Heilongjiang Province Of China Research Articles

Baseline Sensitivity and Toxicity Mechanisms of Prochloraz to Alternaria alternata Strains Associated with Maize Leaf Blight in Heilongjiang Province in China.

Alternaria species are fungal pathogens that can infect maize, causing leaf blight disease and significant economic losses. This study aimed to determine the baseline sensitivity to prochloraz of A. alternata isolates obtained from diseased maize leaves collected from Heilongjiang Province by assessing the half-maximal effective concentration (EC50) values. The EC50 values of prochloraz ranged from 0.0550 to 2.3258 μg/ml, with an average of 0.9995 ± 0.5192 μg/ml. At EC50 (1.2495 μg/ml) and 2EC50 (2.4990 μg/ml), prochloraz increased the number of mycelial offshoots, disrupted the cell membrane integrity of conidia and mycelia, and resulted in a reduced ergosterol content in the mycelia. Prochloraz significantly affected the mycelial cell membrane permeability and increased the malondialdehyde content and superoxide dismutase activity. No cross-resistance was detected between prochloraz and other fungicides. These data demonstrate that prochloraz is a promising fungicide for managing maize leaf blight caused by A. alternata and provide novel insights into understanding the mechanism of prochloraz toxicity against A. alternata isolates.

Hydrological Connectivity Response of Typical Soil and Water Conservation Measures Based on SIMulated Water Erosion Model: A Case Study of Tongshuang Watershed in the Black Soil Region of Northeast China

The black soil region of Northeast China is the largest commercial grain production base in China, accounting for about 25% of the total in China. In this region, the water erosion is prominent, which seriously threatens China’s food security. It is of great significance to effectively identify the erosion-prone points for the prevention and control of soil erosion on the slope of the black soil region in Northeast China. This article takes the Tongshuang small watershed (Heilongjiang Province in China) as an example, which is dominated by hilly landforms with mainly black soil and terraces planted with corn and soybeans. Based on the 2.5 cm resolution Digital Elevation Model (DEM) reconstructed by unmanned aerial vehicles (UAVs), we explore the optimal resolution for hydrological simulation research on sloping farmland in the black soil region of Northeast China and explore the critical water depth at which erosion damage occurs in ridges on this basis. The results show that the following: (1) Compared with the 2 m resolution DEM, the interpretation accuracy of field roads, wasteland, damaged points, ridges and cultivated land at the 0.2 m resolution is increased by 4.55–27.94%, which is the best resolution in the study region. (2) When the water depth is between 0.335 and 0.359 m, there is a potential erosion risk of ridges. When the average water depth per unit length is between 0.0040 and 0.0045, the ridge is in the critical range for its breaking, and when the average water depth per unit length is less than the critical range, ridge erosion damage occurs. (3) When local erosion damage occurs, the connectivity will change abruptly, and the remarkable change in the index of connectivity (IC) can provide a reference for predicting erosion damage.

The Prevalence of Tick-Borne Encephalitis Virus Infection Among Humans in Heilongjiang Province of China in 2020-2023.

Tick-borne encephalitis (TBE) is a serious and acute central nervous system infection caused by the tick-borne encephalitis virus (TBEV). In recent years, TBE has emerged as a growing public health threat, with cases reported across Europe, the Russian Far East, Japan and China. This study aims to assess the prevalence of TBEV infection and examine behaviours associated with an increased risk of infection among individuals who visited the Heilongjiang Red Cross Sengong General Hospital due to tick bites from 2020 to 2023. We collected blood samples and administered survey questionnaires from tick-bitten people. A total of 457 samples were screened using Nested PCR, and the detected TBEV prevalence rate was 29.54% (135/457). The symptoms of redness and swelling at the site of tick bite (42.57%), fever (28.71%) and headache (10.89%) were identified in the TBEV-positive individuals when they visited the hospital by the physician. Phylogenetic analysis of the partial E gene of TBEV revealed that the predominant strains in the region are highly virulent Far Eastern subtype. However, they do not cluster with the three established evolutionary clades of the Far Eastern type. Questionnaires data analysis identified age and first tick bite as important factors associated with TBEV infection. This study provides basic information on the epidemiology of TBEV in Heilongjiang Province in recent years and identifies that the most related risk factor of infecting TBEV is tick exposure. Further research is needed to develop effective prevention and control measures.

