Continuation Research Projects

1. Determining the race structure and genetic diversity of Leptosphaeria species causing Blackleg disease of canola in the Western Cape

   Dr G Mostert, Ms HM Schreuder, Mr AB Folscher¹ and Dr GJ van Coller²
   ¹Stellenbosch University / ²Western Cape Department of Agriculture

   Surveillance of canola production in the Western Cape

   Incidence and severity

   The incidence of leaf lesions (percentage of plants with at least one leaf lesion) caused by Leptosphaeria were determined in 2021 at the rosette stage at Langgewens and Tygerhoek research farms and Uitkyk farm near Riversdale. Incidence measurements for the 2022 season is currently in process.

   Blackleg incidence was slightly higher at Riversdal (87%) than at Langgewens (76%) and Tygerhoek (74%) (Fig. 1). Disease incidence was above 60% in all cultivars at all three locations, except for Hyola 350TT which had the lowest disease incidence at all locations and Blazer at Tygerhoek with around 40% incidence. This may be due to cultivar Hyola 350TT having the most R-genes of all the local canola cultivars, namely: Rlm1, Rlm4, Rlm6, LepR1.

   

   Blackleg severity was also determined in these trails in 2021 two weeks before harvest using the method described by Peng et al. (2021). The severity for the 2022 will be conducted towards the end of the season.

   The results are summarised in Fig. 2 which was also submitted in the report by Dr van Coller on the integrated management of blackleg of canola in the Western Cape by means of cultivar resistance and chemical control. Overall, the highest disease severity was recorded at Langgewens (41%), followed by Riversdale (33%) and Tygerhoek (19%). Due to heavy rains and flooding during planting in May 2021, the trial at Tygerhoek had to be replanted in early June 2021, which negatively influenced the results of this trial. Results from Tygerhoek were therefore omitted from statistical analysis. Combined data from Riversdale and Langgewens indicated that the Clearfield cultivars 45Y95 (20%), 45Y93 (21%), 43Y92 (29%), 44Y94 (30%) had the lowest disease severity, while Blazer (44%), Hyola 650 TT (46%) and Hyola 559 TT (61%) had the highest disease severity. A statistically significant difference was found between these two groups of cultivars.

   

   Sample collection

   In the 2020 and 2021 seasons, symptomatic leaves (flowering stage), crown tissue (two weeks before harvest) and stubble (after harvest) were collected from the cultivar evaluation trials at six locations, including Langgewens, Hopefield and Eendekuil in the Swartland region and Tygerhoek, Napier and Riversdal in the Overberg region. The sampling of leaves from the 2022 season is currently in progress and crown and stubble will also be collected at the end of the growing season.

   To investigate whether seed is a source of inoculum, different lots of retained seed was collected from 29 farmers in the Swartland and Overberg region. In addition to the seeds collected from farmers, seeds were collected from cultivar evaluation trials at five different locations which were retained from the 2021 season: Malmesbury (Langgewens), Riviersonderend (Tygerhoek), Riversdale, Hopefield, and Napier. Sampling of retained seeds from producers was done with a seed probe. To ensure representative sampling, the probe was used to collect seeds from large seed storage bags by inserting the probe at 5-6 different angles at different locations and dispensing the collected seeds into a container that was then used to mix the seeds. A volume of 200 ml sample was then taken and labelled, and stored at 5°C.

   Surveys were designed to understand the behaviours of farmers around the storage and use of seed (Attachment 1). Ethical clearance was obtained from Stellenbosch University to conduct surveys throughout the 2022 growing season.

   Due to typical blackleg symptoms noticed on some of the Brassica crops used as cover crops in the conservation agriculture system in the 2021 growing season, it must be determined to what extend these crops serve as an alternative source of inoculum and contribute to genetic diversity within the pathogen population. Sampling from symptomatic weed and cover crops species will be conducted in the 2022 and 2023 seasons.

   Fungal isolation

   In the 2020 season, 23 isolates were recovered from leaf samples and 806 samples from stubble. In the 2021 season, 544 samples were recovered from leaf samples and 236 samples from infected stems. Stubble isolations for the 2021 season is still in process. To date a total of 1609 isolates have been recovered (Table 1) within cultivar screening trials. Isolations from leaf samples of the 2022 season is also currently in progress, while isolations from infected stems and stubble will commence towards the end of the growing season. Isolations from seed will also be conducted from the seeds collected from farmers from the 2021 and 2022 growing seasons.

   Table 1: The number of isolates of Lepthosphaeria spp. recovered from different locations

   Region	Location	Growing season
   		2020		2021
   Swartland	Langgewens	0	248	105	93
   	Hopefield	0	34	10	—
   	Eendekuil	—	—	103	—
   Overberg	Tygerhoek	0	193	196	77
   	Napier	9	132	62	—
   	Riversdal	14	199	68	66
   Source		Leaves	Stubble	Leaves	Stems

   Characterization of genetic diversity present in Leptosphaeria populations

   Confirmation of species identity

   The DNA of isolates were screened with species-specific as described by Liu et al. (2006). To date 1023 samples were confirmed as L. maculans from the 2020 and 2021 growing seasons. No isolates were thus far identified as L. biglobosa.

   Population genetics study

   Thirty-five isolates collected were sent for whole genome sequencing to Dr Angela van de Wouw at the University of Melbourne, Australia. These isolates will be included in an international Leptosphaeria maculans population study and the information gained through this study will be made available for comparative genomics.

   A representative subpopulation of isolates of 20 isolates from each sampling location per growing season will be selected for whole genome sequencing, instead of using microsatellite markers that were originally envisioned in the proposed project. The genome sequences will be used to determine mating type, to construct a phylogeny, to identify avirulence genes and to determine patterns in migration in the South African L. maculans population. Much more information can therefore be obtained from whole genome sequencing, compared to the microsatellite markers. A subset of 100 isolates have been chosen from the 2020 populations and DNA extraction is in progress. Fifty isolates each from the 2021 and 2022 growing season will also be included in the analysis at a later stage. Some samples isolated from symptomatic weed and cover crop species will also be included in the population genetics study.

   Characterisation of pathogenic potential of L. maculans isolates PCR identification of known avirulence genes

   The DNA of isolates selected for the population genomics study, as well as isolates collected from alternative host species, will be used to screen for the presence or absence of avirulence genes before it will be sent for whole genome sequencing.

   Pathogenicity testing

   Due to the difficulties in availability and import of seed of differential hosts needed for race identification, the race identity will be inferred by the absence and/or presence of the known avirulence genes from the whole genome data generated in the population genomics study, as described by Chen et al. (2021).

2. Integrated management of blackleg of canola in the Western Cape by means of cultivar resistance and chemical control

   Dr GJ van Coller¹, Ms HM Schreuder and Mr AB Folscher²
   ¹Western Cape Department of Agriculture / ²Stellenbosch University

   Introduction

   Blackleg, caused by Leptosphaeria maculans and Leptosphaeria biglobosa, is the most devastating disease of canola globally, with annual losses in 2008 estimated at more than US$ 900M (Fitt et al., 2008). Losses in Australia amount to between 10 and 15% of the annual harvest, although yield losses of up to 90% has been recorded (Van de Wouw et al., 2016b). Blackleg is a known major constraint to canola production locally. While there are no official numbers available on the impact of blackleg on canola in the Western Cape, a yield increase of only 5% during the 2021 growing season would have resulted in an additional 9750 tonnes of grain produced. With a market price of R 10 200 / ton (Grain SA Market report, 2022), this would have resulted in an additional R99 450 000 of revenue generated within the canola industry.

   Blackleg is managed by integrating host resistance with chemical control. Agronomical practices like ploughing or burning of stubble, which decreases the inoculum load, is effective in reducing disease levels (Guo et al., 2005), but cannot be integrated with conservation agriculture (Kassam et al., 2009; Rochecouste et al., 2015). Planting canola at least 500m away from the previous year's stubble, which enables the crop to evade the disease, is also effective (Marcroft et al., 2004), but limited space on farms often makes this impractical. The use of host resistance is the most durable, cost-effective and environmentally friendly approach to manage blackleg (Huang et al., 2018), but must be managed carefully due to the large number of genetically distinct races of the pathogen occurring globally. In Manitoba, Canada, for example, 170 races of the pathogen have been identified (Fernando et al., 2018). Furthermore, the occurrence and frequency of races of the pathogen within a country or region is not static, but changes in response to the major resistance genes present in canola cultivars (Van de Wouw et al., 2018). When cultivars with the same compliment of major resistance genes are cultivated each year in the same region, it can result in the rapid increase of races not suppressed by these resistance genes, up to the point where resistance is effectively overcome. This can happen within three years, as witnessed in Australia and France (Sprague et al., 2006a, b). The pathogens are heterothallic, meaning that the different mating types (similar to male and female) are carried on separate individuals (Fernando et al., 2018). Sexual reproduction occurs easily and in large numbers in canola stubble and results in offspring carrying genetic material from both parents. This ability, coupled with the seedborne nature of the pathogens, allows for the introduction of new races into production regions (Van de Wouw et al., 2016a).

   The use of azole fungicides has contributed to the 50-fold increase in canola production in Australia in the last 25 years (Van de Wouw et al., 2017). Indiscriminate or repeated use of the same fungicides, however, allows for the build-up of tolerance toward fungicides over time, and represent a real threat to continuing canola production. Cases of blackleg isolates highly resistant against triazoles has been reported in Australia, while cross-resistance between triazole and triazole + strobilurin fungicides have also been reported (Van de Wouw et al., 2021).

   The aim of this project will be to evaluate the resistance of local canola cultivars against blackleg in different production regions as well as in the greenhouse against identified local races of the pathogen, to determine the fungicide sensitivity of the local pathogen populations to a range of fungicides, and to screen the efficacy of selected foliar fungicides and seed treatments for the control of blackleg under greenhouse conditions. This project will be complimentary to the project proposed by Dr G. Mostert of the Department of Plant Pathology, Stellenbosch University; together these two proposals will provide a much more complete approach to understanding blackleg in the Western Cape, as well as developing management strategies.

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   Materials and methods

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   Evaluation of canola cultivars for blackleg resistance

   Greenhouse evaluation

   According to the project proposal, greenhouse evaluation of cultivar resistance will commence in 2022. However, after reassessing the objectives of this project, we decided that more meaningful data for canola producers will be generated by including an additional field trial for cultivar resistance evaluation than by conducting greenhouse trails, to ensure that the important production regions are included in the resistance evaluation. A field trial to determine cultivar resistance has thus been established at Waterboerskraal farm near Hopefield in May 2022 and will continue from 2023 onwards. This is in addition to the field trials which started in 2021 at Langgewens research farm (Moorreesburg, Swartland) and Tygerhoek research farm (Riviersonderend) and Uitkyk farm (Riversdale) in the southern region of the Western Cape.

   Field evaluation

   To evaluate the blackleg resistance of cultivars that are commercially available in South Africa, three cultivar trials were established in April/May 2021 at Uitkyk farm (Riversdale), Tygerhoek research farm (Rivier­sonderend) and Langgewens research farm (Swartland), respectively. A total of twelve cultivars were planted at each locality (Table 1). Agronomical practices commonly used in the respective regions were used, including minimum tillage, a standard fertiliser regime, as well as weed and insect control. To ensure infection from as many races of the pathogen occurring naturally in the respective regions, canola stubble from the previous season's canola cultivar evaluation trials at each location was collected and scattered on the planted paddocks immediately after planting. This ensured that emerging seedlings was in the immediate vicinity of fruiting bodies of the pathogen, thereby increasing the likelihood of infection (Marcroft et al., 2004). Given that infection up to the ~5-leaf stage is responsible for crown cankers later in the season (Marcroft et al., 2005), disease incidence was measured at the 5-leaf stage to ensure infection occurred. Results indicated that all cultivars at all three localities were infected.

   The blackleg disease severity index (DSI) was evaluated two weeks before harvest using the method described by Peng et al. (2021), with the DSI calculated as a percentage. The higher the percentage, the more severe the blackleg infection. Due to heavy rains and flooding during planting in May 2021, the trial at Riviersonderend had to be replanted in early June 2021. This, however, is an unfavourable time for planting canola in the Overberg region and the plants subsequently did not develop optimally, which negatively influenced the results of the trial. Therefore, the results from Tygerhoek were not included in the statistical analysis.

   Analysis of variance (ANOVA) for location and cultivar effects and interactions were obtained using the GLM Procedure of SAS software (Version 9.4, SAS Institute Inc, Cary, USA). Homogeneity of trial variance was confirmed using Levene's test (Levene, 1960). To test for deviation from normality, Shapiro-Wilk's test was performed (Shapiro and Wilk, 1965). Fisher's protected least significant differences (LSD) were calculated at the 5% level of significance to establish differences between treatment means (Ott, 1998).

   Table 1. Cultivars evaluated in field trials in the Western Cape for blackleg resistance during 2021

   Cultivar	Herbicide group	R-genes present	R-grouping¹
   Blazer	Conventional	LepR1 (probably Rlm1 also, unconfirmed)	AD
   Diamond	Conventional	Rlm1, Rlm4, Rlm6	ABF
   Quartz	Conventional	Rlm1, Rlm4, LepR1	ABD
   44Y90	Clearfield	Rlm4	B
   43Y92	Clearfield	Rlm4	B
   44Y94	Clearfield	Rlm3, Rlm4	BC
   45Y93	Clearfield	Rlm3, Rlm4	BC
   45Y95	Clearfield	Unknown
   Alpha TT	Triazine tolerant	Unknown
   Hyola 350TT	Triazine tolerant	Rlm1, Rlm4, Rlm6, LepR1	ABDF
   Hyola 559TT	Triazine tolerant	Rlm1, Rlm4, LepR1	ABD
   Hyola 650TT	Triazine tolerant	Rlm1, Rlm4, LepR1	ABD

   ¹ Australian Blackleg Resistance Grouping (Van de Wouw and Howlett, 2020)

   Evaluation of fungicides for control of blackleg

   In vitro fungicide sensitivity and determination of EC50 values.

