Reduction In Fungicide Use Research Articles

Modification of Fungicide Treatment Needs and Antioxidant Content as a Result of Real-Time Ozonation of Raspberry Plants.

Raspberry plants need intensive anti-fungal protection. A solution to this problem could be the application of an ozonation process. For this purpose, a technical solution was proposed and implemented in raspberry plant production. The proposal suggests replacing 25% of standard fungicide treatments with ozonation. It was demonstrated that the use of ozone under the proposed conditions made it possible to maintain stable parameters of chlorophyll content and fluorescence (no significant differences), but the intensity of gas exchange was increased. The greatest differences were observed in the second measurement period (T2), when the plants were in the stage of most active development. Additionally, the content and profile of low-molecular-weight antioxidants and the microbial load were determined in the collected fruits. In periods T2 and T3, the proposed method caused a reduction reaching ~2 log cfu g-1 in the microbial content of raspberry fruits. It was shown that ozone treatment intensified the biosynthesis of low-molecular-weight antioxidants in fruit (increasing the total polyphenol content by more than 20%). The proposed scheme allows a 25% reduction in standard fungicide treatments while maintaining the health of cultivated raspberry plants. The reduction in fungicide use aligns with the EU regulations and produces fruit with better quality.

The effects of chemical fungicides and salicylic acid on the apple microbiome and fungal disease incidence under changing environmental conditions.

Epiphytic and endophytic micro-organisms associated with plants form complex communities on or in their host plant. These communities influence physiological traits, development, and host susceptibility to abiotic and biotic stresses, and these communities are theorized to have evolved alongside their hosts, forming a unit of selection known as the holobiont. The microbiome is highly variable and can be influenced by abiotic factors, including applied exogenous agents. In this study, we compared the impact of chemical fungicide and salicylic acid treatments on the fungal communities of "Honeycrisp" apples at harvest over two consecutive growing years. We demonstrated variations in fungal community structure and composition by tissue type, growing season, and treatment regimes and that fungicide treatments were associated with reduced network complexity. Finally, we show that the inclusion of salicylic acid with 50% less chemical fungicides in an integrated spray program allowed a reduction in fungicide use while maintaining effective control of disease at harvest and following storage.

Exploring Winegrowers’ Behaviours and Ecological Impacts Under Climate Change and Policy Scenarios—Examples from Three European Winegrowing Regions

Viticulture is an example of a socio-ecological system that poses serious challenges for sustainable soil management and pesticide use, with various interactions between winegrowers’ decision-making and ecological consequences. This study introduces an agent-based model (ABM) on winegrowers’ decision on inter-row management and pesticide use. The ABM builds upon an empirical study of winegrowers’ decision-making in European viticultural landscapes and has been built for three case study regions: Leithaberg (Austria), Palatinate (Germany) and Târnave (Romania). The ABM allows for analysing potential effects of policy instruments including mandatory vegetation cover in the inter-rows, the reduction of fungicide use and ban of insecticides against Lobesia botrana. The effects of policies differ between the case study regions, indicating how important the local context is for effective policies. For example, policies aiming at higher inter-row vegetation cover had the strongest effects on vegetation cover, landscape aesthetics and soil loss in Târnave since many vineyards are currently intensively tilled and there exist no policies supporting inter-row vegetation cover in Romania.

ADAPTABILIDADE E ESTABILIDADE DE CULTIVARES DE AVEIA À REDUÇÃO DO USO DE FUNGICIDA COM PRODUTIVIDADE SATISFATÓRIA

Purpose: The objective of the study is to identify oat cultivars with satisfactory productivity and adaptability to reduced use of fungicide concomitant with the longest interval between the last application and grain harvest, in the recommendation of biotype more adjusted to agroecological management. Method/design/approach: The study was developed in 2018, 2019, in Augusto Pestana, RS, Brazil. The experimental design was a randomized block with three replications in a 23 x 5 factorial, for 23 Brazilian oat cultivars and 5 fungicide use conditions, applied on the time scale every 15 days cumulatively: control (no application); one application 60 days after emergence (DAE); two applications at 60, 75 DAE; three applications at 60, 75, 90 DAE and four applications at 60, 75, 90, 105 DAE. Results and conclusion: Experimental strategies with the analysis of adaptability and stability help to identify oat cultivars that are more resilient to the absence or reduction of fungicide use, promoting more sustainable management. The cultivars URS Brava and URS Altiva present satisfactory productivity with adaptability to the absence or reduced use of fungicide, providing a safe interval from the last application to the grain harvest, with the indication for agroecological management. It is necessary to promote food security based on new scenarios, including the environment, technology, economy and society. Originality/value: Unprecedented study seeking to reduce the use of fungicidal pesticides to control oat diseases using adaptability and stability models, providing opportunities for the analysis of different scenarios to identify cultivars more suited to agroecological management.