Does Out-Migration Really Affect Forestry Ecological Security? An Empirical Case Study Based on Heilongjiang Province, China

In the new era, coordinating the relationship between population flow and forestry ecological security has become an important challenge. In this study, we take Heilongjiang Province in China as an example, and through the combination of macro data and micro in-depth interviews, we explore whether population mobility really affects the intrinsic mechanism of forestry ecological security from the perspective of population exodus from forest areas. Based on the DPSIR model, we constructed a forestry ecological security evaluation index system, used the TOPSIS multi-objective decision analysis method to quantify the forestry ecological security status from 2000 to 2022, and utilized the impulse response function of the VAR model to explore the dynamic response relationship between population outflow and forestry ecological security. The results of this study show that, firstly, the comprehensive index of forestry ecological security level in Heilongjiang Province exhibits a fluctuating upward trend from 2000 to 2022. Second, forestry ecological security has a lagged effect on population outflow, and population outflow has almost no effect on forestry ecological security at present. Third, while the population outflow of Luobei County reduces the interference of human activities on the natural environment, it also brings about the pressures of insufficient forestry ecological resource management and forestry personnel. The Dongfanghong Forestry Bureau has effectively improved the efficiency of ecological construction and ecological security through the introduction of digitalized and intelligent equipment, which has effectively compensated for the negative impact of population outflow on the reduction in ecological management personnel. These findings will help realize the coordinated development of population, economy and society, and ecology.

조선족 학교 학생들의 이중 언어 태도 조사 연구

By examining the complex aspects of language use and attitudes among Korean-Chinese students living in Heilongjiang Province in China, this study aims to analyze the bilingual patterns of Korean-Chinese students from various angles and provide an in-depth understanding of their language usage patterns, attitudes toward language, and how bilingual skills are formed and developed in socio-cultural contexts. In this paper, based on the national public language supply policy at Heilongjiang Korean-Chinese School, a field survey and survey were conducted on students from Heilongjiang Province Korean-Chinese School to accurately grasp the status and attitude of bilingualism in Chinese and Korean. For the conduct of the study, first of all, the survey method and the subject of the survey were confirmed as students of 32 Korean-Chinese schools in Heilongjiang Province. Next, the pattern of bilingualism in Korean and Chinese was analyzed through a survey on language attitude, language status cause, language and character use, and language relationship. Next, the problems of bilingualism were confronted, and a strategy for optimizing bilingualism according to the cause was devised. The results of the survey showed that Korean-Chinese school students were deeply interested in Chinese and Chinese culture. In other words, it was premised that they should be able to accurately recognize the superiority of China's bilingual policy and speak both Korean and standard Chinese, which are the native languages of the Korean people, but it showed the reality that the Korean language ability was weakening day by day compared to Chinese. Therefore, in this paper, the optimization strategies for bilingualism were divided into five categories: language dissemination and education programs, socio-cultural environment encouraging language use, the development of bilingual education programs, home and community support for language use, and policy support for language preservation. Therefore, the Heilongjiang provincial government, schools, and parents should set up an environment where Korean language education can develop soundly through policies and measures to promote full promotion and distribution by developing Korean and Chinese in a balanced manner.

Integrating Optical and SAR Time Series Images for Unsupervised Domain Adaptive Crop Mapping

Accurate crop mapping is crucial for ensuring food security. Recently, many studies have developed diverse crop mapping models based on deep learning. However, these models generally rely on a large amount of labeled crop samples to investigate the intricate relationship between the crop types of the samples and the corresponding remote sensing features. Moreover, their efficacy is often compromised when applied to other areas owing to the disparities between source and target data. To address this issue, a new multi-modal deep adaptation crop classification network (MDACCN) was proposed in this study. Specifically, MDACCN synergistically exploits time series optical and SAR images using a middle fusion strategy to achieve good classification capacity. Additionally, local maximum mean discrepancy (LMMD) is embedded into the model to measure and decrease domain discrepancies between source and target domains. As a result, a well-trained model in a source domain can still maintain satisfactory accuracy when applied to a target domain. In the training process, MDACCN incorporates the labeled samples from a source domain and unlabeled samples from a target domain. When it comes to the inference process, only unlabeled samples of the target domain are required. To assess the validity of the proposed model, Arkansas State in the United States was chosen as the source domain, and Heilongjiang Province in China was selected as the target domain. Supervised deep learning and traditional machine learning models were chosen as comparison models. The results indicated that the MDACCN achieved inspiring performance in the target domain, surpassing other models with overall accuracy, Kappa, and a macro-averaged F1 score of 0.878, 0.810, and 0.746, respectively. In addition, the crop-type maps produced by the MDACCN exhibited greater consistency with the reference maps. Moreover, the integration of optical and SAR features exhibited a substantial improvement of the model in the target domain compared with using single-modal features. This study indicated the considerable potential of combining multi-modal remote sensing data and an unsupervised domain adaptive approach to provide reliable crop distribution information in areas where labeled samples are missing.