   According to the project proposal, In vitro fungicide sensitivity screening will begin in 2022, and is planned to commence in July 2022. We will make use of a high throughput screening technique as described in Troskie et al. (2012) which will allow us to include a larger collection of Leptosphaeria isolates. Results from this Objective will be included in the next progress report, relevant to this period.

   Field evaluation

   According to the project proposal, greenhouse evaluation of fungicides will commence in 2022. Similar to Objective 1.1., however, we decided that more meaningful results for canola producers will be generated by conducting field trials at the same locations mentioned for the cultivar evaluation. The first fungicide trails were therefore planted at four locations in April/May 2022 and included 6 different fungicides. More information on these trials will be included in the next progress report relevant to this period.

   Results and discussion

   Langgewens Research farm (Swartland)

   The DSI varied from just over 20% to more than 70% at Langgewens research farm in the Swartland. With the exception of cultivar 44Y90, all Clearfield cultivars were among the best-performing group at Langgewens research farm during 2021. Conversely, the cultivars Alpha TT, Blazer and Hyola 559TT were the worst-performing cultivars (Fig. 1). This may be due to the presence of the LepR1 gene in Blazer, and the absence of the Rlm3 gene in Hyola 559TT, although the race structure of the pathogen population, which is currently being characterised by Ms Huibré Schreuder as part of her PhD, is needed to explain this. It is also important to note that this represents only the first year's data of this project, and data from additional years are needed to verify the resistance/susceptibility of the cultivars.

   

   Uitkyk farm (Riversda!e)

   The DSI varied from ~20% to almost 60% at Uitkyk farm near Riversdale. Similarly, to Langgewens, with the exception of cultivar 44Y90, the Clearfield cultivars were the best-performing group at Uitkyk farm near Riversdale during 2021. Conversely, the cultivars Hyola 650TT and Hyola 559TT were the worst-performing cultivars (Fig. 2). This may be due to the absence of the Rlm3 gene in the latter two cultivars, although the race structure of the pathogen population, which is currently being characterised by Ms Huibré Schreuder as part of her PhD, is needed to explain this. It is also important to note that this represents only the first year's data of this project, and data from additional years are needed to verify the resistance/susceptibility of the cultivars.

   

   Tygerhoek Research farm (Overberg)

   Due to heavy rains and flooding during planting in May 2021, the trial at Riviersonderend had to be replanted in early June 2021. As mentioned, this is an unfavourable time for planting canola in the Overberg region and the plants subsequently developed poorly. This was also evident in the results obtained (Fig. 3), which are believed to be unreliable. The overall low DSI further confirms this.

   

   Overall DSI ratings (locations combined)

   The overall DSI were highest at Langgewens research farm, followed by Uitkyk farm and Tygerhoek research farm. When the data from Uitkyk farm and Langgewens research farm were combined, the Clearfield cultivars 45Y95, 45Y93, 43Y92, 44Y94 had the highest resistance while Blazer, Hyola 650 TT and Hyola 559 TT had the lowest resistance. A statistically significant difference was found between these two groups of cultivars. A summary of the cultivars evaluated for all locations, and the results obtained from blackleg severity ratings are presented in Figure 4.

   Field trials 2022

   The canola field trials to evaluate cultivar resistance during 2022 has been planted in April / June 2022, and include a total of 17 canola cultivars at four different locations (Uitkyk farm near Riversdale, Tygerhoek research farm in the Overberg, Waterboerskraal farm near Hopefield, and Langgewens research farm in the Swartland). Results will be presented in the following progress report.

   

3. Monitoring of Sclerotinia stem rot of canola in the Western Cape

   Ms L Nowers
   Western Cape Department of Agriculture

   The Monitoring project was planned for the canola seasons of 2021, 2022 and 2023 and OPDT approved funding for all three years, with the final report due March 2024.

   The results envisaged for this project (see application document of May 2020) can be reported on by March 2024, as follows:

   • Seed density trials were concluded successfully (see Progress Report of 2022).
   • Spraying time trials were conducted successfully and resulted in a new, separate project being registered by Dr GJ van Coller.
   • Tillage as a contributing factor to Sclerotinia Stem Rot (SSR) has rendered little data thus far, as all of 2021's data was lost due to flooding of the trial and very low infection rates for 2022 did not contribute to much information. One more year would be helpful towards more sound statistical conclusions.
   • The crop rotation systems trial for the Heidelberg-vlakte region concludes in 2023, but a comprehensive summary will be possible by March 2024 due to data collection that was done on this trial by the WCDA since 2013.
   • The crop rotation systems trial for the Ruêns region has been changed to a Regenerative trial in 2022. The Monitoring project will have recorded 2 years of data by March 2024. A third year of data will render a clearer picture of the effect of Regenerative practices vs general Conservation agricultural practices on the occurrence of SSR.

   With regards to the additional objective to use data generated by the Monitoring project for the development of a SSR forecasting model:

   This objective has been fulfilled, as the WCDA and the University of Stellenbosch have collaborated in registering a project specifically for this purpose. An M.Sc student has started working on this project in the 2023 season, stretching until the end of 2024. This study is however dependent on the SSR incidence figures generated by the Monitoring project and should monitoring end in 2023, the Forecasting Model project would not receive disease rate data for 2024. A new addition to the data gathered in the Western Cape with regards to SSR, is the spore counting facility of the M.Sc student in the 2023 season. This data should ideally be matched with the disease monitoring function of the Monitoring project, as spore traps are set up at the Monitoring project's sites. It would be ideal for SSR disease monitoring to continue in conjunction with spore counting.

   Additional factors that contribute to the request to extend the Monitoring project are the following:

   • During the execution of the project, the monitoring technique has been improved through trial and error. For example, initially, only post-harvest sampling was done, but it has become evident that pre-harvest sampling is important (even though it is extremely cumbersome). Pre-harvest sampling could only be done more extensively since the 2022 season, but 2022 had very low SSR-infection rates. One more year of pre-harvest data would be preferable to compare with the 2022 and 2023 data sets.

   The additional request to observe possible susceptibility differences between commercial cultivars, was only received at the end of 2021, hence this was done only for the 2022 season - which was a low infection rate year. This trial is being repeated for 2023, but a third year's data (2024) would be preferable for scientifically sound recommendations to industry.

   During the execution of the project, it was discovered that some data loggers became faulty in their relative humidity readings over the 6 months that they were placed in the field. After deliberation with the UK manufacturer, it was established that the loggers' service and calibration by the manufacturer only guaranteed 6 months' accurate RH-readings (even though the apparatus' pamphlet indicates it should be done only once a year). It was only since the 2023 season that loggers were calibrated shortly before placing them in canola fields. One more year's RH readings from more reliable loggers would be preferable.

   Extremely beneficial relationships with some canola producers have been established over the past three years and requests from them to continue the monitoring motivate this extension request.

   OPDT's financial support was applied to obtain:

   • Good data in 2021 with high SSR incidence;
   • Reasonable data in 2022 (very low SSR incidence); and
   • Expected good data for 2023 (currently mid-season, hence uncertain of outcomes).

   The Monitoring project was executed within the allocated budget thus far. Actual figures from the 2021 season (with infection rates ranging from 0% in the Porterville area to 25% in the Swellendam area) made it possible to accurately calculate that producer incurred losses due to SSR of up to R3 060 per hectare, even with applying fungicides according to general practice. This confirms the necessity to continue monitoring of and research on SSR in the Western Cape.

4. Assessing the effect of planting date and environment on sunflower development, Sclerotinia head rot and yield

   Dr N Creux, M Wilken, E Archer, D Swanevelder and A Mokhele
   University of Pretoria

   In South Africa, where sunflower planting dates rely on the timing of the rains and the potential for Sclerotinia head rot, it is important to understand how a changing environment might alter these strategies in the future. This research project has three main aims focused around understanding the interplay between the sunflower development, the environment and Sclerotinia head rot incidences. The first aim is to evaluate how planting date and weather conditions impact sunflower developmental stages. The second aim is to identify the possible factors involved in Sclerotinia head rot incidence in relation to planting date and environmental conditions. The final aim is to develop a small operational predictive system to explore the possibility of predicting optimal planting dates for yield and limiting head rot incidence.

   The work towards these aims can be broken into three main phases: Phase 1 is a field study testing the extent to which planting date impacts sunflower developmental stages and Sclerotinia head rot incidences; Phase 2 entails a small survey of sunflower growing regions for Sclerotinia head rot incidence; and Phase 3 will use the collected data to inform models and predict the effects of planting date on sunflower development and Sclerotinia head rot occurrence. This multidisciplinary project brings together agronomists, plant scientists, geneticists and meteorologists to provide a holistic view of how environmental factors associated with planting date might affect sunflower development, yield and Sclerotinia head rot incidence. The project was initiated in 2020 and, as with many projects started at this time, there were limitations due to the global pandemic and the move towards a new normal. However, the project has progressed well and is in the finalization stages — largely due to the work of a strong PhD candidate, Ms Phrasia Mapfumo, who is currently writing her thesis with a view to submit early 2024. This work will form the basis of at least three manuscripts with the first accepted with revisions in Plant Pathology this month. Our goal is to write a summary piece of this paper for the Oilseed Focus once the publication process is completed.

   Phase 1 is complete and Ms Mapfumo, in collaboration with the ARC, established three separate planting date trials in two locations over two seasons with the PAN7080 cultivar (Figure 1A). At the ARC experimental farm in Potchefstroom two planting date trials were established, with one located in a regular field site for manual phenotyping (Figure 1B) and one located under the Phenospex FieldScan for automated phenotyping (Figure 1C). At the Innovation Africa@UP field site, five planting dates for the first season and six planting dates for the second season were completed. At the ARC experimental farm four planting dates were completed (November, December, January and February) in season 2020/2021, and four dates in season 2021/2022 (October, November, January and February). Unfortunately, in the second season, heavy rains prohibited planting in December. Manual phenotyping was performed by Ms Mapfumo, and measurements for germination, leaf number, plant height and biomass were collected weekly (UP) or biweekly (ARC Potch). At the ARC Potch site, the first trial was planted under the Phenospex FieldScan for automated phenotyping in 2020/2021. As is the case with much new technology, the first season (2020/2021) was predominantly focused on optimization and trouble shooting. The analysis of the manual phenotyping and yield assessments are complete. For the Phenospex FieldScan approximately 50 000 scans were generated for the 2021/2022 season. A new bioinformatics M.Sc student, Tshego Mbere, is developing an app to analyse this data offline as loadshedding limits the application of the propitiatory software. She has established the start of a Shiny App based in R that will be used to test the application and analyse the data from these trials.

   

   In terms of mean seed yield in Potchefstroom and Pretoria there were some interesting seasonal variations. The 2020/2021 season was hotter and drier than the 2021/2022 season and this is reflected in the mean yield of the trials. In the hotter drier season both sites yielded similarly and there was little difference between the planting dates except for the very late February and March planting dates, which was expected (Figure 2). The very late planting dates function as a control producing expected results and allowing us to compare across the other planting dates from the baseline level. Interestingly, in the wetter, cooler season the planting dates had a significant effect on yield and the earlier November, December planting dates yielded well and did better than the equivalent planting dates in the drier season. In the wetter season the later January and February planting dates appeared to perform worse than the earlier planting dates of the same season but similar to the same planting dates in the drier season. This adds support to the evidence that sunflower yields are stable in harsher environments, but also indicates that planning earlier in wetter years will produce better yields.

   Figure 2. Yield for the 2020/2021 season (a and c) and 2021/2022 season (b and d) for the Potchefstroom (a and b) and Pretoria (c and d) measured in grams per plant with n = 15 per planting date. ANOVA and with a multiple comparison test show significant differences with p-value <0.05. The same letters indicate no significant difference. Error bars indicate standard error.

   

   

   

   

   To assess seed quality we measured oleic acid, linoleic acid and protein content across the locations and planting dates. The oleic and linoleic acid content seemed to fluctuate across season, location and planting date with no clear pattern. It is likely that localized climatic conditions at the timing of flowering and seed development influenced these traits and further analysis is required to understand the factors regulating these traits. There were some interesting patterns observed in seed protein content across planting date, location and season (Figure 3). In Potchefstroom the protein content appeared to be elevated at the later two planting dates in the drier season while in the wetter 2021/2022 season the January planting date had significantly lower protein content and was more similar to the early November planting date. In Pretoria, in the dry 2020/2021 season there was no significant difference in protein content across the planting dates. However, in the wetter, cooler season planting date did influence protein content with later planting dates containing a higher percentage of protein (Figure 3). This indicates in general that seed protein content increases at later planting dates in most situations, but this is dependent on local climates and seasonal variations.

   Figure 3. Seed means protein content for the 2020/2021 (a and c) and 2021/2022 (b and d) seasons for the Potchefstroom (a and b) and Pretoria (c and d) measured in grams per plant with n = 15 per planting date. ANOVA and with multiple comparison tests show significant differences with p-value <0.05. The same letters indicate no significant difference. Error bars indicate standard error.

