Development of Two Early Forecasting Models for Predicting Incidence of Rice Panicle Blast in China.

Early forecasting of rice panicle blast is critical to the management of rice blast. To develop early forecasting models for rice panicle blast, the relationship between the seasonal maximum incidence of rice panicle blast (PBx) and the PBx in the preceding crop, weather conditions, location, and acreage of susceptible varieties was analyzed. Results revealed that PBx in the preceding crop, acreage of the susceptible varieties in class (SVC), altitude, weather conditions 120 to 180 days before the PBx date (dbPBx) and 30 to 90 dbPBx were significantly correlated with the PBx. Subsequently, a logistic model and a two-step hurdle model were developed to predict rice panicle blast. The logistic model was developed to predict whether the PBx was 0 or not based on the preceding PBx, altitude, acreage of susceptible varieties, the longest stretch of days with soil temperatures between 16 and 24°C for the period 120 to 150 dbPBx, and the longest stretch of rainy days in the period 120 to 180 dbPBx. The hurdle model predicted if the PBx was greater than 0 at the first step, and if the prediction was greater than 0, then a regression model was developed for predicting PBx based on the preceding PBx, SVC, altitude, and weather data 180 to 30 dbPBx. Validation with the test datasets showed that the logistic model could correctly predict whether PBx was 0 at a mean test accuracy of 78.39% and that the absolute prediction error of PBx by the two-step hurdle model was smaller than 6.16% for 90% of the records. The model developed in this study will be helpful in management decisions for rice growers and policy makers and offer a useful basis for further studies on the epidemiology and forecasting of rice panicle blast.

A Recognition Method for Rice Plant Diseases and Pests Video Detection Based on Deep Convolutional Neural Network.

Increasing grain production is essential to those areas where food is scarce. Increasing grain production by controlling crop diseases and pests in time should be effective. To construct video detection system for plant diseases and pests, and to build a real-time crop diseases and pests video detection system in the future, a deep learning-based video detection architecture with a custom backbone was proposed for detecting plant diseases and pests in videos. We first transformed the video into still frame, then sent the frame to the still-image detector for detection, and finally synthesized the frames into video. In the still-image detector, we used faster-RCNN as the framework. We used image-training models to detect relatively blurry videos. Additionally, a set of video-based evaluation metrics based on a machine learning classifier was proposed, which reflected the quality of video detection effectively in the experiments. Experiments showed that our system with the custom backbone was more suitable for detection of the untrained rice videos than VGG16, ResNet-50, ResNet-101 backbone system and YOLOv3 with our experimental environment.

Multiscale analyses on a massive immigration process of Sogatella furcifera (Horváth) in south-central China: influences of synoptic-scale meteorological conditions and topography.

Mass landings of migrating white-backed planthopper, Sogatella furcifera (Horváth), can lead to severe outbreaks that cause heavy losses for rice production in East Asia. South-central China is the main infestation area on the annual migration loop of S. furcifera between the northern Indo-China Peninsula and mainland China; however, rice planthopper species are not able to survive in this region over winter. In this study, a trajectory analysis of movements from population source areas and a spatiotemporal dynamic analysis of mesoscale and synoptic weather conditions from 7 to 10 May 2012 were conducted using the weather research and forecasting (WRF) model to identify source areas of immigrants and determine how weather and topographic terrain influence insect landing. A sensitivity experiment was conducted with reduced topography using the WRF model to explain the associations among rainfall, topography, and light-trap catches of S. furcifera. The trajectory modeling results suggest that the source areas of S. furcifera immigrants into south-central China from 8 to 10 May were mainly southern Guangxi, northern Vietnam, and north-central Vietnam. The appearance of enormous catches of immigrant S. furcifera coincided with a period of rainstorms. The formation of transporting southerly winds was strongly associated with the topographic terrain. Additionally, the rainfall distribution and intensity over south-central China significantly decreased when topography was reduced in the model and were directly affected by wind circulation, which was associated with mountainous terrain that caused strong convection. This study indicates that migrating populations of S. furcifera were carried by the southwesterly low-level jets and that topographically induced convergent winds, precipitation, low temperatures, and wind shear acted as key factors that led to massive landings.

Distribution and genetic diversity of Southern rice black-streaked dwarf virus in China.