Prospects for Increasing the Efficacy of Plant Resistance Inducers Stimulating Salicylic Acid

Systemic acquired resistance is a powerful mechanism, based on the salicylic acid (SA) signaling pathway, which allows plants to resist to a wide range of pathogens. High SA, moreover, plays a key role in plant tolerance to abiotic stress. It seems, therefore, desirable to supply analogs of SA or stimulate the production of endogenous SA. Unfortunately, the chemical substances or physical means used for this effect often display a variable efficacy. After providing a review of them, we defend three major ideas: (i) plant resistance inducers (PRIs) must be combined for higher efficacy, notably for exploiting synergic effects between the SA and other signaling pathways, (ii) disease pressure can be reduced by exploiting the fungicidal properties displayed by some PRIs, (iii) biostimulants and crop management techniques should be used to ensure that plants have the resources they need to synthesize the compounds and structures required for efficient and lasting resistance. Some PRIs could also be used for their biostimulant effects in stress conditions. It could be concluded that holistic approaches which jointly address the issues of defense and tolerance stimulation, disease pressure and resource availability in plants are the ones that will allow for substantial reduction in fungicide use without sacrificing crop performance.

Can Decision Support Systems Help Improve the Sustainable Use of Fungicides in Wheat?

Wheat is one of the most economically important field crops worldwide. Foliar diseases are a major threat to wheat productivity and are primarily managed by implementing less susceptible cultivars and using fungicides. With the “Farm to Fork” strategy under consideration by the European Union to reduce pesticide usage by 50% by 2030, this elucidates the importance of utilizing decision support systems (DSS) to optimize fungicide applications. Therefore, three DSSs of different origins, namely the IPM-Wheat Model Schleswig-Holstein (scientific), the ISIP system (federal), and the xarvio© FIELD MANAGER (commercial), were analysed under maritime climate conditions at three locations in a high input area of wheat cultivation in northern Germany from 2019 to 2021. Fungicide efficacy was evaluated for yield as well as for the management of prevalent pathogens (Septoria tritici blotch, glume blotch, tan spot, powdery mildew, stripe rust, and leaf rust) on two different commercially available cultivars (highly and moderately susceptible). Compared to a stage-oriented standard system, no significant decrease in yield was observed in both cultivars, despite up to a 50% reduction in fungicide use through the use of DSSs. This was attributed to an optimized timing of fungicide applications, which resulted in slightly lower but still tolerable disease suppression efficacy compared to the stage-oriented system. In conclusion, minor disease severities are often overestimated, and DSSs can help improve the sustainability of fungicide use in wheat and pesticides in general.

Integrating management of powdery mildew with Botrytis in protected strawberries in the UK

Powdery mildew, caused by Podosphaera aphanis, is an important disease of strawberries under protection. Botrytis fruit rot is an important cause of losses in strawberries particularly under open-field conditions. Current control of both these diseases in the UK is dependent on conventional fungicides. Recently, research in the UK demonstrated that integrating biopesticides and biostimulants with a decision-based management programme could achieve reductions in conventional fungicide use without loss in yield or fruit quality. Further field studies were conducted to extend the decision-based management programme to include control of Botrytis fruit rot on everbearer crops. In 2018, three management programmes were compared to a routine fungicide-based programme and an untreated control. In two management programmes, treatments for Botrytis and powdery mildew were either applied routinely or managed. In the third programme, treatments for both diseases were managed. Disease risks were estimated with a simple lookup table based on past and forecast weather. The results showed that the integrated management for both diseases resulted in a nearly 45% reduction in conventional fungicide use and a cost saving of £699/ha compared to a routine programme with no penalties in yield, fruit quality or disease control. There were no significant effects of treatments on Botrytis rot incidence compared to the untreated control, suggesting that the fungicides applied for controlling Botrytis gave no benefit. In 2019, two treatments based on the decision-based management system for powdery mildew and Botrytis, one of which excluded specific fungicide treatment for Botrytis, were compared to an untreated control and a routine fungicide programme. Cool chain management of the fruit post-harvest was also included to extend post-harvest fruit shelf life. The results showed that the simple decision-based system for determining treatments for mildew and Botrytis based on biopesticides and omitting Botrytis-specific fungicides resulted in a 93% reduction in fungicide use and a cost saving of £924/ha compared to a routine programme with no penalties in yield, fruit quality or disease control. Cool chain management delayed the development of both Botrytis and soft rots. In both years, detectable fungicide residues were considerably reduced in the fruit from the managed programmes.

