Spatial and Temporal Analysis of Squash vein yellowing virus Infections in Watermelon

Temporal Progress and Spatial Patterns of Northern Corn Leaf Blight in Corn Fields in China

Northern corn leaf blight (NCLB), caused by Exserohilum turcicum, is a devastating disease of corn in China. To enhance our understanding of NCLB epidemiology, the temporal progress and spatial patterns of NCLB were investigated. A susceptible corn cultivar, Xianyu 335, was planted in a field in Beijing in 2016 and 2017. Leaf lesions of NCLB on each plant were counted twice a week during the growing seasons. In addition, temporal disease progress was monitored for 8 weeks in three commercial corn fields in each of Yanqing, Miyun, Daxing, and Haidian Districts of Beijing in 2017, and the spatial patterns of diseased plants and NCLB lesion counts per plant were assessed in three commercial corn fields with moderate to high NCLB incidence in Yanqing District. The results demonstrated that a logistic model was the most appropriate to describe the temporal progress of NCLB incidence. The initial disease incidence was the key factor affecting disease epidemics under various conditions in the four districts of Beijing during the study. The higher the initial incidence of NCLB, the higher the final incidence. Thus, the earlier in the season NCLB incidence attained 1%, the higher was the final disease incidence. Greater than 1.0 variance-to-mean ratios suggested that the leaf lesions of NCLB tended to be aggregated on a plant. According to results from join-counts, variance of moving window averages, and semivariogram analysis, diseased corn plants and lesion numbers on each plant were aggregated in the field. The clustered pattern of NCLB lesions and infected plants suggested that conidia produced locally on diseased plants were important for disease spread within the field. The aggregated pattern of diseased plants suggested that plants should be sampled from more sites in a field to accurately estimate incidence of NCLB.

Multiple Stressors in Vegetable Production: Insights for Trait-Based Crop Improvement in Cucurbits

Vegetable production is a key determinant of contribution from the agricultural sector toward national Gross Domestic Product in a country like India, the second largest producer of fresh vegetables in the world. This calls for a careful scrutiny of the threats to vegetable farming in the event of climate extremes, environmental degradation and incidence of plant pests/diseases. Cucurbits are a vast group of vegetables grown almost throughout the world, which contribute to the daily diet on a global scale. Increasing food supply to cater to the ever-increasing world population, calls for intensive, off-season and year-round cultivation of cucurbits. Current situation predisposes these crops to a multitude of stressors, often simultaneously, under field conditions. This scenario warrants a systematic understanding of the different stress specific traits/mechanisms/pathways and their crosstalk that have been examined in cucurbits and identification of gaps and formulation of perspectives on prospective research directions. The careful dissection of plant responses under specific production environments will help in trait identification for genotype selection, germplasm screens to identify superior donors or for direct genetic manipulation by modern tools for crop improvement. Cucurbits exhibit a wide range of acclimatory responses to both biotic and abiotic stresses, among which a few like morphological characters like waxiness of cuticle; primary and secondary metabolic adjustments; membrane thermostability, osmoregulation and, protein and reactive oxygen species homeostasis and turnover contributing to cellular tolerance, appear to be common and involved in cross talk under combinatorial stress exposures. This is assumed to have profound influence in triggering system level acclimation responses that safeguard growth and metabolism. The possible strategies attempted such as grafting initiatives, molecular breeding, novel genetic manipulation avenues like gene editing and ameliorative stress mitigation approaches, have paved way to unravel the prospects for combined stress tolerance. The advent of next generation sequencing technologies and big data management of the omics output generated have added to the mettle of such emanated concepts and ideas. In this review, we attempt to compile the progress made in deciphering the biotic and abiotic stress responses of cucurbits and their associated traits, both individually and in combination.

Spatial and Temporal Physiognomies of Whitefly and Tomato Yellow Leaf Curl Virus Epidemics in Southwestern Florida Tomato Fields

