Forecasting Sclerotinia stem rot in winter rapeseed

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1 Forecasting Sclerotinia stem rot in winter rapeseed Pia Heltoft Jensen 1, Ghita Cordsen Nielsen 2 and Lisa Munk 3 1 Bioforsk, Arable Crop Division, Nylinna 226, 2849 Kapp, Norway. 2 Knowledge Centre for Agriculture, Crop Production, Agro Food Park 15, Skejby, 8200 Aarhus N, Denmark. 3 Department of Agriculture and Ecology, Faculty of Life Sciences, University of Copenhagen, Højbakkegård Alle 13, 2630 Tåstrup, Denmark. pia.heltoft.jensen@bioforsk.no Abstract There are no reliable forecasting models available for Sclerotinia stem rot in Denmark today. The German forecasting model SkleroPro was evaluated in Danish field trials in and was evaluated with historical data from 1998 to Other forecasting models for Sclerotinia stem rot were also evaluated, but unfortunately none of them have proven to be useful in practice under Danish conditions. A survey answered by Danish oilseed growers showed, that there is a need for a forecasting model in Denmark because they often make a routine spraying. Their expectation to a forecasting model is that it should give minimum 70 percent correct predictions before they will use it. Keywords: Sclerotinia sclerotiorum; forecasting model; oilseed rape Sclerotinia stem rot (Sclerotinia sclerotiorum) can cause great yield losses in oilseed rape (Brassica napus L.). In Denmark the fungus caused high yield losses in The level of disease incidence varies a lot from year to year, and therefore there is a need for a forecasting model. SkleroPro I 2006 a new model, SkleroPro, was developed in Germany. SkleroPro showed good results under German conditions and therefore it was decided to test the model in Denmark in the Nordic Field Trial System from It was the hope that the model could be used with no or only a few adjustments to Danish conditions. SkleroPro calculates the need for fungicide treatment by taking the following steps into account Number of infection hours and an economical threshold. Data from weather stations nearby on relative humidity/rh (%/h), precipitation (mm/h), temperature ( C /h) and sunshine duration (h/day). The infection hour based on the relation between RH and temperature. One infection hour is an hour where temp >7 C and relative humidity (RH) >86%.

2 Crop rotation, which has an impact on the threshold for the number of infection hours. If the crop rotation is short there must be less infection hours before the model starts calculating than with a long crop rotation. A continuous period of 23 infection hours when the crop has passed beginning of flowering before the model starts calculating. The economic threshold, which is calculated if there is a high risk of infection. To calculate the economic damage threshold, the user must provide information about expected yield, oilseed price, fungicide costs and labour and machine costs. The final decision for a treatment is done. Recommendation for spraying can only be made during the flowering period of the oilseed rape. The crop rotation effect is included in the model as a modulating factor of the threshold for stem infection. Evaluation of SkleroPro in Germany SkleroPro was evaluated in Danish and German field trials. Results from the German evaluation are shown in Table 1. The prediction accuracy of SkleroPro was evaluated by a retrospective analysis with a historical dataset from 76 field trials conducted from 1994 to 2004 by Koch et al. (2007) and she also evaluated the model in field trials in Additionally the model has been evaluated in field trials carried out by the State Plant Protection service (PPS) in Germany in In 2007 there were a high percentage of underestimated trials (39 percent). There was an unusual late infection of Sclerotinia stem rot in 2007 because of very unusual weather conditions, a very dry period during full flowering, and then a wet period at late flowering to end flowering. According to the model an infection could not happen after flowering even though it actually predicted a period which was favourable for S.sclerotiorum infection. Normally an infection would not take place, but in 2007 infections occurred after flowering. In 2008 and 2009 there were high rates of overestimated trials. In 2008 the explanation was that the price of oilseed rape was higher than the model was developed for. Therefore a very short infection period could result in recommendations to spray. In 2009 the period with favourable conditions for apothecia germination and infection came before flowering and therefore the apothecia dried out before conditions became favourable for infection again. Table 1 Evaluation of SkleroPro in Germany based on historical dataset conducted from 1994 to 2004 and field trials from 2005 to The numbers of trials each year, percentage of correct, overestimated and underestimated trials are presented. Overestimated: recommended spray was not cost-effective. Underestimated: Spray would have been cost-effective but was not recommended (Koch et al., 2007; Röhrig, 2010; Tiedemann and Kleinhenz, 2008; Tschöpe, 2010). Year Number of trials Correct % Overestimated % Underestimated % SkleroPro in Danish Field trials SkleroPro was evaluated in Nordic field trials in The purpose of the evaluation was to see how well SkleroPro works in practice under Danish conditions.

