RUDISCO: Sustainablemanagement strategy for fungal diseases in Rubus: a necessary step forward (RUDISCO)

Sustainable management strategy for fungal diseases in Rubus: a necessary step forward

(Rudisco (1/12/2019 – 30/11/2023))

The cultivation of Rubus species (raspberry and blackberry), is on the rise. This fruit is now available fresh from May to December and has gained a more prominent place in the stores' AGF supply. The fruit is associated with healthy food due to the high levels of vitamins, anti-oxidantia,… present in the fruit and so surfs along on the trend of 'fresh and healthy'. Unfortunately less attention is paid to the disease management strategy mainly by the originally smaller production areas. At this moment there is a lack of knowledge for a sustainable approach of Botrytis fruit rot and powdery mildew control. As a result, too much treatments are probably carried out to control these diseases. This is not least the case for protected production (nearly 100%) of raspberries and blackberries as harvest protection can contribute to avoid yield losses by fungal pathogens.    

The aim of this LA-traject is to make a fundamental step forward in the disease management strategy as compared to the current management strategy for fungal diseases on Rubus. The principle of IPM will be further developed and implemented in the cultivation of raspberries and blackberries. This includes first a correct interpretation of the situation and only if necessary the right management strategy can be applied, meaning biological application if possible and only chemical treatments if absolutely necessary. The ultimate aim is to deliver a qualitatively strong product with the least amounts of residues possible in order to strengthen the image of ‘fresh and healthy’ for these fruits. 

Project partner: KULeuven, Department Biosystemen, afdeling Mechatronica, Biostatistiek en sensoren

Funded by: Vlaio, Flanders Innovation & Entrepreneurship.

The overall objective of this LA trajectory was to improve and implement treatment schedules aimed at targeted control of Botrytis cinerea in blackberry and raspberry cultivation. Within this LA trajectory, various tests were initially conducted to gain insights into the specific infection conditions of B. cinerea in blackberry and raspberry.

 These infection conditions were determined both on the plants and on the fruits. For the experiments on plants, flowers of blackberries and raspberries were inoculated with different spore concentrations of B. cinerea. The plants were placed in climate chambers under various conditions: temperature, humidity, and incubation period. Subsequently, they were returned to the warehouses. Regular samples were taken from flowers (isolation on nutrient medium), unripe and ripe fruits, and leaves. Everything was incubated at room temperature, and if B. cinerea was present, an evaluation was performed.

 In addition, artificial inoculations were carried out on unripe and ripe fruits with different spore concentrations of B. cinerea. These fruits were incubated for 24, 48, or 72 hours under various conditions at room temperature and then evaluated for visible symptoms. The results indicate that an increase in temperature, relative humidity, and spore concentration correlated with an increase in infection.

 The next step in this research was to determine the existing inoculum and latent infections. For the existing inoculum, rotorods were used, placed among the plants from flowering to harvest. Botrytis spores were collected by the rotating rotor rod and then quantified using qPCR. The number of spores was determined for different cultivation systems (rain cover, warehouse). For the presence of latent infections, the percentage of infections was determined by placing flowers and unripe fruits on agar medium, incubating them, and evaluating the presence of B. cinerea. Ripe fruits were incubated in humid boxes. These latent infections were monitored at different locations, revealing a clear difference in latent infections between greenhouses and rain covers, with a higher quantity observed under rain covers.

 All this data was used to create a model that relates the likelihood of infection with B. cinerea to the climatological conditions at a specific moment and in the recent past (up to 6 days ago). More simple decision trees as well as more complex logistic models with a large number of variables were developed separately for raspberry and blackberry. For raspberry, the logistic model was considered the most reliable: the accuracy was 0.95, meaning that in 95% of situations, the model effectively indicated a low (<30%), medium (<60%), or high (>60%) probability of infection for conditions that had actually led to such levels (as determined through latent infection trials). Next, this model was used for further validation in new trials during the last project year. For blackberry, despite in-depth analyses, no suitable model could be developed because latent infections only pointed to low or high probabilities, so there was no information available on conditions that could lead to a medium infection risk.

 The final model provided to growers offers a prediction of the Botrytis infection risk, enabling growers to treat more selectively and perform treatment just before the infection moment. Our advice is to opt for a biological treatment when the risk is ≥30%; only when the risk is ≥60%, do we advise opting for a chemical treatment. Through the use of the models, we aim to reduce not only the number of treatments but also the number of chemical treatments, ensuring treatments are more targeted—i.e., only when necessary, and not weekly or at fixed times in different cultivation systems.

 Within this LA trajectory, efforts were also made to assess the efficiency of biological and alternative agents against B. cinerea. For this purpose, artificial inoculation tests were conducted on unripe and ripe blackberries and raspberries. The fruits were disinfected, with or without wounds (ripe fruits with wounds, unripe without), treated with biological and alternative agents, inoculated with a B. cinerea spore solution, and incubated in moist containers at room temperature. The fungicides Teldor and Signum were included as references in the trial. All of this was compared to an untreated control. It is important to mention that there was a maximum of 4 hours between treatment and inoculation, which might be too short to achieve effective results with certain biological agents. Efficiencies may be even higher in practical conditions, where there is up to 24 hours between treatment with a biological agent and infection with Botrytis.

 From these experiments, we can conclude that Botector has very good efficiency against B. cinerea infection in both blackberry and raspberry, for both unripe and ripe fruits. There is reasonable efficacy on unripe fruits with Serenade ASO and Julietta. On ripe fruits, Julietta has very good efficiency (both in blackberry and raspberry) against Botrytis, and Amylo-X has good efficiency in limiting Botrytis infections in raspberries. The plant defense enhancers Charge and Romeo (not yet recognized in the cultivation of raspberry and blackberry) achieved good efficacy in raspberries and blackberries, respectively. Thus, there are indeed several alternative and biological agents that can be used for the control of B. cinerea. With correct application (based on the model developed in WP 3), these can be an alternative to chemical treatments, when the infection risk allows their use.

 In the last year, the model was validated in various cultivation systems for the first time. It was found that the infection risks were predicted quite well, but further validation is needed before it can be offered on a larger scale. There is also a need for further data on latent infections to develop a model for blackberries. Practically, there is a need to monitor the climatic conditions in more detail; for example, a prediction based on the humidity outside a covering can likely be more accurate if the humidity under the covering, near the plants, can be monitored. It was also revealed that the number of chemical treatments could be reduced by 64.25% with the use of the model. The overall use of treatments could be reduced by 41% using the model.

 For additional information, please contact Tanja Vanwalleghem (tanja.vanwalleghem@pcfruit.be), Wendy Van Hemelrijck (wendy.vanhemelrijck@pcfruit.be), and Annemie Geeraerd Ameryckx (annemie.geeraerd@kuleuven.be).