Development of a simulation model for the population dynamics of the onion fly Delia antiqua in Germany*

Delia antiqua is a serious pest of many species of the genus Allium, including onions and chives. Over a period of two years (1997/1999), we have developed a model to simulate the population dynamics of D. antiqua based on an extended Leslie model. The model structure as well as the developmental functions for the different life stages of D. antiqua are presented. Using daily mean air and soil temperatures, the model calculates the population matrix for developmental stages of D. antiqua including eggs, larvae, pupae and adults. The simulation can be used to optimize the timing of control measurements against a specific life stage of D. antiqua. Flight activity can be simulated using wind speed as additional information. Simulated flight activity and the observed flight activity of D. antiqua monitored with water pan traps in three different regions of Germany in 1998 are presented and discussed. The model, which was programmed as part of the SWAT 3.5 package of programs to simulate the population dynamics of root‐fly pests in horticultural crops, will also be available via other expert systems such as PASO.     

Check-list for scientific names of common parasitic fungi. Series 2d: Fungi on field crops: Vegetables and cruciferous crops

This list is a continuation of Series 2a, b, and c [Nath. J. Pl. Path. 82 (1976) 193–214, 83 (1977) 165–204 and 85 (1979) 151–185], an account of the nomenclature of common parasitic fungi on field crops as used in official publications of the Netherlands Society of Plant Pathology and the Netherlands Ministry of Agriculture and Fisheries.     

PLASMO: a simulation model for control of Plasmopara viticola on grapevine1

The problem of protecting grapevine against diseases is an old one, but in the last few years new techniques have been developed to reduce cost to the farmer and damage to the ecosystem. These are based on mathematical models describing the state of the plant-parasite environment system. A model for forecasting development of grapevine downy mildew (Plasmopara viticola) is presented. The input variables are temperature, rainfall and leaf wetness (determining infection by sporangia), and RH and temperature (for incubation period). The model also takes into account the limited survival of spores. The output is expressed as %, disease progress. Field validation tests, performed in 1990, 1991 and 1992 in several vineyards in Toscana (central Italy) showed a good correlation between observed and simulated infections. The model allowed the number of treatments to be reduced without any increase in downy mildew damage. It could in future be integrated with grapevine growth and development simulation models in an expert system to determine infected tissue area and thus the economic damage threshold.     

内蒙古地区玉米农田土壤墒情动态预测模式

根据多年实际观测资料,在土壤水分平衡参数模拟方法的基础上,利用初始土壤有效水分贮存量、降水量和实际蒸散量三要素,建立了０ｃｍ～５０ｃｍ土层的土壤水分动态预测模式,提出了玉米农田土壤墒情评估方法。通过１０个区域的试用,土壤水分预测准确率在８０％左右,墒情预测准确率可达９０％以上。     

A stochastic simulation model for evaluating the concept of patch spraying

The long-term economic benefits of `patch' spraying are likely to be related to the initial spatial distribution of the target weeds, the demographic characteristics of the species and the weed control and crop husbandry practices to which they are subjected. This paper describes a stochastic simulation model developed to investigate the interaction between weed seed dispersal and patch spraying. Simulated weed plant and seed populations are generated and compared with data from field observations. Lloyd's Patchiness index is used to quantify the patchiness of the weed density distribution, and the parameter k of the negative binomial distribution is used as a measure of distribution shape. A method of assessing the spatial scale of weed aggregation is proposed, in which spatial weed density information is transformed into the frequency domain, using a discrete two-dimensional Fourier transform. In this paper, we simulate `on/off' patch spraying (full or zero herbicide application rate). A quantitative analysis of the effects of sprayer resolution and weed seed dispersal range on the herbicide reduction and yield benefits from patch spraying is performed for three initial spatial seedbank distributions. The model is parameterized for the grass weed Alopecurus myosuroides Huds. Herbicide is applied in square areas (whose size is defined by the spatial resolution of the sprayer) in which mean weed density is greater than or equal to one plant m^–2. For a system conforming to this specification we show that for the control of A. myosuroides , it is unlikely that patch spraying would be profitable in the long term if the control area is larger than 6 m × 6 m. In some circumstances higher resolution may be required.     