Balancing urbanization, agricultural production and ecological integrity: A cross-scale landscape functional and structural approach in China

Projecting land-use allocation under various scenarios can be useful for reconciling conflicts between urbanization, food security, and ecological integrity throughout landscapes, but existing approaches often fail to capture the interactions in land systems that occur across scales and within and between hierarchical jurisdictions of societal organization. This article introduces a cross-scale functional and structural approach for balancing trade-offs in landscape planning and sustainable land management at multiple levels, based on the principles of multifunctional suitability. Using Heilongjiang Province in China as a case, we simulate four landscape scenarios that progressively consider cross-scale and inter-regional trade-offs more broadly, as well as local suitability. In the business-as-usual (BAU) scenario, no multifunctionality objectives are considered at any level; in the own-provincial scale (OPS) scenario, intra-province multifunctionality objectives are considered; the national and provincial scales (NPS) scenario considers multifunctionality within and beyond the province; while the desired land-use (DLU) scenario balances cross-scale multifunctionality while also optimizing for local functional suitability. Promoting multifunctionality as desirable, and evaluated based on minimizing functional land loss, the DLU scenario significantly outperforms the BAU scenario. The results indicate that the DLU scenario outperforms BAU, OPL, and NPS in optimizing urban and cropland layout, and preserving ecosystem integrity. It reduces high-quality arable land loss by 6.5% and minimizes the impact on ecological function areas by 12%, surpassing the BAU scenario. In contrast to the OPS and NPS scenarios, the DLU scenario exhibits a 6% and 2% increase in population and economic agglomeration within the Harbin-Daqing-Suihua (HDS) city cluster, a pivotal component of the national urbanization strategy. Furthermore, it enhances grain production capacity in the national grain-producing area, the Sanjiang Plain (SJP), with 9% and 12% boosts, respectively. Additionally, the DLU scenario expands the ecologically significant area, showing a 3.6% and 1% improvement in the Greater and Lesser Khingan Mountains (GLKM), nationally vital ecological service function areas. These advantages of the DLU scenario are expected to become more pronounced over time. The novel theoretical approach and modelling framework introduced in this study can serve as inspiration elsewhere for reconciling future land-use trade-offs and planning decisions across scales.

Characterization of Fusarium species causing soybean root rot in Heilongjiang, China, and mechanism underlying the differences in sensitivity to DMI fungicides

Soybean root rot is a worldwide soil-borne disease threatening soybean production, causing large losses in soybean yield and quality. Fusarium species are the most detrimental pathogens of soybean root rot worldwide, causing large production losses. Fusarium root rot has been frequently reported in Heilongjiang Province of China, but the predominant Fusarium species and the sensitivity of these pathogens to different fungicides remain unclear. In this study, diseased soybean roots were collected from 14 regions of Heilongjiang province in 2021 and 2022. A total of 144 isolates of Fusarium spp. were isolated and identified as seven distinct species: F. scirpi, F. oxysporum, F. graminearum, F. clavum, F. acuminatum, F. avenaceum, and F. sporotrichioide. F. scirpi and F. oxysporum had high separation frequency and strong pathogenicity. The sensitivity of Fusarium spp. to five different fungicides was determined. Mefentrifluconazole and fludioxonil showed good inhibitory effects, and the sensitivity to pydiflumetofen and phenamacril varied between Fusarium species. In particular, the activity of DMI fungicide prothioconazole was lower than that of mefentrifluconazole. Molecular docking showed that mefentrifluconazole mainly bound to CYP51C, but prothioconazole mainly bound to CYP51B. Furthermore, the sensitivity to prothioconazole only significantly decreased in ΔFgCYP51B mutant, and the sensitivity to mefentrifluconazole changed in ΔFgCYP51C and ΔFgCYP51A mutants. The results demonstrated that the predominant Fusarium species causing soybean root rot in Heilongjiang province were F. scirpi and F. oxysporum and DMI fungicides had differences in binding cavity due to the diversity of CYP51 proteins in Fusarium.

Dynamic assessment of community resilience in China: empirical surveys from three provinces.