   

   

   

   

   An interesting finding has, emerged from the first season on sunflower response to heat waves. In February 2021, a heat wave struck the Pretoria site — and at this time, the December planting was eight weeks old, the January planting was four weeks old, while the February planting was just germinating. This heat wave had the greatest impact on the January and February planting dates, where the February planting date showed very poor germination as expected and the January planting showed stunted growth and small head diameter. Interestingly, at anthesis the stunted January planting showed elevated stigma receptivity. When seed traits were assessed, we found the January planting had significantly fewer unfilled seeds and did not have reduced yield compared to the earlier planting dates, suggesting that pollination in this planting date was more effective. The second season had no heat wave and elevated stigma receptivity was not observed. This suggests that sunflower yield stability is maintained under elevated temperatures, because plants may enhance floral traits and pollination when heat stress is experienced that stunts growth and biomass accumulation. We have had two BSc honours projects (Stiaan Odendaal and Jessica Berry) follow up on this in controlled environments and the same phenomena was observed. Jessica's work has revealed that the floral meristem, which produces the florets is altered under heated conditions indicating that this early life stage heat stress can trigger changes to the flowers at later mature stages, allowing sunflower to adapt to these adverse conditions and contributing to yield stability during these conditions.

   Figure 4. Stigma receptivity for five planting dates in Pretoria for the 2020/2021 and 2021/2022 seasons (a-d).

   ANOVA (a and b) and PCA biplot (c and d) on unfilled seeds, total seeds, filled seeds and grain filling percentage across the five planting dates. The active variables are indicated by red vectors (Unfilled seeds, total seeds, filled seeds, grain filling %). The F1 (horizontal axis) indicates the first principal component, and the F2 (vertical axis) indicates the second principal component. The numbers represent the planting date of the active observations (blue dots) with November (1); December (2); January (3); February (4) and March (5). The light blue shading shows the January planting date's active observations are clustered. n = 15 and error bars are SE. Microscopy images of sunflower floral meristem formation under heated and unheated conditions showing significantly under developed meristems (CZ) in heat stressed plants and a developing control floral meristem forming the precursors to florets (FUM).

   
   
   

   
   
   

   In the second season in Pretoria the very late March planting date also provided us with the opportunity to understand the effect of frost on flowering. The March planting date had highly variable plant with flowers at different stages from mature flowers, flowers mid anthesis and young buds still to open. We observed that the young buds were significantly affected producing little or no filled seed, while the flowers at anthesis were moderately affected and the mature plants yielded as expected. This suggests that different floral stages have different tolerance to extreme weather events and further studies my provide a detailed understanding of the effect of frost during the bloom period.

   Another interesting observation from these field trials was the establishment of disease in the different planting date trials. The focus of Phase 2 is on Sclerotinia incidences, and in both trials Sclerotinia head rot was only observed in the November planting date. Sclerotinia root rot was observed at both sites for the November, December and January planting dates, indicating different growth stages or environmental factors influence the different modes of this disease. We also observed that Alternaria appears to be more prevalent on the later planting dates at both sites. We have also observed several viral diseases associated with planting date, with some being the first report on sunflower in South Africa. These viral diseases are currently being further identified by Dr Davis Reed at FABI. These casual observations are interesting, as they suggest that sunflower may be susceptible to different diseases at different planting dates possibly due to plant growth stage or environmental condition.

   In order to follow up on the Sclerotinia disease observations, in our second field trial, we included a Sclerotinia inoculation trial at the different planting dates, and the progress of the head rot was tracked over time and compared to environmental factors associated with each planting date. As part of the survey component of this project, several isolates of Sclerotinia have been collected from both the UP and ARC sites, and entered into the FABI culture collection for preservation. One of these isolates was selected for the inoculation trial, and used to infect several heads in the field along with a negative and positive control. Disease progression was scored over time after initial inoculation. Ms Mapfumo found that disease progression was different at different planting dates, and this appears to be closely associated with humidity and temperature at or just after inoculation. The November planting date in the 2021/2022 season showed the slowest disease progression likely due to the high temperatures experienced just after inoculation, which limited the disease progression. These findings suggest that infection and progression of Sclerotinia head rot is closely associated with humidity and temperature at time of infection (accepted in Plant Pathology) and will be key information for modelling the interaction of planting date and infection for yield.

   Overall, this project has progressed well, and a great wealth of information has been collected and is currently being analysed and completed as part of Ms Mapfumo's PhD. The work, to date, was well received by the international sunflower community when presented by Dr Creux and Ms Mapfumo at the 20th International Sunflower Conference in Novi Sad, Serbia. Ms Mapfumo was awarded the Runner-up Poster Award for her work on the planting date trials that forms the bulk of this project. The summary of the conference was published in Oilseed Focus (Vol 8 No 4, December 2022 ISSN 2410-1206). Our first scientific publication was accepted last month and is currently undergoing revision before publication in Plant Pathology and this work focuses on Sclerotinia head rot progression associated with climate and planting date.

   The final phase of this project was predominantly dependant on the data collected in phase 1 and phase 2. We have initiated a collaboration with Dr Phillipe Debaeke and Dr Pierre Casadebaige at INRAE in France. We have used the SUNFLO model to model yield against planting date and the next step is to test if Sclerotinia head rot data collected in this project can be used to weight yield predictions based on environment. This work is currently underway and will be further advanced once Ms Mapfumo has submitted her PhD for examination.

5. Effect of fertilization and Sclerotinia on sunflower yield and quality

   Dr SH Ma'ali, Dr B Janse van Rensburg, MW Makgoga, JL Erasmus, TD Mohohlo and DP Nkoko
   ARC Grain Crops Institute, Potchefstroom

   The effects of fertilizers on sunflower yield have been described previously. International studies proved that nitrogen top dressing increases the content of crude fat and linoleic acid while more top dressing of N reduces the content of protein, oleic acid, and palmitic acid. Unfortunately, little or no research has been conducted in South Africa. This study addresses this topic in a scientifically sound manner.

   Five field experiments were established at ARC-Grain Crops Potchefstroom research farm over the last three (2020/21, 2021/22 and 2022/23), growing seasons. The first planting date (planted on 15 December during 2020 and 2022, respectively) was considered the optimum planting date. The second planting date (on 26 January 2021 and 2022, and 18 January 2023, respectively) was considered as late.

   Five sunflower hybrids, i.e. two conventional (PAN 7080 and AGSUN 8251), two Clearfield (AGSUN 5106 CLP and PAN 7160CLP) and one high oleic hybrid (PAN 7158 HO), were planted. Five different levels of nitrogen fertiliser were applied and consisted of 0 (control) or 45 kg/ha^-1 nitrogen as a basal application at planting or as a treatment one month prior to planting. This was followed with a topdressing one month from planting applied as (0, 45 or 75 kg/ha^-1).

   The milled grain mycelium method was used to prepare inoculum and for the inoculation method. Lesion sizes of all heads (from individual plots) were calculated and divided by the number of heads assessed to get an average disease score.

   Results of analysis of variance (ANOVA) for the main and interaction effects of N levels with different time of applications and sunflower hybrids on sunflower yield and quality shows highly significant effects of N levels and sunflower hybrids. Highly significant interaction effects of N levels and sunflower hybrids were only present for oil content and only for a slight interaction for oil yield.

   For N treatment levels, 120 kg N per ha applied as 45 kg/ha^-1 at planting and 75 kg/ha^-1 as topdressing produced the highest yield at both planting dates, this was followed by 90 kg/ha^-1 applied as 45 kg/ha^-1 at planting and 45 kg/ha^-1 as topdressing. There were no significant differences between 45 kg/ha^-1 applied one month before planting and the 45 kg/ha^-1 applied at planting. The seed yield was lowest where no N was applied at the optimum and at the late planting date. Highly significant differences were detected among the different tested sunflower hybrids for seed yield and quality.

   For S. sclerotiorum screenings, significant differences were noticed among different hybrids. An average lesion size of 1.03 cm² was recorded and it ranged from 1.26 cm² for PAN 7158 HO to 0.84 cm² for PAN 7160 CLP. According to the ANOVA results, the nitrogen applications have a significantly influence sclerotinia infections.

   KEYWORDS: Planting dates, N fertilization, Sclerotinia, sunflower

6. Evaluation of commercially available sunflower cultivars

   Dr SH Ma'ali, MW Makgoga, JL Erasmus and TD Mohohlo
   ARC-GCI

   Cultivar trials from previous years showed that the mean yield of the five best cultivars is usually about 0.18 t/ha^-1 higher than the overall mean yield of all the tested cultivars. Considering that the national mean yield that farmers obtain is normally between 1.0 and 1.4 t/ha^-1, it is clear that cultivar selection has a significant effect on the profitability of sunflower production. This project is the only independent source of information on sunflower cultivar performance, available to producers. The aim of this project is to evaluate commercially available sunflower cultivars at different localities in collaboration with seed companies. During the 2022/23 season, 20 cultivars were evaluated in 27 successful locality trials. The highest trial mean yield of 3.57 t/ha^-1 was obtained at Boskop planted on 20th of January 2023 and the lowest of 1.11 t/ha^-1, at Kroonstad planted on 7 February 2023. The five best performing cultivars, in terms of average yield calculated over localities, were PAN 7080, PAN 7180CLP, AGSUN 5270, PAN 65 LP 65 and PAN 7090. The overall mean yield for 2022/23 was 2.23 t/ha^-1, 1.40 % lower than the mean yield of the 2021/22 season.

   Eleven Clearfield and Clearfield Plus cultivars were entered and one of these cultivars PAN 7180 CLP had the one of the highest yields of 2.37 t/ha^-1 and performed the best in terms of seed yield. Seven of these cultivars namely PAN 7180 CLP, P 65 LP 65, PAN 7102 CLP, P 65 LP 54, AGSUN 5111 CLP, AGSUN 5106 CLP and PAN 7160 CLP have yields even or higher than the overall mean yield of all cultivars.

   Fifteen cultivars were evaluated at 63 localities for the last three seasons and the cultivars, PAN 7080, AGSUN 5270, PAN 7160 CLP, PAN 7180 CLP, P 65 LP 65, AGSUN 5106 CLP,PAN 7100, PAN 7102 CLP, P 65LP 54, and P 65 LL 02 had yields higher than the overall mean yield of all cultivars at 2.28 t/ha^-1. Probability to obtain an above average yield was calculated for all cultivars across the usual range of yield potentials. That was done for the 20 cultivars during the 2022/23 growing season, for the 15 cultivars that have been tested at 44 localities for the last two seasons and for the 15 cultivars that have been tested at 63 localities for the last three seasons. The yield probability method is highly recommended for cultivar selection.

7. National soybean cultivar trials

   AS de Beer, L Bonkhorst, HSJ Vermeulen, N Cochrane, NN Mogapi, TC Ramatlotlo and S Seutlwadi
   ARC Grain Crops Institute, Potchefstroom

   The National Soybean Cultivar Trials (project M101/62) were planted for the 45th successive year during the 2022/23 growing seasons. Thirty-two (32) commercially certified cultivars were evaluated in 33 field trials on 29 localities, representing the cool-, moderate- and warm areas. Thirteen (13) of the 32 (41%) cultivars evaluated during the 2022/23 season were new cultivars. These figures emphasise the importance of the constant evaluation of cultivars in an aggressively growing soybean industry. Unfortunately, 6 of the trials were terminated due to flooding and hail damage Cedara), (Chrissiesmeer and Frankfort) flooding (Cornelia) hail damage, (Derby) CV% to high and flooding followed by extreme drought (Lichtenburg). Due the late rains and cool temperatures the harvesting process took longer as anticipated. Only 27 trials were successful and could be included in the report.

   A randomised latinised row/column design with three replicates was used for all field trials. Date of flowering (50% flowering), date of harvest maturity, length of growing season, plant height, pod height, green stem, lodging, shattering, 100 seeds mass, undesirable seed and the yield probability of cultivars calculated. Yield probabilities served as guidelines for cultivar selection.

   The mean number of days from planting to 50% flowering of cultivars calculated across cultivars for the 2022/23 season were 77 days (74 days during 2021/22) for the cool, 63 (61 days during 2021/22) for the moderate, and 60 days (55 days during 2021/22) for the warm production areas, in comparison to the previous season. The unfavourable climate also impacted on the days from planting to harvest, resulted in an average of 168 days (164 days 2021/22), 149 days (149 days during 2021/22) and 148 days (150 days during 2021/22), respectively for the cool, moderate and warm areas.

   The mean yield of cultivars within climate areas varied from 2155 kg/ha^-1 (LS 6860 R) to 3082 kg/ha^-1 (DM 53I54RSF IPRO) (difference 927 kg/ha^-1), 3520 kg/ha^-1 (LS 6860 R) to 4015 kg/ha^-1 (P62T16 R) (difference 495 kg/ha^-1) and 3601 kg/ha^-1 (P57T19 R) to 4684 kg/ha^-1 (RA660 R) (difference 1083 kg/ha^-1) respectively for the cool, moderate and warm production areas. The overall mean yield was 2651 kg/ha^-1, 3776 kg/ha^-1 and 4246 kg/ha^-1 (cool, moderate, warm). Cultivars with a high yield probability are important in the selection of cultivars by producers due to the reliability of the expected future yield. P64T39 R showed an above average yield probability for all yield potentials in the cool, moderate as well as the warm areas. PAN1521 R, RA660 R and P7174 R performed above average for both the moderate and warm areas. DM 5351RSF and PAN 1644 R only performed above average for the cool area, while RA565 R and DM 6.8i RR showed an above average yield probability in warm area.