Check-list for scientific names of common parasitic fungi. Supplement Series 2c,d (additions and corrections): Fungi on field crops: pulse (legumes), forage crops (herbage legumes), vegetables and cruciferous crops

This supplement to Series 2c (Neth. J. Pl. Path. 85 (1979) 151–185) and Series 2d (Neth. J. Pl. Path. 86 (1980) 199–228) includes 12 pathogens not treated before. The data of 30 other pathogenic fungi have been revised or emended and brought in accordance with the present Code of Botanical Nomenclature. One new variety and two new combinations are proposed, viz.Phoma medicaginis var.macrospora Boerema et al.,Phoma boltshauseri (Sacc.) Boerema et al. andPeronospora viciae (Berk.) Casp. f.sp.fabae (Jacz. & Serg.) Boerema et al.     

CERCOPRI: a forecasting model for primary infections of cercospora leaf spot of sugarbeet1

A computerized model for forecasting the appearance of primary infections of cercospora disease on sugarbeet was worked out using meteorological and epidemiological data collected in the western Po Valley from 1980 to 1989. This program, called CERCOPRI, gives a figure for the current risk of disease appearance, a forecast of the risk on a pre-established day or a forecast of the day on which risk will reach a pre-established threshold.     

A crop loss-related forecasting model for sclerotinia stem rot in winter oilseed rape

Sclerotinia stem rot (SSR) is an increasing threat to winter oilseed rape (OSR) in Germany and other European countries due to the growing area of OSR cultivation. A forecasting model was developed to provide decision support for the fungicide spray against SSR at flowering. Four weather variables-air temperature, relative humidity, rainfall, and sunshine duration-were used to calculate the microclimate in the plant canopy. From data reinvestigated in a climate chamber study, 7 to 11 degrees C and 80 to 86% relative humidity (RH) were established as minimum conditions for stem infection with ascospores and expressed as an index to discriminate infection hours (Inh). Disease incidence (DI) significantly correlated with Inh occurring post-growth stage (GS) 58 (late bud stage) (r(2) = 0.42, P /= Inh(i). Historical field data (1994 to 2004) were used to assess the impact of agronomic factors on SSR incidence. A 2-year crop rotation enhanced disease risk and, therefore, lowered the infection threshold in the model by a factor of 0.8, whereas in 4-year rotations, the threshold was elevated by a factor 1.3. Number of plants per square meter, nitrogen fertilization, and soil management did not have significant effects on DI. In an evaluation of SkleroPro with 76 historical (1994 to 2004) and 32 actual field experiments conducted in 2005, the percentage of economically correct decisions was 70 and 81%, respectively. Compared with the common practice of routine sprays, this corresponded to savings in fungicides of 39 and 81% and to increases in net return for the grower of 23 and 45 euro/ha, respectively. This study demonstrates that, particularly in areas with abundant inoculum, the level of SSR in OSR can be predicted from conditions of stem infection during late bud or flowering with sufficient accuracy, and does not require simulation of apothecial development and ascospore dispersal. SkleroPro is the first crop-loss-related forecasting model for a Sclerotinia disease, with the potential of being widely used in agricultural practice, accessible through the Internet. Its concept, components, and implementation may be useful in developing forecasting systems for Sclerotinia diseases in other crops or climates.     

