davidson et al. , 2011a)), significantly reducing seed yield [START_REF] Biddle | Compendium of pea diseases and pests (2nd edn)[END_REF][START_REF] Davidson | Screening field pea germplasm for resistance to downy mildew (Peronospora viciae) and powdery mildew (Erysiphe pisi)[END_REF]. While metalaxyl as a seed dressing can manage downy mildew [START_REF] Biddle | Compendium of pea diseases and pests (2nd edn)[END_REF], farmers are reluctant to do so because of perceived cost or the deleterious effect upon rhizobium inoculant [START_REF] Davidson | Pea yield decline syndrome in South Australia: the role of diseases and the impact of agronomic practices[END_REF]. There is considerable variation within the P. viciae populations, both in Australia (Davidson et al. 2011) and elsewhere, such as in the United Kingdom [START_REF] Taylor | Pathotypes of Peronospora viciae in Britain[END_REF]). Oospores of P. viciae readily survive for long periods in soil (van der [START_REF] Van Der Gaag | Survival characteristics of oospore populations of Peronospora viciae f. sp. pisi in soil[END_REF]) and pathogen elimination via a diversified crop sequence is challenging. Second, Septoria blight also occurs on field pea in some regions, particularly those with higher rainfall. However, in contrast to downy mildew, Septoria blight is generally considered a more minor foliar disease of local importance [START_REF] Biddle | Compendium of pea diseases and pests (2nd edn)[END_REF], for example, in Australia [START_REF] Barbetti | Diseases of peas[END_REF]) and North America [START_REF] Biddle | Compendium of pea diseases and pests (2nd edn)[END_REF].

In Western Australia, delaying sowing is widely recommended as the primary means of reducing the level of Ascochyta blight [START_REF] Salam | Blackspot Manager" for understanding blackspot of peas and Ascochyta blight management. Lupin and Pulse Updates[END_REF](Salam et al. , 2011a,b,c),b,c). However, the effects of delayed time of sowing on other foliar diseases outside the Ascochyta blight complex, and the possible effects of other management options, such as increasing sowing density or diversifying varieties, have not been determined. There is clearly a need to re-evaluate both the 'current recommended' and 'potential alternative' disease management practices. Hence, field studies were undertaken across five field locations in Western Australia, to determine the relative changes in disease severities of up to four foliar pathogens (genera Didymella, Phoma, Peronospora, Septoria), and consequent seed yield, from varying time of sowing and sowing density of four different field pea varieties.

Materials and Methods

General methods. Trials were all sown in the same year (1989) at five field locations in Western Australia; Avondale, East Beverley, Lake Grace, Merredin and Moora. Conventional field pea varieties used were Alma, Dundale, Pennant and Wirrega. Alma and Dundale have greenish-brown seed coats and are 'Dun' type. Wirrega and Pennant are white seeded and, as such, are preferred commercially.Each variety was sown using a cone seeder to three target plant densities of 25, 50, and 100 plants m -2 , and with three sowing dates (early, mid and late (see location-specific details below). Each individual field plot size was 1.44 x 25 m. (1923) where %DI = (sum of all numerical grades) x 100 ÷ (total number of plants scored x maximum rating score). These data for downy mildew and Septoria are presented across different assessment times (see details below). For each location, disease severity assessments were undertaken at multiple times at a range of dates across the season that allowed plants from each sowing time to be rated for disease at 80 days postsowing; i.e., the actual dates representative of 80 days after sowing for each time of sowing (see details below for each location).

Plant density measurements were made on all field plots 3 weeks after germination by counting the numbers of seedlings in each of 10 random quadrats, each 0.5 x 0.5 m, per plot. Sown and actual seedling density data is provided in Fig. 1. Grain yield was assessed by fully mechanically harvesting all plots and recording seed mass per plot that was then converted to kg ha -1 . Experimental design and statistical analyses. A split plot design was used with three replicates and a plot size of 25 m x 1.44 m. There were five separate field locations and all experiments were done in the one year (1989). Plots were blocked into times of sowing, with varieties and seeding rates being completely randomised within time of sowing blocks.

One and two way ANOVAs were conducted using GenStat (VSN International, 2019). Fisher's least significant differences (LSDs) were used to separate significant differences between treatments (P≤0.05).

Results

Results overview. Only data for significant effects of time of sowing, sowing density and cultivar on severity of Ascochyta blight (Fig. 2), downy mildew (Fig. 3), Septoria blight (Fig. 4), and yield (Fig. 5) are provided. Delaying sowing of field pea significantly (P<0.05) reduced severity of Ascochyta blight (all five locations; Fig. 2) and Septoria blight (1 location; Fig. 4), increased severity of downy mildew (4 locations; Fig. 3); but had no effect on seed yield (Fig. 5). In relation to Ascochyta blight severity at 80 days after sowing, at all locations the early time of sowing had more severe Ascochyta blight than the mid and late times of sowing (Fig. 2).). Increased sowing density (actual plant density from 20-25 plants m -2 to 58-78 plants m -2 ; Fig. 1) significantly (P<0.05) increased Ascochyta blight (4 locations; Fig. 2) and downy mildew (1 location; Fig. 3); and increased seed yield at four locations, the latter irrespective of sowing date or variety (Fig. 5) (with the exception of Dundale at Avondale and Merredin locations that showed no response to increasing plant densities).

However, increasing the target plant density from 36-50 and 58-78 plants m -2 (Fig. 1) had no effect on seed yield (Fig. 5).