8. Oilseeds South African Soybean Crop Quality Survey

   Ms W Louw
   SAGL

   Goal

   The goal of this project is to accumulate quality data on the commercial soybean crop on a national level. The specific analyses done are of generic importance to the South African oilseed industry and will on request be adapted according to the industry's requirements. The data will be processed statistically to give an average, minimum and maximum per soya production region.

   This valuable data reveals general tendencies, highlight any quality differences in the commercial soya produced in different production regions for local market requirements and provide important information on the quality of commercial soya intended for export. The information will be available on the Southern African Grain Laboratory's (SAGL) website and the Oilseed Industry will determine the distribution list of the Directly Affected Groups and interested parties nationwide for the distribution of the report.

   The long-term goal of the project is the annual determination of the quality of the commercial soya crop. A detailed database containing information collected over several seasons and different regions is essential.

   To add value to the annual crop quality report, fatty acid profile analyses on 20 composite crop samples representing different production regions as well as 20 cultivar samples from different localities were included in the proposal since the 2018/2019 season. Fatty acid profiles are the most important tool for the identification of the authenticity of vegetable fats and oils. The variation of fatty acids in a specific oil also influences the stability and physical properties of the oil. Fatty acids vary depending on climate, latitude, cultivar as well as seasonal variation. These variations should be included when specifying ranges for identification of authenticity.

   It is imperative to identify the ranges wherein fatty acids vary, to successfully validate the authenticity of a specific vegetable oil. Building of a database requires gathering of information over different seasons, areas, and cultivars to give a true reflection of the ranges wherein fatty acids can differ. Currently, no national updated database is available. If a national database is kept and maintained, time and money lost by the industry because of rejected batches can be avoided.

   The natural variation caused by different cultivars, climate, and locality as well as seasonal variation will be included in the values of this database for the South African produced seed oils.

   Duration of project

   Sampling to ensure representative samples of the country's entire commercial soybean crop will start with the first deliveries during April/May 2023. The analysis of the samples will commence as soon as the funding of this project has been approved and samples are received by the SAGL. Results will be updated weekly on the SAGL website after the commencement of the analyses.

   ---

   Scope of project

   ---

   Number of samples

   Based on an average crop size, the proposal is to analyse 150 samples annually to provide representative data of the commercial crop. The predicted crop for the 2021/2022 season is 2 091 350 tons (National Crop Estimates Committee (NCEC), 5th forecast, 28 June 2022).

   Each registered silo represents a sampling point. A representative sample per class and grade per silo bin/bag/bunker will be taken by each of the commercial grain storage companies handling soybeans. There are two classes of soybeans, namely Class SB and Class Other soybeans. Provision is made for 150 samples (130 SB1 and 20 samples COSB). The Grain Silo Industry (Agbiz Grain) has offered to take and provide the samples to the SAGL. This sampling is done free of charge which has a huge cost saving effect on the survey.

   Based on the agreements between the silo owners and their customers delivering the soybeans at the silos the quality information can only be made available on a regional basis.

   Sampling procedure

   On intake of the soybean crop at the silos, a representative sample for grading is taken in accordance with the Grading Regulations for soybeans, as published in the Government Gazette No. 40794 dated 21 April 2017, Government Notice No. R. 370. After grading, the grading samples are placed in a container representing each bin concerned. Once 80% of the expected harvest has been received, the content of each container is divided in order to obtain a 3 kg sample. This is done for each bin and respective class and grade separately.

   These samples are submitted for analyses to the SAGL by the different commercial grain handlers. Each sample bag is labelled with the name of the silo, bin, and the soya grade. Sampling is to be carried out over the entire production area. All the soya production areas will be covered and will be represented proportionally by the data.

   Types of analyses and methodologies applied

   The following physical and chemical analyses will be done on 150 locally produced soybean samples:

   • RSA Grading: Government Gazette 40794, 21 April 2017, Government Notice No. R. 370
   • Protein, % (d.b.) (AACC Method 46-30.01, latest edition)
   • Fat, % (d.b.) (Soxhlet, In-House Method 024)
   • Moisture, % (17 Hour; 103° C - ISTA, Section 9, latest edition)
   • Ash, % (In-House Method 011)
   • Crude fibre, % (Acid-base digestion; In-House Method 031)
   • Test weight, kg/hl (Kern 222; chrondrometer)
   • NIR, including Protein, Fat, Moisture, Ash and Crude Fibre, %

   On 15 randomly selected locally produced soya seed samples, the following analysis will be performed:

   Genetic Modification (GM) analyses for CP4 EPSPS (RUR) (Envirologix QuickComb kit for bulk soybeans)

   **Fatty Acid Profile (AOCS Ce2-66) analyses will be performed on 20 cultivar trial samples as well as 20 commercial crop samples. These analyses will be subcontracted to Precision Oil Laboratories, a SANAS accredited laboratory (SANAS Accreditation Number T0802).

9. South African sunflower crop quality survey

   Ms W Louw
   SAGL

   Goal

   The goal of this project is to accumulate quality data on the commercial sunflower crop on a national level. The specific analyses done are of generic importance to the South African oilseed industry and will on request be adapted according to the industry's requirements. The data will be processed statistically to give an average, minimum and maximum per production region.

   This valuable data reveals general tendencies, highlight any quality differences in the commercial sunflower crop produced in different production regions for local market requirements and provide important information on the quality of commercial sunflower seed intended for export. The information as well as the report will be available on the Southern African Grain Laboratory's (SAGL) website and the Oilseed Industry will determine the distribution list of the Directly Affected Groups and interested parties nationwide for the distribution of the report.

   The long-term goal of the project is the annual determination of the quality of the commercial sunflower crop. A detailed database containing information collected over several seasons and different regions is essential.

   To add value to the annual crop quality report, this application also includes fatty acid profile analyses on 20 composite crop samples representing different production regions as well as 20 cultivar samples from different localities. Fatty acid profiles are the most important tool for identification of authenticity of vegetable fats and oils. The variation of fatty acids in a specific oil also influences the stability and physical properties of the oil. Fatty acids vary depending on climate, latitude, cultivar as well as seasonal variation. These variations should be included when specifying ranges for identification of authenticity.

   It is imperative to identify the ranges wherein fatty acids vary, to successfully validate the authenticity of a specific vegetable oil. Building of a database requires gathering of information over different seasons, areas, and cultivars to give a true reflection of the ranges wherein fatty acids can differ. Currently, no national updated database is available. If a national database is kept and maintained, time and money lost by the industry because of rejected batches could be avoided.

   The natural variation caused by different cultivars, climate, and locality as well as seasonal variation will be included in the values of the database. This motivation is therefore to continue with the development of a fatty acid profile database for the South African produced seed oils.

   Duration of project

   Sampling to ensure representative samples of the country's entire commercial sunflower crop will start with the first deliveries during April/May 2023. The analyses of the samples will commence as soon as the funding of this project has been approved and samples are received by the SAGL. Results will be updated weekly on the SAGL website after commencement of the analyses.

   ---

   Scope of project

   ---

   Number of samples

   Based on an average crop size, the proposal is to analyse 176 samples annually to provide representative data of the commercial crop. The predicted crop for the 2021/2022 season is 961 350 tons (National Crop Estimates Committee (NCEC), 5th forecast, 28 June 2022).

   Each registered silo represents a sampling point. A representative sample per class and grade per silo bin/bag/bunker will be taken by each of the commercial grain storage companies handling sunflower seed, provision is made for 176 samples. There is only one grade of sunflower seed for classes FH and FS seeds, namely Grade 1. The Grain Silo Industry (Agbiz Grain) has offered to take and provide the samples to the SAGL. This sampling is done free of charge which has a huge cost saving effect on the survey.

   Based on the agreements between the silo owners and their customers delivering the sunflower seeds at the silos the quality information can only be made available on a regional basis.

   Sampling procedure

   On intake of the sunflower crop at the silos, a representative sample for grading is taken in accordance with the Grading Regulations for sunflower seed as published in the Government Gazette No. 39613 dated 22 January 2016, Government Notice No. R. 45.

   After grading, the grading samples is placed in a container representing each bin concerned. After 80% of the expected harvest has been received, the content of each container is divided to obtain a 3 kg sample. This is done for each bin and respective class and grade separately.

   These samples are submitted for analyses to the SAGL by the different commercial grain handlers. Each sample bag is labelled with the name of the silo, bin, and grade/class. Sampling is to be carried out over the entire production area. All the sunflower production areas will be covered and will be represented proportionally by the data.

   Types of analyses and methodologies applied

   The following physical and chemical analyses will be done on 176 locally produced sunflower seed samples:

   • RSA Grading: Government Gazette 39613, 22 January 2016, Government Notice No. R. 45
   • Protein, % (as is) (AACC Method 46-30.01, latest edition)
   • Fat, % (as is) (Soxhlet, In-House Method 024)
   • Moisture, % (5 Hour; 105° C – AgriLASA method 2.1, latest edition)
   • Ash, % (as is) (In-House Method 011)
   • Crude fibre, % (as is) (Acid-base digestion; In-House Method 031)
   • Test weight, kg/hl (Kern 222 chrondrometer)
   • NIR, including Protein, Fat, Moisture, Ash and Crude Fibre, %

   Fatty Acid Profile (AOCS Ce2-66) analyses will be performed on 20 cultivar trial samples as well as 20 commercial crop samples. These analyses will be subcontracted to Precision Oil Laboratories, a SANAS accredited laboratory.

   (SANAS Accreditation Number T0802).

   Format of reporting on website and hard copy

   Individual results are e-mailed to the respective grain handlers on a weekly basis once the results become available.

   SAGL website

   Average results per region are available on the SAGL website as soon as the first results become available. The mean values of all samples from each region are calculated in respect of every quality parameter analysed. These averages are available on the SAGL website per region and per quality parameter grouped into subgroups such as RSA grading and Nutritional values.

   Written report

   The abovementioned averages will be tabled in the written report.

   Distribution of data

   Weekly updates of the data on the SAGL website will be done on the commencement of the analyses. The report, which can be downloaded from the SAGL website, will become available after all the samples have been analysed and the data processed. The written report will be distributed to all the Directly Affected Groups and interested parties. Reports will be submitted to the Trustees of the Oil and Protein Seed Development Trust on completion.

10. The funding of the Supply and Demand Estimates Committee

    Ms F Sundani
    NAMC

    Introduction

    It is important to note that the purpose of the monthly Supply and Demand Estimates Committee (S&DEC) meetings is to capture new information that is available in the market at a specific time. It is also crucial to understand that access to accurate market information plays a central role in any agricultural development and, to some extent, information can address other issues such as food security. In 2011, Grain South Africa applied for a statutory measure for grain traders to report information on export and import contracts. A similar approach is practiced in the United States of America. The application by Grain SA was opposed by other directly affected groups such as the South African Cereals and Oilseeds Trade Association (SACOTA); however, collaboration between SACOTA and the Supply and Demand Estimates Committee was subsequently established. The proposed statutory measure was then put on hold, and the committee sought to perform its activities without the interference of the statutory measure. The industry thus appointed Dr John Purchase as Chairperson of this committee, with the National Agricultural Marketing Council (NAMC) acting as secretariat. Following all industry engagements and consultations, the first official Supply and Demand Estimates report was published at the end of June 2013. The establishment of this committee was demand driven by the need to produce accurate and transparent market information to ensure that the market functions more efficient for the participants.

    Purpose of the South African Supply and Demand Estimates (SASDE) Report

    The report provides an analysis of the fundamental conditions of the major grains and oilseeds in South Africa. The report is normally released within four to five working days after the Crop Estimates Committee (CEC) meeting. The report is released into the public domain with the approval of the South African competition authorities. Please see Annexure 1 for publication dates.

    Composition of the S&DEC

    The S&DEC is a technical committee that communicates directly with industry role-players through the Supply and Demand Estimates Liaison Committee (S&DELC). The S&DEC consists of a chairperson with two independent specialists appointed by the industry; the NAMC acts as the secretariat with three staff members and the South African Grain Information Service (SAGIS) and the secretariat of the CEC from the Department of Agriculture, Forestry and Fisheries (DAFF).

    NAMC representatives

    • Dr Moses Lubinga — Manager: Agro Food Chains
    • Ms Lizette Mellet — Senior Economist: Statutory Measures
    • Ms Funzani Sundani — Senior Economist: Grain Specialist

    DAFF representatives

    • Ms Rona Beukes — Senior Statistician: Crop Estimates
    • Ms Marda Scheepers — Senior Statistician: Crop Estimates

    SAGIS representative

    • Mr Bernard Schultz — CEO: SAGIS

    Independent specialists

    • Dr Andre Jooste
    • Prof Johan Willemse
    • Dr Anton Lubbe

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    Methodology used by the S&DEC

    ---

    Process before the meeting

    • The S&DEC meeting takes place three to five working days after the CEC meeting, at the end of each month with the exclusion of December.
    • A reminder is sent to all co-workers approximately seven days before the S&DEC meeting, requesting that they submit estimates on imports, exports and consumption for selected grains and oilseeds.
    • The S&DEC meeting takes place in a lockdown room with no cell phones allowed, except when there is uncertainty about any of the figures sent by co-workers.

    Factors that are taken into account during the meeting

    • Supply figures
    • CEC published figures
    • S&D historical figures
    • Demand figures
    • Historical figures (SAGIS)
    • Current deliveries published by SAGIS (extrapolations, regression modelling)
    • Co-workers' figures, without disclosing their identity
    • SAGIS figures
    • Figures and opinions of, and discussions with, co-workers
    • Baseline modelling figures on demand and consumption from the Bureau for Food and Agricultural Policy (BFAP)
    • Other modelling, including industry forecasting modelling and computable general equilibrium (CGE modelling), is also considered for use in the future, taking into consideration the expansion incapacity.