昆虫杆状病毒流行病模拟模型及Java模拟软件(英文)

研究昆虫杆状病毒流行病模拟模型,对确定基因工程改造杆状病毒的主攻方向,明确病毒病田间流行的机制与关键因素,以及制定生物防治策略,均具有重要的理论与实践意义。本研究研制了用于昆虫杆状病毒流行病模拟的数学模型和Java模拟软件,该模型包括描述种群动态的一个微分方程组,描述气温变化、作物生长及病毒动态的若干模型等。模拟软件用工具包JDK和JavaScript开发,由主计算类、图形类、结果显示类、参数输入界面类、警告信息类、主页、用户指南页、版权页、计数页等组成。在参数文件中编入有关作物、病毒、害虫等方面的参数,输入初始的各龄健康、染病虫量、叶面积、病毒密度等,运行后可输出各龄健康、染病及病死的虫量,作物损失,病毒积累等动态,以及图形等等。该模型适用于各种杆状病毒,各种有叶作物,各种食叶性的全变态昆虫。应用该模拟模型,对温度、病毒施用虫龄、病毒施用时间、病毒施用剂量等进行了灵敏度分析,得到了一些重要结论。     

A dynamic simulation model for powdery mildew epidemics on winter wheat*

A system dynamic model for epidemics of Blumeria graminis (powdery mildew) on wheat was elaborated, based on the interaction between stages of the disease cycle, weather conditions and host characteristics. The model simulates the progress of disease severity, expressed as a percentage of powdered leaf area, on individual leaves, with a time step of one day, as a result of two processes: the growth of fungal colonies already present on the leaves and the appearance of new colonies. By means of mathematical equations, air temperature, vapour pressure deficit, rainfall and wind are used to calculate incubation, latency and sporulation periods, the growth of pathogen colonies, infection and spore survival. Effects of host susceptibility to infection, and of leaf position within the plant canopy, are also included. Model validation was carried out by comparing model outputs with the dynamics of epidemics observed on winter wheat grown at several locations in northern Italy (1991–98). Simulations were performed using meteorological data measured in standard meteorological stations. As there was good agreement between model outputs and actual disease severity, the model can be considered a satisfactory simulator of the effect of environmental conditions on the progress of powdery mildew epidemics.     

Development of a forecasting model for scald,Rhynchosporium secalis,on rye in relation to climatic conditions1

In a large-scale forecasting project financed by the German Ministry of Agriculture, in collaboration with the National Plant Protection Service, data for modelling forecasting systems in field and horticultural crops are obtained and evaluated. Using climatic records from automatic weather stations and weekly disease assessments in the field, a practical model for forecasting Rhynchosporium secalis on rye has been established with a discriminant function in which temperature, leaf wetness and a disease index during the infection period were used as classification variables. This function decides on application of fungicide sprays.     

A simulation model for the development of brown rust epidemics in winter wheat

A model simulating the progress of Puccinia recondita severity, expressed as a percentage of rusted leaf area (both as average and its 95% confidence interval) on individual wheat leaves over the course of a growing season, with a time step of one day, was elaborated using laboratory and field data from literature. Data on the stages of each infection cycle (uredospore germination, penetration, latency, uredium eruption and infectiousness) were transformed into model parameters by curve fitting, Montecarlo stochastic procedures, corrections and empirical assumptions. Data on host growth, like the timing of all phenological stages, the dynamic of the green area of each leaf from appearance to complete senescence, and tillering were obtained from a specific sub-model. Model validation was performed on actual data not used in model building and representing a wide range of conditions (several winter wheat cultivars grown at eight locations in northern Italy between 1990 and 1994) by using subjective, non-parametric and parametric tests: it revealed a satisfactory agreement between the data simulated by the model and actual data.     

