A generalized linear modeling approach for characterizing disease incidence in a spatial hierarchy

ABSTRACT Several statistical models are introduced to quantify the effect of heterogeneity on disease incidence relationships in a three-scale spatial hierarchy: the sampling unit level (highest), the leaf scale (intermediate), and the leaflet scale (lowest). The models are an extension of the theory previously developed for a two-scale hierarchy and were tested using data collected from strawberry leaf blight epidemics. Disease incidence at the sampling-unit scale (proportion of sampling units with one or more diseased leaflets) increased as a saturation-type curve with increasing leaflet or leaf disease incidence (proportion of leaflets or leaves diseased) as predicted by the good fit of the beta-binomial distribution to the leaflet and leaf data. The relationship could be accurately described, without curve fitting, by several simple nonlinear models, in which the aggregation of disease was represented by a modified binomial function incorporating an effective sample size that was either constant or dependent on mean incidence. The relationship between incidence at the leaflet and leaf scales could be modeled based on the combined sampling-unit models for leaflets and leaves. By taking the complementary log-log (CLL) transformation of incidence, the equations could be expressed as generalized linear models, and curve fitting used to estimate the parameters. Generally, curve fitting gave slight to no improvement in the accuracy of the predictions of incidence. These models have broad applicability in sampling for disease incidence, and results can be used to interpret how diseased individuals at the lowest level in a hierarchy are arranged within sampling units.     

Spatial pattern analysis of strawberry leaf blight in perennial production systems

ABSTRACT Spatial pattern of the incidence of strawberry leaf blight, caused by Phomopsis obscurans, was quantified in commercial strawberry fields in Ohio using statistics for heterogeneity and spatial correlation. For each strawberry planting, two transects were randomly chosen and the proportion of leaflets (out of 15) and leaves (out of five) with leaf blight symptoms was determined from N = 49 to 106 (typically 75) evenly spaced sampling units, thus establishing a natural spatial hierarchy to compare patterns of disease. The beta-binomial distribution fitted the data better than the binomial in 92 and 26% of the 121 data sets over 2 years at the leaflet and leaf levels, respectively, based on a likelihood ratio test. Heterogeneity in individual data sets was measured with the index of dispersion (variance ratio), C(alpha) test, a standard normal-based test statistic, and estimated theta parameter of the beta-binomial. Using these indices, overdispersion was detected in approximately 94 and 36% of the data sets at the leaflet and leaf levels, respectively. Estimates of the slope from the binary power law were significantly (P < 0.01) greater than 1 and estimates of the intercept were significantly greater than 0 (P < 0.01) at both the leaflet and leaf levels for both years, indicating that degree of heterogeneity was a function of incidence. A covariance analysis indicated that cultivar, time, and commercial farm location of sampling had little influence on the degree of heterogeneity. The measures of heterogeneity indicated that there was a positive correlation of disease status of leaflets (or leaves) within sampling units. Measures of spatial association in disease incidence among sampling units were determined based on autocorrelation coefficients, runs analysis, and a new class of tests known as spatial analysis by distance indices (SADIE). In general, from 9 to 22% of the data sets had a significant nonrandom spatial arrangement of disease incidence among sampling units, depending on which test was used. When significant associations existed, the magnitude of the association was small but was about the same for leaflets and leaves. Comparing test results, SADIE analysis was found to be a viable alternative to spatial autocorrelation analysis and has the advantage of being an extension of heterogeneity analysis rather than a separate approach. Collectively, results showed that incidence of Phomopsis leaf blight was primarily characterized by small, loosely aggregated clusters of diseased leaflets, typically confined within the borders of the sampling units.     