    Distribution and users of the SASDE Report

    The NAMC retrieves the number of website hits every month. The purpose of this exercise is to track the number of end-users of the SASDE report. It is noted from the NAMC monthly website hits that about 1000 hits are received for the SASDE report. The report is mainly utilized by the following:

    • Academia
    • Financial and investment institutions
    • Government officials
    • Grain Millers
    • Oilseed processors
    • Feed manufactures
    • Grain and oilseed traders
    • Grain and oilseed storage handlers
    • Oilseed storage handlers
    • Baking industry
    • Research institutions and transport organisations
    • Others

    Actual expenses for 2022/23 and new proposed budgets

    The S&DEC want to extend their gratitude to the Maize Trust, Oil and Protein Seeds Development Trust, and the Sorghum Trust for the payment of their contributions for the 2022/23 financial year. The decision was taken to depart with a zero base budget and based on the actual expenses and contributions received for the 2022/23 financial year. For the proposed budget for the 2023/24 financial year, expenses were recalculated based on tariffs and occurrences applicable to meetings and planned excursions. The contributions from the Trusts were calculated based on the difference between the total expenses and the NAMC contribution and allocated according to the same percentages as used by SAGIS. The salaries and allowances were adjusted by 2% going forward from the actual expenditures of 2022/23 and all the other expenditures were adjusted by 6%. From Table 2, it can be seen that the travel and accommodation budget line shows a noticeable increase from 2022/23 to 2023/24 because there was only one physical meeting(s) held during the 2022/23 financial year as well as no planned excursions.

    Supply and Demand Estimates Committee (S&DEC)	Actual Expenses 2022/23	Budget 2023/24	Budget 2024/25
    Incomes
    NAMC	595 351	631 000	643 620
    Maize Trust (66.2% of diff.)	201 174	246 087	254 091
    Oil & Protein (15.8% of diff.)	65 494	58 734	60 644
    Winter Cereal (13.5% of diff.)		50 184	51 816
    Sorghum Trust (4.5% of diff.)	21 532	16 728	17 272
    Total Income	883 551	1 002 733	1 027 444
    Salaries and allowances	871 285	872 831	890 288
    Travel & Accommodation	25 272	117 404	124 448
    Catering		3 498	3 708
    Miscellaneous	-13 006	9 000	9 000
    Total expenses	883 551	1 002 733	1 027 444

    On the proposed budgets, the Winter Cereal trust is still listed, but the S&DEC is investigating the viability of this and also possible replacements.

    Stakeholder engagements

    As part of the Supply and Demand Estimates initiative, it is imperative to establish relationships with key industry stakeholders to ensure that the Supply and Demand Estimates Report gives an in-depth overview of key industry information pertaining to grains and oilseeds.

    To that end, the Grain Specialist and the Chairperson of the Liaison Committee met with industry stakeholders on March 22nd, 2023. The objective of these meetings was to foster relationships and assure the collection of critical information about grains and oilseeds. The stakeholders who were engaged were from the manufacturing and trade industries. Information was exchanged during these meetings for the benefit of the NAMC and the engaged stakeholders. It is worth noting that, in addition to physical visits there is an ongoing telephone consultation process with various stakeholders to ensure that the Supply and Demand Estimates Committee's estimates reflect a comprehensive overview of the trends pertaining to grains and oilseeds.

    Conclusion

    The efficacy of information plays a significant role in developing nations. Relevant and accurate information can ensure the sustainability of the market and that a nation's food security is well-considered following private and government objectives. It is initiatives such as generating the SASDE report that could provide effective information to the market for a specific period. The publication of the SASDE report has taken the grain and oilseeds market in South Africa and the region to another level, as evident from the statistics about the end-users of the report. The mutual understanding and collaboration of the NAMC and the trusts have also contributed significantly to the functioning of the S&DEC. Such support is what the committee requires to ensure that its functions are fulfilled and continuously improved.

11. Cultivar evaluation of oil and protein seeds in the winter rainfall area: Western and Southern Cape (canola)

    Mr PJA Lombard, Ms L Smorenburg and Dr JA Strauss
    Department of Agriculture: Western Cape

    During 2022, the number of trials in the Swartland and Southern Cape has been increased to five localities per area. Additionally to that, two sowing date trials were planted on Langgewens and Tygerhoek Research Farms, including an Elite trial on both locations. All the trials in the 2022 season have been harvested. In the 2022 cultivar evaluation program, a total of 17 cultivars were tested. In 2022, eight new cultivars were tested and all cultivars were, as in the past few seasons, hybrid cultivars. The cultivars consisted of five conventional, four Cl (Clearfield, Imasamox-tolerant), eight from the TT group (Triazine-tolerant) and for the second time a combination type cultivar was included in the trials that covered both the Cl and TT-tolerance (Enforcer CT).

    Climate

    The 2022 growing season at Langgewens was the 4th driest season since 1964. The rainfall during all the months of the growing season was below average. The temperatures were also higher than in 2021, although the average minimum temperature during September was 0.9°C lower than the long-term average. Canola plants are very sensitive to high temperatures during the period from flowering (July) to the end of seed filling.

    The yield from the earlier planting date trial on Langgewens was over 1000 kg ha^-1 lower (2622 kg ha^-1) than in 2021. The seed only germinated after the first significant rain on 29 May. In 2021, the trial germinated on 15 May with a very average rainy season. The 2022 rainfall not only started late, but it was also very dry in the entire Swartland.

    Tygerhoek, in the Southern Cape, received 269 mm of rain during the 2022 growing season. This was less than the average of 303 mm over the last 15 years. During the period from May to August, the monthly average rainfall was more than the long-term average. However, September and October, which are considered two important months for increased crop yield, were drier than normal.

    Above-average warm maximum temperatures occurred during the growing season. The minimum tem­peratures were very close to the longterm average, except for August and September which were colder than normal. Low night temperatures are very important for the recovery of the plant. On 23 and 24 August, the Southern Cape experienced temperatures of >28°C over the two days. This shortened the flowering period of the canola in most areas. The cooler than normal night temperatures were indeed beneficial to the recovery of the plant.

    Results

    In the Swartland, the dry season affected the yield negatively, particularly at Eendekuil, and the trial's data were not included. Very little Sclerotinia occurred in 2022. The harvest season was late in the Swartland, due to the later than normal germination. The higher than normal humidity during September and October con­tributed to the best seed yield (kg seed) mm^-1 rainfall in history, at Langgewens.

    Swartland

    In the Swartland, the average yields per trial varied between 2849 kg/ha^-1 (Pools in Piketberg district) to 1693 kg/ha^-1 at Hopefield. The trial at Pools started germinating on 30 May, two weeks before the rest of the trials (most of Langgewens' plants started germinating on 15 June). The seed of the line CC91117 was not 100% pure and this may negatively influence the seed yield. The line CC90014 (2535 kg/ha^-1) produced the highest yield on average, followed by the cultivar Diamond (2440 kg/ha^-1) and Hyola 90013 (2363 kg/ha^-1). The yields of the three cultivars did not differ significantly from each other.

    Of the four Cl cultivars tested in 2022, 43Y92 (2535 kg/ha^-1) produced the highest yield within the group. The new Cl cultivar 44Y94 produced the second highest yield (2436 kg/ha^-1) followed by the cultivars with a longer growing season (45Y93 and 45Y95). The second planting date at Langgewens was 22 June, which is considered extremely late and this adversely affected the yield of the cultivars with longer growing seasons. The planting date had to be postponed, as the first planting date trial did not fully germinate until after the rain on 15 June.

    The new TT cultivar HyTTec Trophy produced the highest yield (2238 kg/ha^-1) within the TT group, followed by another new TT cultivar, HyTTec Trifecta. Unfortunately, these cultivars will only be available for the local market in 2024. Blazer TT (2111 kg/ha^-1) was the best producer among the commercially available TT cultivars and followed by Alpha TT and Hyola350 TT. The three cultivars did not differ significantly from each other. The average yield of the TT cultivars in 2022 was 15% lower than the conventional and Cl cultivars.

    Southern Cape

    In the Rûens the combined seed yield at Klipdale was the best (2550 kg/ha^-1), followed by Napier (2322 kg/ha^-1). The average yield in 2022 was 2124 kg/ha^-1, compared to 3271 kg/ha^-1 and 3704 kg/ha^-1 in 2021 and 2020 respectively.

    The Southern Cape had a below average rainfall season and the period during seed filling was extremely dry. This negatively affected the yield of all the cultivars. The CL cultivar 43Y92 (2429 kg/ha^-1) produced the highest yield within the group. The cultivar, 44Y94 produced the second highest yield (2227 kg/ha^-1) followed by the cultivars with longer growing seasons, 45Y95 and 45Y93. The yield of the CL cultivar 43Y92 was significantly higher. The conventional line/cultivar CC90014 (2470 kg/ha^-1) produced the highest yield within the conventional group, followed by Diamond (2350 kg/ha^-1). There was no significant difference between CC90014 and Diamond. The cultivars in 3rd and 4th place were Quartz and Hyola 90013 respectively.

    The TT cultivar Alpha TT (2196 kg/ha^-1) followed by Blazer TT (2060 kg/ha^-1) was the highest-producing cultivar within the TT group. They were followed by the new TT cultivar HyTTec Trophy. The three cultivars did not differ significantly from each other. The average yield of TT cultivars was 12% and 6% lower than the conventional and Cl cultivars respectively.

    Conclusion

    Canola as a crop has proven its adaptability to local climate conditions in 2022. In the Swartland, humid conditions during the night in spring cooled the plants to such an extent that a reasonable yield was possible, even though the seed germinated very late in the growing season. Yields of well above 2 tons/ha^-1 can be expected with an average rainfall season. Please be aware of the risk of Sclerotinia during a wetter growing season - this remains a risk and can drastically reduce yield.

12. Sudden death syndrome of soybean in South Africa: etiology detection and management

    Dr S Lamprecht
    ARC-PPRI

    Sudden death syndrome (SDS) of soybean is one of the most important soilborne diseases of soybean and is responsible for economically devastating reductions in yields in North and South America. Several Fusarium species including Fusarium brasiliense, F. crassistipitatum, F. tucumaniae, and F. virguliforme cause the disease in other countries. All these species, as well as F. azukicola, and F. cuneirostrum, were recently included into the newly described Neocosmospora phaseoli. SDS was first reported in South Africa in 2013 in the Lydenburg/Badfontein area, Mpumalanga Province. The causal organism was initially reported to be F. virguliforme, but later re-identified as F. brasiliense and a novel Fusarium sp. Judging by published information on the disease in other countries, SDS may pose a threat to the South African soybean industry. In order to conduct any epidemiological research and develop management strategies for SDS in South Africa, it is essential to determine the distribution and identity of all SDS-causing Neocosmospora spp. (Fusarium spp.) in soybean-producing areas in South Africa. The first phase of the project therefore aimed to determine the distribution of the disease, identify the causal organisms, and developed a molecular technique for rapid identification of the SDS-causing pathogen/s and for detection and quantification of these pathogens in soil and plant material. Surveys conducted in soybean production areas showed that N. phaseoli was present on soybeans in the Free State, KwaZulu-Natal, Limpopo, Mpumalanga, and North West provinces. These results indicate that SDS is widespread and may be a concern for producers when environmental conditions are conducive to disease development. A species-specific TaqMan probe-based qPCR assay was also developed for the specific detection of N. phaseoli in naturally infected soybean crown, root and soil samples with DNA quantities well within the quantifiable range of the assay. This detection assay will be an invaluable tool for the rapid and sensitive detection of SDS in samples submitted by farmers. The project thus far has clarified the distribution of N. phaseoli on soybean in South Africa. Furthermore, a sensitive and specific qPCR assay was developed that can reliably detect and quantify N. phaseoli in soybean plant and soil samples. During the next phase of the project, strategies for the management of SDS will be investigated and developed.

13. South African Sclerotinia Research Network (SASRN)

    Dr L Rothmann
    University of the Free State

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    Community of Practice

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    The South African Sclerotinia Research Network (SASRN) was established to foster collaboration between relevant stakeholders involved with Sclerotinia research and disease management.

    Three projects were initiated at the University of the Free State:

    • Community of Practice (Dr Lisa Rothmann)
    • Phenotypic and genotypic screening of soybean to identify potential sources of resistance to the destructive pathogen, Sclerotinia sclerotiorum (Dr Adré Minnaar- Ontong)
    • Sclerotinia sclerotiorum disease potential and management responses in soybean and sunflower (Dr Lisa Rothmann)

    Introduction

    Sclerotinia sclerotiorum is a prolific fungal plant pathogen, with multiple host crops of agricultural and economic importance. South African host crops of importance include soybean, sunflower and canola which make significant contributions to the South African economy.

    The South African Sclerotinia Research Network (SASRN) was established to promote collaboration among researchers involved with Sclerotinia research, enable engagements between researchers and industry members as well as to facilitate interactions between researchers and producers affected by Sclerotinia diseases. The virtual community of practice (CoP) serves as a platform for researchers to create collaborations, to allow for parallel and comprehensive research and to act as catalyst for the development of applied intervention technologies for producers. Furthermore, generating social and academic capital, where experienced investigators exchange knowledge with junior investigators, will contribute to developing skills related to Sclerotinia diseases, ensuring technology and intellectual transfers, and contribute significantly to advancement of research on this pathogen.