Epidemics of tomato yellow leaf curl virus (TYLCV; species Tomato yellow leaf curl begomovirus) have been problematic to tomato production in the southeastern United States since the first detection of the virus in Florida in the late 1990s. Current strategies for management focus on farm-centric tactics that have had limited success for controlling either TYLCV or its whitefly vector. Areawide pest management (AWPM)-loosely defined as a coordinated effort to implement management strategies on a regional scale-may be a viable management alternative. A prerequisite for development of an AWPM program is an understanding of the spatial and temporal dynamics of the target pathogen and pest populations. The objective of this study was to characterize populations of whitefly and TYLCV in commercial tomato production fields in southwestern Florida and utilize this information to develop predictors of whitefly density and TYLCV disease incidence as a function of environmental and geographical factors. Scouting reports were submitted by cooperating growers located across approximately 20,000 acres in southwestern Florida from 2006 to 2012. Daily weather data were obtained from several local weather stations. Moran's I was used to assess spatial relationships and polynomial distributed lag regression was used to determine the relationship between weather variables, whitefly, and TYLCV. Analyses showed that the incidence of TYLCV increased proportionally with mean whitefly density as the season progressed. Nearest-neighbor analyses showed a strong linear relationship between the logarithms of whitefly densities in neighboring fields. A similar relationship was found with TYLCV incidences. Correlograms based on Moran's I showed that these relationships extended beyond neighboring fields and out to approximately 2.5 km for TYLCV and up to 5 km for whitefly, and that values of I were generally higher during the latter half of the production season for TYLCV. Weather was better at predicting whitefly density than at predicting TYLCV incidence. Whitefly density was best predicted by the number of days with an average temperature between 16 and 24°C (T16to24), relative humidity (RH) over the previous 31 days, and vapor pressure deficit over the last 8 days. TYLCV incidence was best predicted by T16to24, RH, and maximum wind speed over the previous 31 days. Results of this study helped to identify the extent to which populations of whitefly and TYLCV exist over the agricultural landscape of southwestern Florida, and the environmental conditions that favor epidemic growth. This information was used to propose an approach to AWPM for timing control measures for managing TYLCV epidemics.

Citrullus ecirrhosus: Wild Source of Resistance Against Bemisia tabaci (Hemiptera: Aleyrodidae) for Cultivated Watermelon

Members of the highly polyphagous Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) species complex cause major crop damage by feeding and by transmitting plant viruses. The Middle East-Asia Minor 1 (MEAM1) of the B. tabaci complex is by far the most problematic whitefly affecting crops including cultivated watermelon (Citrullus lanatus; Cucurbitaceae: Cucurbitales). Watermelon cultivars share a narrow genetic base and are highly susceptible to whiteflies. We studied the potential of C. ecirrhosus, a perennial desert species that can be hybridized with C. lanatus, as a source of whitefly resistance for cultivated watermelon. The results of this study indicate that C. ecirrhosus offers resistance (although not total) against the MEAM1 B. tabaci based on, at least, antibiosis and antixenosis. Whitefly performance concerning developmental survival, body size attainment, and nonpreference were suppressed on C. ecirrhosus compared with the watermelon cultivar 'Sugar Baby'. Also, our olfactometer results indicated that the adults were less attracted to leaf volatiles of C. ecirrhosus. Although there is a pungent odor associated with the leaves of C. ecirrhosus, the leaf volatiles had no toxic effect on adult whitefly survival as compared with cultivated watermelon. We also demonstrated that plants of C. ecirrhosus can be clonally propagated from vine cuttings of the parent plant. Using traditional breeding procedures, C. ecirrhosus was hybridized with C. lanatus and viable F1 and F2 seeds were produced. This is the first report of pest resistance in C. ecirrhosus. This wild species offers a source of resistance against whiteflies for the improvement of cultivated watermelon.

Twenty-Five Years of the Binary Power Law for Characterizing Heterogeneity of Disease Incidence

Spatial pattern, an important epidemiological property of plant diseases, can be quantified at different scales using a range of methods. The spatial heterogeneity (or overdispersion) of disease incidence among sampling units is an especially important measure of small-scale pattern. As an alternative to Taylor's power law for the heterogeneity of counts with no upper bound, the binary power law (BPL) was proposed in 1992 as a model to represent the heterogeneity of disease incidence (number of plant units diseased out of n observed in each sampling unit, or the proportion diseased in each sampling unit). With the BPL, the log of the observed variance is a linear function of the log of the variance for a binomial (i.e., random) distribution. Over the last quarter century, the BPL has contributed to both theory and multiple applications in the study of heterogeneity of disease incidence. In this article, we discuss properties of the BPL and use it to develop a general conceptualization of the dynamics of spatial heterogeneity in epidemics; review the use of the BPL in empirical and theoretical studies; present a synthesis of parameter estimates from over 200 published BPL analyses from a wide range of diseases and crops; discuss model fitting methods, and applications in sampling, data analysis, and prediction; and make recommendations on reporting results to improve interpretation. In a review of the literature, the BPL provided a very good fit to heterogeneity data in most publications. Eighty percent of estimated slope (b) values from field studies were between 1.06 and 1.51, with b positively correlated with the BPL intercept parameter. Stochastic simulations show that the BPL is generally consistent with spatiotemporal epidemiological processes and holds whenever there is a positive correlation of disease status of individuals composing sampling units.