Strengthening the construction of community resilience and reducing disaster impacts are on the agenda of the Chinese government. The COVID-19 pandemic could alter the existing community resilience. This study aims to explore the dynamic change trends of community resilience in China and analyze the primary influencing factors of community resilience in the context of COVID-19, as well as construct Community Resilience Governance System Framework in China. A community advancing resilience toolkit (CART) was used to conduct surveys in Guangdong, Sichuan, and Heilongjiang provinces in China in 2015 and 2022, with community resilience data and information on disaster risk awareness and disaster risk reduction behaviors of residents collected. The qualitative (in-depth interview) data from staffs of government agencies and communities (n = 15) were pooled to explore Community Resilience Governance System Framework in China. Descriptive statistics analysis and t-tests were used to investigate the dynamic development of community resilience in China. Hierarchical regression analysis was performed to explore the main influencing factors of residential community resilience with such socio-demographic characteristics as gender and age being controlled. The results indicate that community resilience in China has improved significantly, presenting differences with statistical significance (p < 0.05). In 2015, connection and caring achieved the highest score, while disaster management achieved the highest score in 2022, with resources and transformative potential ranking the lowest in their scores in both years. Generally, residents presented a high awareness of disaster risks. However, only a small proportion of residents that were surveyed had participated in any "community-organized epidemic prevention and control voluntary services" (34.9%). Analysis shows that core influencing factors of community resilience include: High sensitivity towards major epidemic-related information, particular attention to various kinds of epidemic prevention and control warning messages, participation in epidemic prevention and control voluntary services, and formulation of epidemic response plans. In this study, we have constructed Community Resilience Governance System Framework in China, which included community resilience risk awareness, community resilience governance bodies, community resilience mechanisms and systems. During the pandemic, community resilience in China underwent significant changes. However, community capital was, is, and will be a weak link to community resilience. It is suggested that multi-stages assessments of dynamic change trends of community resilience should be further performed to analyze acting points and core influencing factors of community resilience establishment at different stages.

Recognition and rejection of foreign eggs of different colors in Barn Swallows

Brood parasitic birds lay eggs in the nests of other birds, and the parasitized hosts can reduce the cost of raising unrelated offspring through the recognition of parasitic eggs. Hosts can adopt vision-based cognitive mechanisms to recognize foreign eggs by comparing the colors of foreign and host eggs. However, there is currently no uniform conclusion as to whether this comparison involves the single or multiple threshold decision rules. In this study, we tested both hypotheses by adding model eggs of different colors to the nests of Barn Swallows (Hirundo rustica) of two geographical populations breeding in Hainan and Heilongjiang Provinces in China. Results showed that Barn Swallows rejected more white model eggs (moderate mimetic to their own eggs) and blue model eggs (highly non-mimetic eggs with shorter reflectance spectrum) than red model eggs (highly non-mimetic eggs with longer reflectance spectrum). There was no difference in the rejection rate of model eggs between the two populations of Barn Swallows, and clutch size was not a factor affecting egg recognition. Our results are consistent with the single rejection threshold model. This study provides strong experimental evidence that the color of model eggs can has an important effect on egg recognition in Barn Swallows, opening up new avenues to uncover the evolution of cuckoo egg mimicry and explore the cognitive mechanisms underlying the visual recognition of foreign eggs by hosts.

Analysis on the Relationships of Smartphone Addiction, Learning Engagement, Depression, and Anxiety: Evidence from China.

With the popularization of the Internet and smartphones, smartphone addiction among college students is becoming increasingly common, causing the problems of their learning engagement, anxiety, and depression. The study aimed to analyze the relationships of smartphone addiction, learning engagement, anxiety and depression among Chinese college students. Based on the Self-Determination Theory, in January 2023, 780 college students from 6 universities in Heilongjiang Province in China were selected as examples for the study. Internet Addiction Test, Utrecht Work Engagement Scale-Student, Chinese version of Beck Depression Inventory-II, and Spielberger Trait Anxiety Inventory were employed to measure smartphone use, learning engagement, depression, and anxiety among college students. Pearson correlation and multiple logistic regressions were also used. Smartphone use was negatively correlated with learning engagement (r = -0.097, P < 0.001), whereas it was positively correlated with depression (r = 0.184) and anxiety (r = 0.18, P < 0.001). Significant differences were observed in learning engagement and depression and anxiety symptoms in different degrees of smartphone use. Taking severe smartphone addiction as a comparison standard, depression and anxiety symptoms had a significant influence on different levels of smartphone use, whereas learning engagement did not have a significant influence on different smartphone use levels. The intervention and prevention of college students' smartphone addiction can improve their learning engagement, relieve their anxiety and depression, and enhance their mental health level.

First Report of Pectobacterium versatile Causing Diseases on Potato in Xinjiang Uygur Autonomous Region and Heilongjiang Province, China.