Spatial pattern analysis of hop powdery mildew in the pacific northwest: implications for sampling

ABSTRACT The spatial pattern of hop powdery mildew was characterized using 3 years of disease incidence data collected in commercial hop yards in the Pacific Northwest. Yards were selected randomly from yards with a history of powdery mildew, and two to five rows were selected for sampling within each yard. The proportion of symptomatic leaves out of 10 was determined from each of N sampling units in a row. The binomial and the beta-binomial frequency distributions were fit to the N sampling units observed in each row and to SigmaN sampling units observed in each yard. Distributional analyses indicated that disease incidence was better characterized by the beta-binomial than the binomial distribution in 25 and 47% of the data sets at the row and yard scales, respectively, according to a log-likelihood ratio test. Median values of the beta-binomial parameter theta, a measure of small-scale aggregation, were near 0 at both sampling scales, indicating that disease incidence was close to being randomly distributed. The variability in disease incidence among rows sampled in the same yard generally increased with mean incidence at the yard scale. Spatial autocorrelation analysis, used to measure large-scale patterns of aggregation, indicated that disease incidence was not correlated between sampling units over several lag distances. Results of a covariance analysis showed that heterogeneity of disease incidence was not dependent upon cultivar, region, or time of year when sampling was conducted. A hierarchical analysis showed that disease incidence at the sampling unit scale (proportion of sampling units with one or more diseased leaves) increased as a saturation-type curve with respect to incidence at the leaf level and could be described by a binomial function modified to account for the effects of heterogeneity through an effective sample size. Use of these models permits sampling at the sampling unit scale while allowing inferences to be made at the leaf scale. Taken together, hop powdery mildew was nearly randomly distributed with no discernable foci, suggesting epidemics are initiated from a well-distributed or readily dispersible overwintering population. Implications for sampling are discussed.     

玉米三种叶斑病混发时的流行过程及产量损失研究

 通过2年的田间小区人工接种试验,观察比较了玉米大斑病、弯孢叶斑病和灰斑病单独及混合发生时的流行过程及对玉米产量损失的影响。结果表明,在病害混发初期,病害间无明显的负相关性,随着病情的发展,病害间的负相关性逐渐增大并达到显著水平,说明病害间有明显的抑制作用。病害混发时造成产量损失并不完全等于各病害单独造成损失之和,其中大斑病和弯孢叶斑病、弯孢叶斑病和灰斑病混合发生所造成的损失约为各病害单独造成损失之和的76%～88%,大斑病和灰斑病混合发生所造成的损失可近似看作两种病害各自引起产量损失之和,3种病害同时发生时最终损失率约为各自造成损失之和的67%～72%。     

Spatial heterogeneity,incidence-incidence and incidence-lesion density relationship of apple scab (<Emphasis Type="Italic">Venturia inaequalis</Emphasis>) in managed orchards

The spatial pattern of apple scab was characterized using 10 years of disease incidence and lesion density data collected in managed orchards located in Quebec, Canada. Distributional analyses indicated that scab incidence was better characterized by the beta-binomial than the binomial distribution in 53 and 65% of the data sets at the leaf and shoot scales, respectively. Median values of the beta-binomial parameter θ, a measure of small-scale aggregation, were near 0 (0.003 and 0.028) at both sampling scales, indicating that disease incidence was close to being randomly distributed (low degree of aggregation). For lesion density, the negative binomial distribution fitted the data better than the Poisson distribution in 86% of the data sets at the leaf scale. The median value of the index of dispersion k was 0.068, indicating that aggregation was present. For all apple scab measurements, the power law models provided a good fit to the data. The estimated slope and intercept parameters were significantly greater than 1 and 0, respectively, suggesting that spatial heterogeneity changed systematically with disease incidence. Results of a covariance analysis showed that spatial heterogeneity of scab incidence at both scales and lesion density was not dependent upon shoot type but that spatial heterogeneity of scab incidence and lesion density at the leaf scale was influenced by the sampling period. A hierarchical analysis showed that scab incidence at the tree scale increased as a saturation-type curve with respect to incidence at the leaf or shoot scales. A similar relationship was observed for incidences at the shoot and leaf scales. An effective sample size model based on the binary power law parameters (Madden and Hughes, Phytopathology 89:770–781, 1999) gave the best fit to the leaf and shoot data, respectively. The incidence-lesion density relationship at both scales was well described by a complementary log-log (CLL) and log transformation model ( R_adj² = 0.97 and R_adj² = 0.94 ) \left( {R_{{adj}}^2 = 0.97\,and\,R_{{adj}}^2 = 0.94} \right) , however, the models tended to underestimate lesion density. The information of the spatial relations of apple scab within and between hierarchical scales acquired from this study can be used in developing and evaluating practical disease management strategies and to improve apple scab assessments for fungicide or cultivar susceptibility trials.     

