Designing Strategies to Control Grey Mould in Strawberry Cultivation Using Decision Support Systems

Grey mould is one of the major diseases in strawberry cultivation. Fungicides to control Botrytis cinerea are applied frequently during flowering and sometimes at harvest. Reduction of pesticide use is one of the major aims of the Dutch government. Implementation of a Decision Support System (DSS) helps to achieve this goal. Pin point timing of fungicide application can possibly improve the efficacy of the treatment and reduce the number of spray applications. Predicted weather data to forecast infection risks are used by most DSS’s. However in strawberry cultivation irrigation is a daily practice. The effect of overhead irrigation on the Botrytis infection risk is unknown. This is one of the reasons that strawberry growers infrequently use DSS’s. Therefore adaptation of the model to agricultural management is necessary. Under low disease pressure DSS BoWaS controlled Botrytis fruit rot 62% better then routine applications of fungicides, with a 50% reduction of fungicide input. Adding an irrigation or a disease pressure sub-routine did not improve the model under low disease pressure. BoWaS based on disease pressure and weather resulted in better control of grey mould then the weather based BoWaS, under high disease pressure. Adding an irrigation rule did not improve the model further. Using the modified BoWaS reduced fungicide input with 36% compared to routine applications with the same efficacy. INTRODUCTION Grey mould caused by Botrytis cinerea is a major threat to strawberry cultivation in the open field. In conventional strawberry growing, under field conditions several spray applications with fungicides are necessary. Public concern on fungicide use requires reduction of pesticide input in horticultural cultivation. The risk of infection of the flowers by B. cinerea depends on temperature and humidity (Bulger et al., 1997). At the optimum temperature short periods of leaf wetness are sufficient for the fungus to infect flowers. At sub-optimal temperatures prolonged leaf wetness periods are necessary for the fungus to infect strawberries. Pin point timing of fungicide application can possibly improve the efficacy of grey mould control and surely reduce the number of spray applications (Wander et al., 2004). Several Decision Support Systems (DSS) can be used as an aid to control grey mould. Predicted weather data, combined with measured weather data are used by most of these models to forecast Botrytis infection risk. However, in strawberry cultivation irrigation is an almost daily practice. The effect of overhead irrigation on the Botrytis infection risk is unknown. Generally DSS’s predict the infection risk correctly. However sometimes the infection risk was not predicted but did occur. This is considered a risk since no fungicides are registered with a curative mode of action in the Netherlands. Furthermore disease pressure based on inoculum density is not incorporated in the models. These are reasons that Dutch strawberry growers infrequently use DSS’s. The aim of our research was to evaluate additional decision rules dealing with overhead irrigation and disease pressure. 247 Proc. VI th Internat. Strawberry Symposium Ed.: J. López-Medina Acta Hort. 842, ISHS 2009 MATERIALS AND METHODS The experimental site was situated at Vredepeel on a sandy soil with 2.7% organic matter and a pH of 5.1. Cold stored waiting bed plants (cv. ‘Elsanta’) were planted on May 16 2006 and May 9 2007. Each net plot consisted of 20 strawberry plants, in a slightly elevated bed 150 cm wide with two rows 55 cm apart. Strawberry plants were planted 29 cm apart within rows. To control Botrytis in strawberry, plants were sprayed with registered fungicides based on Decision Support Systems (Table 1). Strawberry Actual (treatment D) provided by WeerOnline BV and BoWaS (treatment C) provided by Agrovision BV, which was developed in cooperation with Applied Plant Research were used. Sub-routines dealing with the effect of overhead irrigation (C-I) and/or Botrytis disease pressure (C-DP1 and C-DP2) were made. The irrigation sub-routine assumes that farmers irrigate the crop daily, thus lengthening the leaf wetness period. An adjusted infection risk based on temperature and the modified leaf wetness period was then calculated. The disease pressure sub-routine (C-DP1) was calculated in 2006 by estimating sporulation density (modified from Sosa-Alvarez et al., 1995). With high sporulation density the spray interval was shortened with 1 or 2 days. The disease pressure sub-routine (C-DP2) was adjusted in 2007 and was based on previous and predicted infection risks. The spray interval could either be shortened by 3 days or lengthened by 2 days. The fruits of 20 plants per plot were handpicked twice a week. Fruits were rated class 1, small (<28 mm), class 2, cracked or rotten. Fruits of each quality rating were weighed. Percentage fruit rot caused by B. cinera was calculated. Data were analysed using Genstat 9.0 (Rothampstead Experimental Station, UK). Analysis of variance was applied to the cumulative incidence of Botrytis fruit rot and marketable yield. A randomised block design with three replicates was used. RESULTS AND DISCUSSION Marketable yield was significantly lower in the untreated control compared to treatments in which grey mould was controlled chemically, except for treatments C-DP1 and D in 2006 (Table 1). The number of days with high infection risks during flowering and harvest were relatively low in 2006 and high in 2007. The calculated infection risk of both models is based on temperature and leaf wetness adjusted from a model developed in the USA (Bulger et al., 1987). Preharvest Botrytis fruit rot is caused by infection of flowers primarily (Jarvis and Borecka, 1968; Mertely et al., 2002). After bloom, environmental factors showed considerably less association with disease incidence than during blooming (Wilcox and Seem, 1994). Emphasis on control should focus on peak bloom (Mertely et al., 2002), a fact which is used in both DSS’s. BoWaS uses a dynamic flowering model to calculate infection risk. The threshold for infection risk is lowest at full bloom and higher at the first week of flowering and during harvest. Strawberry Actual uses a fixed threshold of 5%, but infection risk calculated during flowering is higher than during harvest. Differences in susceptibility between flowers (flowering stages) and fruits (Jarvis and Borecka, 1968) are built into both DSS’s. The number of spray applications was less when DSS’s were used compared to the number of spray applications according to routine. This is in accordance with Wander et al. (2004). Grey mould control using Strawberry Actual (D) and BoWaS including subroutines (C-I; C-DP1), were comparable to routine application of fungicides in 2006. Grey mould control based on BoWaS (C) was significantly better than routine applications of fungicides in 2006. In a season with relatively few days with high infection risks fungicide input could be reduced with 50% and this coincided with a 62% better efficacy compared to routine application. However in a season with several days with high infection risk (2007) both BoWaS and Strawberry Actual were less effective than routine application in controlling grey mould. The number of sprays advised by BoWaS was 5 less than in the routine treatment. The spray interval advised or applied was too long under heavy disease pressure. Therefore the spray interval advised should be