Pectobacterium spp. and Dickeya spp. cause aerial stem rot on potatoes worldwide (Charkowski, 2018). Potato plants (cv. Xisen6# or Youjin) with aerial stem rot or blackleg symptoms (Fig. S1) were observed in the commercial fields in Changji, Xinjiang Province in September 2021 and Harbin, Heilongjiang Province in August 2021, in China. The field disease incidences were 45-50% and 15-20% in Changji (2 ha) and Harbin (1 ha), respectively. Five diseased plants from each field site were collected to isolate the pathogen. Symptomatic stems were soaked in 75% ethanol for 2 min, rinsed, and ground in sterile distilled water (Handique et al. 2022). The suspension was plated onto a crystal violet pectate agar (CVP) plate (Ge et al. 2018). Three days after incubation at 28°C, bacterial colonies that developed pits on CVP plates were purified and sequenced for identification using the universal 16S rRNA gene primer set 27F/1492R (Monciardini et al. 2002). Amplified 16S rDNA sequences from two isolates designated as ZRIMU1267 and ZRIMU1366 showed more than 99% sequence identity to P. versatile CFBP6051T type strain and the sequences were submitted to GenBank (accession numbers: OP476349, OP476350). Additionally, six housekeeping genes sequences were uploaded to GenBank: proA (OP487826, OP487832), gyrA (OP487828, OP487834), icdA (OP487823, OP487829), mdh (OP487825, OP487831), gapA (OP487824, OP487830), and rpoS (OP487827, OP487833) (Ma et al. 2007; Waleron et al. 2008). A phylogenetic tree based on concatenated sequences (MLSA) of the housekeeping genes (Fig. S2) of the two isolates was constructed using MEGA X (Tamura et al. 2013).The phylogenetic tree of MLSA sequences shows that the sequences from isolates ZRIMU1267 and ZRIMU1366 clustered with P. versatile CFBP6051T indicating that these isolates are P. versatile at the species level. Koch's postulate were performed on 3-week-old potato seedlings (cv. Favorita) and tubers. The bacterial suspension (100 μl, 105 CFU/ml) or sterile phosphate-buffered solution was injected into the crown area of the seedlings for the development of aerial stem rot or drenched in the potting mix for the development of blackleg, and the plants were covered with polybags to keep 100% humidity at 25° for 2 days. Five seedlings were inoculated for each strain and the experiment was repeated twice. Seven days after stem injection, the infected area of the inoculated seedlings was rotten, turned black, or even lodged, while the controls were symptomless (Fig. S3a). Four days after drench application, the seedlings were wilted and lodged, while the controls were symptomless (Fig. S3 c). Tuber slice assay for soft rot development was performed by adding bacterial suspension (100 μl, 105 CFU/ml). One day after inoculation, the infected tubers rotted, while the controls were symptomless (Fig. S3 b). ZRIMU1267 and ZRIMU1366 were reisolated from infected tissues on CVP plates and identified by 16S rRNA sequences to complete Koch's postulate. Diseases on potato has been reported to be caused by P. atrosepticum, P. carotovorum, P. brasiliense, P. parmentieri, P. polaris, and P. punjabense in China (Zhao et al. 2018; Cao et al. 2021; Wang et al. 2021; Handique et al. 2022). P. versatile causing aerial stem rot on potatoes have been reported in Hebei province (Han et al. 2022), while our study reports P. versatile strains that are able to cause multiple diseases on potatoes in Xinjiang Uygur Autonomous Region and Heilongjiang provinces of China. The results indicate that P. versatile might be widely distributed in northern China, and it is necessary to include cropping season and post-harvest strategies to control diseases caused by P. versatile.

Genetic and In Vitro Characteristics of a Porcine Circovirus Type 3 Isolate from Northeast China.

Porcine circovirus 3 (PCV3) is an emerging virus first discovered in the United States in 2015, and since then, PCV3 has been found in many regions of the world, including America, Asia, and Europe. Although several PCV3 investigations have been carried out, there is a lack of knowledge regarding the pathogenicity of PCV3, mostly due to the limited number of PCV3 isolates that are readily available. In this study, PCV3-DB-1 was isolated in PK-15 cells and characterized in vitro. Electron microscopy revealed the presence of PCV-like particles, and in situ hybridization RNA analysis demonstrated the replication of PCV3 in PK-15 cell culture. Based on phylogenetic analysis of PCV3 isolates from the Heilongjiang province of China, PCV3-DB-1 with 24 alanine and 27 lysine in the Cap protein was originally isolated and determined to belong to the clade PCV3a.