Compared with varieties Dundale, Wirrega and Pennant, variety Alma showed significantly (P<0.05) less severe Ascochyta

(1 location), downy mildew (1 location) and Septoria blight (1 location). Grain yield was highest for the early time of sowing at Lake Grace, Moora and Avondale (Fig. 5). At Avondale and East Beverley, delaying to the late time of sowing had no significant effect on grain yield. However, at both Lake Grace and East Beverley, the mid time of sowing yielded significantly (P<0.05) less than the early and late times of sowing. Varieties Alma, Dundale and Wirrega were the highest yielding varieties at four locations, with Pennant yielding significantly (P<0.05) less than these other three varieties (Fig. 5). The percentage of isolations of individual Ascochyta blight pathogens varied greatly, and at 80 days after first time of sowing showed Didymella from 25-93% and Phoma from 6-23% across the five field locations. There was a predominance of Didymella by a 3.5 to 16 fold across the Avondale, East Beverley, Merredin and Moora locations, but <1 fold predominance of Didymella at Lake Grace (Table 1).

Location-specific results -Avondale. For Ascochyta blight, at 80 days after sowing, there were significant effects of time of sowing (P<0.001) with the early time of sowing showing more severe Ascochyta blight (P<0.01) than the mid and late times of sowing (Fig. 2). There were no effects of variety but there was a significant effect (P<0.01) of sowing density

where Ascochyta blight was more severe (P<0.05) at a sowing density of 100 plants m -2 compared to 25 plants m -2 (Fig.

2

). By August 28, there was a significant effect of time of sowing (P<0.001), where early time of sowing had more severe Ascochyta blight (P<0.05) than the mid time of sowing and this in turn had more severe disease (P<0.05) than the late time of sowing. By September 8, there was a significant effect of time of sowing (P<0.001), where the early time of sowing had more severe Ascochyta blight (P<0.05) than the mid and late times of sowing. By September 19, the early time of sowing had more severe Ascochyta blight (P<0.05) than the mid time of sowing and this in turn had more severe disease (P<0.05) than the late time of sowing. By October 13, there was a significant effect of time of sowing (P<0.001), where the early time of sowing had more severe Ascochyta blight (P<0.05) than the mid time of sowing and this in turn had more severe disease than the late time of sowing. There was a significant effect (P<0.05) of sowing density on Ascochyta blight where disease was more severe (P<0.05) at a sowing density of 100 plants m -2 compared to 25 plants m -2 . There was also a significant (P<0.05) interaction of time of sowing with sowing density. At 80 days after first time of sowing, direct examination and plating Ascochyta blight lesions on leaves and stems onto potato dextrose agar indicated that Didymella had an excellent association with lesions (84%) while Phoma a much lower association (23%) for this same range of lesions (Table 1).

For downy mildew, there was a rapid decrease in severity over the three assessments from August 28 to September 19. Downy mildew was more severe (P<0.05) with delayed time of sowing at both August 28 and September 8, but not at September 19 (Fig. 3).

For Septoria blight, by August 28, there were significant effects of time of sowing, variety and sowing density (all P<0.001) and a significant interaction (P<0.05) of time of sowing with sowing density in relation to its severity. Early and mid-times of sowing had more severe Septoria blight (P<0.05), compared to the late time of sowing. Alma and Dundale had more severe Septoria blight (P<0.05) than Pennant and Wirrega. Septoria blight was more severe (P<0.05) at a sowing density of 100 plants m -2 compared with 50 plants m -2 which in turn had more severe disease than at 25 plants m -2 . By September 8, there were significant effects of time of sowing (P<0.01), variety (P<0.001) and sowing density (P<0.001).

The early time of sowing had more severe Septoria blight (P<0.05) compared to the mid and late times of sowing. Alma had more severe Septoria blight (P<0.05) than Pennant and Wirrega, while Dundale had more disease (P<0.05) than Pennant. Septoria blight was more severe (P<0.05) at a sowing density of 100 plants m -2 compared to 50 plants m -2 , which in turn had more severe disease (P<0.05) than at 25 plants m -2 (Fig. 4).

Location-specific results -East Beverley. For Ascochyta blight, by 80 days after sowing, disease levels were generally low and the early time of sowing had more severe Ascochyta blight than the mid and late times of sowing (Fig. 2). Ascochyta blight was more severe (P<0.05) both in Alma compared to Pennant and Wirrega, and at sowing density 100 plants m -2 compared to 25 plants m -2 (Fig. 2). There was a significant interaction of time of sowing with both variety and with sowing density (both P<0.01). By August 14, there were significant effects of time of sowing (P<0.001), variety dextrose agar indicated that Didymella had excellent association (98%) with lesions while Phoma had poor association (6%) with these lesions (Table 1).

For downy mildew for assessments made at August 14 and 28, severity was greater (P<0.05) in the mid and late times of sowing compared with the early time of sowing where only a trace of downy mildew was observed (Fig. 3). Downy mildew declined rapidly over this assessment period and was no longer evident by a September 8 assessment. No Septoria blight appeared at this site.

Location-specific results -Lake Grace. For Ascochyta blight at 80 days after sowing, there were significant effects of time of sowing (P<0.001) and sowing density (P<0.01) and a significant interaction between time of sowing with sowing density (P<0.001) in relation to severity of Ascochyta blight. The early time of sowing had more severe Ascochyta blight (P<0.05) than the mid and late times of sowing (Fig. 2). Disease was more severe (P<0.05) at a sowing density of 100 plants m -2 compared to 50 or 25 plants m -2 (Fig. 2). Direct examination and plating Ascochyta blight lesions on leaves and stems onto potato dextrose agar as sampled at 80 days after the first time of sowing indicated that Didymella had excellent association (98%) with lesions while Phoma had poor association (6%) with these lesions (Table 1). There was no downy mildew or Septoria at this site.

Location-specific results -Merredin. For Ascochyta blight, by 80 days after sowing, the only significant effect was time of sowing (P<0.001), where the early and mid times of sowing had more severe Ascochyta blight (P<0.05) than the late time of sowing (Fig. 2). Disease levels were generally low and the early and mid times of sowing had more severe Ascochyta blight (P<0.05) than the late time of sowing (Fig. 2). There were no effects of sowing density or differences in disease susceptibility between the varieties. By July 24, again, the only significant effect was time of sowing (P<0.001).

