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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.

In recent years, the convolution neural network has been the most widely used deep learning algorithm in the field of plant disease diagnosis and has performed well in classification. However, in practice, there are still some specific issues that have not been paid adequate attention to. For instance, the same pathogen may cause similar or different symptoms when infecting plant leaves, while the same pathogen may cause similar or disparate symptoms on different parts of the plant. Therefore, questions come up naturally: should the images showing different symptoms of the same disease be in one class or two separate classes in the image database? Also, how will the different classification methods affect the results of image recognition? In this study, taking rice leaf blast and neck blast caused by Magnaporthe oryzae, and rice sheath blight caused by Rhizoctonia solani as examples, three experiments were designed to explore how database configuration affects recognition accuracy in recognizing different symptoms of the same disease on the same plant part, similar symptoms of the same disease on different parts, and different symptoms on different parts. The results suggested that when the symptoms of the same disease were the same or similar, no matter whether they were on the same plant part or not, training combined classes of these images can get better performance than training them separately. When the difference between symptoms was obvious, the classification was relatively easy, and both separate training and combined training could achieve relatively high recognition accuracy. The results also, to a certain extent, indicated that the greater the number of images in the training data set, the higher the average classification accuracy.

The identities of Sclerotinia isolates obtained from chickpea plants showing stem and crown rot were determined using morphological characteristics, variations in group I introns, and internal transcribed spacer (ITS) sequences. Isolates could be separated into two groups based on growth rates at 22°C, fast growing (about 40 mm per day) versus slow growing (about 20 mm per day). All fast-growing isolates induced stronger color change of a pH-indicating medium than did slow-growing isolates at 22°C. The slow-growing isolates contained at least one group I intron in the nuclear small subunit rDNA, whereas all fast-growing isolates lacked group I introns in the same DNA region. ITS sequences of the slow-growing isolates were identical to sequences of Sclerotinia trifoliorum. Those of the fast-growing isolates were identical to sequences of S. sclerotiorum. Finally, the slow-growing isolates showed ascospore dimorphism, a definitive character of S. trifoliorum, whereas the fast-growing isolates showed no ascospore dimorphism. Isolates of both species were pathogenic on chickpea and caused symptoms similar to those observed in the field. This study not only associated the differences between S. sclerotiorum and S. trifoliorum in growth rates, group I introns, ITS sequences, and ascospore morphology, but also represented the first report that S. trifoliorum causes stem and crown rot of chickpea in North America.

In this study, spatial analyses were conducted at three different scales to better understand the epidemiology of rice blast, a major rice disease caused by Magnaporthe oryzae. At the regional scale, across the major rice production regions in China, rice blast incidence was monitored on 101 dates at 193 stations from 10 June to 10 September during 2009 to 2014, and surveyed in 143 fields in September 2016; at the county scale, three surveys were done covering one to five counties in 2015 to 2016; and, at the field scale, blast was evaluated in six fields in 2015 to 2016. Spatial cluster and hot spot analyses were conducted in the geographic information system on the geographical pattern of the disease at regional scale, and geostatistical analysis was performed at all three scales. Cluster and hot spot analyses revealed that high-disease areas were clustered in mountainous areas in China. Geostatistical analyses detected spatial dependence of blast incidence with influence ranges of 399 to 1,080 km at regional scale and 5 to 10 m at field scale but not at county scale. The spatial patterns at different scales might be determined by inherent properties of rice blast and environmental driving forces, and findings from this study provide helpful information to sampling and management of rice blast.

Concrete structure is widely used in civil engineering. Concrete cracking, a common and frequently occurring disease, is one of the main factors that cause impaired concrete structure durability. This paper analyzes the generation process and features of non-longitudinal concrete cracking. With on-site investigation of selected buildings in Ningbo, the paper discusses the main existing non-longitudinal cracks and their impact on the durability of concrete structure.

Condition assessment of cables has gained more attention for the bridge safety. The cable is under tensile load in service. The effect of tensile load for detecting broken wires on parallel wire cable based on guided waves is investigated. The sample cable with broken wires under several levels of tensile load is detected using guided waves based on the magnetostrictive effect. The amplitude of flaw echo increases monotonically with the increasing of tension. The results indicate that the tensile load brings benefit for detecting broken wires in the parallel wire cable.

