Next Article in Journal
Agronomic Performance and Resistance to Maize Lethal Necrosis in Maize Hybrids Derived from Doubled Haploid Lines
Previous Article in Journal
Altitude Distribution Patterns and Driving Factors of Rhizosphere Soil Microbial Diversity in the Mountainous and Hilly Region of Southwest, China
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Unravelling the Current Status of Rice Stripe Mosaic Virus: Its Geographical Spread, Biology, Epidemiology, and Management

by
Md. Atik Mas-ud
1,†,
Md. Rayhan Chowdhury
2,
Sadiya Arefin Juthee
3,
Muhammad Fazle Rabbee
4,†,
Mohammad Nurul Matin
4,* and
Sang Gu Kang
4,*
1
College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
2
Graduate School of Medicine, Science and Technology, Shinshu University, Minamiminowa, Nagano 399-4598, Japan
3
Department of Crop Botany, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
4
Department of Biotechnology, Yeungnam University, Gyeongsan 38541, Republic of Korea
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Agronomy 2024, 14(10), 2442; https://doi.org/10.3390/agronomy14102442
Submission received: 24 July 2024 / Revised: 17 October 2024 / Accepted: 17 October 2024 / Published: 21 October 2024

Abstract

:
Rice stripe mosaic virus (RSMV) belongs to the Cytorhabdovirus species in the Rhabdoviridae family. Recently, RSMV was widely spread in East Asia and caused severe yield losses. RSMV is transmitted by the planthopper vectors, Recilia dorsalis, Nephotettix virescens, and Nilaparvata lugens, that mostly affect rice. The adult vectors can hibernate, transmit the virus, lay eggs on rice plants, and, finally, multiply in subsequent generations, resulting in new infection outbreaks. RSMV-infected rice varieties display striped mosaicism, mild dwarfism, stiff and twisted leaves, delayed heading, short panicles with large unfilled grains, and yield reduction. In nature, the infection of multiple pathogens in the same host is widespread, which is defined as co-infection. It can be antagonistic or synergistic. Pathological synergistic effects between RSMV and other viruses can generate strains with new genetic characteristics, leading to unpredictable epidemiological consequences. After the first identification of RSMV in 2015, significant advancements in understanding the disease’s characteristics, symptoms, cycles, geographic distribution, potential vectors, and synergistic interaction, as well as its management strategies, were developed. To reduce the damage due to RSMV infection, many scientists have recommended pest control techniques to target adult vectors. It is also essential to confirm the actual time of monitoring, development of resistant varieties, and changes in cultivation systems. Due to the limitations of the conventional plant disease control technologies, improvements in efficiency and safety are in high demand. Therefore, to find efficient and environmentally safe controls to mitigate these challenges, reviews of research are the foremost step. In this review, we summarize the basic epidemiological information about the origin of RSMV and its infection symptoms in the field, synergistic interaction with viruses during co-transmission, yield losses, formulation of the disease cycle, and control strategies from several case studies. Finally, we recommend the formulation of the disease cycle and management strategies of RSMV infection.

1. Introduction

Rice is the most widely grown cereal grain consumed around the world. Asia is the world’s top rice producer (<7.05 billion tons per year), led by China, where 148.5 million metric tons was produced in 2018, indicating Asia accounts for more than 90% of the total global rice production [1,2,3]. However, due to several biotic and abiotic constraints, especially diseases, rice farming is constantly at risk. Plant diseases, particularly viral diseases, have been a limiting factor for the sustainable production of crops and are increasing globally, which may be due to global warming. The recently identified rice stripe mosaic virus (RSMV) is a novel virus that belongs to the Cytorhabdovirus species in the Rhabdoviridae family that mostly infects rice as a suitable host. It has recently been identified that viral infections in rice have had a serious effect on yield damage [4,5,6]. It has been described that current rice production is highly vulnerable to insect-borne viral diseases, especially southern rice black-streaked dwarf virus (SRBSDV), rice black-streaked dwarf virus (RBSDV), and rice gall dwarf virus (RGDV) [7]. RBSDV and RGDV outbreaks have been observed annually in southern China, and it has been identified that most of the studied rice varieties showed widespread vulnerability to RBSDV and RGDV, which are transmitted by small brown planthoppers and zigzag leafhoppers, respectively, and suggested that most of the rice varieties lacked broad-spectrum resistance to viruses [7]. Likewise, RSMV infection has been the most prevalent virus infection in rice in recent times, and it has caused yield losses between 30 and 40% [8,9,10,11,12,13,14].
Until now, the mechanism of RSMV infection in the carrier mostly remains unknown. The insect-borne plant RSMV predominantly spreads into rice by the planthopper vectors Recilia dorsalis, Nephotettix virescens, and Nilaparvata lugens in a persistent–propagative manner [4,15,16,17,18]. RSMV was first detected in a small region in southern China in 2015 [17,19], then spread widely throughout southern China in 2017. In some of the fields, the incidence of infection exceeded 70% and caused severe damage to rice production [4,18,20,21].
The understanding of the morphology, transmission, and molecular biology of RSMV is limited. The virion of RSMV is bacilliform, measuring 300–375 nm in length, and 45–55 nm in diameter. Its RNA genome consists of a negative-sense strand of 12.7 kb [3,8,22,23,24]. The RSMV genome encodes a structural or nucleoprotein (N), P-like or phosphoprotein (P), non-structural protein (P3) or movement protein (MP), matrix protein (M), G-like structural protein or glycoprotein (G), basic ancillary or non-structural protein (P6), and L-like or large polymerase protein (L) [4,25]. The RSMV ribonucleoprotein (RNP) cores are formed inside the viroplasm, the bacilliform non-enveloped virions are assembled at the periphery, and the enveloped virions are assembled in the endoplasmic reticulum [26]. RSMV is dispersed in mesophyll cells, while the residues also parasitize the dispersed phloem cells of rice. The primary distinguishing characteristic of RSMV-infected rice is the presence of mosaic patterns, yellow stripes, and twisted leaf tips. Additionally, infected plants tend to have an increased number of rudimentary tillers, experience late heading, often produce empty grains, and ultimately suffer from yield losses [15,27].
Due to the severe damaging potency of RSMV to rice production, there has been considerable progress in understanding RSMV infection [18]. Since the virus was first discovered in 2015, a few studies have examined the symptoms of the rice diseases and the yield losses brought on by RSMV infection. It is crucial to comprehend the nature of the diseases, the agents that cause them, how they spread, the losses they cause, and the controls used to prevent outbreaks of any disease. The early detection of symptoms followed by implementing preventive measures could reduce the destructive effects of the virus and protect crops from significant yield losses. The primary aims of the plant disease management strategy should be strengthening food security for society and, meanwhile, safeguarding the well-being of accompanying ecosystems. To achieve these, sustainable plant disease management should rely on resistance, avoidance, elimination, and remediation strategies individually and collectively, to facilitate host growth and development while being adverse to pathogen reproduction and evolution [28].
Intensive research has been conducted on many other viruses in rice, including on the determination of virus pathogenicity, replication, and movement, the identification of resistant varieties, the mechanisms underlying resistance to infection, and the interactions between viruses, rice, and vectors. However, RSMV is relatively less understood compared to other plant viruses. Therefore, the goal of this study is to emphasize the comprehensive presentation and analysis of the latest findings on RSMV infection, including its geographic distribution, symptoms, yield impact, disease cycle, and management strategies. Owing to the limitation of length, only the literature related to plant pathogenic microbes that might potentially help to explore the efficient and environmentally safe control of pathogenic microorganisms like RSMV infection in rice was included in this review.