Relationships between disease incidence at two levels in a spatial hierarchy

ABSTRACT Relationships between disease incidence measured at two levels in a spatial hierarchy are derived. These relationships are based on the properties of the binomial distribution, the beta-binomial distribution, and an empirical power-law relationship that relates observed variance to theoretical binomial variance of disease incidence. Data sets for demonstrating and testing these relationships are based on observations of the incidence of grape downy mildew, citrus tristeza, and citrus scab. Disease incidence at the higher of the two scales is shown to be an asymptotic function of incidence at the lower scale, the degree of aggregation at that scale, and the size of the sampling unit. For a random pattern, the relationship between incidence measured at two spatial scales does not depend on any unknown parameters. In that case, an equation for estimating an approximate variance of disease incidence at the lower of the two scales from incidence measurements made at the higher scale is derived for use in the context of sampling. It is further shown that the effect of aggregation of incidence at the lower of the two scales is to reduce the rate of increase of disease incidence at the higher scale.     

Sequential sampling for incidence of phomopsis leaf blight of strawberry

ABSTRACT Sequential sampling models for estimation and classification were developed for the incidence of strawberry leaflets infected by Phomopsis obscurans. Sampling protocols were based on a binary power law analysis of the spatial heterogeneity of Phomopsis leaf blight in commercial fields in Ohio. For sequential estimation, samples were collected until mean disease incidence could be estimated with a preselected coefficient of variation of the mean (C). For sequential classification, samples were collected until there was sufficient evidence to classify mean incidence as being below or above a threshold (p(t)) based on the sequential probability ratio test. Monte-Carlo simulations were used to determine the theoretical average sample number (ASN) and probability of classifying mean incidence as less than p(t) (operating characteristic) for any true value of incidence. Estimation and classification sampling models were both tested with bootstrap simulations of randomly selected data sets and validated by data sets from another year that were not utilized in developing the models. In general, achieved (or calculated) C after sequentially sampling for estimation was close to the preselected C of 0.2, and mean incidence was estimated with little bias. Achieving a C of 0.1 with less than 75 sampling units (the nominal value for many original data sets) was more problematical, especially with true incidence less than 0.2. ASN for classification was only 9 to 18 at disease incidence values near p(t), and approximately five or less at incidence values far from p(t). Correct classification decisions were made in over 88% of the validation data sets. Results indicated that it is possible to estimate Phomopsis leaf blight with high precision and with high correct classification probabilities.     

A survey of rice diseases in Bangladesh

Abstract

A survey conducted during 1979–81 in Bangladesh revealed 20 rice diseases, including two viral, two bacterial, 13 fungal, two nematode and one micronutrient deficiency problem. Of these diseases. 16 appeared as major during the period under report. The number of diseases were 17, 16 and 16 during the Boro. Aus and transplant Aman seasons, respectively, with 12 common in all three seasons. Thirteen diseases including bacterial blight, bacterial leaf streak, sheath blight, sheath rot, blast, brown spot, grain spot, stem rot and leaf scald were classified as major; and tungro, bakanae, cercospora leaf spot and zinc‐deficiency were classified as either major or minor, and were common to all regions. Diseases not common in all regions were stack burn, root knot, and ufra classified as major or minor, and false smut, seedling blight. Yellow dwarf and damping off which were always classified as minor. Diseases which were typical for Boro. Aus and transplant Aman seasons were seedling blight and damping off. Yellow dwarf, and false smut respectively. Aus the most humid and warmest season, and the coastal humid areas experienced more major diseases. Seasonal and regional differences in the disease incidence appeared related to agro‐climatic variations.     