Research Article Resistance of oat cultivars to reduction in fungicide use and a longer interval from application to harvest to promote food security

Research Article Resistance of oat cultivars to reduction in fungicide use and a longer interval from application to harvest to promote food security

Predicting rice blast disease: machine learning versus process-based models

BackgroundIn this study, we compared four models for predicting rice blast disease, two operational process-based models (Yoshino and Water Accounting Rice Model (WARM)) and two approaches based on machine learning algorithms (M5Rules and Recurrent Neural Networks (RNN)), the former inducing a rule-based model and the latter building a neural network. In situ telemetry is important to obtain quality in-field data for predictive models and this was a key aspect of the RICE-GUARD project on which this study is based. According to the authors, this is the first time process-based and machine learning modelling approaches for supporting plant disease management are compared.ResultsResults clearly showed that the models succeeded in providing a warning of rice blast onset and presence, thus representing suitable solutions for preventive remedial actions targeting the mitigation of yield losses and the reduction of fungicide use. All methods gave significant “signals” during the “early warning” period, with a similar level of performance. M5Rules and WARM gave the maximum average normalized scores of 0.80 and 0.77, respectively, whereas Yoshino gave the best score for one site (Kalochori 2015). The best average values of r and r2 and %MAE (Mean Absolute Error) for the machine learning models were 0.70, 0.50 and 0.75, respectively and for the process-based models the corresponding values were 0.59, 0.40 and 0.82. Thus it has been found that the ML models are competitive with the process-based models. This result has relevant implications for the operational use of the models, since most of the available studies are limited to the analysis of the relationship between the model outputs and the incidence of rice blast. Results also showed that machine learning methods approximated the performances of two process-based models used for years in operational contexts.ConclusionsProcess-based and data-driven models can be used to provide early warnings to anticipate rice blast and detect its presence, thus supporting fungicide applications. Data-driven models derived from machine learning methods are a viable alternative to process-based approaches and – in cases when training datasets are available – offer a potentially greater adaptability to new contexts.

New Generation of Resistant Sugar Beet Varieties for Advanced Integrated Management of Cercospora Leaf Spot in Central Europe.

Cercospora leaf spot (CLS) epidemics in sugar beet have been increasing in recent years causing higher use of fungicides. Concomitantly, the availability of effective fungicides is at risk because of resistance development in the fungus, the lack of new active ingredients as well as restrictive approval practices. A key option for an integrated management of CLS is cultivation of resistant varieties. Because of the yield penalty in resistant varieties, acceptance in commercial practice so far has been low. The aim of our study was to characterize recent sugar beet varieties registered in Germany in terms of resistance and tolerance to CLS and their value for integrated pest management. The genetic basis of CLS resistance in varieties is protected by intellectual property rights even after variety registration and not open to the public due to economic competition. To gain reliable data for cultivation, varieties have to be tested for their resistance traits under field conditions at varying levels of infection with Cercospora beticola. In collaboration with variety related stakeholders, 15 sugar beet varieties were tested in 49 field trials in Germany from 2014 to 2016 for their yield response to CLS. The trials were set up in a split-plot design with and without infection (i.e., with and without fungicide). The classification of varietal reaction to CLS is based on symptomatic leaf area (susceptibility) and the resulting relative yield loss (tolerance). Since the relation between both parameters varied among varieties, it was used as an additional parameter to describe tolerance. On this basis, three groups of varieties were identified. They can be characterized as a susceptible, a resistant and a presumably tolerant cluster. A comparison of the data with an older dataset originating from 2009 to 2011 revealed that yield performance of recent varieties with resistance to C. beticola caught up with susceptible varieties due to breeding progress. They showed no yield penalty in the absence of the disease and better economic performance than susceptible varieties. It is assumed that these varieties will allow a substantial reduction of fungicide use for an advanced integrated pest management under central European conditions.

Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application

Late blight is one of the most important potato diseases. To minimize yield losses, various protective measures are used including fungicide application. Active use of fungicides results in a contamination of the environment. Therefore, crop protection strategies optimizing the number of treatments are of great interest. Using information about late blight development in an experimental potato field recorded over 30 seasons, a simulator to forecast yield losses caused by the disease was developed based on the number of 5-d periods favorable for reinfection of plants during a vegetation season. The simulator was successfully verified using independent data on the disease development from nine unprotected potato fields in the Netherlands and Germany. The average difference between the calculated and real yield losses did not exceed 5%. Using the simulator and weather data for a period of 2007–2017, yield losses were calculated for several areas of the Bryansk, Tambov, and Orenburg Regions of Russia. The results revealed differences in disease development between these regions and may be used to develop recommendations for a frequency of fungicide applications according to the regional risk of epidemics, leading to a significant reduction in fungicide use.

Site-Specific Management of Cotton Root Rot Using Airborne and High-Resolution Satellite Imagery and Variable-Rate Technology

Abstract. Cotton root rot is a century-old cotton disease that now can be effectively controlled with Topguard Terra fungicide. Because this disease tends to occur in the same general areas within fields in recurring years, site-specific application of the fungicide only to infested areas can be as effective as and considerably more economical than uniform application. The overall objective of this research was to demonstrate how site-specific fungicide application could be implemented based on historical remote sensing imagery and using variable-rate technology. Procedures were developed for creating binary prescription maps from historical airborne and high-resolution satellite imagery. Two different variable-rate liquid control systems were adapted to two existing cotton planters, respectively, for site-specific fungicide application at planting. One system was used for site-specific application on multiple fields in 2015 and 2016 near Edroy, Texas, and the other system was used on multiple fields in both years near San Angelo, Texas. Airborne multispectral imagery taken during the two growing seasons was used to monitor the performance of the site-specific treatments. Results based on prescription maps derived from historical airborne and satellite imagery of two fields in 2015 and one field in 2016 are reported in this article. Two years of field experiments showed that the prescription maps and the variable-rate systems performed well and that site-specific fungicide treatments effectively controlled cotton root rot. Reduction in fungicide use was 41%, 43%, and 63% for the three fields, respectively. The methodologies and results of this research will provide cotton growers, crop consultants, and agricultural dealers with practical guidelines for implementing site-specific fungicide application using historical imagery and variable-rate technology for effective management of cotton root rot. Keywords: Airborne imagery, Cotton root rot, High-resolution satellite imagery, Prescription map, Variable-rate application.

A STOCHASTIC FRONTIER ANALYSIS TO EXAMINE RESEARCH PRIORITIES FOR GENETICALLY ENGINEERED PEANUTS

AbstractPesticide applications are essential for peanut production to control insects, weeds, and other plant pathogens and for a profitable operation. We use a stochastic frontier analysis/primal system approach to test the hypothesis of the overuse of fungicides among peanut farmers. With nationally representative data available from the Agricultural and Resource Management Survey, we find evidence that U.S. peanut growers used excessive amounts of fungicides to prevent fungal infections. If those farmers adopt a new cultivar resistant to fungal pathogens, they could reduce the total cost of chemicals up to 36.2%. The reduction in fungicide use would have spillover environmental benefits.

Variety resistance to Cercospora leaf spot and fungicide application as tools of integrated pest management in sugar beet cultivation – A German case study