2. Geographic Distribution of RSMV Infection in China

RSMV was first detected in southern China in 2015 and was first reported in 2017 [4]. To date, the occurrence of RSMV-infected rice plants has only been detected and reported in China. The three most prevalent provinces in China, where severe infections were identified, were Guangdong, Guangxi, and Hainan (Figure 1). In southern China’s Guangdong province, RSMV was initially discovered in 2015; however, it has spread rapidly throughout the area. In the Guangdong province, from 2015 to 2016, RSMV was found only in five rice production regions, including Taiping, Songgui, Luoping, Luoding, and Lianzhou; later on, RSMV was detected in most parts of the country [4]. Observations between 2015 and 2018 revealed that, in the Guangdong province, approximately 70.6% of the samples tested positive for RSMV [4,27]. In the Guangxi province, approximately 50.4% of the samples tested positive [1,27], while in the Hainan province, only 5.0% of the samples tested positive for RSMV (Figure 2) [15,27]. In the Guangdong province, Taiping (33.40%) and Luoping (20.99%) had the highest rates of disease (Figure 2A). In the Guangxi province, the cities with the highest disease rates were Wuzhou (42.00%) and Hezhou (32.00%) (Figure 2B), while the Hainan province had significantly lower rates (Figure 2C). RSMV infections gradually spread in southern China and was occasionally found to be increased in other rice-growing zones, including the Yunnan, Hunan, and Jiangxi provinces in southern China [4,15,17].
Since 2019, there have also been sporadic reports of RSMV-infected rice seedlings in the Jiangxi, Hunan, and Yunnan provinces [17,19,27]. These reports indicate that RSMV is spreading slowly but surely and the risk of damage is increasing. The viruses detected in the Guangdong province exhibit a greater genetic variance compared to those in the other two provinces, indicating that the Guangdong province might be the possible origin of RSMV, with the highest mutation frequency [27]. After analyzing various investigations, it was concluded that RSMV is predominantly found in Guangdong, Guangxi, and Hainan in China.
Global warming facilitates the movement and spread of rice planthoppers in northeast Asia, including in China, South Korea, and Japan. In particular, the year 2024 has seen a sustained high temperature in the Korean Peninsula until mid-September, leading to a rapid increase in rice planthopper populations and a corresponding rise in damage to rice crops during the harvesting period. As a result, serious planthopper damage occurred in the southern regions of the Korean Peninsula, including Chungcheongnam-do, Jeollanam-do, and Gyeongsangnam-do, in September 2024 (Rural Development Administration) [29]. Damage from rice planthoppers has also occurred in southern Japan, including in Kyushu (Ministry of Agriculture, Forestry and Fisheries of Japan).
Every year, rice planthoppers from southeastern China and southeast Asia migrate to the Korean Peninsula and southern Japan across the East China Sea due to westerly winds. Generally, the planthoppers that move into these regions do not survive the harsh winter and die off. However, due to recent global warming, prolonged high temperatures and monsoon seasons have been observed in these regions, resulting in rice planthoppers spreading and causing damage in certain areas of northeast Asia. Therefore, the increase in rice planthopper damage in the southern regions of the Korean Peninsula and southern Japan may lead to the spread of RSMV in these areas.

3. Symptoms of RSMV Infection

RSMV and other rice viruses are transmitted persistently by planthoppers, resulting in various effects on infected plants [5,10,14,15]. Our review of the literature revealed that RSMV-infected plants exhibited yellow striped leaves, slight dwarfing, occasional twisting, and a mosaic appearance (Figure 3A–C). Insignificant variations in the symptoms of RSMV infection were detected under diverse environmental conditions. The infected plants produced inferior inflorescence and twisted leaf sheathes; therefore, the panicles could not exert well and thereby remained partially emerged from leaf sheaths (Figure 3D,E). The new leaves of the infected plants had golden stripes [4] and consequently exhibited inward-curled tips and inferior heading (Figure 3E,F). Mosaic symptoms were also observed, and grains were commonly unfilled (Figure 3F). Mostly, hybrid rice varieties were affected by RSMV compared to the inbred lines. At the beginning of the infection, the hybrid rice exhibited a light yellow or bright yellow appearance, followed by the development of yellow stripes and the entire leaf showing signs of mosaicism, and eventually, the affected plants exhibited severe dwarfism [4,27]. From various previous research, it can be concluded that all three RSMV-infected rice varieties (i.e., japonica-“Nipponbare”, “indica-Meixiangzhan”, and hybrid “Wuyou 1179”) showed distinctive signs, including dwarfing, striped mosaicism, twisted leaves, crinkled stiffness, short panicles, delayed heading, and huge unfilled grains [4,17,27,30].

4. Rice Yield Losses Associated with RSMV Infection

Crop pathogen infections often reduce both yield and quality, with frequent viral infections having the potential to cause significant losses in seed production and quality [31,32,33]. RSMV is a recently identified rice virus, so there is not much information available on its effects. The estimated global yield losses for the major five crops (wheat, maize, rice, soybean, and potato) stand at about 10.1 to 41.1%, whereas rice only accounts for about 20–40% of annual production loss because of plant diseases [33,34]. Many rice varieties have been studied for symptoms of yield loss due to several viral infections; however, very little is known about RSMV-associated rice yield loss. Here, we present the RSMV-associated yield loss in the rice variety Nipponbare as an example that has been intensively studied by Chen et al. [15]. The RSMV-infected plants displayed significant dwarfing and reduced yield due to incomplete headings and dramatic delays in heading times (Figure 3G). Interestingly, even the infected plants had an increased number of tillers and panicles (Figure 3H); most of the tillers failed to develop effective panicles and could not emerge properly from the leaf sheath. As a result, the lengths of the panicles were significantly reduced (Figure 3I). Additionally, due to incomplete headings and delayed heading times, most of the spikelets remained unfilled (Figure 3J); consequently, this led to a drastic yield loss [2,4,15,17]. The weights of the panicles and seed setting rates of the RSMV-infected plants were significantly lower than those of healthy panicles [1,15]. Similar results regarding all the parameters were observed for the “Meixiangzhan”, “Nipponbare” and “Wuyou 1179” rice varieties, where the yields were significantly reduced to 68.44%, 76.14%, and 74.35%, respectively, due to RSMV infection [15].

5. RSMV Infection Cycle

Plants and pathogens are in a universal race that never ends where plants shield themselves from pathogens and pathogens intend to evade plants’ defenses to infect and cause disease [35,36]. Moreover, there are natural relationships among viruses, vectors, and hosts, and this complexity makes it difficult to understand the natural relationships among them [37]. RSMV infection progresses through several stages, including transmission, entry, replication, systemic movement, and symptom development. The primary transmission of RSMV occurs through the feeding on rice plants by the vector in a persistent–propagative manner, where the virion is acquired by vectors from the infected plants within a few hours [1,18,38]. The average dormant transmission period of RSMV in brown planthoppers is 13 days, and the virus replicates in the body of vectors [1]. Infected rice serves as the primary source of infection, providing a habitat where the virus can overwinter. The vectors acquire the virus by feeding on the infected rice plants and subsequently transmit it to new hosts, perpetuating the cycle from one season to the next. In a few minutes of feeding on the infected rice, the planthoppers became RSMV-positive [1]. The presence of virus thresholds in the vectors has also been proven to be a crucial factor in facilitating the virus transmission. In irrigated rice cultivation systems, where asynchronous and susceptible planting is common, major virus infections typically occur shortly after transplanting. After acquiring the virus, the active vectors act as the primary agents for the virus transmission from rice stumps, grasses, and nearby fields into the newly transplanted paddy field. Then, they introduce it into the plant’s vascular system through their stylets during feeding. Once inside the plant, the virus moves from cell to cell. The movement within cells allows the virus to spread locally. Primary infection in the early summer rice facilitates the propagation of the vector and virus, which can rapidly spread throughout the area and potentially cause an outbreak. RSMV and the vectors’ infection cycle are projected in Figure 4. Primary infection is brought on when overwintered nymphs feed on infected rice in the early spring and spread the virus to new seedlings [15]. Then, over generations, planthoppers become viruliferous and spread viruses, leading to outbreaks. In the meantime, the nymphs can overwinter in rice or other grasses that facilitate the furthering of the infection cycle (Figure 4).
RSMV primarily accumulates in the epithelial cells of the R. dorsalis, then proceeds to the visceral muscles. Subsequently, it progresses to the salivary glands. Meanwhile, RSMV spreads to the midgut, hindgut, esophagus, hemolymph, and central nervous system of the host [18]. Like RSMV, rice grassy stunt virus (RGSV) and rice stripe virus (RSV) are also transmitted in a persistent–propagative manner and have been intensively studied to show that the infection starts at the midgut epithelium and then travels through the midgut visceral muscles. RGSV and RSV move from the hemolymph to the salivary gland of the vector [39,40]. Given this, both RSMV and planthoppers compete for intracellular polyamine enzymes for efficient propagation. Involved polyamine-metabolizing enzymes, ornithine decarboxylase 1 (ODC1), and its antizyme 1 (OAZ1) in the activation of viral propagation has been recently described. The RSMV matrix (M) protein directly captures OAZ1 to ensure the proper assembly of bacilliform non-enveloped virions in the vector and effectively competes with ODC1 to bind to OAZ1 and, thus, the OAZ1-mediated degradation of ODC1 is significantly inhibited, which promotes the viral persistent propagation in the vector [26].
The RSMV infection cycle continues to spread from one plant to another, and the infected plants serve as sources for further transmission. The cycle continues throughout the growing season, if it is not managed. Therefore, understanding the infection cycle of RSMV is crucial for implementing effective disease management strategies. Control measures that target either the vector populations, the transmission process, or the virus replication within plants can help break the infection cycle and reduce the impact of RSMV on rice.