3 The evaluation of SkleroPro was done with data from the treatments: 1. Control treatment, which is untreated. 2. Routine treatment, which is 0.35 kg Cantus at growth stage SkleroPro treatment, which is 0.35 kg Cantus when SkleroPro recommends spraying. The treatment is carried out on the date or few days after the date of recommendation from SkleroPro dependent on the conditions for spraying. If the evaluation of SkleroPro is based alone on net additional yield, it gives a correct forecast where SkleroPro has a positive and higher net additional yield than the routine treatment. SkleroPro made a correct forecast in 50 percent of the trials, in 40 percent of the trials the forecasting was overestimated (Figure 1). correct overestimated underestimated 10% 40% 50% Figure 1 Evaluation of forecasting by SkleroPro in 20 field trials. Overestimated: recommended spray was not cost-effective. Underestimated: Spray would have been cost-effective but was not recommended. The additional yields were only significant in 2 of 20 trials when comparing the difference in additional yields in the SkleroPro treatment to the routine treatment with 0.35 kg Cantus or the control. Therefore we set a threshold of 1 dt for the differences between net additional yields. Then we saw 65 percent correct predictions, 25 percent overestimated and 10 percent underestimated. SkleroPro has also been evaluated with historical data from Figure 2 shows that SkleroPro makes a correct forecast in 47 percent of the trials, in 33 percent the forecast is overestimated and in 20 percent of the trials the forecast is underestimated.

4 correct overestimated underestimated 20% 47% 33% Figure 2 Evaluation of forecasting by SkleroPro in 40 field trials on basis of historical data from With variable rapeseed price, fungicide costs and labour and machine costs. Overestimated: recommended spray was not cost-effective. Underestimated: Spray would have been cost-effective but was not recommended. The additional yields were significant in 8 of 40 trials when comparing the difference in additional yields in the SkleroPro treatment to the untreated control. Therefore we also here set a threshold of 1 dt for the differences between net additional yields, and then we found 60 percent correct predictions, 27 percent overestimated and 13 percent underestimated predictions. Generally the model has not performed satisfactory according to the number of correct, overestimated and underestimated trials, even when we set a threshold of 1 dt. It should be mentioned that the model has only been evaluated under a low disease pressure in Denmark, which can have an effect on the results. SkleroPro did not seem to be a satisfactory tool for decision making in its present form, so it was attempted to change some factors in the model to adapt it to Danish conditions. The crop rotation factor is considered to be the most important factor, when changing the model to work under Danish conditions. In Denmark a crop rotation of 4 years or 5 years between oilseed rape is commonplace according to an evaluation made in 2003 where 426 fields were evaluated (Table 2) (Jensen and Nielsen, 2003), whereas it is 3 years in Germany where the model is developed according to Koch et al. (2007). Table 2 Output from SAS(statistical analysis system). A dataset with 426 fields in total shows the variation in (from left) years since oilseed rape, frequency, percent of trials, cumulative frequency and cumulative percent (Jensen and Nielsen, 2003) Years since oilseed rape Frequency Percent Cumulative Frequency Cumulative Percent

5 In SkleroPro the crop rotation factors were set to: < 3 year crop rotation the factor is year crop rotation the factor is 1 > 3 year crop rotation the factor is 0.8 In the following the options of crop rotation factor is expanded with a crop rotation factor of 0.6 and 0.4 to adapt the model to Danish conditions. The crop rotation factors were changed to fit the most used crop rotations in Denmark. When changing the crop rotation factor to a smaller factor, it decreases the risk of disease. It takes longer before the threshold of 23 infection hours is exceeded, and it takes longer before the summarized infection hours reach the economic damage threshold. The new crop rotation factors according to crop rotation are set to: 5 year crop rotation the factor is year crop rotation the factor is 0.4 The number of correct predictions by SkleroPro increases when the crop rotation factor is changed from 0.8 to 0.6 and 0.4 (Figure 3). The percentage of correct predictions changes from 50 to 65 percent when changing the crop rotation factor from 0.8 to 0.6. When changing the crop rotation factor to 0.4 the percentage of correct predictions is 76. The rate of overestimated predictions also changes from 31 percent with a crop rotation factor of 0.8 to 13 percent with a crop rotation factor of 0.6 and only 2 percent when the crop rotation factor is % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% factor 0,8 factor 0,6 factor 0,4 underestimated overestimated correct Figure 3. Evaluation of forecasting by SkleroPro in 55 trials when the crop rotation factor is 0.8, 0.6 or 0.4. Overestimated: recommended spray was not cost-effective. Underestimated: Spray would have been cost-effective but was not recommended. Unfortunately it was found, after further statistical analyses, that the model did not give a better result when changing the crop-rotation factor. The problem occurred, when it was discovered that the crop rotation factor did not regulate the amount of inoculum in the field but instead it only regulates the length of an infection hour and thereby also the threshold for summarized number of infection hours.