Variety resistance is a principal element of integrated pest management and part of the integrated control of Cercospora leaf spot (CLS) in sugar beet. Currently, varieties with a high level of resistance to CLS yield lower than susceptible ones and consequently lack acceptance in commercial farming in Germany. In a comparative analysis of three different trial series, yield performance of selected sugar beet varieties with varying susceptibility to CLS was examined with regard to CLS-disease severity of the trial site. In disease-free environments, the current resistant varieties yielded 5–7% less than susceptible varieties, indicating progress in sugar beet breeding and a reduction in yield-penalty by half within the last 20 years. In environments with strong infestation, the resistant variety achieved a white sugar yield (WSY) comparable to varieties with generally higher yield potential. The observed changes in variety-ranking, especially between environments with low to medium and strong CLS-infestation, suggested that superiority of some varieties depended on disease pressure in the respective growing area. It is concluded that disease severity of CLS should be taken into account for the characterisation of varieties in order to improve variety-recommendations and to allow conclusions about the superiority of varieties in regions with varying disease pressure.An analysis of the effect of different control strategies agreed with prior studies that WSY is higher in treatments with fungicide applications according to the summary threshold system than in the non-treated control. Preventive fungicide applications appeared to be unnecessary for German growing areas as they did not increase WSY. Moreover, a reduced strategy related to the summary threshold system may allow a reduction in fungicide use as it achieved a WSY comparable to the threshold strategy but with omission of the last application.

Do some IPM concepts contribute to the development of fungicide resistance? Lessons learned from the apple scab pathosystem in the United States

One goal of integrated pest management (IPM) as it is currently practiced is an overall reduction in fungicide use in the management of plant disease. Repeated and long-term success of the early broad-spectrum fungicides led to optimism about the capabilities of fungicides, but to an underestimation of the risk of fungicide resistance within agriculture. In 1913, Paul Ehrlich recognized that it was best to 'hit hard and hit early' to prevent microbes from evolving resistance to treatment. This tenet conflicts with the fungicide reduction strategies that have been widely promoted over the past 40 years as integral to IPM. The authors hypothesize that the approaches used to implement IPM have contributed to fungicide resistance problems and may still be driving that process in apple scab management and in IPM requests for proposals. This paper also proposes that IPM as it is currently practiced for plant diseases of perennial systems has been based on the wrong model, and that conceptual shifts in thinking are needed to address the problem of fungicide resistance.

Socioeconomic impact of SARO agro allied organic cocoa programme on beneficiary cocoa farmers in Nigeria

Organic cocoa farming involves cultivation of cocoa with rational use of allowable inputs (fungicides and bio-insecticides). SARO Agro Allied Nigeria and her foreign partner ADM/Schokinag started the organic cocoa project (OCP) in 2006/2007 cocoa season in four of their major operating states in Nigeria (Ondo, Osun, Ekiti and Cross River). This study was designed to evaluate the income profile, biological and socioeconomic impact of OCP on the pilot farmers who were purposively selected for the study. Data were analyzed using frequency, percentages, mean and T-test statistics. Significant difference was recorded in 5 socioeconomic variables between 2007 and 2010, while a positive relationship was established between organic cocoa production, yield and farmers income profile. Three major sources of income (yield increase, savings from pesticide use reduction and premium) were identified from the 471 respondents. The cocoa yield increased from 0.5 mt/ha in 2007 to 0.73 mt/ha in 2010, there was 40% reduction in fungicide use which translated to N13.2 m savings for the 471 farmers, revenue from yield increase was N112.7 m, while revenue from premium for organic cocoa production was N24.7 m. Total revenue as a result of organic cocoa production per farmer was thus N319,745.22. Moreover, land under organic production by the pilot farmers was 1687 ha which the same remained over the study period. The study concluded that the OCP impacted positively in increased yield, input cost reduction, environmental and health improvement and increased revenue.

Field models for the prediction of leaf infection and latent period of Fusicladium oleagineum on olive based on rain, temperature and relative humidity

Although much is known about the effect of climatic conditions on the development of peacock leaf spot of olive, field‐operational models predicting disease outbreaks are lacking. With the aim of developing such models, a 10‐year survey was conducted to relate leaf infection to climate parameters that can be easily monitored in the field. As outbreaks of disease are known to be linked to rain, models were evaluated for their ability to predict whether infection would occur following a rain event, depending on air temperature and duration of relative humidity above 85%. A total of 134 rain events followed by confirmed leaf infection and 191 rain events not followed by detectable infection were examined. The field data were adequately fitted (both specificity and sensitivity >0·97) with either a multilayer neural network or with two of six tested regression models describing high boundary values of high humidity duration, above which no infection occurred over the temperature range, and low boundary values below which no infection occurred. The data also allowed the selection of a model successfully relating the duration of latent period (time between infection and the first detection of leaf spots) as a function of air temperature after the beginning of rain (R2 > 0·98). The predictive abilities of these models were confirmed during 2 years of testing in commercial olive orchards in southern France. They should thus provide useful forecasting tools for the rational application of treatments and foster a reduction in fungicide use against this major disease of olive.