6. Synergistic Interaction of RSMV

Due to the greater abundance of viruses compared to their target hosts, multiple viral infections frequently occur in nature and display viral interactions, which is termed co-infection and may be antagonistic (advantageous for the host) or synergistic (detrimental for the host) [41]. Mixed viral infections in insect vectors can lead to synergistic effects that enhance virus–virus interactions. These interactions can result in the emergence of new variants with novel pathological features, leading to unpredictable pathological and epidemiological consequences [41,42,43]. Synergistic interaction enhances viral pathogenicity and has increased hosts damage and yield losses in many crops [44,45]. Therefore, the identification of virus–virus interactions in plants is of crucial significance for the understanding of viral pathogenesis and evolution and might lead to the development of competent and stable control strategies. The co-infection of Triticum mosaic virus (TriMV) and Wheat streak mosaic virus (WSMV) has induced disease synergism [45]. Papaya ringspot virus (PRSV) and Papaya mosaic virus (PapMV) have developed mixed infection [43]. The garlic mosaic virus (GMV) of Potyvirus, the garlic latent virus (GarLV) of Carlavirus, and the garlic virus (GarV) of Allexiviruses have abundantly formed mixed infection in a garlic plant in Korea [46].
Severe yield losses have also been identified in rice with various viral co-infections; rice yellow stunt virus (RYSV) and rice dwarf virus (RDV) caused substantial agricultural losses in Asia in the 1960s to 1980s [47]. Very recently, the synergistic interaction of RSMV with rice gall dwarf virus (RGDV) has been described, where, RSMV and RGDV co-infected vectors have enhanced their transmission to rice [25]. It was found that RSMV acquisition and transmission efficiencies, incidence, and spread in the field were facilitated when the vectors were co-infected by RGDV and RSMV, indicating that RGDV significantly promotes the propagation of RSMV in co-infected vectors [25,48]. From the field surveys in Luoding city in southern China, it was found that RSMV and RGDV frequently co-infected rice. More interestingly, planthoppers preferred to feed on the co-infected rice plants that boosted viral release into rice phloem, creating an increasing risk of damage to rice production [48]. Phenotypically, the co-infected plants exhibited more severe dwarfing, mosaic, and galls along the leaf sheaths than in plants individually infected by RSMV or by RGDV, and the infection rate was about 50–64% higher for co-infection than individual infection [48]. This synergism between RSMV and RGDV was confirmed by Jai et al. through RT-qPCR assay, infection outbreak, immunofluorescence, and electron microscopy [25,48].
Jai et al. identified that the nonstructural protein Pns11 of RGDV modifies RSMV-induced initial autophagy by the recruitment of the N protein of RSMV that promotes the propagation of the virus in the vector in a synergistic manner [25]. Further studies have suggested that non-enveloped RSMV particles aggregate at the periphery of viroplasms and directly target the outer membranes of Pns11-induced autophagosomes. Then, RSMV directly exploits RGDV-induced autophagosomes at the sites of the assembly of enveloped virions in co-infected vectors via the direct interaction of RSMV N with RGDV Pns11 proteins and facilitates RSMV propagation [25]. Overall, the effects of the synergistic interactions of co-infections on the degree of transmission deserve special attention because they might have serious ecological and epidemiological consequences.

7. Interplay Between Climatic Factors and Disease Dynamics

Changes in climatic factors, such as temperature and altered rainfall patterns, influence pathogens’ behavior by affecting their geographical distribution, seasonal phenology, and population dynamics [49]. Climate change can affect the seasonal timing of pathogen life cycle events, possibly bringing them to align with the host plant development stages or the existence of natural antagonists or synergists. Additionally, temperature variations can impact the population dynamics of rice pathogens by affecting factors such as survival and overwintering rates, infection efficiency, and the duration of latency periods. Consequently, these changes can alter the frequency and intensity of diseases in a given region. It is anticipated that a thorough grasp of the temporal and spatial variation in the structure of virus infections and disease development will improve the sustainability and effectiveness of disease management techniques [50]. The combined interaction of climatic conditions, disease dynamics, genetic traits, and planting dates in relation to the prediction of RSMV intensity is still not well understood. In this regard, improvements in the physiology and morphology of the host may lead to the adjustment of the defense mechanism. The major concern in the context of climate change and its effects on different host–pathogen interactions is the modification of genetic resistance in host plants to combat pathogen infections. This relationship could be used to improve rice’s resistance to RSMV.

8. Protein–Protein Interaction (PPI) Network with Other Plant Viruses

To facilitate viral replication in the host, viruses use virus–host protein–protein interactions (PPIs) that are termed as PPI networks [51]. PPI describes the relationship between proteins and biochemical factors that contribute to these interactions and shows how the related genes and proteins are connected [52,53]. Whole genome information was downloaded from the NCBI database, URL https://www.ncbi.nlm.nih.gov/ (accessed on 15 November 2023). The evolutionary relationships and classification of the differentially expressed genes of RSMV with other plant viruses were constructed through an unrooted phylogenetic tree using the neighbor joining (NJ) method using MEGA v11.0 software with multiple sequence alignment data consisting of seven RSMV, three ADV, three BYSMV, three CBDaV, three CoRSV, two LBVaV, three DYVV, three EMDV, three LNYV, three LYMoV, three MFSV, three MIMV, three MMV, three NCMV, three OFV, three PYDV, four RYSV, one RPV, one RLBV, and one RLRV genes (Figure 5). The results categorized RSMV and other plant virus protein family members into five subgroups: Clade I through to Clade V. Among these, Clade V was the largest, comprising 26 members (44.83%), while Clade I and III contained only RSMV P3 and RYSV M proteins, respectively (Figure 5). The total genes list with the descriptions used in this study are summarized in Table 1.

9. RSMV Disease Control Strategies

Even the genome of plant viruses is very simple; however, their dynamic genomic diversity, structure and evolution, incredibly successful transmission ability, broad adaption potential to diverse environments, and inadequacy of management strategies make them exceptionally difficult to control. From studies on the prevention and control of viral infections, several control methods have been established [79,80,81,82,83]. Even though RSMV infection is newly detected, its rate is increasing drastically as vector populations are unexpectedly becoming much more common and widespread [17]. Moreover, an exclusive understanding of the infection system, damages, losses, and mode of prevention is under examination. Even then, few preventive measures have been implemented; however, it is still unrealistic to conclude that prevention is perfect. Therefore, this novel infection should be treated with exceptional care to minimize the risk of further outbreaks. Even though traditional disease management strategies have a long history, they often show limitations in control efficiency, with multiple drawbacks. Chemical-based strategies are less reliable because pathogens’ resistance, the destruction of non-target organisms, and environmental pollution are associated drawbacks [84]. Considering these scenarios, sustainable and effective strategies are needed against RSMV infection. It should be considered that, to achieve this, the mindset should not be focused only on the agronomic yield of a crop but rather on the comprehensive integration of productivity with associated ecological, economic, and environmental dimensions. Some of the strategies we describe here could be implemented to combat RSMV infection.

9.1. Use of Resistant Rice Varieties

For the foreseeable future, a safer and efficient major approach of preventing and controlling rice virus infection and disease is the breeding and planting of resistant rice types. The development of inherent disease resistance in rice varieties through different breeding strategies provides an environmentally friendly approach to plant disease management [85]. Breeding programs should be focused on developing cultivars with genetic resistance against the virus. Moreover, transgenic rice plants with miRNA that directly target virus genes may also have effective disease resistance. For example, the expression of artificial miRNA targeting RSV MP have shown strong resistance to RSV in transgenic rice plants [86]. In addition, integrating the current knowledge of miRNA with conventional and modern molecular breeding technologies could be a well-adapted approach for developing resistant rice varieties [87,88]. Antiviral breeding processes for resistance are limited due the limitations of antiviral gene resources; however, several strategies for viral resistance have been employed, including the encapsulation of viral genomes, silencing of viral genes, expression of ribozyme, or modification of host factors. For example, the expression of the RNA-dependent RNA polymerase of rice yellow mottle virus (RYMV) was found to be resistant to RYMV strains and even showed the complete suppression of virus multiplication [89]. These resistant varieties can significantly reduce the incidence and severity of RSMV infection. Even though resistant rice varieties are effective against viruses, few varieties have been generated yet. Many resistant genes have been identified for several viruses, such as the RSV-resistant gene, stv-b, which has successfully controlled RSV in Japan [21,90]. However, resistance to RSMV still requires ongoing work on breeding and screening rice cultivars. Therefore, there is an urgent need to identify and use more resistant gene resources in future breeding. There are still ways to develop a new model in rice breeding by integrating the existing techniques in order to create resistance cultivars for RSMV.

9.2. Seed Treatment and Seedling Management

Seed treatment with hot water, aerated steam, dry heat, or mild chemical treatments can help to reduce RSMV transmission through infected seeds. Heat treatment at a specific temperature for a specific duration can eliminate the virus from infected seeds without affecting seed viability [91]. Microbial seed treatments may also control seed-borne pathogens and pathogenic soil-borne inoculum [92]. Seedlings are more susceptible to viruses, which can result in significant yield losses. The severity of the symptoms is directly related to the timing of the infection, with earlier infections leading to more severe symptoms [83]. Therefore, it is crucial to determine effective methods for protecting rice seedlings from viral infections in nurseries. Some of the most common, economical, and effective preventive measures have been practiced for viral diseases in rice. These measures include timing the plantation to avoid high vector populations in the tropical rice-growing region, which greatly reduces seedling disease. Another measure is covering the seedling beds with insect-proof nets to protect the seedlings from viruliferous insects [93,94,95]. Additionally, growing seedlings in a greenhouse has also been found to be effective.