BACKGROUND: Rice and maize dwarf diseases caused by the newly introduced Southern rice black-streaked dwarf virus (SRBSDV) have led to severe economic losses in South China in recent years. The distribution and diversity of SRBSDV have not been investigated in the main rice and maize growing areas in China. In this study, the distribution of SRBSDV in China was determined by using reverse transcription-polymerase chain reaction (RT-PCR). RESULTS: Between 2009 and 2010, 2404 plant samples (2294 rice, 110 maize samples, and more than 300 cultivars) with dwarf symptoms were collected from fields in 194 counties of 17 provinces in China and SRBSDV was detected. The results indicated that 1545 (64.27%) of samples (both rice and maize) were infected with SRBSDV. SRBSDV was detected widely in Hainan, Guangdong, Guangxi, Yunnan, Guizhou, Chongqing, Fujian, Jiangxi, Hunan, Hubei, Anhui, Jiangsu, and Zhejiang provinces, which suggests SRBSDV is an important pathogen causing rice dwarfing diseases in South China. Phylogenetic analysis of 15 representative virus isolates revealed that SRBSDV isolates in China had high levels of nucleotide and amino acid sequence identities (>97.8%). CONCLUSIONS: SRBSDV spreads naturally in Yangtze River basin and south region, the location of the major rice production areas. In comparison, the virus rarely spreads north of Yangtze River in North China. Distribution of SRBSDV is consistent with the migrating and existing ranges of its vector WBPH, suggesting that SRBSDV might be introduced into South China along with the migration of viruliferous WBPH.

Genomic analysis, trajectory tracking, and field surveys reveal sources and long-distance dispersal routes of wheat stripe rust pathogen in China.

Identifying sources of phytopathogen inoculum and determining their contributions to disease outbreaks are essential for predicting disease development and establishing control strategies. Puccinia striiformis f. sp. tritici (Pst), the causal agent of wheat stripe rust, is an airborne fungal pathogen with rapid virulence variation that threatens wheat production through its long-distance migration. Because of wide variation in geographic features, climatic conditions, and wheat production systems, Pst sources and related dispersal routes in China are largely unclear. In the present study, we performed genomic analyses of 154 Pst isolates from all major wheat-growing regions in China to determine Pst population structure and diversity. Through trajectory tracking, historical migration studies, genetic introgression analyses, and field surveys, we investigated Pst sources and their contributions to wheat stripe rust epidemics. We identified Longnan, the Himalayan region, and the Guizhou Plateau, which contain the highest population genetic diversities, as the Pst sources in China. Pst from Longnan disseminates mainly to eastern Liupan Mountain, the Sichuan Basin, and eastern Qinghai; that from the Himalayan region spreads mainly to the Sichuan Basin and eastern Qinghai; and that from the Guizhou Plateau migrates mainly to the Sichuan Basin and the Central Plain. These findings improve our current understanding of wheat stripe rust epidemics in China and emphasize the need for managing stripe rust on a national scale.

The Early Northward Migration of the White-Backed Planthopper (Sogatella furcifera) is Often Hindered by Heavy Precipitation in Southern China during the Preflood Season in May and June.

Seasonal weather systems that establish prevailing winds and seasonal rainfall on a large scale largely determine insect migration patterns, especially for micro-insects with completely windborne migration. Recent studies indicated that the summer migration of the brown planthopper (BPH, Nilaparvata lugens) in eastern China is related to the strength and position of the Western Pacific Subtropical High-Pressure (WPSH) system and its associated wind and rainfall patterns. Compared with the BPH, the white-backed planthopper (WBPH, Sogatella furcifera) has a similar diet, analogous body size, and strong long-distance migration ability. Thus, the migration pattern for the WBPH can be speculated to be similar to that of the BPH. However, the migration pattern of the WBPH and how this pattern relates to climatic conditions have scarcely been described. Based on almost three decades of data (1977-2003), it was suggested that the WBPH in southern China (south of approximately 27° N) migrates into the middle and lower reaches of the Yangtze River after the abrupt movements of the WPSH in mid-June, similar to the BPH. By contrast, the emigration of the WBPH in southern China begins in late May. Further analysis indicated that the migration of the WBPH in late May and early June was short or unsuccessful due to heavy precipitation during the preflood season in southern China from late May to middle June. The results herein demonstrate the differences in migration patterns between two rice planthoppers in the eastern Asia migration arena. We also provide new information that could assist with forecasting outbreaks and implementing control measures against these migratory pests.