    The Community of Practice also drives communication between producers and network members. Producer-focused research is pivotal for the network and will be supported through collaborations established. These collaborations promote communication between the parties involved, which prevents duplication and allows researchers to inform the industry directly of findings, and vice versa. In addition, the network is a platform where industry and academia can listen to the needs of producers to actively resolve issues through applied and directed research questions.

    The SASRN focuses on three key themes, namely: 1) generating a virtual centre of excellence and expertise (through the use of a website and communication platform); 2) the role South Africa can play in the Sclerotinia research arena internationally and most importantly 3) developing and communicating practical management strategies for diseases caused by Sclerotinia for local producers.

    The objectives through which the SASRN aims to achieve the above themes are as follows:

    • Host an Annual General Meeting to facilitate discussions between researchers and industry;
    • Host research Accountability Meetings to monitor the progress of research objectives;
    • Industry engagements;
    • Share information via a website;
    • Share information on social media platforms;
    • Provide extension services to producers via farmer's days, laboratory analyses, the Sclerotinia hotline, surveys and extension articles.

    Progress

    Annual General Meeting

    The Annual General Meeting allows for the network to communicate and strengthen the community. It further serves as a platform for the research community at large to communicate with industry and align priorities. Continuous meetings take place to discuss project progress and research focus areas. Dr Rothmann will be presenting the progress of the CoP and Research Consortium at the Rhizobia Symposium in September 2022.

    Research accountability meetings

    Focused meetings were held between SASRN researchers and Grain SA.

    Industry engagements

    Meetings were held with representatives from chemical companies to discuss these companies' specific needs. As trials are notoriously difficult to execute successfully (due to the sporadic nature of the disease), the support which can be provided by researchers was discussed. This includes providing inoculum for trials, conducting trials to test the efficacy of products and conducting disease screening. As the products which are being tested are either not registered for use in South Africa, or not registered for use on either sunflower or soybean, these engagements take place between the company and the researcher to maintain con­fidentiality (all costs related to the support provided are carried by the company. Funds provided by OPDT are not used in this regard).

    Website

    The SASRN website was launched as a tool which provides useful information on topics such as scouting for sclerotia in the field, the disease cycle and management strategies. The Knowledge Hub stores all popular media articles written for various agricultural magazines as well as those written uniquely for the website.

    Lisa Rothmann was interviewed on AgriScoops, a radio programme for Afrikaans listeners on the 22nd of February 2022. This was the result of a short article being published at SA Grain, with Dr Miekie Human, titled: "Sclerotinia alert: Is 2022 a good year for an outbreak?". It can be found at this link.

    Furthermore, Lisa Rothmann will be uploading "banners" of short information on disease diagnosis, symptoms and sign identification. These have been uploaded:

    • Weed hosts associated with Sclerotinia sclerotiorum
    • Sclerotinia sclerotiorum diagnostics rolfsii
    • Sclerotinia sclerotiorum diagnostics
    • Sclerotiorum and rolfsii
    • SclerotiniaZA Pamphlet
    • SclerotiniaZA Pamphlet (Continued)

    Social media

    The social media accounts are updated regularly with diagnostic tips, photos, videos and short articles. A significant increase in Facebook followers and likes has been observed over the last few months. Short videos were posted which were widely viewed and proved popular.

    

    Extension services

    • Farmer's days

      The University of the Free State attended the annual, in person farmers day in Delmas for the Network and their research in the first week of March 2022. Over 150 producers attended the information day and successful interactions were made, sharing the pamphlets made for the Network.

      Producers have contacted the SASRN telephonically, specifically to discuss management options, in lieu of meeting in person. Telephonic contact was also made with producers referred by Grain SA.

      Dr Rothmann in collaboration with Annelie De Beer presented their first Farmers Day at the end of March in the Eastern Cape province. Dr Rothmann could not attend in person as planned, due to the change in the dates, although a video recording was sent to share on the day.

      Dr Rothmann and Ms Bontleng Bolokwe, an Agricultural Advisor for the North West Department of Agriculture and Rural Development, organised a Producer Information Day in Mooifontein, near Mafikeng, NW. Dr Miekie Human, Grain SA attended with Dr Godfrey Kgatle, Postdoctoral fellow, Plant and Soil Sciences, University of Pretoria who presented the findings of the survey he has been championing. Ms Bolokwe invited ~50 producers she is 'responsible for' and are within a 10 km radius from location of the Information Day. Although, we only presented to the 12 attendees, the day was a success as this was the first interaction the producers had with plant pathology, and specifically requested information about Sclerotinia head rot. Each producer who attended was able to take a pamphlet (or two) about the Sclerotinia Research Network and Sclerotinia diagnosis and management.

      We plan to continue with this information day again in the future, with better communication and engagements, to plan the information day during the season with the inclusion of apothecia scouting and disease diagnosis.

    • Sclerotinia hotline

      Producers, agents and researchers continue to contact the SASRN regarding Sclerotinia control options. Many of the queries were related to Sclerotinia head rot of sunflower.

    • Extension articles

      A short article was published at SA Grain, with Dr Miekie Human, titled: "Sclerotinia alert: Is 2022 a good year for an outbreak?". Dr Rothmann is writing an article on S. sclerotiorum associated with soybean seed for the Oilseed Focus Magazine, this research was funded by Dr Rothmann with internal UFS research funds, although utilising seed from the harvested 2020/2021 season funded by the SASRN funders.

    Activities to be continued

    It is proposed that the activities as set out in the Community of Practice continue as originally proposed.

    Conclusion

    As Sclerotinia is becoming a more serious issue amongst the producers we are also receiving more attention from producers. A material transfer agreement was set up for the Sclerotinia culture collection and this will enable fluid and transparent transfer of cultures between institutions and researchers, further building trust and collaboration.

    The website will continue to publish short research articles, as well as in collaboration with collaboration with Pula Imvula to reach emerging producers. Social media sites continue to grow, and members of the public interact with the materials provided.

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    Project 2: Phenotypic and genotypic screening of soybean to identify potential sources of resistance to the destructive pathogen, Sclerotinia sclerotiorum

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    Introduction

    Soybean is highly susceptible to S. sclerotiorum and the impact of infection on this crop is high. The use of avoidance mechanisms such as upright and open plant structure, less dense canopies and branching patterns, elevated pod set and reduced lodging have been suggested to reduce the damage caused by Sclerotinia diseases, however, in an environment that is favourable for disease development these practices are often not sufficient. Therefore, resistant varieties remain the best alternative for Sclerotinia disease management. Despite the impact of the disease on crops and the numerous breeding and selection efforts, progress has been limited and acceptable levels of resistance to S. sclerotiorum diseases have not been forthcoming (Hoffman et al., 2002), especially in South Africa. In South Africa, no known acceptable sources of resistance to Sclerotinia diseases are available and knowledge of sources of resistance is limited because of various screening constraints. However, various resistance sources from different countries/regions are available for soybeans to be used in breeding programmes (Zhoa et al., 2015; McCaghey et al., 2017; Demetrijevic & Horn 2018).

    Genotypic screening is considered a powerful tool in the identification of Sclerotinia resistances genes/QTLs which can lead to the effective control and management of Sclerotinia diseases worldwide. DNA markers are employed to select a targeted trait at seedling stage (Foolad and Sharma 2005), decreasing the time it takes to know the phenotype of a plant and reducing labour for the breeder because undesirable plants can be eliminated early in the breeding programme. The DNA markers used are also not affected by the influence of the environment and can be used to identify and select for traits controlled by polygenes through marker-assisted breeding (Jiang 2013).

    The aim of this study is to screen South African commercial soybean cultivars for Sclerotinia resistance by using both phenotypic and genotypic screening methods. South African commercial soybean cultivars identified as tolerant from a previous project as well as tolerant/resistant cultivars attained from breeding companies and research institutes from abroad (Canada, North Dakota, Argentina and Brazil) will be screened to determine the genotypic compilation of these cultivars with regards to Sclerotinia resistance genes/QTLs. Lines showing resistance potential will be subjected to several greenhouse and field trials to confirm the genotypic data generated. The identification of SA cultivars with resistance potential can help with the improvement of soybean production as well as disease management and control.

    The four objectives of this study are:

    • Selection of potential resistant lines based on the targeted Sclerotinia resistant QTLs.
    • Identification and selection of potential resistant lines/cultivars available from South African germplasm.
    • Phenotypic validation of resistance using best inoculation method in both greenhouse and field trials.
    • Establish and maintain a culture collection of South African S. sclerotiorum isolates.

    Progress

    • Selection of potential resistant lines based on the targeted Sclerotinia resistant QTLs

    Eight soybean cultivars with partial resistance to Sclerotinia were obtained from Argentina. Cultivars were genotypically screened using 54 SSR markers. Cultivars had different combinations of the known resistance QTLs and 6 Major QTLs were identified. From literature, it is expected that the combination of 3 major QTL indicates partial resistance. All combinations had at least 3 major QTLs, but more major QTL combinations are desired.

    Cultivars with the best combination of targeted Sclerotinia resistance QTLs were selected for phenotypic screening under greenhouse and field conditions to validate the tolerance.

    • Greenhouse screening: Completed.

      Disease evaluation for this trial was completed in December 2020. The results obtained from all 3 repetitions correlate very well with the genotypic screening.

      A detach leaf assay was done in Feb/March 2021 to confirm the phenotypic validation with the straw inoculation method. This experiment was completed successfully and also confirmed the results obtain from marker data and the phenotypic validation.

    • Field screening: In progress.

      Two repetitions of the field trials have been completed and the third will be conducted in November 2022. Thus far, variations have been observed for some cultivars in response to inoculation with the pathogen. Results from the third repetition under field conditions will be important to draw conclusions from the data.

    In addition, a cultivar was recently released by the USDA which is described as having complete resistance (this will be the first cultivar with complete resistance to Sclerotinia). Twenty seeds were received, of which five seeds were planted for multiplication and six will be used for adaptation testing. Testing of the USDA cultivar under local conditions will shed light on whether this cultivar is indeed completely resistant to Sclerotinia disease, or whether the observed resistance is due to tolerance and other mechanisms such as disease escape. Testing of this cultivar was significantly delayed as attempts were made since August 2018 to obtain seed, which only arrived in 2022.

    • Identification and selection of potential resistant lines/cultivars available from South African germplasm

    Forty-two local commercially available soybean cultivars were screened, which included 6 cultivars previously identified through phenotypic screening as having partial resistance. Genotypic screening using the same 54 SSR markers (as used for international germplasm) has been completed and indicated that five of the 42 cultivars have potential for tolerance. Two of these were from the six cultivars which were previously identified as partially resistant. Screening revealed different combinations of known resistance QTLs and all combinations had at least one major QTL, although three or more QTLs are desired.

    Cultivars with the best combination of targeted Sclerotinia resistance QTLs were selected for phenotypic screening under greenhouse and field conditions to validate the tolerance.

    • Greenhouse screening: Completed.

      Disease evaluation for this trial was completed in December 2020. The results obtained from all 3 repetitions correlate very well with the genotypic screening. A detach leaf assay was done in Feb/March 2021 to confirm the phenotypic validation with the straw inoculation method. This experiment was completed successfully and also confirmed the results obtain from molecular marker data and the phenotypic validation.

    • Field screening: In progress.

      Two repetitions of the field trials have been completed and the third will be conducted in November 2022. Thus far, variations have been observed for some cultivars in response to inoculation with the pathogen. Results from the third repetition under field conditions will be important to draw conclusions from the data.

      • Phenotypic validation of resistance using best inoculation method in both greenhouse and field trials

        Pathogen selection for screening trials: Completed.

        Thirty S. sclerotiorum isolates from the population genetic studies were selected for screening. After pathogenicity tests, five isolates were selected to proceed with based on level of pathogenicity. The straw inoculation-method was identified as the best greenhouse inoculation method.

      • Establish and maintain a culture collection of South African S. sclerotiorum isolates

    The culture collection is growing and contains isolates collected from more than six different crops from the UFS population genetic studies on Sclerotinia sclerotiorum. These isolates were collected across all nine South African provinces, as an isolate was recently obtained from Aliwal-North in the Eastern Cape.

    New isolates from various crops are incorporated into the culture collection on a regular basis. Some of the isolates from the culture collection was distributed to other researchers within SASRN to contribute to their research.

    The culture collection is updated regularly and a digital recordkeeping is in place. A filing system is in place with the location, morphology and pathogenicity profile of isolates.

    Activities still to be completed

    The national lockdown resulting from the COVID-19 pandemic resulted in delays in phenotypic validation of genotypic screening. While the greenhouse screening has been completed, the field evaluations still need to be completed. Therefore, we are requesting an extension on this project to complete a third repetition of the field screening. As costs allocated to this activity are still remaining, no additional funds are requested.

    Conclusion

    The project is progressing well. Sources of resistance in international germplasm has been obtained as well as cultivar from the USDA which has been reported to be completely resistant to disease. Significant delays were experienced with obtaining this USDA cultivar due to phytosanitary requirements for import. The USDA cultivar was received and multiplication and adaptation trials are ongoing. Furthermore, five local cultivars were identified with potential sources of resistance, which will be confirmed in a third field trial later in this year.