9.3. Monitoring and Surveillance

The regular monitoring and surveillance of RSMV infection in rice fields might help to detect early infections, which would facilitate the establishment of timely disease management practices. Early detection allows for prompt action to prevent further spread and minimize losses in crop yields. Early monitoring would allow for the detection of diseased seedlings and facilitate their replacement with healthy ones. In cases where fields are severely affected, they may need to be abandoned and replaced with other crops [83,96,97,98].

9.4. Sanitation and Crop Rotation

Practicing good sanitation in fields is crucial to reducing the spread of RSMV. Infected plants should be promptly removed and destroyed to prevent further transmission. Destroying other crops by irrigating the field after plowing will also help in getting rid of the disease sources [17]. Crop rotation has been widely accepted as an economically and ecologically sustainable method for managing plant disease. Crop rotation with non-host crops can break the virus–host–disease cycle, which might reduce the risk of infection in the subsequent rice cultivation. By reducing overwintering, as well as summer vectors’ establishments in the winter, the severe spreading of infection could be prevented.

9.5. Vector Management and Cultural Practices

Planthoppers are the primary insect vector responsible for transmitting RSMV from one plant to another. Implementing strategies to manage their populations would be an effective approach for controlling the spread of diseases transmitted by these vectors. This can be achieved through the use of insecticides, biological control agents, or cultural practices to reduce vector populations. For example, NC-170 [4-chloro-5- (6-chloro-3-pyridylmethoxy)-2-(3, 4-dichlorophenyl)-pyridazin-3(2H)-one] has strongly inhibited the metamorphosis, oviposition, and embryogenesis of R. dorsalis, and the affected insects could not develop into normal adults [99]. The populations of the leafhopper (Nephotettix virescens) have been controlled by natural enemies such as damselflies (Odonata: Coenagrionidae) and a fungal disease of the hopper [100]. Now, it is time to switch to an integrated pest management strategy, carefully balancing plant health care with cultural and chemical control, even if it cannot outsmart these vectors.
Implementing cultural practices can aid in controlling RSMV. Adjusting planting dates to avoid peak vector populations, maintaining optimal plant nutrition, and avoiding excessive nitrogen fertilization can help to reduce the attractiveness of rice plants to the virus and vectors [101]. The removal of rice ratoons by ploughing paddy fields after harvest and excluding grass from the soil of paddy fields have both been shown to be effective in reducing rice disease [12,102].

9.6. Molecular Breeding and Biotechnological Approaches

Disease-resistant crop varieties have been developed by plant breeding methods in the past. Advancements in molecular breeding techniques, such as whole-genome sequencing, marker-assisted selection, and QTL detection, can enhance the accuracy of breeding practices to develop rice varieties resistant to RSMV. These techniques enable the identification and selection of specific genes associated with resistance, leading to faster and more precise breeding efforts. Additionally, the genetic engineering and biotechnology approaches involved in the direct alteration of an organism’s genetic material, which allows for addition, deletion and modification at a desired position in the genome, enables the production of crops with desired agronomic qualities. Using the quantitative trait nucleotides (QTNs) technique, Wu et al. [7] identified seven QTNs significantly associated with viral tolerance and suggested the possibility of investigating the genetic mechanisms of rice viral resistance using the QTNs technique, and we suggest this could also be applicable in RSMV disease control.
Biotechnological tools, such as RNA interference (RNAi), offer promising avenues for the targeted manipulation of host or viral genes to enhance resistance against RSMV. RNAi is used to suppress viral gene expression, while genome editing can create specific modifications in rice genes associated with virus recognition and defense. Moreover, in order to prevent or mitigate the impact of diseases from RSMV, it is important to characterize the functions of all RSMV proteins. Additionally, efforts should be made to identify RSMV resistance genes as soon as possible. Until now, more than 60 economically important plant virus species have been successfully targeted using RNAi technology [103]. According to Chen et al. [104], viral coat proteins can serve as biochemical targets for antiviral compounds. This discovery may offer valuable insights for the future development of safe and effective antiviral pesticides. A bean variety resistant to the DNA virus bean golden mosaic virus (BGMV) has been developed using RNAi [105]. Successful resistant rice has been generated against rice tungro bacilliform virus (RTBV) and rice tungro spherical virus (RTSV) through RNAi technology [106,107,108]. Viral glycoprotein NSvs2-N has mediated RSV infection in the small brown planthopper (SBPH) vector’s midgut. Transgenic rice harboring the exogenous NSvs2-N gene has restricted RSV acquisition and transmission by SBPHs [109].
The other genome editing technology, clustered regularly interspaced palindromic repeats (CRISPR), and CRISPR-associated protein 9 (Cas9) endonucleases have been implemented exclusively in resistant breeding [110]. The CRISPR/Cas9 system has facilitated targeted mutagenesis precisely in plants to boost resistance to specified diseases. Rice resistance to the rice blast disease has been enhanced by this system through the targeting of the negative regulators related to the defense mechanism [111]. Combining CRISPR–Cas9 gene editing with RNAi can create a synergistic effect, resulting in increased resistance against RSMV in rice. This approach allows for targeting multiple genes and enhancing defense mechanisms, potentially leading to higher levels of virus resistance in rice. Rice tungro disease (RTD) is caused by interactions between rice tungro spherical virus (RTSV) and rice tungro bacilliform virus (RTBV). Mutations in the translation initiation factor 4 gamma (eIF4G) from using CRISPR/Cas9 in the RTSV-susceptible rice variety IR64 has conferred resistance to RTSV [112].
The viral genome also has been edited by CRISPR/Cas9, which renders the virus unfit for replication and transcription. Wheat dwarf virus (WDV) [113] and beet severe curly top virus (BSCTV) [114] have been edited to develop resistant crops. The Southern rice black-streaked dwarf virus (SRBSDV) RNA genome has been edited using CRISPR/Cas9 technology and transferred into rice, conferring significant resistance against SRBSDV [115]. A transgenic rice plant harboring the CRISPR/Cas13a system targeting the single strand RNA genome of RSMV has exhibited potential resistance against RSMV [115]. Recently, the application of this technology for viral disease resistance has been extensively reviewed by Muha-Ud-Din et al. [116].

9.7. Chemical Pesticides

Even though pesticides may cause some unexpected environmental and ecological damages and side effects and lose efficacy due to pathogen evolution, their regulated use can provide a level of protection from plant diseases caused by pathogens [117,118]. The overwintering or first generation of the vectors can be controlled by applying prescribed and prudent pesticides, which can help to significantly suppress RSMV transmission. They are also used in rice seedlings and seedbeds to reduce the population of the vectors and minimize transmission. For maximizing the chemicals’ efficiency and reduce their application, multicomponent disease forecasting would help in the affordable use of agrochemicals; this includes understanding the functional activity of agrochemicals, the type and level of resistance present in pathogens, host resistance and pathogen infectivity, the pathotypes infecting hosts, and the type and level of agrochemicals to be used [119]. The development of chemical agents that are safe and efficient for regulating RSMV, such as dufulin, amino oligosaccharide, and moroxydine hydrochloride, which have been used for the treatment of viral diseases, is also crucial [104].

9.8. Plant Extracts and Nanotechnology

The application of plant extracts might be a promising sustainable method to induce systemic resistance against viruses. The application of Pseudomonas fluorescence and Azospirillum irakense at 108 CFU (colony forming unit)/mL, sea force extract (organic fertilizer prepared from sea algae extracts supplemented with microelements), and Elsa fungicide at 1 mL/L has induced systemic resistance in wheat and barley against barley yellow dwarf virus (BYDV) [120]. Ailanthus altissima extracts have been applied against rice stripe virus [121]. Moreover, plant extracts combined with nanoparticles would also be an effective agent for eliminating viruses. Nanoparticles and nanoscale delivery systems can be utilized to target the delivery of antiviral agents, siRNAs, or CRISPR components into rice cells. Nanotechnology offers precise and efficient delivery mechanisms, enabling the effective control of RSMV with a reduced environmental impact. Numerous studies and reviews in recent times reflect the exponentially rising interest of phytopathogen researchers in the antiviral properties of nanoparticles [122,123]. A comprehensive model (Figure 6) for the application of nanoparticles in crop disease management has been proposed recently by Farooq at al. [122].
Even though a large amount of research has been conducted on nanoparticle-based disease management for many crops, research related to rice viruses is limited. In a leaf-detached assay, Kora et al. (2020) used 30-day-old rice leaf powder for silver nanoparticle (AgNP) synthesis, where 20 ppm of AgNP completely controlled sheath blight disease in rice [124]. Biosynthesized zinc oxide nanoparticles (ZnO NPs) from mangosteen peel have exhibited the significant inhibition of rice blight pathogen (Xanthomonas oryzae pv.) and demonstrated an in vitro 50% inhibitory concentration (IC50) value of 1.895 mg/mL and a minimum inhibitory concentration (MIC) value of 4 mg/mL [125]. AgNPs synthesized from Azadirachta indica (neem) have shown antimicrobial activity against the bacterial leaf blight of rice pathogen, demonstrating 10 ppm of AgNPs provide a better efficacy compared to 200 ppm of streptocycline [126].