Spatial Aspects of Light Leaf Spot (Pyrenopeziza brassicae) Epidemic Development on Winter Oilseed Rape (Brassica napus) in the United Kingdom

ABSTRACT In microplot experiments in 1998-99 and 1999-2000, the start of light leaf spot epidemics could be predicted from weather data, using empirical equations for Pyrenopeziza brassicae apothecial (ascospore) development, ascospore infection criteria, and the latent period of P. brassicae. The dates when P. brassicae sporulation was first observed fitted predictions and initial spread of light leaf spot from an inoculum source was mostly in the prevailing wind direction, with differences between the two growing seasons attributable to differences in wind patterns. Subsequent secondary spread of disease could be predicted using temperature and rainfall data, and observations fitted predicted dates. In both 1998-99 and 1999-2000, initial spatial patterns of observed disease in January were random, because data were not significantly different from a binomial distribution (P = 0.18). Analysis of spatial data from samples in February and March indicated aggregation, because data fit was significantly different from a binomial distribution (P 相似文献   

中国苹果病害发生与分布现状调查

本研究于2010-2012年在我国18个省(市、自治区)的1 100个苹果园采用隔行踏查法进行了实地调查。调查内容包括果园面积、品种名称、树龄结构以及各种病害发生情况。调查结果表明,3年间在我国苹果主产区共发现病害50种,其中包括新发现的2种病害:丝核菌叶枯病和炭疽菌叶枯病。通过分析确定了各种病害的严重度,明确了腐烂病、轮纹病、褐斑病和斑点落叶病4种主要病害及苹果锈病等8种中度发生病害的发生程度及区域分布,为各苹果主产省开展病害防控提供了理论依据。     

甘肃玉米主要病害发生动态调查

为了掌握甘肃玉米病害的发生动态,明确主要病害的流行趋势,采用随机抽查法调查了甘肃庆阳、平凉、天水、陇南、定西、武威和张掖7个市/地区的玉米病害类群。结果表明,普通锈病、红叶病和穗腐病普遍发生并较严重,在7个市/地区的平均病株率分别为81.6%、80.6%和77.3%;大斑病、纹枯病、交链孢叶斑病、茎腐病、小斑病、瘤黑粉病和鞘腐病局部发生较重,在7个市/地区平均病株率分别为83.3%、44.9%、29.1%、27.5%、25.6%、14.4%和8.3%,矮花叶病和丝黑穗病普遍发生但发病较轻,在7个市/地区病株率分别为3.1%和1.1%,但矮花叶病在旱作区平凉市依然严重,丝黑穗病在武威市和张掖市的玉米制种田发病率依然较高。调查表明,甘肃玉米叶部病害、穗腐病和茎腐病有加重趋势,今后应该加强多病害抗性品种选育和防治用化学药剂的筛选研究。     