Accelerated soil degradation with repeated application was suggested to be responsible for the lack of efficacy of commercial fungicides to control lettuce drop caused by Sclerotinia minor in the Salinas Valley in California. In 2000, a study was initiated in a field artificially infested with S. minor to evaluate the efficacy and degradation potential of four selected fungicides (i.e., Rovral, Botran, Switch, and Endura). Crisphead lettuce was direct-seeded twice a year (spring and fall season) from 2000 to 2002. Fungicides were applied at recommended label rates twice during each season. Disease incidence was evaluated in fungicide treatments and nontreated control plots weekly starting immediately after thinning until harvest, and areas under the disease progress curves (AUDPC) were compared between treatments from 2000 to 2002. Soil samples (0–15 cm) were collected at regular intervals during the spring and fall 2002 lettuce seasons, and analyzed for residual fungicide concentration. Disease progress and final disease incidence were significantly affected by the fungicide treatment, season, year and interactions among these factors (p

Three-dimensional (3-D) spacer fabric composite is a novel lightweight sandwich structure, the reinforcement of which is integrally woven with two facesheets connected by continuous fibers (named piles) in the core. Usually the 3-D spacer fabric composite without extra reinforcement is called mono-spacer fabric composite, which provides outstanding facesheet / core debonding resistance. However, its mechanical properties cannot meet the demand of structure application because of the thin facesheet and low load-bearing capacity of high piles. Hence, two reinforcement methods were developed by laminating additional weaves at the facesheet and filling foam materials in the core to strengthen the facesheet and piles, respectively. This paper aims to investigate the influences of reinforcement methods on the mechanical behaviors and damage modes of 3-D spacer fabric composites under flatwise compressive, shear, edgewise compressive and three-point bending loads, by comparing with mono-spacer fabric composites. The results indicate that additional weaves reinforcement can enhance edgewise compressive and flexural properties effectively. Foam filling is one of the best options to improve the flatwise compressive and shear properties, and especially, there are synergistic effects between piles and foam under flatwise compressive load. Besides, the failure modes of reinforced and mono-spacer fabric composites are different.

To better understand the genetic relationships between Verticillium dahliae isolates from lettuce and other phytopathogenic Verticillium spp. isolates from various hosts and geographic locations, the complete intergenic spacer (IGS) region of the nuclear ribosomal RNA gene (rDNA) and the β-tubulin gene were amplified and sequenced. The sequences of the complete IGS region and the β-tubulin gene were used alone and in combination to infer genetic relationships among different isolates of Verticillium with the maximum-likelihood distance method. Phylogenetic analyses set sequences into four distinct groups comprising isolates of V. albo-atrum, V. tricorpus, and V. dahliae from cruciferous and noncruciferous hosts. Within the four Verticillium groups, isolates of V. dahliae from cruciferous hosts displayed the closest affinity to V. dahliae from noncruciferous hosts. Isolates of V. dahliae from noncruciferous hosts could be further divided into four subgroups based on sequence similarities within the IGS region. Cross-pathogenicity tests demonstrated that most Verticillium isolates were as virulent on other hosts as on their hosts of origin. A phenogram based on the cross pathogenicity of individual isolates resembled those derived from the IGS and β-tubulin sequence comparisons. On the basis of the data presented, the potential origin of some isolates of V. dahliae pathogenic on lettuce is proposed.

Downy mildew, caused by Sclerospora graminicola, is a major pathogen of pearl millet (Pennisetum glaucum) in Asia and Africa. So development of resistant cultivars has been a major goal of national and international breeding programs. Stability of resistance in pearl millet lines developed at ICRISAT was studied through a collaborative International Pearl Millet Downy Mildew Virulence Nursery (IPMDMVN). The reactions to downy mildew of 11 pearl millet lines at 17 locations in India, Burkina Faso, Mali, Niger, and Nigeria from 1995 to 1999 were recorded. Disease incidence varied significantly among lines, locations, and years. The tested pearl millet lines exhibited significant differential resistance. Resistance in lines IP 18292, IP 18293, 700651 and P 310-17 was most stable regardless of the location or season. Analysis of the variation in resistance also suggested that the resistance in IP 18292 and IP 18293 was variable and depended on the locations and years, while the resistance in 700651 and P 310-17 was highly stable across locations and over years. The latter two lines could prove to be the most valuable sources of downy mildew resistance. The results also revealed significant differences in S. graminicola populations at different locations, with the highest disease at Bagauda (Nigeria) and Durgapura (India) and lowest from Coimbatore and Aurangabad (India). Based on the reaction of the 11 pearl millet lines, the 17 S. graminicola populations were grouped into six putative pathotypes (undefined populations closer to races).