9.9. Other Approaches

In addition, precise forecasting is also an effective early preemptive measure for the RSMV epidemic. Recently, the importance of social media has been discussed, and how it can bridge the gap between plant pathology and the public [35]. Social media can be utilized by scientists to communicate with colleagues both within and outside their field, as well as to engage with the public. Current rice farming practices and cultivars also promote RSMV infection and increase vector populations in fields. Additionally, the active growth of ratoon seedlings and harvesting leftovers provides an improved habitat for vectors to survive. In recent times, atmospheric pressure non-thermal plasma has received attention in managing plant diseases [127,128]. Due to its effective antimicrobial activity, plasma can be applied to eliminate pathogenic microbes, and has been applied in tobacco mosaic virus inactivation [129].
Sustainable plant disease management relies on immediate action to reduce the incidence, severity, and frequency of disease epidemics and long-term action to reduce the rate of the evolution of new pathotypes [130]. Therefore, multidisciplinary collaboration between evolutionary plant pathologists and geneticists is needed to design effective management practices that maximize the host plant defense while minimizing the opportunities for pathogens to develop. By integrating these disease control methods, farmers can effectively manage RSMV and reduce its impact on rice production. This will contribute to improved crop yields and agricultural sustainability in adaptive, economic, ecological, and environment friendly ways.
We have summarized potential strategies in Figure 7. This can be used as a guide for early disease detection, the prompt implementation of preventative and control measures, and the assessment of diseases.

10. Conclusions and Future Perspectives

Viruses have the potential to modify their vectors or even incorporate changes in the host that facilitate pathogens’ outbreaks. Therefore, understanding the relationship between plants, viruses, and insects might provide a clue as to how epidemics occur and how to design effective strategies for sustainable disease control. RSMV is a newly discovered and potentially distinct rice virus. Since RSMV infection is not well studied yet, many of the signs and symptoms of this infection may still be unidentified. Considering this situation, our review highlighted the latest innovations in RSMV and demonstrated the geographical distribution and occurrence of the infection, specifically in regions within China, using the fundamental information in field surveys. This review also studied RSMV infection by considering fields’ ecological conditions, along with the symptoms, cause of yield losses, disease cycle, and disease management. Our disseminated data and suggestions might assist rice growers, consumers, and scientists in the future to make strategic decisions in the development of prevention and disease control policies. The implementation of improved disease control policies can help farmers to minimize losses in crop yields and grain quality, as well as enhance food security. This can lead to higher crop yields with safer and more nutritious grains, thereby increasing consumer satisfaction and ensuring a steady supply of grains at reduced prices. This review defined the most recent developments in the prospective investigation guidelines for RSMV and furthered the understanding of the pathogenesis of this virus. This provides a solid foundation for the comprehensive study of RSMV.
Virus outbreaks and the new emergence of rice viruses are very common in nature. We know little about the nature of their existence. Therefore, it is essential to accumulate valuable information on viral biological roles, such as pathogenicity, vector transmission, and viral replication, in order to fully understand the RSMV disease cycle and to develop effective tools for sustainable disease control. The future perspective for controlling RSMV involves integrating cutting-edge technologies, advancing molecular understanding, and implementing sustainable agricultural practices. Here are some actionable insights into potential future directions in RSMV management:
High-throughput omics technologies, like transcriptomics, proteomics, and metabolomics, can be employed to identify key regulatory pathways targeting genetic engineering for disease suppression and controlling the host–pathogen interaction. However, it is acknowledgeable that there are varied perspectives on the consumption of genetically engineered foods worldwide. Harnessing beneficial plant–microbe interactions, such as endophytes or mycorrhizal fungi, may enhance the defense mechanisms of rice plants against RSMV. These interactions can induce systemic resistance, priming the plant’s immune system for a faster and stronger response to viral infections. Implementing climate-smart agricultural practices can aid in reducing the impact of RSMV on rice production. Optimal planting dates, efficient water management, and crop diversification can improve crops’ resilience to viral infections. By utilizing big data and artificial intelligence (AI) algorithms, the identification of RSMV resistance can be accelerated, molecular breeding can be facilitated, and disease outbreaks can be predicted. AI can be implemented to analyze genomic data at large scales to detect markers, genomic sequences, or gene clusters that contribute to virus resistance in crops and can help breeders pinpoint key resistance genes by comparing the genetic profiles of resistant and susceptible crops. Also, AI techniques, such as convolutional neural networks (CNNs), can process leaf images to detect sign of infection at early stages. Collaborations between research institutions, private sectors, and farmers’ organizations can foster the sharing of cutting-edge technologies and knowledge for instant disease control. Collaboration among governments, policymakers, and scientists is essential to address potential concerns and promote public acceptance.
Finally, implementing innovative strategies, sustainability, and inclusive partnerships will be key to ensuring adequate rice production for food security in the face of the emerging challenges posed by RSMV and other viral diseases. Given the complexity of biology, it will be necessary to combine several methodologies and work together with plant pathologists, molecular biologists, and entomologists to gain a better understanding of the interactions between RSMV, vectors, and rice.