The early and mid-time of sowing had more severe Ascochyta blight than the late time of sowing. For both the August 7 and 27 assessments, there were significant effects of time of sowing, variety, and sowing density (all P<0.001) and a significant interaction between time of sowing with variety (P<0.001) and with sowing density (P<0.05) for August 7 and Direct examination and plating Ascochyta blight lesions on leaves and stems onto potato dextrose agar as sampled 80 days after the first time of sowing showed that Didymella had good association (77%) with lesions, while Phoma had much lower association (12%) (Table 1).

For downy mildew, at August 27, there were significant effects of time of sowing, variety, and sowing density, and a significant interaction between time of sowing with variety and with sowing density (all P<0.001) in relation to its severity.

There was more severe downy mildew (P<0.05) in the late time of sowing compared to the mid time of sowing which in turn had more severe disease than the early time of sowing (Fig. 3). Alma had more severe downy mildew compared with Dundale, which in turn had more than Pennant, that in turn had more than Wirrega (all P<0.05); these effects particularly evident at the late time of sowing (Fig. 3). Downy mildew was more severe (P<0.05) at 50 and 100 plants m -2 seeding rate compared to 25 plants m -2 , particularly for the late time of sowing (Fig. 3). Across all times of sowing there was a very rapid decrease in the severity of downy mildew as the season progressed, from a %DI of 55 to 2, 15 to 0.1 and 0.5 to <0.01, respectively, for the third, second and first times of sowing. There was no Septoria blight at this site.

Location-specific results -Moora. For Ascochyta blight, by 80 days after sowing, there were significant effects of time of sowing (P<0.001), and a significant interaction between time of sowing with variety (P<0.05) in relation to severity of Ascochyta blight. The early time of sowing had more severe Ascochyta blight (P<0.05) than the mid and late times of sowing (Fig. 2). There were no effects of variety or sowing density. By August 15, there were significant effects of time of sowing (P<0.001), and a significant interaction between time of sowing with variety (P<0.05) in relation to severity of Ascochyta blight. The early time of sowing had 6-fold more severe (P<0.05) Ascochyta blight compared with the mid and late times of sowing. By September 4 and at September 18, the only significant effect was from time of sowing (P<0.001) in relation to severity of Ascochyta blight. At both times, the early time of sowing showed more severe Ascochyta blight (P<0.05) compared with the mid and late times of sowing. Direct examination and plating Ascochyta blight lesions on leaves and stems onto potato dextrose agar as sampled at 80 days after the first time of sowing indicated that Didymella had excellent association (93%) with lesions while Phoma had poor association (12%) with these lesions (Table 1).

For downy mildew assessments across the period August 15 to September 4 and 18, there was a rapid decrease in severity, being most severe (P<0.05) for the late time of sowing at both August 15 and September 4 but not at September 18 assessments (Fig. 3). By August 15, there was also a significant (P<0.001) interaction between variety and sowing density, where most severe disease on Alma was at sowing densities 50 and then 25 plants m -2 , on Dundale at sowing densities 50 then 100 plants m -2 , on Pennant at sowing densities 100 then 50 plants m -2 , and on Wirrega at sowing densities 25 then 100 plants m -2 (Fig. 3). There was no Septoria blight at this site.

Discussion

These studies, undertaken across five field locations in Western Australia in a single year (1989), highlight the relative changes in disease severity and subsequent field pea yield from up to four foliar pathogens associated with the field pea foliar disease complex (viz. genera Didymella, Phoma, Peronospora, Septoria). There were contrasting and locationspecific effects from delaying sowing of field pea, where it reduced severity of Ascochyta blight (all five locations) and Septoria blight (1 location), increased severity of downy mildew (4 locations); but, had no effect on seed yield. In relation to Ascochyta blight severity at 80 days after sowing, at all locations the early time of sowing had more severe Ascochyta blight than the mid and late times of sowing. Where seasonal conditions allow, delayed sowing is widely recommended and practiced across southern Australia (Salam et al. 2011c,d;[START_REF] Khan | Mycosphaerella pinodes and its management in field pea: challenges and opportunities[END_REF]). However, an overriding challenge with utilizing a delayed time of sowing approach, was that while it reduced Ascochyta blight and Septoria blight, the end of season water stress for later sowings precluded any yield advantage from reduced Ascochyta and Septoria blights. That grain yield was highest in the current study for the early time of sowing at three locations highlights these seasonal challenges with delaying sowing, challenges as noted earlier by Salam et al. (2011c,e).

Plant density effects were also often location-specific. For example, at four locations, increasing sowing density significantly increased Ascochyta blight (4 locations) and downy mildew (1 location). Despite this increase in Ascochyta blight and downy mildew, there was increased seed yield at four locations, irrespective of sowing date for all these locations and irrespective of variety for three of these locations. Towards offsetting the end of season water deficit, especially where delayed sowing has been employed as the major Ascochyta blight management strategy, there remains further scope to better exploit this particular cultural management option. The precise reasons for the variations in the severity of the different diseases in the current study were not determined, but many factors are known to influence their epidemic development. For example, for D. pinodes infection and development in the field, plant height, growth habit, canopy morphology, lodging and precocity, are all known to effect the microclimate in the canopy and conidia splash dispersal [START_REF] Schoeny | Assessment of airborne primary inoculum availability and modelling of disease onset of Ascochyta blight in field peas[END_REF][START_REF] Schoeny | Effect of pea canopy architecture on splash dispersal of Mycosphaerella pinodes conidia[END_REF]Le May et al. 2009a,b;[START_REF] Fernández-Aparicio | Intercropping reduces Mycosphaerella pinodes severity and delays upward progress on the pea plant[END_REF]). In addition, there will be significant interactions between the different pathogens as has been shown for those within Ascochyta blight complex, not only in terms of the consequent overall severity of disease, but the differential disease severities across the different plant components (e.g., leaf, stem, epicotyl, root) [START_REF] Tran | Relative host resistance to black spot disease in field pea (Pisum sativum) is determined by individual pathogens[END_REF][START_REF] Tran | Pea black spot disease complex on field pea: dissecting the roles of the different pathogens in causing epicotyl and root disease[END_REF].