Hierarchical extraction of cropland boundaries using Sentinel-2 time-series data in fragmented agricultural landscapes

Accurately extracting cropland field parcels from satellite data in fragmented agricultural landscapes presents huge challenges due to small field sizes and irregular field shapes. Here, we developed a hierarchical framework for agricultural field boundary extraction from Sentinel-2 satellites based on the concept of the degree in field fragmentation. Our framework focused on three tasks, including a core task for agricultural field extraction and two auxiliary tasks to address special situations in two different fragmented regions, namely the Plains-Basin scenes with relatively regular shapes and diverse crop types, and the Plateau-Hilly scenes, with irregular shapes and small field sizes. First, the field boundaries were delineated using a modified Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net), and post-processed using morphological filtering and the Douglas-Peucker algorithm (DPA). A rule-based decision fusion strategy assisted with a classification method was developed to address the under-segmentation problem in the Plains-Basin scenes, and an adaptive generalized buffer algorithm (AGBA) was used to address the incomplete-segmentation problem in the Plateau-Hilly scenes. We tested the proposed methods in Yangming County, Heilongjiang Province of China, using time series Sentinel-2 imageries with 10-m spatial resolution. Compared with the results from using R2U-Net or a single-temporal image alone, the fragmented field boundaries show an outstanding performance, with an overall accuracy of 86.42% and 84.15% and F1 score of 0.85 and 0.83 in Plains-Basin scenes and Plateau-Hilly scenes, respectively. Our proposed methods provide a feasible solution to finely extract field boundaries in highly fragmented and heterogeneous agricultural landscapes.

The Maize Supply Chain Coordination Mechanism under Yield Uncertainty Caused by Drought: A Study in the Heilongjiang Province of China

The Maize Supply Chain Coordination Mechanism under Yield Uncertainty Caused by Drought: A Study in the Heilongjiang Province of China

First Report of Aphelenchoides besseyi Causing White Tip Disease of Rice in Heilongjiang Province of China.

Aphelenchoides besseyi is considered one of the most damaging plant parasitic nematodes to rice and can cause white tip disease. It was first discovered in Kyushu, Japan in 1915 and introduced into China from Japan in the 1940s. The disease is mainly found in rice-planting areas in South China (Zhu et al. 2016; Wang et al. 2017; Xu et al. 2019), causing yield losses of 30%-50% in irrigated rice (Wang et al. 2014). In summer 2021, rice plants displaying distortion and discoloration on new leaves, white tips on flag leaves, erect and shorter panicles, and fewer or less filled spikelets were observed in the rice field in Acheng district, Harbin city, Heilongjiang Province, China (13°32'33″S, 58°48'51″W). Plant samples with the typical symptoms of 'white tip' in the flag leaves were collected and transported to the laboratory for further pathogen identification. Nematodes were extracted from the leaves and panicles of diseased plants using Baermann funnel method, and the population density of nematode was an average of 57 individuals per sample (total 28 diseased samples). The main morphological characteristics of females (n = 20) and males (n = 15) were individually determined using a microscope (LEICA, DM2500). Female body was slender, and straight to ventrally curved when heat-relaxed, with a rounded cephalic region, the lateral field with four incisures, the excretory pore close to the anterior edge of the nerve ring, a narrow post-vulval sac and less than 1/3 the distance from the vulva to the anus, and a conoid tail with star-shaped mucro. Female measurements: body length = 724.6 (593.3 to 867.5) μm, stylet = 11.7 (10.9 to 12.5) μm, tail length = 39.4 (35.8 to 44.4) μm, a = 45.2 (38.6 to 51.0), b = 10.1 (9.4 to 10.7), c = 18.47 (14.7 to 21.4), and V = 71.1 (65.0 to 79.6). The body of male usually showed in a 'J' shape when relaxed, spicule length between 17.1 and 19.4 μm, and a conoid tail, with terminal mucro bearing two to four pointed processes. Male measurements: body length = 546.3 (521.7 to 587.6) μm, stylet = 11.9 (10.7 to 12.6) μm, tail length = 32.54 (29.53 to 34.35) μm, a = 37.7 (35.7 to 40.4), b = 8.7 (8.5 to 9.1), c = 17.8 (15.8 to19.4). The key morphological characteristics were coincident with the description of A. besseyi by Christie (1942), Ou et al. (2014) and Chen et al. (2020). DNA was extracted from six fresh nematodes, and the partial 18S-rRNA was amplified with a pair of primers 1813F/2646R (5'-CTGCGTGAGAGGTGAAAT-3'; 5'-GCTACCTTGTTACGACTTTT-3') (Holterman et al. 2006). PCR products of expected size were purified and sequenced. The newly obtained sequence (accession no. ON629604) was submitted to GenBank and displayed more than 99.5% identity with that of A. besseyi isolates (KT943536, KT454963, JQ957877). Additionally, the isolated nematodes were further confirmed using the species-specific primers Abess_11F/Abess_11R (5'-GTATTCAATCCCGCGACACT-3'; 5'-CATCCTGTTCGGGCATAGTT-3'), and the PCR amplification generated a 570 bp fragment which was specific to the 28S rDNA region of A. besseyi reported previously (Noronha et al. 2020). The pathogenicity test was confirmed in a pot assay. Approximately 2000 mixed-stage A. besseyi (juveniles, males and females) were obtained from the field-diseased rice plants, and ten-day-old rice seedlings (Japonica rice variety, Keyou 1) (n = 5) were inoculated with 400 nematodes per seedling and maintained in a greenhouse. During early growth stages (fifty days after inoculation), some young leaves of infected plants showed the chlorotic tips. Ninety days after inoculation, similar field symptoms (white tip on leaves) were observed on the aerial tissues of the inoculated plants, and an average of 237 A. besseyi were re-isolated from each plant. To the best of our knowledge, this is the first report of A. besseyi on rice plant in Heilongjiang Province of Northeast China. This finding indicates that A. besseyi could become a severe threat to rice production in Heilongjiang Province and contributes to the further inspection and prevention of white tip disease in rice-growing areas of Heilongjiang Province.