6 Evaluation of other forecasting models Since the late 1980 s there have been many proposals for forecasting systems for Sclerotinia stem rot in oilseed rape in Denmark. The forecasting models include an apothecia germination model, risk-point system model, an agar test and a PCR-test. But, in their present form, none of the available models have proved to be satisfactory forecasting systems in practice. The apothecia germination model is not precise enough because the sclerotial depot is often placed too far from the field concerned and local weather conditions are therefore not taken into consideration. Besides, the model requires the user to know the history of the field and to have certain knowledge about the disease pressure in the soil. The risk-point system cannot be used because a statistical analysis showed that there was no correlation between the factors and the disease incidence in all cases. Finally the agar-test requires too much time and the forecasting based on PCR-test of petals needs further development. The need for a forecasting model in Denmark To get an overview of whether a forecasting model for Sclerotinia stem rot would be used by farmers in Denmark, a survey was made in cooperation with Knowledge Centre for Agriculture where Landmandspanelet (Farmer s panel) was asked two questions. 77 out of 103 answered the question about their spraying routine. Of these 25 (32.5 percent) do not grow oilseed rape. Of the remaining 52 respondents 40.4 percent of the respondents spray oilseed rape against fungi during flowering every year percent of the respondents never spray against fungi. The answers are presented in Figure 4. Percent Every year Every second year Every third year Every fourth year Seldom Never Figure 4 Answers to the question: How often do you spray your winter oilseed rape against fungi during flowering? n= of 103 answered the question about expectations to a forecasting model for Sclerotinia stem rot in oilseed rape. Of these 16 (21.1 percent) do not grow oilseed rape. Of the remaining 60 respondents, 40 percent requests the predictions of a forecasting model for Sclerotinia stem rot to be percent correct before they will use it percent request the prediction to be percent correct. In total 81.7 percent request the predictions to be more than 70 percent correct before they will use it. 5 percent of the respondents will not use a forecasting model. The answers are shown in Figure 5.

7 Percent % correct 60-70% correct % correct % correct % correct I do not want to use a forecasting model 5 10 Figure 5 Answers to the question: How correct should prediction of the forecasting model be if you should use it? n=60 It is concluded that the number of respondents was satisfactory to trust the results of the survey. The survey indicates that a forecasting model would be well received by oilseed rape growers in Denmark. Only 5 percent does not want to use a forecasting model. The survey also shows, that Sclerotinia stem rot is often controlled by a routine spraying, which means that spraying sometimes occur even when it is not needed. This is of both environmental and economical concern and increases the interest in optimizing the use of pesticides and to use pesticides only when it is needed. The reason why farmers spray every year is that they always want a stable yield despite the year and risk of Sclerotinia stem rot. They fear getting high losses in years when the risk of getting heavy infections with Sclerotinia stem rot is high as it has happened in for instance 1996 and 2007 in Denmark (Nielsen, 2010b). Development of a good disease forecasting model could solve the problems concerning environment and economy, but the expectations to a forecasting model are high. It is expected that the predictions must be more than 70 percent correct before farmers will use it. Conclusion It was found that there are still no reliable forecasting models available for Sclerotinia stem rot. But parts of both SkleroPro and the other models can be used to develop a new and better model. However, further investigations are needed before a new forecasting model can be developed. Jensen J.E., Nielsen G.C. (2003) Monitering af knoldbægersvamp i raps Statistisk analyse i SAS (Statistical Analysis System). Landscentret, Dansk Landbrugsrådgivning. Koch S., Dunker S., Kleinhenz B., Röhrig M., Tiedemann A.v. (2007) A crop Loss-related Forecasting Model for Sclerotinia Stem Rot in Winter Oilseed Rape, Phytopathology. pp Nielsen G.C. (2010b) Personal communication: Landskonsulent, Planteproduktion, Specialviden, Direkte telefon: , Telefax: , Mobiltelefon: , GCN@vfl.dk, Internet: NordicFieldTrialSystem. (2010) Svampebekæmpelse i vinterraps, Nordic Field Trial System. Retrieved , from a.

8 Röhrig M. (2010) Personal communication. ISIP e.v. Geschäftsstelle, Rüdesheimer Str , Bad Kreuznach, Internet: Tel. +49 (0)6 71/ Fax Tiedemann A.v., Kleinhenz B. (2008) Prognose contra Praxis? DLG Mitteillungen 3: Tschöpe B. (2010) Personal communication. ZEPP (Zentralstelle der länder für edv-gestützte Entscheidungshilfen und Programme im Pflanzenschutz), Rüdesheimer Straße 60-68, Bad Kreuznach, Telefon , Telefax , Geschäftsführung: Dr. Benno Kleinhenz Tschöpe B., Kleinhenz B. (2010) Ist eine Blütenbehandlung im Raps gegen Sclerotinia immer wirtschaftlich. Raps 2:82-84.