There has been a failure to develop varieties with effective host resistance to Ascochyta blight, and reasons for this are many and varied. First, as demonstrated in both current and earlier studies (e.g., Tran et al. 2014a), the relative proportions of component pathogens of the Ascochyta blight complex fluctuate widely across time and geographic locations. This is particularly problematic for field screening and selection for varietal resistance, where resistance(s) are unintentionally identified to the particular pathogen complex components prevailing at each particular field screening location. It is also problematic for subsequent commercialisation of any such resistance(s) as their deployment shifts the composition of different pathogens within the complex towards other pathogens in the Ascochyta blight complex less restricted by that particular resistance. The challenges in developing varietal resistance against multiple pathogens of the Ascochyta blight complex have been previously reported where individual defence proteins down-regulated against P.

koolunga [START_REF] Tran | Expression of defense related genes in stems and leaves of resistant and susceptible field pea (Pisum sativum) during infection by Phoma koolunga[END_REF]) are in fact up-regulated against D. pinodes (Prioul-Gervais et al 2011; Fondevilla et al. 2001).

Second, that the expressions of host resistance across field pea genotypes are generally different on stem versus leaf [START_REF] Tran | Relative host resistance to black spot disease in field pea (Pisum sativum) is determined by individual pathogens[END_REF], with stem and leaf resistances generally being inherited independently. For example, the two non-allelic stem resistance genes, Rmp1 and Rmp2, differ from the two leaf resistance genes, Rmp3 and Rmp4 [START_REF] Clulow | Genetic analysis of resistance to Mycosphaerella pinodes in pea seedlings[END_REF].

Further, some screening tests under controlled conditions remain focused solely on either stems or leaves rather than including both plant components. Third, that no truly effective sources of resistance against D. pinodes have been commercialized. However, [START_REF] Tran | Relative host resistance to black spot disease in field pea (Pisum sativum) is determined by individual pathogens[END_REF] showed that it is possible to achieve improved host resistance if germplasm is screened against each individual pathogen of the Ascochyta blight complex and separately on both stems and on leaves.

Such an approach potentially offers improved outcomes for field pea breeders and producers, provided that such resistances could subsequently be pyramided together. However, despite these three major challenges to the search for improved host resistance, it is encouraging that some identified 'less susceptible' pea genotypes, both in the current study and subsequently, likely facilitate a modest basis for combining with a range of cultural and/or fungicidal management options into Integrated Disease Management packages against Ascochyta blight.

While yield losses due to Ascochyta blight can be large, these also vary depending upon environmental conditions, location and cropping practices, as highlighted in the current study. Similar variations are also reported in other studies, such as for France, where only in 7 years out of 10 does Ascochyta blight reduce yield by 20% [START_REF] Maufras | L'anthracnose[END_REF]; for Canada, where average yield losses approximate 10% but can exceed 50% in some situations [START_REF] Xue | Effects of timings of inoculation with Mycosphaerella pinodes on yield and seed infection of field pea[END_REF]; and in Australia, where overall annual average yield losses approximating 10% [START_REF] Bretag | The epidemiology and control of Ascochyta blight in field peas: a review[END_REF]) hide the extensive variation in losses across different locations. In all three countries, yield losses can range from relatively low to as high as 30-75%, with losses dependent upon the particular season [START_REF] Xue | Effects of timings of inoculation with Mycosphaerella pinodes on yield and seed infection of field pea[END_REF][START_REF] Roger | Effects of temperature and moisture on disease and fruit body development of Mycosphaerella pinodes on pea (Pisum sativum)[END_REF][START_REF] Kaiser | Foliar diseases of cool season food legumes and their control[END_REF][START_REF] Bretag | Foliar diseases caused by fungi[END_REF][START_REF] Mcdonald | Effects of crop rotation, residue retention and sowing time on the incidence and survival of Ascochyta blight and its effect on grain yield of field peas (Pisum sativum L.)[END_REF]. However, of even greater challenge, is the wider foliar disease complex than just Ascochyta blight. For example, in the current study, variety Alma showed less severe Ascochyta (1 location), downy mildew (1 location) and Septoria blight (1 location) compared with varieties Dundale, Wirrega and Pennant. However, there was no indication that overall the greenish-brown seeded 'Dun' types Alma and Dundale were overall more resistant thant the white seeded Wirrega and Pennant varieties. Hence, a broader approach that includes searching for varietal resistance(s)

to prevailing foliar diseases outside the Ascochyta blight complex should be beneficial in the long term. However, in the interim until improved host resistance against at least the most damaging pathogens within the Ascochyta blight complex becomes available, there is clearly a need to better exploit a wider range of cultural management options, including those in the current study.

The percentage of isolations of individual Ascochyta blight pathogens varied greatly in the current study, yielding Didymella from 25-93% and Phoma from 6-23% across the five field locations. This fluctuating nature of individual pathogen types and proportions within the Ascochyta blight complex, along with variation in occurrence of Peronospora and Septoria, highlights the challenges to understand and manage the complexities of co-occurring different foliar pathogens of field pea. Even just the different individual pathogens in the Ascochyta blight complex can 'disappear' or 'appear'. For example, while A. pisi was reported in Western Australia in 1912, 1927 and 1968, it was not found either in the current study or in the comprehensive survey of Ascochyta blight pathogens undertaken by Tran et al. (2014a). Further, B. exigua var. exigua was recorded at three locations in Western Australia in 1989 (Tran et al. 2014a), but not subsequently; and P. herbarum and P. glomerata were only identified in 2010 and 2012 (Tran et al. 2014a), respectively.