Author Contributions

Conceptualization, M.A.M.-u., M.N.M. and S.G.K.; software, M.A.M.-u., S.A.J. and M.R.C.; validation, M.N.M., M.F.R. and S.G.K.; formal analysis, M.A.M.-u., M.N.M., M.R.C. and M.F.R.; investigation, M.N.M., M.F.R. and S.G.K.; resources, M.N.M.; data curation, M.A.M.-u., S.A.J. and M.R.C.; writing—original draft preparation, M.A.M.-u.; writing—review and editing, M.N.M., S.A.J., M.F.R. and S.G.K.; visualization, M.N.M.; supervision, M.N.M.; project administration, M.N.M.; funding acquisition, M.N.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are within the text.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Yang, X.; Zhang, T.; Chen, B.; Zhou, G. Transmission biology of rice stripe mosaic virus by an efficient insect vector Recilia dorsalis (Hemiptera: Cicadellidae). Front. Microbiol. 2017, 8, 2457. [Google Scholar] [CrossRef] [PubMed]
  2. Lv, M.F.; Xie, L.; Wang, H.F.; Wang, H.D.; Chen, J.P.; Zhang, H.M. Biology of southern rice black-streaked dwarf virus: A novel fijivirus emerging in East Asia. Plant Pathol. 2017, 66, 515–521. [Google Scholar] [CrossRef]
  3. Guo, L.; Wu, J.; Chen, R.; Hong, J.; Zhou, X.; Wu, J. Monoclonal antibody-based serological detection of rice stripe mosaic virus infection in rice plants or leafhoppers. Virol. Sin. 2020, 35, 227–234. [Google Scholar] [CrossRef] [PubMed]
  4. Yang, X.; Huang, J.; Liu, C.; Chen, B.; Zhang, T.; Zhou, G. Rice stripe mosaic virus, a novel cytorhabdovirus infecting rice via leafhopper transmission. Front. Microbiol. 2017, 7, 2140. [Google Scholar] [CrossRef] [PubMed]
  5. Jin, L.; Qin, Q.; Wang, Y.; Pu, Y.; Liu, L.; Wen, X.; Ji, S.; Wu, J.; Wei, C.; Ding, B. Rice dwarf virus P2 protein hijacks auxin signaling by directly targeting the rice OsIAA10 protein, enhancing viral infection and disease development. PLoS Pathog. 2016, 12, e1005847. [Google Scholar] [CrossRef] [PubMed]
  6. Gaafar, Y.Z.A.; Richert-Pöggeler, K.R.; Maaß, C.; Vetten, H.-J.; Ziebell, H. Characterisation of a novel nucleorhabdovirus infecting alfalfa (Medicago sativa). Virol. J. 2019, 16, 55. [Google Scholar] [CrossRef]
  7. Wu, J.-G.; Yang, G.-Y.; Zhao, S.-S.; Zhang, S.; Qin, B.-X.; Zhu, Y.-S.; Xie, H.-T.; Chang, Q.; Wang, L.; Hu, J.; et al. Current rice production is highly vulnerable to insect-borne viral diseases. Natl. Sci. Rev. 2022, 9, nwac131. [Google Scholar] [CrossRef]
  8. Gao, Q.; Xu, W.Y.; Yan, T.; Fang, X.D.; Cao, Q.; Zhang, Z.J.; Ding, Z.H.; Wang, Y.; Wang, X.B. Rescue of a plant cytorhabdovirus as versatile expression platforms for planthopper and cereal genomic studies. New Phytol. 2019, 223, 2120–2133. [Google Scholar] [CrossRef]
  9. Huang, Y. Discussion on the occurrence and control countermeasures of rice yellow dwarf virus. J. Guangxi Agric. 2015, 30, 15–17. [Google Scholar]
  10. Huang, R.; Li, Y.; Tang, G.; Hui, S.; Yang, Z.; Zhao, J.; Liu, H.; Cao, J.; Yuan, M. Dynamic phytohormone profiling of rice upon rice black-streaked dwarf virus invasion. J. Plant Physiol. 2018, 228, 92–100. [Google Scholar] [CrossRef]
  11. Li, S.; Hao, W.; Lu, G.; Huang, J.; Liu, C.; Zhou, G. Occurrence and identification of a new vector of rice orange leaf phytoplasma in South China. Plant Dis. 2015, 99, 1483–1487. [Google Scholar] [CrossRef] [PubMed]
  12. Shiba, T.; Hirae, M.; Hayano-Saito, Y.; Ohto, Y.; Uematsu, H.; Sugiyama, A.; Okuda, M. Spread and yield loss mechanisms of rice stripe disease in rice paddies. Field Crop. Res. 2018, 217, 211–217. [Google Scholar] [CrossRef]
  13. Sun, K.; Zhou, X.; Lin, W.; Zhou, X.; Jackson, A.O.; Li, Z. Matrix-glycoprotein interactions required for budding of a plant nucleorhabdovirus and induction of inner nuclear membrane invagination. Mol. Plant Pathol. 2018, 19, 2288–2301. [Google Scholar] [CrossRef]
  14. Towata, T.; Matsukura, K.; Sanada-Morimura, S.; Matsumura, M. Varietal differences in ovicidal response to the white-backed planthopper Sogatella furcifera (Hemiptera: Delphacidae) and susceptibility to Southern rice black-streaked dwarf virus in rice. Appl. Entomol. Zool. 2017, 52, 615–621. [Google Scholar] [CrossRef]
  15. Chen, S.; Li, W.; Huang, X.; Chen, B.; Zhang, T.; Zhou, G. Symptoms and yield loss caused by rice stripe mosaic virus. Virol. J. 2019, 16, 145. [Google Scholar] [CrossRef]
  16. Wang, H.; Liu, Y.; Mo, L.; Huo, C.; Wang, Z.; Zhong, P.; Jia, D.; Zhang, X.; Chen, Q.; Chen, H. A neuron-specific antiviral mechanism modulates the persistent infection of rice rhabdoviruses in leafhopper vectors. Front. Microbiol. 2020, 11, 513. [Google Scholar] [CrossRef]
  17. Wang, Z.; Chen, B.; Zhang, T.; Zhou, G.; Yang, X. Rice stripe mosaic disease: Characteristics and control strategies. Front. Microbiol. 2021, 12, 715223. [Google Scholar] [CrossRef]
  18. Zhao, P.; Sun, X.; Li, P.; Sun, J.; Yue, Y.; Wei, J.; Wei, T.; Jia, D. Infection characteristics of rice stripe mosaic virus in the body of the vector leafhoppers. Front. Microbiol. 2019, 9, 3258. [Google Scholar] [CrossRef]
  19. Zhang, C.; Chen, D.; Yang, G.; Yu, X.; Wu, J. Rice stripe mosaic virus–encoded P4 is a weak suppressor of viral RNA silencing and is required for disease symptom development. Mol. Plant-Microbe Interact. 2020, 33, 412–422. [Google Scholar] [CrossRef]
  20. Yazdkhasti, E.; Hopkins, R.J.; Kvarnheden, A. Reservoirs of plant virus disease: Occurrence of wheat dwarf virus and barley/cereal yellow dwarf viruses in Sweden. Plant Pathol. 2021, 70, 1552–1561. [Google Scholar] [CrossRef]
  21. Zhou, X.; Sun, K.; Zhou, X.; Jackson, A.O.; Li, Z. The matrix protein of a plant rhabdovirus mediates superinfection exclusion by inhibiting viral transcription. J. Virol. 2019, 93, e00680-19. [Google Scholar] [CrossRef] [PubMed]
  22. Li, L.; Zhang, H.; Chen, C.; Huang, H.; Tan, X.; Wei, Z.; Li, J.; Yan, F.; Zhang, C.; Chen, J. A class of independently evolved transcriptional repressors in plant RNA viruses facilitates viral infection and vector feeding. Proc. Natl. Acad. Sci. USA 2021, 118, e2016673118. [Google Scholar] [CrossRef] [PubMed]
  23. Xu, Y.; Fu, S.; Tao, X.; Zhou, X. Rice stripe virus: Exploring molecular weapons in the arsenal of a negative-sense RNA virus. Annu. Rev. Phytopathol. 2021, 59, 351–371. [Google Scholar] [CrossRef] [PubMed]
  24. Zhou, X.; Lin, W.; Sun, K.; Wang, S.; Zhou, X.; Jackson, A.O.; Li, Z. Specificity of plant rhabdovirus cell-to-cell movement. J. Virol. 2019, 93, e00296-19. [Google Scholar] [CrossRef] [PubMed]
  25. Jia, D.; Liang, Q.; Chen, H.; Liu, H.; Li, G.; Zhang, X.; Chen, Q.; Wang, A.; Wei, T. Autophagy mediates a direct synergistic interaction during co-transmission of two distinct arboviruses by insect vectors. Sci. China Life Sci. 2023, 66, 1665–1681. [Google Scholar] [CrossRef]
  26. Jia, D.; Liu, H.; Zhang, J.; Wan, W.; Wang, Z.; Zhang, X.; Chen, Q.; Wei, T. Polyamine-metabolizing enzymes are activated to promote the proper assembly of rice stripe mosaic virus in insect vectors. Stress Biol. 2022, 2, 10. [Google Scholar] [CrossRef]
  27. Yang, X.; Chen, B.; Zhang, T.; Li, Z.; Xu, C.; Zhou, G. Geographic distribution and genetic diversity of rice stripe mosaic virus in southern China. Front. Microbiol. 2018, 9, 3068. [Google Scholar] [CrossRef]
  28. He, D.-c.; Zhan, J.-s.; Xie, L.-h. Problems, challenges and future of plant disease management: From an ecological point of view. J. Integr. Agric. 2016, 15, 705–715. [Google Scholar] [CrossRef]
  29. Rural Development Administration. Available online: https://www.rda.go.kr/board/board.do?boardId=farmprmninfo&prgId=day_farmprmninfoEntry&mode=updateCnt&searchOrgDeptKey=org&dataNo=100000798530 (accessed on 6 September 2024).
  30. Li, P.; Zhang, J.; Yue, Y.; Chen, H.; Wu, W.; Wei, T.; Jia, D. Effects of Rice stripe mosaic virus on the growth, reproduction and feeding behavior of the vector Recilia dorsalis (Hemiptera: Cicadellidae). Acta Entomol. Sin. 2020, 63, 174–180. [Google Scholar]
