Resistance to Leveillula taurica in the genus Capsicum

One hundred and sixty-two Capsicum genotypes were evaluated for powdery mildew (Leveillula taurica) resistance, following inoculations with a suspension of 5 × 10⁴ conidia mL⁻¹ on 10-leaved to 12-leaved plants. Genotypes were graded into five resistance classes, based on the areas under the disease progress curves calculated from disease incidence (percentage infected leaves per plant) and severity (total number of colonies per plant). Results revealed a continuum from resistance to susceptibility, with the majority (70%) of C. annuum materials being classified as moderately to highly susceptible to L. taurica. Conversely, C. baccatum, C. chinense and C. frutescens were most often resistant, indicating that resistance to L. taurica among Capsicum species is found mainly outside the C. annuum taxon. Nevertheless, some resistant C. annuum material was identified that may be useful for resistance breeding. Eight genotypes were identified as immune to the pathogen: H-V-12 and 4638 (previously reported), and CNPH 36, 38, 50, 52, 279 and 288. Only H-V-12 and 4638 are C. annuum, while all others belong to the C. baccatum taxon. Latent period of disease on a set of commercial sweet pepper genotypes varied, indicating diverse levels of polygenic resistance. The latent period progressively reduced with plant maturity, from 14·3 days in plants at the mid-vegetative stage to 8·6 days in plants at the fruiting stage. Young plants of all commercial genotypes tested at the early vegetative stage were immune, irrespective of the reaction of the genotype at later stages, demonstrating widespread juvenile resistance to L. taurica in the Capsicum germplasm. Inoculation of plants of different botanical taxa with a local isolate indicated a wide host range. Some hosts, including tomato (Lycopersicon esculentum), artichoke (Cynara scolymus) and poinsettia (Euphorbia pulcherrima), produced large amounts of secondary inoculum. Other hosts included okra (Abelmoschus esculentus), eggplant (Solanum melongena), cucumber (Cucumis sativus), Solanum gilo, Chenopodium ambrosioides and Nicandra physaloides.     

Decision support systems used in the Netherlands for reduction in the input of active substances in agriculture

Since the middle of the 1980s, Dutch farmers have been using decision support systems (DSS) as an aid in the control of pests. This started with EPIPRE, then weather-related potato blight warning systems were developed (Prophy and Plant-Plus). In the 1990s, many weather-based DSS were developed against pests of orchards, flower bulbs, arable crops and field-produced vegetables. Also, a DSS was developed to predict and check the effect of meteorological conditions on the effectiveness of application timing of plant protection products (GEWIS). The use of these systems resulted in more sustainable crop protection: sustainable because the use of DSS led to a lower risk of crop damage and, in many cases, to a lower input of active substances, by optimization of the product and dose to actual phytosanitary and meteorological conditions. The use of GEWIS to ensure application at the right time of day further reduced the input of active substances and increased efficacy.     

The Pacific Pest List Database for agricultural trade facilitation

The Pest List Database for the Pacific is a user-friendly database that provides information on agricultural pest occurrences within a country as required to facilitate trade in terms of the International Plant Protection Convention and International Standards For Phytosanitary Measures. Its main outputs are: (a) a pest list for any specified crop intended for export and (b) a list of pest incursions detected on imported goods from any selected country. The system is designed for use by the 22 Pacific Island countries and territories that the Secretariat of the Pacific Community serves and is so far installed in five countries with a new one being delivered every 3–4 months. It is typically delivered with a few thousand known pest occurrence records of that country, and look-up lists of several thousand Pacific pests and a few hundred crops.     

Development and use of a forecasting model for Cydia pomonella*

For more than 10 years, a forecasting model for Cydia pomonella in apple orchards, worked out by the French NPPO, has described the development of emergence cohorts in spring, and followed their development and descent, through the whole agricultural season. In homogeneous areas, this tool, still under development, can be used to define periods for effective treatment (ovicides, larvicides, mating disruption) and the tolerance for codling moth levels in various situations. Alternation of insecticides is provided for, so as to manage resistance phenomena. The reliability of the model is based on rigorous continuous biological checks on the forecasts made by the algorithm, on scientific surveillance by INRA and on regular collaboration between the advisers involved and the agrometeorological services. The model forms part of a wider decisional scheme, or expert system, in which the fruit grower and his adviser provide observations on the changes which cannot be provided by the model: installation of hail protection nets, night lights, fruit spreading. More parameters will be incorporated in future and the geographical validity of the model will be extended, particularly to more northerly areas.     

Application of fuzzy logic for the simulation of Plasmopara viticola using agrometeorological variables*

A mechanistic model called PLASMO was developed earlier to simulate grapevine downy mildew (Plasmopara viticola) and has been applied in several viticultural areas of Italy since 1988 by the collaboration of several research institutions of Firenze. In this study, a new simulation model based on fuzzy logic has been developed for the same structure (biological cycle of P. viticola). This approach allows classical quantitative information to be used together with qualitative information. Vague concepts can also be handled. Agrometeorological data is used, with an hourly time step, starting from budbreak to the end of the growing season. Air temperature, relative humidity, rainfall and leaf wetness are required. The simulated processes are the growth of grapevine leaf area and the main phases of the biological cycle of the pathogen: incubation, sporulation, germination, spore survival and inoculation. The main epidemiological outputs are timing of infection events and disease intensity. The performance of the model is evaluated and the mechanistic and fuzzy logic approaches are compared.     

Estimating the potential development of Diaporthe helianthi epidemics in Italy*

Diaporthe helianthi is the causal agent of a severe sunflower disease but, in Italy, disease outbreaks are sporadic with no significant losses. The present work investigates the role of meteorological conditions on the potential development of D. helianthi epidemics in Italy, using the French model Asphodel, which simulates the effect of air temperature, relative humidity and rainfall on ascospore maturation and dispersal, infection establishment, disease onset and severity during the period of host susceptibility. Meteorological data measured in eight stations distributed from north to south Italy, over a 5‐year period (1995–99), was used as model input. Results showed that meteorological conditions in Italy are frequently favourable for D. helianthi infections on sunflower, and severe epidemics are possible. Therefore, climatic conditions are not a limiting factor for disease development in the Italian sunflower‐growing areas. The lack of disease epidemics in Italy may be related to differences in the pathogen populations compared with the French ones.