That one or more species of the complex can 'disappear' or 'reappear' is well documented (e.g., [START_REF] Li | First report of Phoma herbarum on field pea (Pisum sativum) in Australia[END_REF][START_REF] Li | First report of black spot caused by Boerema exigua var. exigua on field pea in Australia[END_REF]Tran et al. 2014a) and highlights the highly fluctuating nature of the Ascochyta blight complex, certainly for Western Australia.

Further examples include a survey across South Australia in 1976 where A. pisi was the most prevalent pathogen causing leaf and pod spot on field pea [START_REF] Ali | Selection of pea lines for resistance to pathotypes of Ascochyta pinodes, A. pisi and Phoma medicaginis var. pinodella[END_REF][START_REF] Ali | Current status and future strategy in breeding pea to improve resistance to biotic and abiotic stresses[END_REF], and in Victoria, Australia, where [START_REF] Bretag | Importance of seed-borne inoculum in the etiology of the Ascochyta blight complex of field peas (Pisum sativum L) grown in Victoria[END_REF] reported 95% of isolates from >435 seed lots tested were D. pinodes, only 4% were P. pinodella and 1% A. pisi. Similarly, in France, A.

pisi was found at high incidence in the southern regions, but D. pinodes remained the dominant pathogen. In France, Le May et al. (2009b) found both antagonism and synergism between the different pathogens of the pea Ascochyta blight complex. In Canada 85% of seed lots infected with one or more pea Ascochyta blight pathogens were infected by A. pisi [START_REF] Hwang | Effects of seed infection by Ascochyta spp., fungicide seed treatment, and cultivar on yield parameters of field pea under field conditions[END_REF][START_REF] Tivoli | Comparison of the epidemiology of Ascochyta blights on grain legumes[END_REF]. In Spain, a pea Ascochyta blight epidemic in 2005-2006 was primarily attributed to A. pisi [START_REF] Kaiser | First report of Ascochyta blight outbreak of pea caused by Ascochyta pisi in Spain[END_REF], despite it being widely considered the least damaging among the pathogens in the pea Ascochyta blight complex [START_REF] Wallen | Field evaluation and the importance of the Ascochyta complex on peas[END_REF]. In contrast, in India, only 1 out of 40 Ascochyta blight isolates recovered across pea growing areas of Himachal Pradesh was A. pisi [START_REF] Padder | Identification and genetic diversity analysis of Ascochyta species associated with blight complex of pea in a northwestern hill state of India[END_REF].

Dominance, or otherwise, of any foliar pathogen in a region or location can be strongly influenced by crop management decisions. For example, development and deployment of even low levels of host resistance against particular pathogens within the foliar disease complex likely radically shifts the composition of the population towards pathogen species that are less sensitive to particular host resistance(s) (Tran et al. 2014a). An example is for Canada, where introduction of resistance to A. pisi in the mid-1960's resulted in D. pinodes becoming the dominant species on field pea seed [START_REF] Tivoli | Comparison of the epidemiology of Ascochyta blights on grain legumes[END_REF]. The same can situation can occur with fungicides, as the efficacy of fungicides currently applied to manage pea Ascochyta blight in Australia (e.g., [START_REF] Bretag | The epidemiology and control of Ascochyta blight in field peas: a review[END_REF][START_REF] Mcmurray | Combining management and breeding advances to improve field pea (Pisum sativum L.) grain yields under changing climatic conditions in south-eastern Australia[END_REF] or elsewhere (e.g., [START_REF] Chongo | Foliar fungicides to manage Ascochyta blight Ascochyta rabiei of chickpea in Canada[END_REF][START_REF] Maude | The control of fungal seed-borne diseases by means of a thiram seed soak[END_REF][START_REF] Kyle | Seed treatments with benomyl and other fungicides for the control of Ascochyta pisi on peas[END_REF][START_REF] Warkentin | Fungicidal control of Ascochyta blight of field pea[END_REF] are not equally effective across the spectrum of pathogens within the Ascochyta blight complex. In fact, in three other field trials in Western Australia conducted in the same year (1989) as the current studies, diverse fungicide seed and soil treatments for Ascochyta blight management were also found to be location-specific, effective at only at one of the three locations (MJ Barbetti et al., unpubl. data). Hence, current management practices involving host resistance and/or fungicides actually ensure that the pea foliar disease complex, particularly the Ascochyta blight component, remains severe despite advances in management practices, especially plant breeding programs. These examples highlight the fluidity of composition of the Ascochyta blight complex across time, geographic location and cropping practices, variability that continues to impede improved disease management in relation to deployment of effective host resistance and/or fungicidal management measures. Tran et al. (2014a) highlighted how failure to understand the true nature and modus operandi of the different pathogens within the pea Ascochyta blight complex impedes their management, despite its variable nature having been long-established.