  31. Jones, R.A.C.; Sharman, M.; Trębicki, P.; Maina, S.; Congdon, B.S. Virus diseases of cereal and oilseed crops in Australia: Current position and future challenges. Viruses 2021, 13, 2051. [Google Scholar] [CrossRef]
  32. Adhab, M.; Al-Kuwaiti, N.; Al-Ani, R. Biodiversity and occurrence of plant viruses over four decades: Case study for Iraq. In Proceedings of the 2021 Third International Sustainability and Resilience Conference: Climate Change, Online, 15–16 November 2021; pp. 159–163. [Google Scholar]
  33. Savary, S.; Willocquet, L.; Pethybridge, S.J.; Esker, P.; McRoberts, N.; Nelson, A. The global burden of pathogens and pests on major food crops. Nat. Ecol. Evol. 2019, 3, 430–439. [Google Scholar] [CrossRef] [PubMed]
  34. Oerke, E.C. Crop losses to pests. J. Agric. Sci. 2006, 144, 31–43. [Google Scholar] [CrossRef]
  35. Oakley, B. From laboratory to laptop: How science communication can bridge the gap between plant pathology and the public. Physiol. Mol. Plant Pathol. 2023, 125, 102032. [Google Scholar] [CrossRef]
  36. Adhab, M.; Angel, C.; Rodriguez, A.; Fereidouni, M.; Király, L.; Scheets, K.; Schoelz, J.E. Tracing the Lineage of Two Traits Associated with the Coat Protein of the Tombusviridae: Silencing Suppression and HR Elicitation in Nicotiana Species. Viruses 2019, 11, 588. [Google Scholar] [CrossRef]
  37. Adhab, M.; Finke, D.; Schoelz, J. Turnip aphids (Lipaphis erysimi) discriminate host plants based on the strain of Cauliflower mosaic virus infection. Emir. J. Food Agric. 2019, 31, 69–75. [Google Scholar]
  38. Hogenhout, S.A.; Ammar, E.-D.; Whitfield, A.E.; Redinbaugh, M.G. Insect vector interactions with persistently transmitted viruses. Annu. Rev. Phytopathol. 2008, 46, 327–359. [Google Scholar] [CrossRef]
  39. Zheng, L.; Mao, Q.; Xie, L.; Wei, T. Infection route of rice grassy stunt virus, a tenuivirus, in the body of its brown planthopper vector, Nilaparvata lugens (Hemiptera: Delphacidae) after ingestion of virus. Virus Res. 2014, 188, 170–173. [Google Scholar] [CrossRef]
  40. Wu, W.; Zheng, L.; Chen, H.; Jia, D.; Li, F.; Wei, T. Nonstructural Protein NS4 of Rice Stripe Virus Plays a Critical Role in Viral Spread in the Body of Vector Insects. PLoS ONE 2014, 9, e88636. [Google Scholar] [CrossRef]
  41. Syller, J. Facilitative and antagonistic interactions between plant viruses in mixed infections. Mol. Plant Pathol. 2012, 13, 204–216. [Google Scholar] [CrossRef]
  42. Rodrigues, N.B.; Godoy, R.S.M.; Orfano, A.S.; Chaves, B.A.; Campolina, T.B.; Costa, B.d.A.; Félix, L.d.S.; Silva, B.M.; Norris, D.E.; Pimenta, P.F.P.; et al. Brazilian Aedes aegypti as a Competent Vector for Multiple Complex Arboviral Coinfections. J. Infect. Dis. 2021, 224, 101–108. [Google Scholar] [CrossRef]
  43. Chávez-Calvillo, G.; Contreras-Paredes, C.A.; Mora-Macias, J.; Noa-Carrazana, J.C.; Serrano-Rubio, A.A.; Dinkova, T.D.; Carrillo-Tripp, M.; Silva-Rosales, L. Antagonism or synergism between papaya ringspot virus and papaya mosaic virus in Carica papaya is determined by their order of infection. Virology 2016, 489, 179–191. [Google Scholar] [CrossRef] [PubMed]
  44. Kareem, K.T.; Taiwo, M.A. Interactions of viruses in cowpea: Effects on growth and yield parameters. Virol. J. 2007, 4, 15. [Google Scholar] [CrossRef] [PubMed]
  45. Tatineni, S.; Graybosch, R.A.; Hein, G.L.; Wegulo, S.N.; French, R. Wheat cultivar-specific disease synergism and alteration of virus accumulation during co-infection with Wheat streak mosaic virus and Triticum mosaic virus. Phytopathology 2010, 100, 230–238. [Google Scholar] [CrossRef] [PubMed]
  46. Kang, S.-G.; Koo, B.-J.; Lee, E.-T.; Chang, M.-U. Allexivirus transmitted by eriophyid mites in garlic plants. J. Microbiol. Biotechnol. 2007, 17, 1833–1840. [Google Scholar]
  47. Xie, L.H. Research on rice virus disease in China. Trop. Agric. Res. 1986, 19, 45–50. [Google Scholar]
  48. Jia, D.; Luo, G.; Shi, W.; Liu, Y.; Liu, H.; Zhang, X.; Wei, T. Rice Gall Dwarf Virus Promotes the Propagation and Transmission of Rice Stripe Mosaic Virus by Co-infected Insect Vectors. Front. Microbiol. 2022, 13, 834712. [Google Scholar] [CrossRef]
  49. West, J.S.; Holdgate, S.; Townsend, J.A.; Edwards, S.G.; Jennings, P.; Fitt, B.D.L. Impacts of changing climate and agronomic factors on fusarium ear blight of wheat in the UK. Fungal Ecol. 2012, 5, 53–61. [Google Scholar] [CrossRef]
  50. Albahri, G.; Alyamani, A.A.; Badran, A.; Hijazi, A.; Nasser, M.; Maresca, M.; Baydoun, E. Enhancing essential grains yield for sustainable food security and bio-safe agriculture through latest innovative approaches. Agronomy 2023, 13, 1709. [Google Scholar] [CrossRef]
  51. Schoelz, J.E.; Adhab, M. Caulimoviruses (Caulimoviridae). In Encyclopedia of Virology, 4th ed.; Bamford, D.H., Zuckerman, M., Eds.; Academic Press: Oxford, UK, 2021; pp. 313–321. [Google Scholar]
  52. Suresh, N.T.; Ravindran, V.E.; Krishnakumar, U. A computational framework to identify cross association between complex disorders by protein-protein interaction network analysis. Curr. Bioinform. 2021, 16, 433–445. [Google Scholar] [CrossRef]
  53. Basar, M.A.; Hosen, M.F.; Paul, B.K.; Hasan, M.R.; Shamim, S.M.; Bhuyian, T. Identification of drug and protein-protein interaction network among stress and depression: A bioinformatics approach. Inform. Med. Unlocked 2023, 37, 101174. [Google Scholar] [CrossRef]
  54. Tamura, K.; Stecher, G.; Kumar, S. MEGA11: Molecular evolutionary genetics analysis version 11. Mol. Biol. Evol. 2021, 38, 3022–3027. [Google Scholar] [CrossRef] [PubMed]
  55. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [PubMed]
  56. Letunic, I.; Bork, P. Interactive Tree Of Life (iTOL) v5: An online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021, 49, W293–W296. [Google Scholar] [CrossRef] [PubMed]
  57. Ruedas, J.B.; Perrault, J. Insertion of Enhanced Green Fluorescent Protein in a Hinge Region of Vesicular Stomatitis Virus L Polymerase Protein Creates a Temperature-Sensitive Virus That Displays No Virion-Associated Polymerase Activity In Vitro. J. Virol. 2009, 83, 12241–12252. [Google Scholar] [CrossRef] [PubMed]
  58. Luo, M.; Green, T.J.; Zhang, X.; Tsao, J.; Qiu, S. Conserved characteristics of the rhabdovirus nucleoprotein. Virus Res. 2007, 129, 246–251. [Google Scholar] [CrossRef]
  59. Bejerman, N.; Giolitti, F.; De Breuil, S.; Trucco, V.; Nome, C.; Lenardon, S.; Dietzgen, R.G. Complete genome sequence and integrated protein localization and interaction map for alfalfa dwarf virus, which combines properties of both cytoplasmic and nuclear plant rhabdoviruses. Virology 2015, 483, 275–283. [Google Scholar] [CrossRef]
  60. Yan, T.; Zhu, J.-R.; Di, D.; Gao, Q.; Zhang, Y.; Zhang, A.; Yan, C.; Miao, H.; Wang, X.-B. Characterization of the complete genome of Barley yellow striate mosaic virus reveals a nested gene encoding a small hydrophobic protein. Virology 2015, 478, 112–122. [Google Scholar] [CrossRef]
  61. Jackson, A.O.; Dietzgen, R.G.; Goodin, M.M.; Bragg, J.N.; Deng, M. Biology of plant rhabdoviruses. Annu. Rev. Phytopathol. 2005, 43, 623–660. [Google Scholar] [CrossRef]
  62. Higgins, C.M.; Bejerman, N.; Li, M.; James, A.P.; Dietzgen, R.G.; Pearson, M.N.; Revill, P.A.; Harding, R.M. Complete genome sequence of Colocasia bobone disease-associated virus, a putative cytorhabdovirus infecting taro. Arch. Virol. 2016, 161, 745–748. [Google Scholar] [CrossRef]
  63. Ramalho, T.O.; Figueira, A.R.; Sotero, A.J.; Wang, R.; Duarte, P.S.G.; Farman, M.; Goodin, M.M. Characterization of Coffee ringspot virus-Lavras: A model for an emerging threat to coffee production and quality. Virology 2014, 464, 385–396. [Google Scholar] [CrossRef]