Optimizing sustainable biomass–coal co-firing power plant location problem under ambiguous supply

Promoting biomass–coal co-firing power generation technology in existing coal-fired power plants is a practical and relatively low-cost short-run choice for the coal-fired power industry to reduce carbon emissions and develop sustainably. However, the uncertainty of biomass supply complicates the location of co-firing power plants among existing coal-fired plants. To address the challenge that only limited historical data of uncertain supply are available, this paper proposes a new ambiguity distribution set to characterize the uncertain supply capacity, supply price, and supply quality (i.e., energy conversion coefficient). Accordingly, a novel bi-objective distributionally robust fuzzy optimization model is developed for the sustainable co-firing power plant location (SCPPL) problem to balance conflicting objectives of minimizing total cost and maximizing carbon emission reduction. Subsequently, the computationally tractable counterpart of the proposed model is derived against the worst-case distribution by reformulating the distributionally robust credibility objective and constraints as their solvable equivalent forms. Furthermore, the Pareto optimal solutions of the proposed bi-objective model are generated using the augmented ϵ-constraint method. Finally, a realistic case study of Heilongjiang Province in China is conducted to verify the feasibility and effectiveness of the proposed optimization method. The experimental results demonstrate that the proposed model can hedge against the distributional ambiguity of uncertain parameters and provides a robust co-firing power plant location strategy. By comparison with the nominal distribution model and analysis of the sensitivity of selected parameters, management insights are summarized for decision-makers.

The Road of Post-Industrialization Transformation in Developing Countries Based on Weighted Markov and Grey Correlation Theory, Taking the Change of Industrial Structure in Heilongjiang Province of China as a Case Study

In the context of economic globalization, the comparative advantages of developing countries and developed countries tend to be more complex. After the economic crisis in 2008, the challenges of developing countries are intensified, and the game is more cyclical; Especially in the critical period when the “Fourth Industrial Revolution” is pending, many countries have increased their efforts in policy formulation and efficiency improvement, focusing on industrial transformation and upgrading, and closely combining structural reform with the industrialization process. Therefore, it is particularly important to analyze, change and forecast the industrial structure of post-industrial regions in developing countries based on data science algorithms, and to reshape the understanding of the adjustment of the world economic order and the evolution of the international trade division system. Based on the proportion of gross regional product and output value of three industries in Heilongjiang Province of China from 2001 to 2020, the minimum deviation model of industrial structure in Heilongjiang Province is constructed through Markov theory. The Lingo software is used to obtain the transition probability matrix of the industrial structure state, and combined with the autocorrelation coefficient of each order and the transfer weight, the change trend of the proportion of the output value of the three industries and the change of the contribution rate of the three industries (to GDP) in Heilongjiang Province in the next 10 years are obtained; At the same time, through the grey correlation index and spss software, this paper analyzes the correlation changes between the three industrial adjustments and economic development in Heilongjiang Province in the past 20 years, discusses the new growth points of economic development in Heilongjiang Province and puts forward corresponding suggestions for the adjustment of different industrial structures in Heilongjiang Province, and finally extends the general rules of the development of post-industrialization in the world. This article believes that it is necessary to adjust the structure of the first, second, and third industries reasonably based on different historical and natural endowments, contemporary backgrounds, and other practical factors, in accordance with local conditions, circumstances, and each with its own emphasis. At the same time, it also requires the support and inclination of government policies; Adapting industrial structure to local economic development while actively leading productivity and local economic development.