Historically, there has been a strong focus on the above ground component of the Ascochyta blight complex, compared with much less focus on the soilborne component of this pathogen complex. Even when reported on roots, D. pinodes and P. pinodella have frequently been noted simply as 'non virulent pathogens' or as pathogens 'occasionally isolated from roots' (e.g., [START_REF] Tu | Incidence and etiology of pea rots in southwestern Ontario[END_REF][START_REF] Tu | Integrated control of the pea root rot disease complex in Ontario[END_REF][START_REF] Tu | Management of root rot diseases of peas, beans, and tomatoes[END_REF][START_REF] Persson | Prevalence and pathogenicity of foot and root rot pathogens of pea in southern Scandinavia[END_REF]). Yet, D. pinodes, P. pinodella and P. koolunga not only survive as mycelium on infected pea trash, but also as sclerotia and/or chlamydospores in the soil. Hence, it is not surprising that root disease of field peas from D. pinodes and P. pinodella occurs widely in fields previously cropped to peas [START_REF] Bretag | The epidemiology and control of Ascochyta blight in field peas: a review[END_REF], that these pathogens readily attack roots and epicotyls (Bretag et al. 2001[START_REF] Bretag | The epidemiology and control of Ascochyta blight in field peas: a review[END_REF][START_REF] Tran | Pea black spot disease complex on field pea: dissecting the roles of the different pathogens in causing epicotyl and root disease[END_REF], and that there is strong correlation between the level of soilborne Ascochyta blight fungi and decline in field pea yield (Bretag et al. 2001). In the Netherlands, [START_REF] Oyarzun | Pathogenic fungi involved in root-rot of peas in the Netherlands and their physiological specialization[END_REF] reported D. pinodes and P. pinodella as prevalent root rot pathogens;

while in Sweden and Denmark, [START_REF] Persson | Prevalence and pathogenicity of foot and root rot pathogens of pea in southern Scandinavia[END_REF] found P. pinodella to be one of the most frequently isolated pathogens from pea roots. Significantly, [START_REF] Tran | Pea black spot disease complex on field pea: dissecting the roles of the different pathogens in causing epicotyl and root disease[END_REF] found that combinations of the different Ascochyta blight pathogens synergistically caused the most severe disease on epicotyls, lateral and tap roots. Perhaps this is a consequence not only of all three pathogens naturally co-occurring together in soil (Davidson et al. 2011), but that soilborne pathogens readily 'cooperate' as a complex to increase disease severity on legumes [START_REF] Barbetti | Response of subterranean clover cultivars to root rot fungi[END_REF][START_REF] Foster | Widespread decline of subterranean clover pastures across diverse climatic zones is driven by soilborne root disease pathogen complexes[END_REF]. Clearly, the soilborne component of the Ascochyta blight complex needs more serious consideration as it magnifies the challenge in resolving disease management solely through host resistance and/or fungicidal strategies onlny targeting the foliar component of field pea. There is a need to seriously reconsider and further investigate cultural management options, including those in the current study, for their potential to be effective components towards improved management of the Ascochyta blight complex both above and below ground.

Modeling offers the best practical opportunity to both understand and resolve the complexities of managing Ascochyta blight complexes, both below and above ground, and the wider foliar disease complex. There are several pre-existing models for Ascochyta blight, especially from France and Australia, but these only specifically deal with the foliar disease component. These include those involving: radiation use and interception efficiency and photosynthetically active radiation, and/or canopy structure (e.g., [START_REF] Béasse | A simple model of pea (Pisum sativum) growth affected by Mycosphaerella pinodes[END_REF][START_REF] May | Improvement and validation of a pea crop growth model to simulate the growth of cultivars infected with Ascochyta blight (Mycosphaerella pinodes)[END_REF], 2008); and primary inoculum assessment modes based on weather-dependent values such as temperature, humidity, leaf wetness, wind speed data (e.g., [START_REF] Schoeny | Assessment of airborne primary inoculum availability and modelling of disease onset of Ascochyta blight in field peas[END_REF]Salam et al. 2011a,b,c;[START_REF] Richard | Effect of pea canopy architecture on microclimate and consequences on Ascochyta blight infection under field conditions[END_REF][START_REF] Bénézit | Impact of climate and diseases on pea yields: what perspectives with climate change? Oilseeds and fats[END_REF]. However, despite such modeling approaches, modeling the different pathogen components of the Ascochyta blight complex, and/or the wider foliar disease complex, and/or aspects of the soilborne Ascochyta blight complex component, all remain as opportunities yet to be exploited. In particular, modeling offers unique opportunities to understand and define the Ascochyta blight complex, involving the same pathogen species that operate above and below ground. This is perhaps the most realistic way to better understand and fully exploit the opportunities for utilizing a more inclusive approach to manage the Ascochyta complex, one that accommodates the differences across the different pathogen species in terms of their epidemiology, responses to host resistance, fungicidal and cultural options, influences of different farming systems, and effects of environmental factors.

In conclusion, the current study highlights the complexities of changes in relative disease severities across four different pathogens (viz. genera Didymella, Phoma, Peronospora, Septoria) and subsequent field pea yield across different times of sowing, sowing densities and varieties, based on varieties and pathogen strains present in the farming system at the end of the 1980's. The contrasting effects from delaying sowing of field pea, where it reduced severity of Ascochyta blight and Septoria blight, but increased severity of downy mildew, and all this with no net yield advantage, were generally location-specific in the current study. Similarly, sowing density effects were also generally location-specific, where increased plant density increased yield despite increased Ascochyta blight and/or downy mildew at particular locations.

Varietal differences in the current study were also location-specific and other field studies have shown location-specific responses to fungicide applications (MJ Barbetti et al., unpubl. data). Clearly, there is a need to better define and understand the role and influence of location-specific conditions on the makeup of foliar disease complexes, as this is fundamental towards enabling integrated and effective cultural, host resistance or fungicidal management. In the interim, while the search for the elusive but more effective host resistance continues, it is imperative that a wider array of cultural management approaches are further explored and exploited, such as focussing on crop sequence diversification, intercropping, manipulating time of sowing and stand density, and application of improved seed sanitation and residue/inoculum management practices.