Long-term seasonal forecasting of a major migrant insect pest: the brown planthopper in the Lower Yangtze River Valley.

Rice planthoppers and associated virus diseases have become the most important pests threatening food security in China and other Asian countries, incurring costs of hundreds of millions of US dollars annually in rice losses, and in expensive, environmentally harmful, and often futile control efforts. The most economically damaging species, the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae), cannot overwinter in temperate East Asia, and infestations there are initiated by several waves of windborne spring or summer migrants originating from tropical areas in Indochina. The interaction of these waves of migrants and synoptic weather patterns, driven by the semi-permanent western Pacific subtropical high-pressure (WPSH) system, is of critical importance in forecasting the timing and intensity of immigration events and determining the seriousness of subsequent planthopper build-up in the rice crop. We analysed a 26-year data set from a standardised light trap network in Southern China, showing that planthopper aerial transport and concentration processes are associated with the characteristics (strength and position) of the WPSH in the year concerned. Then, using N. lugens abundance in source areas and indices of WPSH intensity or related sea surface temperature anomalies, we developed a model to predict planthopper numbers immigrating into the key rice-growing area of the Lower Yangtze Valley. We also demonstrate that these WPSH-related climatic indices combined with early-season planthopper catches can be used to forecast, several months in advance, the severity of that season's N. lugens infestations (the correlation between model predictions and outcomes was 0.59), thus allowing time for effective control measures to be implemented.

Minor Components Play an Important Role in Interspecific Recognition of Insects: A Basis to Pheromone Based Electronic Monitoring Tools for Rice Pests.

Several lepidopteran species share the same pheromone blend consisting of (Z)-11-hexadecenal (Z11-16:Ald) and (Z)-9-hexadecenal (Z9-16:Ald) at different ratios and active doses. In rice pest Chilo suppressalis, (Z)-11-hexadecenol, (Z11-16:OH) and octadecanal (18:Ald) were identified as minor components in the pheromone gland of female moths, and these components were previously not considered as part of the sex pheromone of C. suppressalis. Z11-16:Ald, Z9-16:Ald and (Z)-13-octadecenal (Z13-18:Ald) frequently trapped other lepidopteran species, such as rice pests Scirpophaga incertulas and Mythimna separate, corn and vegetable pests Helicoverpa armigera in the field, suggesting a lack of specificity in the pheromone blend. Our data showed that the minor component Z11-16:OH did not have a synergistic effect on the attractiveness of the blend to C. suppressalis; however, pheromone mixtures containing Z11-16:OH failed in trapping male H. armigera moths. We confirmed the identity and specificity of the C. suppressalis sex pheromone and demonstrated that Z11-16:OH plays a key role in the reproductive isolation of C. suppressalis, M. separata, and H. armigera moths, and a similar role of Z9-18:Ald in that of S. incertulas and C. suppressalis. This phenomenon could be more widely applicable to interspecific interactions in the pheromone communication between insects, which is crucial to developing the electronic automatic counting device for automatically monitoring the pest population by pheromone trapping based on its species specificity.

Brown planthopper Nilaparvata lugens was concentrated at the rear of the typhoon Soudelor in Eastern China in August 2015.

Sometimes, extreme weather is vital for the population survival of migratory insects by causing sudden population collapse or outbreak. Several studies have shown that rice planthopper migration was significantly influenced by typhoons in eastern Asia. Most typhoons occur in the summer, especially in August. In August, brown planthopper Nilaparvata lugens (Stål) migrates northward or southward depending on wind direction, and thus typhoons can potentially influence its migration process and population distribution. However, this has not yet been studied. This paper reported a case study on the effects of Typhoon Soudelor on the summer migration of N. lugens in eastern China in 2015. The migration pathways of N. lugens were reconstructed for the period under the influence of a typhoon by calculating the trajectories and migration events in eight counties of the Yangtze River Valley region with ancillary information. Trajectory modelling showed that most migrants took short distance migrations (less than 200 km) under the influence of the Typhoon Soudelor. Numerous N. lugens migrants were concentrated and deposited at the rear of the typhoon during the last 5 days of Typhoon Soudelor on August 9-13 due to horizontal convergence, and this led to an outbreak population. These results indicated that the N. lugens population was redistributed by the typhoon in the summer and that the population dynamics at the rear of a typhoon should be kept under close surveillance. This study provided insight into migratory organisms adapting to atmospheric features.