Rice Diseases in Nigeria

Abstract

The two major fungal diseases of rice in Nigeria are rice blast (Pyricularia oryzae Cav.) and brown spot (Cochliobolus miyabeanus (Ito and Kuribayashi) Dreschler ex Dastur). The loss in grain yield attributable to these diseases ranges from 11.5–39.6% and 12–43% respectively, Mancozeb, blasticidin-S, fentin hydroxide, benomyl and edifenphos as foliar sprays effectively control rice blast in the laboratory and field. Brown spot is controlled by spraying with thiram, mancozeb or blasticidin-S. A more useful approach to the control of these diseases being adopted in Nigeria is the search for horizontally resistant varieties. Other fungal diseases of rice in Nigeria are the green smut (Ustilaginoidea virens (Cooke) Tak.), basal sheath rot (Rhizoctonia solani Kühn), sheath blight (Corticium sasakii (Shirai), Matsumoto.), leaf scald (Rhynchosporium oryzae Hashioka and Yokogi), narrow brown leaf spot (Cercospora oryzae Miyake) and bakanae disease, a foot rot caused by Fusarium moniliforme Sheldon. Two suspected cases of virus diseases have been reported; grassy stunt disease (transmitted by Nilaparvata lugens Stal.), and orange leaf disease (transmitted by Inazuma dorsalis (Motschulsky). No bacterial disease of rice has been found in Nigeria.     

黑龙江省马铃薯晚疫病菌交配型及对甲霜灵敏感性测定

马铃薯晚疫病(late blight)是由致病疫霉(Phytophthora infestans)引起的马铃薯生产中最具毁灭性的病害,明确晚疫病菌的交配型及对甲霜灵敏感性状况对制定马铃薯晚疫病防治策略具有重要意义。本研究对2011—2013年采自黑龙江省黑河、齐齐哈尔、绥化等马铃薯主产区的晚疫病菌菌株进行交配型及对甲霜灵敏感性测定,采用对峙培养法对153株晚疫病菌进行交配型检测,结果表明,A1交配型79株,占51.63%,A2交配型74株,占48.37%;采用菌落直径法对143株晚疫病菌进行甲霜灵敏感性测定,结果表明,83.92%表现高抗,8.39%表现中抗,7.69%表现敏感。     

防治玉米叶斑病高效药剂筛选及药剂减施增效技术

为有效防治玉米小斑病和弯孢叶斑病并减少化学农药使用量,本研究采用菌丝生长速率法从11种杀菌剂中选取抑菌效果较好的8种药剂进行田间小区药效试验。同时选取对两种叶部病害兼具防效的最佳药剂再与中量元素水溶肥、腐植酸、氨基寡糖素、芸苔素内酯等产品混配开展田间药效试验,确定该药剂田间施用浓度和增效组合。结果显示,各供试药剂对2种病菌菌丝生长具有不同的抑制作用,其中25%丙环唑EC、25%戊唑醇WP、40%氟硅唑EC、30%氟菌唑WP、12.5%烯唑醇WP在供试各浓度下对2种病菌抑制率均为100%,田间小区药效筛选测定中,25%戊唑醇WP防治效果最好,对玉米小斑病和弯孢叶斑病两种叶部病害防效分别为81.07%和72.22%。田间试验中,25%戊唑醇WP防治玉米小斑病和弯孢叶斑病的最佳施用浓度为2 000倍液,防效分别为59.48%和53.96%。在减量50%情况下防效有所下降,配施氨基寡糖素后,防效可提高37.40百分点和22.98百分点,与最佳施用浓度防效相当,达到了减药增效的作用。     

鸡骨草叶枯病调查及其病原鉴定

在广西鸡骨草种植基地,发现一种发生严重的叶枯病,植株自下部叶片开始枯黄,然后向上蔓延,严重时整株枯死。经田间调查、标本采集、病原菌分离、形态学鉴定及致病性测定,明确该病害由丝核菌属（Rhizoctonia）引起。该病害在田间的发病率为69%～88%,病情指数为17.4～34.6。     