(

  P<0.05) and sowing density (P<0.01) and significant interactions between time of sowing with both variety (P<0.01) and with sowing density (P<0.001) in relation to severity of Ascochyta blight. The early time of sowing had more severe Ascochyta blight (P<0.05) compared to the mid and late times of sowing. Alma and Dundale had more severe Ascochyta blight (P<0.05) than Pennant and Wirrega. Ascochyta blight was more severe (P<0.05) at 100 plants m -2 compared to 50 and 25 plants m -2 . By August 28, there were significant effects of time of sowing (P<0.001), variety (P<0.05) and sowing density (P<0.01) and significant interactions between time of sowing with both variety (P<0.01) and with sowing density (P<0.001) in relation to severity of Ascochyta blight. The early sowing had more severe Ascochyta blight (P<0.05) compared to the mid and late times of sowing. Alma and Dundale had more severe Ascochyta blight (P<0.05) than Pennant and Wirrega, and Ascochyta blight was more severe (P<0.05) at 100 and 50 plants m -2 compared to 25 plants m -2 . By September 8, there were significant effects of time of sowing (P<0.001), variety (P<0.01) and sowing density (P<0.001) and significant interactions between time of sowing with both variety (P<0.01) and with sowing density (P<0.001) in relation to severity of Ascochyta blight. The early sowing had more severe Ascochyta blight (P<0.05) compared to the mid and late times of sowing. Alma and Dundale had more severe Ascochyta blight (P<0.05) than Pennant and Wirrega. Ascochyta blight was more severe (P<0.05) at a sowing density of 100 plants m -2 compared to 50 or 25 plants m -2 . By October 13, there were significant effects of time of sowing (P<0.001) and sowing density (P<0.01) and a significant interaction between time of sowing with seeding density (P<0.05) in relation to severity of Ascochyta blight. The mid sowing had more severe Ascochyta blight (P<0.05) compared to the early sowing, which in turn had more severe disease (P<0.05) than the late sowing. Ascochyta blight was more severe (P<0.05) at a sowing density of 100 plants m -2 compared to 25 plants m -2 . At 80 days after first time of sowing, direct examination and plating Ascochyta blight lesions on leaves and stems onto potato

  P<0.001 for August 27 in relation to severity of Ascochyta blight. The early time of sowing had more severe Ascochyta blight (P<0.05) than the mid time of sowing, which in turn had more severe disease than the early time of sowing. Pennant had more severe Ascochyta blight (P<0.05) than the other varieties. Ascochyta blight was more severe at a sowing density of 50 and 100 plants m -2 compared to 25 plants m -2 . On August 22 there was a three-way interaction between time of sowing, variety and sowing density There was also a significant (P<0.05) interaction of time of sowing with variety, and time of sowing with sowing density. For the September 5 assessment, there were significant effects of time of sowing, variety, and sowing density (all P<0.001) and a significant interaction between time of sowing with variety (P<0.001) and with sowing density (P<0.001) in relation to severity of Ascochyta blight. The early time of sowing had more severe Ascochyta blight (P<0.05) than the mid time of sowing, which in turn had more severe disease (P<0.05) than the early time of sowing. Pennant had more severe Ascochyta blight (P<0.05) than the other varieties. Ascochyta blight was more severe (P<0.05) at 100 compared to 50 plants m -2 , which in turn had more severe disease (P<0.05) than at 25 plants m -2 .

Fig. 1 .Fig. 2 .Fig. 3 .DFig. 4 .

 1234 Fig.1. Mean field pea seedling densities at 3 weeks post-germination made by counting the numbers of seedlings in 10 random quadrats each 0.5 x 0.5 m per field plot (for plots originally sown at a density of 25, 50 or 100 plants m -2 ) at Avondale, East Merredin, and Moora field locations in Western Australia.

  Plants were assessed for Ascochyta blight severity on the stem and foliage using a 6 level ordinal scale where : 100% stem and foliage. A total of 80 leaves and 80 stems showing Ascochyta blight symptoms were sampled at each disease assessment, examined directly under the microscope and then surface sterilized in 4% NaOCl for 4 min and plated onto moist sterilized blotter paper in Petri dishes. Samples on moist blotter were examined at 24 h intervals under dissecting microscope for pathogen sporulation, then slides made and examined under an Olympus compound microscope

													𝑆 𝐵 0
	symptomless; : trace of disease on base of plant; : disease affecting lower 25% stem length and foliage; : disease 𝑆 𝐵 1 𝑆 𝐵 2 𝑆 𝐵 3
	affecting lower 50% of stem length and foliage; : disease affecting lower 75% of stem and foliage; : disease affecting 𝑆 𝐵 4 𝑆 𝐵 5
							𝑆 𝐷𝑀 0	: nil disease;	𝑆 𝐷𝑀 1 :	1-10%;	𝑆 𝐷𝑀 2	: 11-20%;	𝑆 𝐷𝑀 3	: 21-30%;	𝑆 𝐷𝑀 4	:
	31-40%;	𝑆 𝐷𝑀 5	: 41-50%	𝑆 𝐷𝑀 6	: 51-60%;	: 1-70%; 𝑆 𝐷𝑀 7	𝑆 𝐷𝑀 8	:71-80%;	𝑆 𝐷𝑀 9	: 81-90%;	𝑆 𝐷𝑀 10	: 91-100% of diseased leaf area.
	Septoria blight was assessed on a six level ordinal scale, where : nil disease; : 1-20%; : 21-40%; : 41-60%; : 𝑆 𝑆 0 𝑆 𝑆 2 𝑆 𝑆 3 𝑆 𝑆 4 𝑆 𝑆

to determine if Phoma or Didymella spores were present on each lesion. From this the percentage incidence of Phoma and Didymella associated with the disease symptoms calculated. In each case, identifications were confirmed by plating 1 x 1 mm 2 discs of leaf and stem diseased tissues onto potato dextrose agar containing 25 ppm aureomycin hydrochloride.