耦合气象影响因素和Logistic方程的水稻纹枯病发病等级动态预测模型研究

本文基于植保、气象等数据研究水稻纹枯病发病等级-时间动态的预测方法和模型。利用2010年-2016年湖南省12个县的植保调查数据和气象观测值,以水稻纹枯病流行机理为基础将Logistic方程与构建的温度影响模块和湿度影响模块耦合,建立Logistic-RICEBLA病害预测模型。通过对模型参数进行调优、训练和验证,实现对水稻纹枯病发病等级的动态预测。结果表明,Logistic-RICEBLA模型能够较好地响应温度、湿度等气象条件的变化,模型预测结果与实际的水稻纹枯病发病等级-时间变化曲线具有较高的一致性。经验证,模型预测结果在单时相上精度达到R~2=0.68,RMSE=1,容错准确率P＿bias=88%,表明预测值与实际发病等级的误差基本控制在±1级范围内。在多时相整体趋势的验证方面,模型预测的病害流行曲线下面积(AUDPC)与病害实际发展的AUDPC保持高度一致性,决定系数(R~2)达到0.86,表明模型能给出纹枯病在水稻不同生育期发病等级变化的整体趋势。本研究构建的Logistic-RICEBLA模型能由简单的气象数据和植保数据驱动,对水稻纹枯病发病等级进行动态预测,有助于在植保管...     

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.     

A review of Phytophthora diseases of different Mediterranean crops in Turkey1

In the last 20 years, seven different Phytophthora species (P. cambivora, P. hibernalis, P. citrophthora, P. capsici, P. cactorum, P. drechsleri and P. infestans) have been determined in Turkey on chestnut, citrus, pepper, strawberry, melon, and potato respectively. Two of them, P. citrophthora and P. capsici, which attack citrus and pepper, are very destructive and have the greatest economic importance. P. citrophthora has caused approximately 15% fruit losses every year and 8–30% infection on a susceptible lemon cultivar in Cukurova region. P. capsici is very dangerous for pepper-spice and pepper-paste production because it causes up to 100% drying and killing of pepper plants under conditions of poor drainage and incorrect irrigation practices. P. cambiuora, which causes the ink disease of chestnut, has spread from the Black Sea coast to the Mediterranean; about 20 000 chestnut trees have been killed by this organism from 1952 to 1970. Recently, P. infestans on potato is achieving importance, as the potato area increases. The other species of Phytophthora do not have any economic importance and only first records have been noted.     

基于误差校正的二次非线性能源需求预测

能源需求预测是能源规划和政策制定的基础.通过对影响能源需求的因素进行分析,建立了基于影响因素的二次非线性能源需求预测模型,并通过混沌遗传算法(CGA)求解模型的参数得到具体的预测模型.在模型基础之上,进一步研究了模型误差,通过数据变换技术对误差建立GM(1,1)预测模型.通过对二次非线性模型进行误差校正,进一步提高了模型的预测精度.依据1985-2014年的历史数据建立了基于误差校正的二次非线性能源需求预测模型,并预测了在经济新常态的形势下,2020年中国能源的需求量约为48.57亿t标准煤.     

洛川苹果腐烂病发生流行预测模型的研究

以陕西省洛川县1999～2004年气象资料和苹果腐烂病的发生流行程度为基础,运用数据分析软件SAS分析了苹果腐烂病发生流行程度与气象因子间的关系,并获得了预测模型:y=8.80703-0.749 17T3-0.016 36RH8+0.052 34T12-0.000 890 25RF7。     

基于随机森林算法构建白眉野草螟监测预警模型

为科学防治白眉野草螟Agriphila aeneociliella,以16种气象因子为自变量,以白眉野草螟发生程度为因变量,采用随机森林算法构建白眉野草螟的监测预警模型,并利用构建的模型对2010—2016年影响鲁东地区白眉野草螟发生程度的关键气象因子进行分析。结果表明,当特征值为9,决策树数量为400时,白眉野草螟监测预警模型的袋外估计错误率最低,为17.88%,轻度发生和重度发生的错误率分别为17.58%和18.18%。利用测试数据检验模型,模型错误率为20.00%。通过所构建的模型分析显示影响鲁东地区白眉野草螟发生程度的关键气象因子为平均水汽压、日最低气温、平均气温和日最高气温,其Gini值分别为18.82、14.84、13.67和9.30。