Automated identification of sugar beet diseases using smartphones

Cercospora leaf spot (CLS) poses a high economic risk to sugar beet production due to its potential to greatly reduce yield and quality. For successful integrated management of CLS, rapid and accurate identification of the disease is essential. Diagnosis on the basis of typical visual symptoms is often compromised by the inability to differentiate CLS symptoms from similar symptoms caused by other foliar pathogens of varying significance, or from abiotic stress. An automated detection and classification of CLS and other leaf diseases, enabling a reliable basis for decisions in disease control, would be an alternative to visual as well as molecular and serological methods. This paper presents an algorithm based on a RGB‐image database captured with smartphone cameras for the identification of sugar beet leaf diseases. This tool combines image acquisition and segmentation on the smartphone and advanced image data processing on a server, based on texture features using colour, intensity and gradient values. The diseases are classified using a support vector machine with radial basis function kernel. The algorithm is suitable for binary‐class and multi‐class classification approaches, i.e. the separation between diseased and non‐diseased, and the differentiation among leaf diseases and non‐infected tissue. The classification accuracy for the differentiation of CLS, ramularia leaf spot, phoma leaf spot, beet rust and bacterial blight was 82%, better than that of sugar beet experts classifying diseases from images. However, the technology has not been tested by practitioners. This tool can be adapted to other crops and their diseases and may contribute to improved decision‐making in integrated disease control.     

Assessment of the impact of mid-season late blight infection on disease development and yield of potato variety Russet Norkotah in Maine

Development of late blight of potatoes caused by Phytophthora infestans (US 8 fungal genotype, A2 mating type) was monitored in two Russet Norkotah commercial fields at Fort Fairfield in 1996 and Duncan Farm in 1997. Experimental plots representing various disease treatments (low, moderate, high and random late blight severity levels) were established in two fields in 1996. In 1997, only low and high disease treatments were established. The application of fungicides for late blight control was conducted in both years. Late blight incidence and severity were assessed in each plot of each treatment. Components of late blight disease development, tuber blight incidence and tuber yields were determined from each plot. Progress of late blight disease was rapid in 1996 but not in 1997. During the 1996 cropping season, mean disease incidence and severity in the random disease treatment plots were 84 and 21% respectively within 10 days of disease detection. In 1997, low levels of late blight severity were detected in the field plots. Average numbers of late blight leaf and stem lesions on infected plant and fungal sporangia on the diseased leaf were not significantly affected by disease treatment. Late blight foliar severity significantly affected potato tuber yields. Lowest tuber yield was obtained in plots with high disease levels and highest yields were recorded in plots with low late blight severity in 1996. Late blight severity was significantly correlated with tuber yield but not with per cent tuber blight.     

外引玉米种质对3种玉米叶斑病的抗性鉴定与评价

2012-2013年,应用田间人工接种的方法对引进的165份国外玉米种质进行了玉米大斑病、灰斑病、弯孢菌叶斑病等3种病害同步抗性鉴定与评价,结果表明:引进的国外玉米种质对3种玉米叶斑病的抗性表现均存在差异,表现抗病的种质较少,大部分种质表现感病或高度感病;抗性种质均以中抗为主,表明国外玉米种质对3种叶斑病的抗病能力较低。筛选出一批单抗性种质和兼抗2种或3种叶斑病的多抗性种质37份,为抗病育种提供了重要基础材料。     

云南省3个海拔区域滇牡丹主要叶部病害发生动态分析

为了解云南省滇牡丹叶部病害的发生动态, 本研究开展了3个海拔区域滇牡丹主要叶部病害周年调查及病原真菌初步鉴定, 并探讨海拔高度、温度和降雨量对滇牡丹病害发生的影响。结果表明, 3个海拔区域滇牡丹主要叶部病害为黑斑病、红斑病和炭疽病, 病原菌分别为链格孢属Alternaria、枝孢属Cladosporium和刺盘孢属Colletotrichum的真菌。其中黑斑病和炭疽病在稗子乡(2 000 m)发病较重, 其次是梁王山(2 400 m)和香格里拉(3 400 m), 发病率和病情指数呈现随海拔升高逐渐下降的趋势。此外, 稗子乡的病害发生动态与月平均温度、降雨量的变化规律基本趋于一致, 且3种病害的发病程度与月平均温度、降雨量显著相关。综上所述, 低海拔且温湿度较大的区域滇牡丹叶部病害发生较重, 本研究为滇牡丹病害防治提供了参考依据。