The Influence of Sogatella furcifera (Hemiptera: Delphacidae) Migratory Events on the Southern Rice Black-Streaked Dwarf Virus Epidemics.

Southern rice black-streaked dwarf virus (SRBSDV) caused serious rice losses. After the first outbreak in 2009 in northern Vietnam and southern China, the virus ravaged crops again on enormous scales in 2010, but infections have decreased sharply since 2011. We presumed that the sudden epidemics and fadeout of SRBSDV would be closely related to the migratory events of the insect vector, Sogatella furcifera. This study sought the source area of SRBSDV using the trajectory analysis method, and revealed the relationship between SRBSDV dynamics and migration of S. furcifera populations via an in-depth analysis of meteorological background of S. furcifera migration fields. The results showed that Northern Vietnam was the direct virus source area of the SRBSDV infection in China, and South Central Coast of Vietnam was the original source area of SRBSDV. Southwesterly winds were prevalent in spring of 2010 and carried large numbers of viruliferous S. furcifera to China from northern Vietnam. This infestation of S. furcifera was the direct cause of the SRBSDV outbreak in China in 2010. In 2011, the winter-spring temperatures were abnormally low and southeasterly and easterly winds dominated; therefore, the number of viruliferous S. furcifera that entered China was small, and consequently, the occurrence area of SRBSDV was rapidly reduced. The return of viruliferous S. furcifera to South Central Coast of Vietnam was an important factor that affected the occurrence scale of SRBSDV in the following year.

Outbreaks of the brown planthopper Nilaparvata lugens (Stål) in the Yangtze River Delta: immigration or local reproduction?

An effective control strategy for migratory pests is difficult to implement because the cause of infestation (i.e., immigration or local reproduction) is often not established. In particular, the outbreak mechanisms of the brown planthopper, Nilaparvata lugens (Stål), an insect causing massive losses in rice fields in the Yangtze River Delta in China, are frequently unclear. Field surveys of N. lugens were performed in Jiangsu and Zhejiang Provinces in 2008 to 2010 and related historical data from 2003 onwards were collected and analyzed to clarify the cause of these infestations. Results showed that outbreaks of N. lugens in the Yangtze River Delta were mostly associated with an extremely high increase in population. Thus, reproduction rather than immigration from distant sources were the cause of the infestations. Although mass migration occurred late in the season (late August and early September), the source areas of N. lugens catches in the Yangtze River Delta were mainly located in nearby areas, including the Yangtze River Delta itself, Anhui and northern Jiangxi Provinces. These regions collectively form the lower-middle reaches of the Yangtze River, and the late migration can thus be considered as an internal bioflow within one population.

The influence of Typhoon Khanun on the return migration of Nilaparvata lugens (Stål) in eastern China.

Migratory insects adapt to and exploit the atmospheric environment to complete their migration and maintain their population. However, little is known about the mechanism of insect migration under the influence of extreme weather conditions such as typhoons. A case study was conducted to investigate the effect of typhoon Khanun, which made landfall in the eastern China in Sept. 2005, on the migration of brown planthopper, Nilaparvata lugens (Stål). The migration pathways of N. lugens were reconstructed for the period under the influence of the typhoon by calculating trajectories using the MM5, a mesoscale numerical weather prediction model, and migration events were examined in 7 counties of the Yangtze River Delta region with ancillary information. The light trap catches and field observations indicated that the migration peak of N. lugens coincided with the period when the typhoon made landfall in this region. The trajectory analyses revealed that most emigrations from this region during this period were hampered or ended in short distances. The sources of the light-trap catches were mainly located the nearby regions of each station (i.e. mostly less than 100 km away, with a few exceeding 200 km but all less than 300 km). This disrupted emigration was very different from the usual N. lugens migration which would bring them to Hunan, Jiangxi, and southern Anhui from this region at this time of year. This study revealed that the return migration of N. lugens was suppressed by the typhoon Khanun, leading to populations remaining high in the Yangtze River Delta and exacerbating later outbreaks.