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    Project 3: Sclerotinia sclerotiorum disease potential and management responses in soybean and sunflower

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    Introduction

    The fungal pathogen Sclerotinia sclerotiorum has an intriguing epidemiology as it has the potential to cause plant diseases in more than 500 host species (Bolton, Thomma & Nelson, 2006). In South Africa, primary risk crops are soybean and sunflower, with an increasing risk to canola. The economic importance of many of the crops affected by Sclerotinia spp. emphasises the need for effective disease management strategies. Management of these diseases is limited by the extensive host range and duration of survival of sclerotia in soil, as well as the lack of registered active ingredients for chemical control, or available material for conventional resistance breeding. Cultivar selection would be the preferred method of Sclerotinia disease management in South Africa, as it is economically viable. The development of cultivars resistant to Sclerotinia diseases would be ideal as it would provide producers with a longer-term solution to reduce disease risk. Timely fungicide applications, at critical host growth stages, can provide an effective management strategy for Sclerotinia diseases. Currently, there are a limited number of registered preventative active ingredients in South Africa for use as fungicides against Sclerotinia.

    Currently, no soybean and sunflower cultivars with complete resistance to S. sclerotiorum are available, although numerous cultivars have been identified with partial resistance / tolerance locally and internationally (Kim and Diers, 2000; McLaren and Craven, 2008; Calla et al., 2009; Zhao et al., 2015; Andrade et al., 2018; Mbedzi et al., 2019). Host resistance describes the ability of a plant to reduce the ability of the pathogen to infect and colonise tissues, either partially or completely (Politowski and Browning, 1978). In this study we consider tolerance to be influenced by both host genetics and factors beyond plant genetics (such as environmental conditions). Tolerant cultivars therefore are able to tolerate high levels of disease potential before succumbing to the pathogen, thus providing various degrees of risk reduction (McLaren, 1992; 2000; 2002). The development of cultivars resistant to Sclerotinia diseases would be ideal as it would provide producers with a longer-term solution to reduce disease risk.

    To achieve the above aim, the following objectives were identified:

    • Develop an artificial inoculation technique for field trials (completed).
    • Develop a robust methodology for evaluating cultivar response to Sclerotinia infection during field trials (completed).
    • Implement above methodology to evaluate the tolerance/susceptibility of soybean and sunflower cultivars to Sclerotinia in field trials (in progress).
    • Test alternative management options (completed).

    Progress

    • Develop an artificial inoculation technique for field trials.

    This work has been completed.

    • Develop a robust methodology for evaluating cultivar response to Sclerotinia infection during field trials.

    This work has been completed.

    • Implement above methodology to evaluate the tolerance/susceptibility of soybean and sunflower cultivars to Sclerotinia in field trials

      Commercially available soybean cultivars (18) and sunflower cultivars (26) were screened for tolerance to Sclerotinia, from 2017 to 2021, in sequentially planted field experiments. All cultivars needed to be present in each season for inclusion into the modified Finlay-Wilkinson regression analysis, which was used to determine response types based on the relationship between observed disease incidence (%) within a cultivar and disease potential. Only 10 soybean cultivars and 21 sunflower cultivars had sufficient data to be included in the analyses presented here.

      Sclerotinia disease potential is defined as the mean disease incidence across all cultivars within a planting date, in either artificially inoculated or naturally infected plots per crop. Three cultivar reaction types were identified, i.e., high tolerance to increasing sclerotinia disease potential (b > 1), low tolerance to increasing sclerotinia disease potential (b < 1), and linear relationship with changing sclerotinia disease potential (b ≈ 1). The sclerotinia disease potential required to initiate disease onset and the rate of response after onset were also determined. Low levels of tolerance to sclerotinia were recorded in all but two soybean cultivars (DM 5302 RSF; SSS5449 tuc) and four sunflower cultivars (AGSUN 5101 CLP ; LG 5678 CLP; LG 5710; RN 28485) where b > 1.30 and onset potentials of > 10.00%. The regression approach can be used to quantify a cultivar's tolerance level, if an adequate number of disease potentials are included. Planting cultivars with a b > 1.00, a high onset potential and subsequent low response rate could contribute to reducing the risk of sclerotinia diseases.

      Amongst all the soybean cultivars, the b-parameters and calculated onset potentials ranged from b = 0.59 and onset potential = 1.72% in RA 565 R, indicating a highly susceptible response to increasing Sclerotinia disease potential to b = 1.97 and onset potential = 12.04% in DM 5302 RSF, indicating a delayed onset response to increasing Sclerotinia disease potential (Table 1).

      PAN 7170 was the most susceptible to Sclerotinia head rot potential, with a b-parameter of 0.73, a low Sclerotinia disease onset potential of 1.87% and a high response rate subsequent to Sclerotinia disease onset, 1.95% per Sclerotinia disease potential unit. In contrast, LG 5710 had the greatest tolerance with a b-parameter of 2.08, a high Sclerotinia disease onset potential of 19.42% and a slow response rate subsequent to Sclerotinia disease onset, i.e., 0.54% per Sclerotinia disease potential unit (Table 2).

      These results have been formalised into a peer reviewed paper which has been submitted to Crop Protection in June 2022, this will enable a wider readership to understand the escape resistance mechanism associated with South African soybean and sunflower cultivars.

    Table 1. Disease screening data of ten soybean cultivars were subjected to the adapted Finlay and Wilkinson (1963) regression methodology

    Calculated parameters include the relationship between observed Sclerotinia stem rot and Sclerotinia stem rot potential in soybean cultivars, 5.00% Sclerotinia stem rot onset potential and rate of response at onset. Planting cultivars with a b > 1.00, a high onset potential and subsequent low response rate could contribute to reducing the risk of sclerotinia.

    Soybean cultivar	Company	b	R²	Observed Sclerotinia stem rot (%)	Sclerotinia stem rot onset potential (5%)	Rate of response at disease onset
    DM 5302 RSF	Don Mario	1.97	0.81	5.42	12.04	0.82
    DM 5953 RSF	Don Mario	0.69	0.50	3.62	9.53	0.36
    P 61 T 38 R	Pioneer	0.70	0.93	7.41	3.63	0.96
    P 64 T 39 R	Pioneer	1.03	0.88	10.19	4.52	1.14
    PAN 1521 R	Pannar	0.74	0.75	6.10	5.65	0.66
    RA 565 R	Agri-Seed and Sanata Rosa	0.59	0.96	10.18	1.72	1.71
    RA 568 R	Agri-Seed and Sanata Rosa	0.99	0.97	10.85	4.03	1.23
    RA 660 R	Agri-Seed and Sanata Rosa	1.03	0.92	12.44	3.76	1.37
    SSS 5052 (tuc)	Sensako (Syngenta)	0.91	0.97	8.81	3.52	1.30
    SSS 5449 (tuc)	Sensako (Syngenta)	2.44	0.90	7.32	11.21	1.09

    Table 2. Disease screening data of 22 sunflower cultivars were analysed using the adapted Finlay and Wilkinson (1963) regression methodology

    Parameters for the relationship between observed Sclerotinia head rot and Sclerotinia head rot potential in sunflower cultivars, 5.00% Sclerotinia head rot onset potential and rate of response at onset were calculated. Planting cultivars with a b > 1.00, a high onset potential and subsequent low response rate could contribute to reducing Sclerotinia risk.

    Sunflower cultivar	Company	b	R²	Observed Sclerotinia head rot (%)	Sclerotinia head rot onset potential (5%)	Rate of response at disease onset
    AGSUN 5101 CLP	Agricol	1.93	0.91	19.79	16.76	0.57
    AGSUN 5102 CLP	Agricol	1.15	0.97	29.11	6.61	0.87
    AGSUN 5103 CLP	Agricol	0.86	0.94	27.50	3.46	1.25
    AGSUN 5106 CLP	Agricol	1.16	0.98	25.50	7.69	0.76
    AGSUN 5270	Agricol	0.71	0.96	31.96	1.84	1.94
    AGSUN 5273	Agricol	0.79	0.98	19.77	4.03	0.98
    AGSUN 5278	Agricol	0.83	0.94	25.81	3.22	1.30
    AGSUN 8251	Agricol	1.09	0.98	27.71	6.24	0.87
    LG 5626 HO	Link Seed	1.04	0.99	20.01	5.90	0.88
    LG 5678 CLP	Link Seed	1.56	0.97	27.14	11.88	0.66
    LG 5710	Link Seed	2.08	0.95	21.15	19.42	0.54
    P 64 LL 23	Pioneer	0.88	0.98	27.55	3.43	1.28
    P 65 LL 02	Pioneer	0.85	0.97	33.10	2.91	1.46
    P 65 LL 14	Pioneer	0.86	0.98	36.57	2.70	1.60
    P 65 LP 54	Pioneer	1.17	0.98	29.84	6.83	0.86
    PAN 7100	Pannar	1.26	0.96	32.26	7.43	0.85
    PAN 7102 CLP	Pannar	0.78	0.97	34.25	2.30	1.70
    PAN 7156 CLP	Pannar	0.88	0.97	31.62	2.92	1.50
    PAN 7170	Pannar	0.73	0.98	31.15	1.87	1.95
    RN 28485	Syngenta	1.34	0.96	15.16	11.58	0.58
    SY ARIZONA	Syngenta	0.75	0.98	25.06	2.54	1.47

    Please note the cultivars recommended to have escape resistance towards S. sclerotiorum reflect the genotype-environment interaction of the Delmas and Clocolan environments, and variation may occur if cultivars are planted at other localities.

    Data from 2021/2022 season are still being processed, and we look forward to seeing if similar trends are observed across the seasons between the cultivars.

    • Test alternative management options

    This objective addressed two producer-posed questions regarding sclerotia viability within production systems. The first aim was to simulate the effect of crop stubble burning, through assessing the effect of dry heat temperatures on sclerotial viability. A four factor completely randomised factorial experiments with four replicates were conducted to determine the germination ability of sclerotia from four different weight classes exposed to 125°C, 150°C, 185°C or 200°C, for 5 min, 10 min or 15 min durations either buried at 5 cm in soil or left on the surface (n = 384). The second aim was to determine the ability of sclerotia to survive in the rumen of cattle and hence the system of postharvest grazing. Faecal samples (n = 104; 10 – 14 days old) of cattle which grazed on S. sclerotiorum infected sunflower and relieved themselves, were collected. The first aim's results indicated larger sclerotia survived increasing temperatures and durations more readily than smaller structures. Temperatures exceeding 185°C yielded all sclerotia non-viable. Sclerotia on the soil surface were less sensitive to increasing temperatures compared to buried sclerotia, most likely due to rapid heat dissipation after heating. Less than 4% of sclerotia in cattle manure were able to germinate, suggesting that allowing cattle to graze on infested field stubble and moving them to potentially uninfested fields poses a reduced risk.

    Mean germination (%) with different letter are significantly different (p = 0.05) according to LSD (14.11%). error bars = Standard error of the mean.

    Activities to be continued

    Sunflower and soybean field trials will continue in Delmas and Clocolan, with additional disease screening to be conducted in collaboration with Annelie de Beer and Dr Safiah Ma'ali on the soybean and sunflower cultivar evaluations. Continuing with the evaluations will increase the robustness of the analyses, to provide producers with the best possible information for decision-making.

    Conclusion

    The season was successfully completed, and Marlese Meiring completed her PhD. Dr Meiring found permanent employment elsewhere, and now we have the opportunity to train a new M.Sc student (who has been identified) in the crucial skills of inoculum generation, field trials, cultivar screening, data analyses and report writing. We are excited to see how the results of this season will compare with previous seasons and to write a popular article with our colleagues at the Agricultural Research Council.

14. Oilseeds information

    Mr B Schultz
    SAGIS Forums and Trusts

    Forums and Trusts

    During the 2022/23 financial year the Oilseed Industry held five hybrid forum meetings. These meetings were attended by the General Manager, Mr Bernard Schultz. The information of SAGIS was presented to the meetings. All information of SAGIS were made available on the website of SAGIS.

    SAGIS' Board of Directors during the 2022/23 financial year

    Dr Erhard Briedenhann and Mr De Wet Boshoff (Resigned 31 January 2023) with Mr Ralph Küsel as the alternate director represented the Oil and Protein Seeds Development Trust and oilseeds industry on SAGIS' Board of Directors.

    Dr Erhard Briedenhann was elected as the chairperson and Mr Chris Schoonwinkel was elected as Vice Chairperson on the Board of SAGIS.

    Financial year 2022/23

    Subscription: Main Function (VAT excluded)

    A net amount of R17 149 231 was approved by the Members for utilisation during the 2022/23 financial year and the final expenditure was equal to it. This included an amount of R1 325 577 for the replenishment of the Capital Reserve Fund.

    The portion of the Oil and Protein Seeds Development Trust was 15.7% or R2 692 429.27 (VAT excluded).

    Audit

    The audit of the 2022/23 financial statements was conducted by "The Ashton CA (SA) Group Inc." and an unqualified audit report was issued.

    General Information

    Co-workers in the Oilseeds Industry

    The number of returns per commodity in the oilseeds industry, at 28 February 2023, was as follows:

    Commodity	28 February 2021	28 February 2022	29 February 2023
    Canola	22	25	26
    Groundnuts	75	75	72
    Soybeans	106	106	106
    Sunflower	109	108	107
    Total	312	315	311

    Product Information

    An amount of R92 550 (VAT excl.) was approved by the Trust for the Product Information. This was sufficient to cover all expenses for the 2022/23 financial year.

    The publication dates are available on SAGIS' website. On 28 February 2023, the actual number of returns from registered co-workers was 83 returns for the oilseed industry.

    Weekly information

    An amount of R44 678 (VAT excl.) was approved by the Trust for the Weekly Information. This was sufficient to cover all expenses for the 2022/23 financial year.