Economically optimal timing for crop disease control under uncertainty: an options approach.

Severe large-scale disease and pest infestations in agricultural regions can cause significant economic damage. Understanding if and when disease control measures should be taken in the presence of risk and uncertainty is a key issue. We develop a framework to examine the economically optimal timing of treatment. The decision to treat should only be undertaken when the benefits exceed the costs by a certain amount and not if they are merely equal to or greater than the costs as standard net-present-value (NPV) analysis suggests. This criterion leads to a reduction in fungicide use. We investigate the effect of the model for disease progress on the value required for immediate treatment by comparing two standard models for disease increase (exponential and logistic growth). Analyses show that the threshold value of benefits required for immediate release of treatment varies significantly with the relative duration of the agricultural season, the intrinsic rate of increase of the disease and the level of uncertainty in disease progression. In comparing the performance of the delay strategy introduced here with the conventional NPV approach, we show how the degree of uncertainty affects the benefits of delaying control.

PCR detection of Pseudoperonospora humuli in air samples from hop yards

Downy mildew of hop, caused by Pseudoperonospora humuli, is an important disease in most regions of hop production and is managed largely with regular fungicide applications. A PCR assay specific to P. humuli and the related organism P. cubensis was developed and used to monitor airborne inoculum in hop yards to initiate fungicide applications. The PCR amplified as little as 1 fg of genomic DNA of P. humuli, and yielded an amplicon in 70% of reactions when DNA was extracted from single sporangia. In the presence of 25 mg of soil, an amplicon was amplified in 90% of reactions when DNA was extracted from 10 or more sporangia. During nine location‐years of validation, PCR detection of the pathogen in air samples occurred no later than 8 days after the appearance of trace levels of disease signs and/or detection of airborne spores in a volumetric spore sampler. Inoculum was detected on average 4·5 days before (range −8 to 14 days) the first appearance of basal spikes in six commercial yards, or 1·3 days after (range −5 to 1 days) sporangia were detected in a volumetric spore sampler in experimental plots. In commercial yards, use of PCR to initiate the first fungicide application led to enhanced disease control or a reduction in fungicide use in four of six yards compared to growers’ standard practices. These results indicate that the efficiency and efficacy of hop downy mildew management can be improved when control measures are timed according to first detection of inoculum.

Segregation and transmission of host resistance to scab ( Venturia pirina) in pear breeding progeny under natural infection in an orchard

The introduction of scab ( Venturia pirina) resistant pear varieties will increase the economic return of fruit growers and benefit food safety and the environment through a reduction of fungicide use. Seedling progenies of 11 families derived from the controlled cross-pollination of 10 pear varieties: Ya Li, Hood, Buttira Precoce Morettini (BPM), Guyot, Howell, Corella, Rogue Red, Comice, Williams’ Bon Chretien (WBC) and Eldorado, were examined for their response to scab infection in a diseased orchard during the 2004/05 and 2005/06 cropping seasons. The infection was rated by a 9-point scale on diseased leaves of seedling trees with nine being most severe infection. The weather conditions in both seasons were conducive to the disease epidemics with a higher mean disease severity in 2005/06. When progenies with a score of 4 or less were classified as resistant all progeny of the two resistant (R) × resistant (R) families, Ya Li × BPM and Guyot × Hood, were resistant, and those of the R × susceptible (S) family, Eldorado × BPM, were susceptible. In the other families, however, segregation was observed with a proportion of 26–66% progeny being resistant. The segregation patterns observed in all the families can be interpreted by a model of two triallelic genes. The gene, designated as Vp a , has an allele ( V p a 2 ) conferring resistance and two alleles ( V p a 1 and V p a 3 ) conferring susceptibility with V p a 1 being dominant to V p a 2 and V p a 2 being dominant to V p a 3 . Similarly, the gene, designated as Vp b , has an allele ( V p b 2 ) conferring moderate resistance and two alleles ( V p b 1 and V p b 3 ) conferring susceptibility with V p b 1 being dominant to V p b 2 and V p b 2 being dominant to V p b 3 . Breeding strategies for enhancing scab resistance in pears were discussed.