Identification and Spatial Correlation of Imported Timber Landing Processing Industrial Clusters in Heilongjiang Province of China

This paper analyzed the clustering degree and spatial distribution characteristics of the imported timber landing processing industry in China’s Heilongjiang province based on the survey and statistical data during 2019–2021. The location entropy method was used to quantify the clustering degree of timber landing processing. Multi-distance spatial clustering analysis, hotspot analysis, and spatial autocorrection analysis were conducted to identify the spatial pattern of enterprises and analyze the hotspots and spatial correlation among the prefecture-level cities in the region. Results showed that there was obvious industrial agglomeration in imported timber landing processing in Heilongjiang Province, and the overall spatial pattern of the industry showed significant spatial aggregation at different spatial scales. The hotspots were primarily concentrated in the southeast of the province with a high level of industrial development, while the cold spots were primarily in the western and northern parts with a low level of industrial development. The distribution of the imported timber landing processing industry at the provincial level was positively correlated, but not very significantly. There was large spatial heterogeneity for the imported timber landing processing industry. Some suggestions were put forward in order to accelerate the construction of imported timber landing processing industrial clusters in the region.

First report of Alternaria alternata causing leaf spot of Cynanchum atratum Bunge in China.

Cynanchum atratum Bunge belongs to Asclepiadaceae, and is distributed in North Korea, Japan and China. Its roots and rhizomes have antibacterial, antiviral, anti-inflammatory and anti-tumor effects. In July 2021, a leaf spot was observed in a 1.3 ha plantation of C. atratum in Harbin, Heilongjiang Province in China. The incidence was more than 85%. Initial symptoms were yellowing leaves with circular, or ellipsoid brown spots forming on leaf apexes or leaf margins. Small spots expanded and coalesced to form large circular or irregular, pale to light brown lesions, and leaves finally withered. Thirty, 5 × 5 mm, leaf pieces excised from the junction of symptomatic and healthy tissues were collected from different leaves with typical symptoms on ten plants, sterilized in 75% ethanol for 30s, then in 2% NaClO for 30s, rinsed in sterile water three times, placed on potato dextrose agar (PDA) plates, incubated for 5 days at 28°C in the dark, further purified by single spore method and transferred to new PDA and potato carrot agar (PCA) plates. Finally, 12 fungal isolates, most with similar morphology, were selected. After a 7-day incubation in the dark, colonies on PDA were 53 to 70 mm in diameter, circular and grayish brown. A total of 150 conidia were evaluated for morphology. Conidia were single or in chains, ovoid to inverted pear-shaped, with 2 to 6 transverse septa, 0 to 4 longitudinal or oblique septa, and measured 16.5 to 56.5μm × 9.0 to 16.5 μm. Beaks and supposititious beaks were mostly columnar, rarely conical, 0 to 22.5 μm × 2.5 to 4.0 μm. Conidiophores were solitary or clustered, pale brown, erect or bent, branched or unbranched, separated, 53.5 to 120.5 μm × 2.5 to 6.0 μm (Fig 1). Based on morphological characteristics, the fungus was identified as Alternaria alternata (Simmons 2007). Two representative isolates (BW and BW2) were used for molecular identification. Internal transcribed spacer rDNA regions (ITS), RNA polymerase II second largest subunit (RPB2), Alternaria major allergen (Alt a 1), translation elongation factor 1-alpha (TEF-1 α) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene were amplified and sequenced with the primers ITS1/ITS4 (White, et al. 1990), RPB2-5F2/RPB2-7CR (Khodaei and Arzanlou. 2013), Alt-F /Alt-R (Hong et al. 2005), TEF-F/TEF-R (Carbone and Kohn. 1999) and GDF/GDR (Templeton et al. 1992). The sequences obtained were deposited in GenBank (ITS: OM317915, ON534349; RPB2: OM296253, ON550475; Alt a 1: OM171248, O550474; TEF: OM238096, O550473; GAPDH: OM296217, ON550472). The phylogenetic analysis of maximum likelihood tree by MEGA 7 showed that the two isolates had 98% similarity with A. alternata CBS 916.96 (Fig 2). To test pathogenicity, 40-day-old plants were sprayed with spore suspensions (1×106 spores /mL) from 7-day-old cultures of BW and BW2. Each isolate was inoculated onto 3 leaves on 3 separate plants. Three other plants were sprayed with sterile distilled water as a control. The plants were incubated in the greenhouse (natural light, T: 25℃, H: 50%). After 15 days, the leaves turned yellow and irregular grayish spots appeared. The fungi reisolated from the inoculated leaves shared the same morphological and molecular features as A. alternata, fulfilling Koch's postulates. No fungi were isolated from the control group. This is the first time to report A. alternata causing leaf spot on C. atratum. Leaf spot can reduce the yields of C. atratum and this study provides a basis for the prevention and control of the disease.