    The publication dates are available on SAGIS' website. On 28 February 2023, the actual number of returns from registered co-workers was 86 returns for the oilseed industry.

    Inspection Department

    Type of mistakes as well as non-compliance to the statutory measures on the whole grain and oilseeds returns per commodity.

    Mistakes as well as non-compliance to the statutory measures (March-February)	Canola		Groundnuts		Soybeans		Sunflower		Total
    	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023
    Returns late / outstanding	3	3	33	22	39	33	40	36	115	94
    Registration details incorrect	—	—	—	—	—	—	1	—	1	—
    Premises of origin incorrect	—	—	5	2	2	—	3	2	10	4
    Utilisation type incorrect	—	—	—	—	1	—	—	—	1	—
    Opening stock quantity incorrect	—	—	1	—	—	—	1	—	2	—
    Receipts quantity incorrect	—	—	4	2	2	2	5	1	11	5
    Sub class and grades incorrect	—	—	—	—	—	—	—	—	—	—
    Utilisation quantity incorrect	—	—	4	2	2	1	3	1	9	4
    Closing stock quantity incorrect	—	—	5	—	5	2	3	1	13	3
    Stock variance < 5%	—	—	1	—	2	—	1	1	4	1
    TOTAL	3	3	53	28	53	38	57	42	166	111

    Net effect of mistakes as well as non-compliance to the statutory measures found during audits on (under) / over declarations on SAGIS' publications on:

    Receipt of whole grain and oilseeds

    March-February
    	Mass over declared		Mass under declared		Total mass declared incorrect		Total received audited		Mass declared incorrect as % of total received		Net effect of (under) / over declared
    	Ton		Ton		Ton		Ton		%		Ton
    	a	b	c	d	e	f	g	h	e:g	f:h	a-c	b-d
    	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023
    Canola	—	—	—	—	—	—	280 704	156 179	—	—	—	—
    Groundnuts	571	522	474	518	1 045	1 040	76 224	76 600	1.4	1.4	97	4
    Soybeans	87	—	—	321	87	321	1 782 765	2 596 636	—	—	87	(321)
    Sunflower	101	3 073	107	3 073	208	6 146	398 273	1 933 229	0.1	0.3	(6)	—

    Utilisation of whole grain and oilseeds

    March-February
    	Mass over declared		Mass under declared		Total mass declared incorrect		Total received audited		Mass declared incorrect as % of total received		Net effect of (under) / over declared
    	Ton		Ton		Ton		Ton		%		Ton
    	a	b	c	d	e	f	g	h	e:g	f:h	a-c	b-d
    	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023
    Canola	—	—	—	—	—	—	199 412	111 552	—	—	—	—
    Groundnuts	108	4	—	—	108	4	84 633	68 777	0.1	—	108	4
    Soybeans	—	—	—	321	—	321	924 860	1 686 009	—	—	—	(321)
    Sunflower	—	9	3 675	5	3 675	14	380 527	1 414 822	1.0	—	(3 675)	4

    Whole grain and oilseeds stocktaking

    March-February
    Commodity	Physical stock-taking		Adjusted stock counted (t)		Stock declared on returns (t)		Net effect of under / (over) declared (t)		Difference between stock counted and declared on returns
    			a	b	c	d	a-c	b-d	Under (t)		Over (t)		Under (%)		Over (%)
    	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023
    Canola	73 990	19 846	75 397	19 809	72 614	19 209	2 783	600	2 783	600	—	—	3.83	3.12	—	—
    Groundnuts	22 965	17 864	24 921	20 577	25 193	20 350	(272)	227	—	227	272	—	—	1.12	1.08	—
    Soybeans	551 793	672 545	581 219	681 990	584 308	693 099	(3 089)	(11 109)	—	—	3 089	11 109	—	—	0.53	1.60
    Sunflower	37 541	269 262	38 840	271 675	38 526	272 483	314	(808)	314	—	—	808	0.82	—	—	0.30
    	686 289	979 517	720 377	994 051	720 641	1 005 141	(264)	(11 090)	3 097	827	3 361	11 917	0.43	0.09	0.47	1.19

    Note: For comparison purposes, the physical stock was adjusted to compare it with the stock declared on the return as per month-end.

    Oilseeds products

    	Mass over declared		Mass under declared		Total mass declared incorrect		Total received audited		Mass declared incorrect as % of total received		Net effect of (under) / over declared
    	Ton		Ton		Ton		Ton		%		Ton
    	a	b	c	d	a+c=e	b+d=f	g	h	e:g	f:h	a-c	b-d
    	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023	2022	2023
    Coconut oil	—	—	—	—	—	—	50	531	—	—	—	—
    Palm oil and derivatives	—	—	—	—	—	—	259 163	164 759	—	—	—	—
    Soybean oil	—	25	—	93	—	119	229 160	133 837	—	0.1	—	(670
    Groundnut oil	—	—	—	—	—	—	—	14	—	—	—	—
    Sunflower oil	72	—	—	—	72	—	306 617	249 888	—	—	72	—
    Rapeseed / Canola oil	—	—	—	—	—	—	3 836	31 940	—	—	—	—
    Cottonseed oil	—	—	—	—	—	—	2 000	2 763	—	—	—	—
    Corn (maize) oil	—	—	—	—	—	—	5 449	—	—	—	—	—
    Other oil (blends or mixes not included in the above oil)	—	—	—	—	—	—	48 057	4 670	—	—	—	—
    Cottonseed oilcake	—	—	—	—	—	—	—	52 616	—	—	—	—
    Sunflowerseed oilcake	—	—	369	—	369	—	336 799	153 306	0.1	—	(369)	—
    Coconut oilcake	—	—	—	—	—	—	—	—	—	—	—	—
    Palmnut oilcake	—	—	—	—	—	—	—	21 943	—	—	—	—
    Soybean oilcake	—	—	—	500	—	500	1 065 900	477 586	—	0.1	—	(500)
    Rapeseed / Canola oilcake	—	—	—	—	—	—	58 503	37 808	—	—	—	—
    Biodiesel	—	—	—	—	—	—	—	670	—	—	—	—
    Soybean flours and meals	—	—	—	—	—	—	34 878	50 961	—	—	—	—
    Soybean full-fat	71	43	—	422	71	465	92 174	94 853	0.1	0.5	71	(379)
    Peanutbutter and paste	51	—	—	—	51	—	32 636	5 697	0.2	—	51	—
    Textured vegetable protein	—	—	—	—	—	—	525	46 977	—	—	—	—

    Conclusion

    AGIS appreciates the support and co-operation of all the role-players.

    We wish to express our gratitude especially towards the Members of the Oil and Protein Seeds Development Trust for their continued support, financially and otherwise.

15. Investigation of the aggressive, seedborne nematode species Robustodorus arachidis n. comb. on groundnut

    Dr S Steenkamp, Mr SS Kwena, E du Randt, Dr A Swart and Dr R Knoetze
    ARC GRAIN CROPS INSTITUTE, POTCHEFSTROOM

    The newly discovered nematode Robustodorus arachidis, was recovered during 2016 in large numbers from severely damaged hulls and kernels of groundnut from a commercial field in the Vaalharts irrigation Scheme, Northern Cape Province. It was suspected that this nematode was similar to the pod nematode, Ditylenchus africanus, which has significant financial implications for the groundnut industry. Pod nematode has a qualitative effect on groundnut, causing downgrading of consignments. Urgent research was therefore needed to study the unknown R. arachidis and to determine its damage potential and hence, a threat to the groundnut industry. Without relevant information on this newly discovered nematode, it would be impossible to implement effective and sustainable management strategies. The aims of this study were to establish whether currently, registered nematicides are effective for R. arachidis control, to establish the damage potential and economic impact of this nematode and to establish its reproduction potential, survival and host range. Nematicides and crops other than groundnut was evaluated in field trials, the damage potential and economic impact and the survival abilities of this nematode were studied in microplots and the reproduction potential and life cycle of this nematode in the laboratory. Currently, registered nematicides are not effective in keeping this nematode under control. Similar to pod nematode, the main effect of R. arachidis on groundnut is qualitative. They cause premature germination and discoloration of the kernels, which leads to the downgrading of groundnut consignments. The economic impact differs from season to season depending on the current prices for each grading class and the loss consignments incur from these. The life cycle of R. arachidis is ten days, which means that it can produce a number of generations per summer growing season and that only a small number is needed at the beginning of a growing season to cause damage at harvesting. In the cold winter months or in the absence of water they can go into anhydrobiosis in order to survive the adverse conditions. These anhydrobiosis can recover and still cause significant damage to a follow up groundnut crop. In the absence of groundnut R. arachidis can survive on maize. Its effect on this crop is currently unknown.

16. Proficiency testing scheme for soybeans and soybean meal

    Ms W Louw
    Southern African Grain Laboratory

    Proficiency testing schemes are designed to provide participants with an independent assessment and the tools to supplement their internal quality control systems. They can use the proficiency testing report to investigate any outlier results, identify the root cause of the problem and improve their testing procedures.

    The soybean proficiency scheme was developed in 2021 at request of the Oilseed Industry. Since 2021, SAGL has presented this scheme in four cycles per year - February, May, July and November. The proficiency scheme is done for both soybeans and soybean meal.

    Since this project is funded by the Oilseeds Advisory Committee and the Oil and Protein Seed Development Trust (OAC/OPDT), the participants have access to valuable information on a continuous basis and at no cost to the participants.

    Soybean Meal is sourced from producers in the industry who are also participating in the scheme. These producers are used on a rotational basis. The soybean samples are made up of retention samples received for analysis.

    All the samples are tested for homogeneity before it is packed and distributed to the participants. In the table below is the list of the parameters for analysis included for both soybean and soybean meal:

    Soybeans	Soybean meal
    Grading	Ash
    Ash	Crude Fibre
    Crude Fibre	Crude Fat (oil)
    Crude Fat (oil)	Crude Protein
    Crude Protein	Protein Solubility in KOH (KOH)
    Moisture	Moisture
    	Protein Dispersibility Index (PDI)
    	Trypsin Inhibitor Activity (TIA)
    	urease Activity (UA)

    The participants conduct the analyses with their own testing methods and the results submitted by the participants are statistically analysed to provide an assigned value for each analyte. The assigned value for each analyte is derived from the consensus of the results submitted by the participants.

    Where applicable, the assigned values are then used in combination with the standard deviation for proficiency to calculate the z-score for each result. Participants receive a report, compiled by the SAGL and each participant has their own uniquely coded results to preserve confidentiality.

    Information on specific methods used by the participants is also included in the report. This provides the participants with additional information on the different methods being used by other testing facilities.

    Summary of Results

    The reporting of the results was standardized to 'as is' values which improved the comparison between the participants.

    Protein results between the participants correlate well and the protein results of the May 2023 cycle for both soybeans and soybean meal are shown below:

    

    

    Where necessary, further statistical evaluation is used to analyse the data and final results are presented in the report. Below are examples for the KOH analysis results from the February and May 2023 soybean meal report. Because of the wide spread of analysis results received during the February 2023 round, no z-scores were reported.

    

    

    The reporting of more detailed information on the methods used by the participants contributed to a better understanding of differences between the participants. More information is required on the test methods used for the determination of crude fibre and ash, as these results between the participants do not correlate well.

    Below is an example of the % crude fibre results from the May 2023 soybean quality report.

    

17. Website

    Ms M du Preez and Ms Y Papadimitropoulos
    OAC/OPDT

    During the period 2022/2023 the day-to-day tasks were mainly updating existing and adding new content to the OPDT/OAC's website. On 28 February 2023, the OPDT/OAC's website hosted a total of 606 static HTML pages - excluding dynamically created pages – across 15 content sections.

    Google Analytics 4 (GA4)

    Google has announced that standard Universal Analytics (UA) will stop processing data starting 1 July 2023 as it will be replaced with the next generation Google Analytics 4, or GA4 for short. New features include mobile app tracking, event-based tracking, better integration with Google products, a customizable interface, cookie-less tracking, and machine learning capabilities. GA4 has a different data model than UA, and it is therefore not possible to transfer historical statistics to the new GA4 property. To build up a traffic history on OPDT/OAC's website, a new GA4 property has been running concurrently with the existing UA property since December 2022.

    Reporting Year	Unique Visitors (Raw values *)	Unique Visitors (Google values)
    	*	Visitors	Pages	Pages per visit
    2007	11	–	–	–
    2008	74	–	–	–
    2009	752	–	–	–
    2010	2 964	–	–	–
    2011	4 037	788	3 284	3.21
    2012	4 052	720	3 775	4.25
    2013	4 342	674	3 296	3.94
    2014	4 503	1 086	4 600	3.62
    2015	4 800	1 340	6 993	4.14
    2016	4 329	927	5 042	3.83
    2017	6 384	909	5 406	4.39
    2018	5 428	1 841	8 885	3.59
    2019	8 307	1 661	8 340	3.43
    2020	14 982	4 805	12 475	2.03
    2021	24 972	10 946	18 934	1.73
    2022	30 324	7 338	17 511	1.85

    Google values show a decrease in page views and a decrease in unique visitors. Page views decreased by approximately 1423 during the year. The most page views came from the following pages in order of percentage share:

    • Home page, 17.5%
    • Oil and Protein Seeds Development Trust (OPDT) / Oilseeds Advisory Committee (OAC): 13.2%
    • Soybean cultivation in South Africa by Wessel van Wyk: 4.9%
    • Soybean categorised project database index: 4.5%
    • Soy Oilcake Price Average: 4.3%