For Ascochyta blight, only data for 80 days after the first time of sowing are presented. Where downy mildew occurred, plants were assessed on a 11 level ordinal scale where 5 61-80%; : >80% of leaf surface area was diseased. All disease ordinal disease scores were transformed into percentage 𝑆 𝑆 5 disease indices (%DI) based on McKinney

Location-specific details and experimental factors. At

  Avondale, soil type was a red-brown sandy loam to clay loam over red brown to dark brown clay at 18 cm. Sowing dates were: Early, June 9; Mid, June 20; and Late, June 30.

	mean monthly maximum/minimum temperature were 22.5/10.6, 18.8/8.4, 17.6/7.3, 18.3/7.1, 20.5/7.6 ºC, respectively. All
	times of sowing were assessed for diseases on August 15, September 4 and 18. These dates represent 80 days from
	Approximately 95 kg ha -1 plain superphosphate fertilizer was drilled with seed. Mean monthly rainfall May to September sowing assessment for the first, second and third times of sowing respectively.
	inclusive were 46.9, 62.7, 69.9, 52.6, 35.5 mm, respectively, while mean monthly maximum/minimum temperature were
	21.3/7.8, 17.2/5.9, 16.0/5.1. 18.0/5.1, 20.7/5.8 ºC, respectively. All times of sowing were assessed for diseases on August
	28, September 9, 19 and October 13. The first three times of assessment represent the 80 days from sowing assessment
	for the first, second and third times of sowing respectively. At East Beverley, soil showed a surface A horizon of grey brown
	sand over a pale clayey sand [pH (H 2 O) 5.5-6.5] overlying a sandy clay subsoil [pH (H 2 O) 6.6-7.0] at a depth of 20-30 cm.
	Sowing dates were: Early, May 25, Mid, June 9, and Late, July 19. Approximately 100 kg ha -1 plain superphosphate
	fertilizer was drilled with seed. Mean monthly rainfall May to September inclusive were 46.7, 66.6, 63.3, 47.6, 32.1 mm,
	respectively, while mean monthly maximum/minimum temperature were 21.3/7.8, 17.2/5.9, 16.0/5.1. 18.0/5.1, 20.7/5.8 ºC,
	respectively (Avondale being the closest location with available temperature data). All times of sowing were assessed for
	diseases on August 14, 28, September 8 and October 13. The first three dates of assessment represent the 80 days from
	sowing assessment for the first, second and third times of sowing respectively. At Lake Grace, soil type was a brown sandy
	loam 0-5 cm over clay. Sowing dates were: Early, May 26, Mid, June 22, and Late, July 17. Approximately 100 kg ha -1
	plain superphosphate fertilizer was drilled with seed. Mean monthly rainfall May to September inclusive were 41.7, 48.6,
	47.7, 44.9, 32.8 mm, respectively, while mean monthly maximum/minimum temperature were 20.8/7.5, 17.7/5.6, 16.5/4.6,
	17.6/4.7, 20.4/5.9 ºC, respectively. All times of sowing were assessed for diseases on August 17, 31 and September 11.
	These three dates of assessment represent the 80 days from sowing assessment for the first, second and third times of
	sowing respectively. At Merredin, soil type was a reddish brown sandy clay loam [pH (CaCl 2 ) 6.0] over yellowish red heavy
	clay [pH 7.8] at 30cm. Early, May 3; Mid, May 19; and Late, June 2. Approximately 100 kg ha -1 plain superphosphate
	fertilizer was drilled with seed. Mean monthly rainfall May to September inclusive were 40.0, 48.7, 50.2, 39.3, 25.5 mm,
	respectively, while mean monthly maximum/minimum temperature were 19.9/8.9, 15.8/6.7, 15.0/5.5,17.4/5.6, 21.4/6.7 ºC,
	respectively. All times of sowing were assessed for diseases on July 24, August 7, 22 and September 5. The first three
	dates of assessment represent the 80 days from sowing assessment for the first, second and third times of sowing
	respectively. At Moora, soil type was a heavy brown sandy loam [pH (H 2 O) 5.95] and with clay at 40 cm. Sowing dates
	were: Early, May 26; Mid, June 16; and Late, June 30. Approximately 130 kg ha -1 plain superphosphate fertilizer was drilled
	with seeds. Mean monthly rainfall May to September inclusive were 59.8, 88.3, 87.8, 68.7, 43.8 mm, respectively, while

Table 1 .

 1 Relative percentage incidence of foliage isolations from field pea (Pisum sativum) yielding Didymella as compared with Phoma at 80 days after sowing at the five field trials at Avondale, East Beverely, Lake Grace, Merredin and Moora locations in Western Australia. A total of up to 80 leaves and 80 stems showing Ascochyta blight symptoms were sampled, examined directly under the microscope and then surface sterilized in 4% NaOCl for 4 minutes and plated onto moist sterilized blotter paper in Petri dishes. Samples on moist blotter were examined at 48 h intervals under dissecting microscope for pathogen sporulation, slides made and examined under an Olympus compound microscope to determine if Didymella or Phoma spores were present on each lesion and relative percentage incidence of Didymella and Phoma associated with the disease symptoms calculated. In each case, identifications were confirmed by plating 1 x 1 mm 2 discs of leaf and stem diseased tissues onto potato dextrose agar containing 25 ppm aureomycin hydrochloride.

	Field location	% isolations yielding Didymella	% isolations yielding Phoma
	Avondale	84	23
	East Beverley	98	6
	Lake Grace	25	15
	Merredin	77	12
	Moora	93	12

Acknowledgements

The field trials were funded by the Department of Primary Industry and Development Western Australia. We thank DPIRD technical staff for help with running field trials at Avondale, East Beverley, Lake Grace, Merredin and Moora. Martin Barbetti benefited from a grant of the INP-Toulouse visiting senior scientist program under the umbrella of Pr Grégory Dechamp-Guillaume (ENSAT), to visit and work with French colleagues on this data. The authors declare that they have no known

competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.