  64. Sasaya, T.; Kusaba, S.; Ishikawa, K.; Koganezawa, H. Nucleotide sequence of RNA2 of Lettuce big-vein virus and evidence for a possible transcription termination/initiation strategy similar to that of rhabdoviruses. J. Gen. Virol. 2004, 85, 2709–2717. [Google Scholar] [CrossRef] [PubMed]
  65. Dietzgen, R.G.; Innes, D.J.; Bejerman, N. Complete genome sequence and intracellular protein localization of Datura yellow vein nucleorhabdovirus. Virus Res. 2015, 205, 7–11. [Google Scholar] [CrossRef] [PubMed]
  66. Zhai, Y.; Miglino, R.; Sorrentino, R.; Masenga, V.; Alioto, D.; Pappu, H.R. Complete genomic characterization of eggplant mottled dwarf virus from Agapanthus sp. By deep sequencing and de novo assembly. J. Plant Pathol. 2014, 96, 593–595. [Google Scholar]
  67. Dietzgen, R.G.; Callaghan, B.; Wetzel, T.; Dale, J.L. Completion of the genome sequence of Lettuce necrotic yellows virus, type species of the genus Cytorhabdovirus. Virus Res. 2006, 118, 16–22. [Google Scholar] [CrossRef]
  68. Heim, F.; Lot, H.; Delecolle, B.; Bassler, A.; Krczal, G.; Wetzel, T. Complete nucleotide sequence of a putative new cytorhabdovirus infecting lettuce. Arch. Virol. 2008, 153, 81–92. [Google Scholar] [CrossRef]
  69. Tsai, C.-W.; Redinbaugh, M.G.; Willie, K.J.; Reed, S.; Goodin, M.; Hogenhout, S.A. Complete genome sequence and in planta subcellular localization of maize fine streak virus proteins. J. Virol. 2005, 79, 5304–5314. [Google Scholar] [CrossRef]
  70. Ghorbani, A.; Izadpanah, K.; Dietzgen, R.G. Completed sequence and corrected annotation of the genome of maize Iranian mosaic virus. Arch. Virol. 2018, 163, 767–770. [Google Scholar] [CrossRef]
  71. Reed, S.E.; Tsai, C.-W.; Willie, K.J.; Redinbaugh, M.G.; Hogenhout, S.A. Shotgun sequencing of the negative-sense RNA genome of the rhabdovirus Maize mosaic virus. J. Virol. Methods 2005, 129, 91–96. [Google Scholar] [CrossRef]
  72. Tanno, F.; Nakatsu, A.; Toriyama, S.; Kojima, M. Complete nucleotide sequence of Northern cereal mosaic virus and its genome organization. Arch. Virol. 2000, 145, 1373–1384. [Google Scholar] [CrossRef]
  73. Kondo, H.; Maruyama, K.; Chiba, S.; Andika, I.B.; Suzuki, N. Transcriptional mapping of the messenger and leader RNAs of orchid fleck virus, a bisegmented negative-strand RNA virus. Virology 2014, 452, 166–174. [Google Scholar] [CrossRef]
  74. Ghosh, D.; Brooks, R.E.; Wang, R.; Lesnaw, J.; Goodin, M.M. Cloning and subcellular localization of the phosphoprotein and nucleocapsid proteins of Potato yellow dwarf virus, type species of the genus Nucleorhabdovirus. Virus Res. 2008, 135, 26–35. [Google Scholar] [CrossRef] [PubMed]
  75. Huang, Y.; Zhao, H.; Luo, Z.; Chen, X.; Fang, R.-X. Novel structure of the genome of Rice yellow stunt virus: Identification of the gene 6-encoded virion protein. J. Gen. Virol. 2003, 84, 2259–2264. [Google Scholar] [CrossRef] [PubMed]
  76. Chao, S.; Wang, H.; Zhang, S.; Chen, G.; Mao, C.; Hu, Y.; Yu, F.; Wang, S.; Lv, L.; Chen, L. Novel RNA Viruses Discovered in Weeds in Rice Fields. Viruses 2022, 14, 2489. [Google Scholar] [CrossRef] [PubMed]
  77. McGavin, W.J.; Mitchell, C.; Cock, P.J.A.; Wright, K.M.; MacFarlane, S.A. Raspberry leaf blotch virus, a putative new member of the genus Emaravirus, encodes a novel genomic RNA. J. Gen. Virol. 2012, 93, 430–437. [Google Scholar] [CrossRef]
  78. He, Y.; Yang, Z.; Hong, N.; Wang, G.; Ning, G.; Xu, W. Deep sequencing reveals a novel closterovirus associated with wild rose leaf rosette disease. Mol. Plant Pathol. 2015, 16, 449–458. [Google Scholar] [CrossRef]
  79. Hančinský, R.; Mihálik, D.; Mrkvová, M.; Candresse, T.; Glasa, M. Plant viruses infecting Solanaceae family members in the cultivated and wild environments: A review. Plants 2020, 9, 667. [Google Scholar] [CrossRef]
  80. Korbecka-Glinka, G.; Przybyś, M.; Feledyn-Szewczyk, B. A survey of five plant viruses in weeds and tobacco in Poland. Agronomy 2021, 11, 1667. [Google Scholar] [CrossRef]
  81. Makkouk, K.M.; Kumari, S.G. Epidemiology and integrated management of persistently transmitted aphid-borne viruses of legume and cereal crops in West Asia and North Africa. Virus Res. 2009, 141, 209–218. [Google Scholar] [CrossRef]
  82. Souza, T.A.; Macedo, M.A.; Albuquerque, L.C.; Inoue-Nagata, A.K. Host range and natural infection of tomato chlorosis virus in weeds collected in Central Brazil. Trop. Plant Pathol. 2020, 45, 84–90. [Google Scholar] [CrossRef]
  83. Zhou, G.; Xu, D.; Xu, D.; Zhang, M. Southern rice black-streaked dwarf virus: A white-backed planthopper-transmitted fijivirus threatening rice production in Asia. Front. Microbiol. 2013, 4, 270. [Google Scholar] [CrossRef]
  84. Elqdhy, M.b.; Ait Hamza, M.; Askarne, L.; Fossati-Gaschignard, O.; Lakhtar, H.; El Mousadik, A.; Ait Benoumar, A.; Msanda, F.; Boubaker, H. Biology, ecology and control of the Mediterranean fruit fly, Ceratitis capitata (Diptera: Tephritidae), with special reference to biological control using entomopathogenic nematode (EPN): A review. J. Plant Dis. Prot. 2024, 131, 365–402. [Google Scholar] [CrossRef]
  85. Sánchez-Martín, J.; Keller, B. Contribution of recent technological advances to future resistance breeding. Theor. Appl. Genet. 2019, 132, 713–732. [Google Scholar] [CrossRef] [PubMed]
  86. Zhou, L.; Yuan, Q.; Ai, X.; Chen, J.; Lu, Y.; Yan, F. Transgenic Rice Plants Expressing Artificial miRNA Targeting the Rice Stripe Virus MP Gene Are Highly Resistant to the Virus. Biology 2022, 11, 332. [Google Scholar] [CrossRef] [PubMed]
  87. Jabbar, B.; Iqbal, M.S.; Batcho, A.A.; Nasir, I.A.; Rashid, B.; Husnain, T.; Henry, R.J. Target prediction of candidate miRNAs from Oryza sativa for silencing the RYMV genome. Comput. Biol. Chem. 2019, 83, 107127. [Google Scholar] [CrossRef]
  88. Tang, J.; Chu, C. MicroRNAs in crop improvement: Fine-tuners for complex traits. Nat. Plants 2017, 3, 17077. [Google Scholar] [CrossRef]
  89. Pinto, Y.M.; Kok, R.A.; Baulcombe, D.C. Resistance to rice yellow mottle virus (RYMV) in cultivated African rice varieties containing RYMV transgenes. Nat. Biotechnol. 1999, 17, 702–707. [Google Scholar] [CrossRef]
  90. Kisimoto, R.; Yamada, Y. A planthopper-rice virus epidemiology model: Rice stripe and small brown planthopper, Laodelphax striatellus Fallén. In Plant Virus Epidemics: Monitoring Modelling and Predicting Outbreaks; Academic Press: Sydney, Australia, 1986. [Google Scholar]
  91. Rees, A.R. Effect of Heat-Treatment for Virus Attenuation on Tomato Seed Viability. J. Hortic. Sci. 1970, 45, 33–40. [Google Scholar] [CrossRef]
  92. Koch, E.; Roberts, S.J. Non-chemical Seed Treatment in the Control of Seed-Borne Pathogens. In Global Perspectives on the Health of Seeds and Plant Propagation Material; Gullino, M.L., Munkvold, G., Eds.; Springer: Dordrecht, The Netherlands, 2014; pp. 105–123. [Google Scholar]
  93. Ammar, E.-D.; Tsai, C.-W.; Whitfield, A.E.; Redinbaugh, M.G.; Hogenhout, S.A. Cellular and molecular aspects of rhabdovirus interactions with insect and plant hosts. Annu. Rev. Entomol. 2009, 54, 447–468. [Google Scholar] [CrossRef]
  94. Mrkvová, M.; Hančinský, R.; Predajňa, L.; Alaxin, P.; Achs, A.; Tomašechová, J.; Šoltys, K.; Mihálik, D.; Olmos, A.; Ruiz-García, A.B. High-throughput sequencing discloses the Cucumber mosaic virus (CMV) diversity in Slovakia and reveals new hosts of CMV from the Papaveraceae Family. Plants 2022, 11, 1665. [Google Scholar] [CrossRef]
  95. Sun, F.; Xu, Q.; Chen, Z.; Fan, Y.; Zhou, Y. Advances in rice black-streaked dwarf disease in China. Jiangsu J. Agric. Sci. 2013, 29, 195–201. [Google Scholar]
  96. Chalupniková, J.; Kundu, J.K.; Singh, K.; Bartaková, P.; Beoni, E. Wheat streak mosaic virus: Incidence in field crops, potential reservoir within grass species and uptake in winter wheat cultivars. J. Integr. Agric. 2017, 16, 523–531. [Google Scholar] [CrossRef]
  97. Kormelink, R.; Garcia, M.L.; Goodin, M.; Sasaya, T.; Haenni, A.-L. Negative-strand RNA viruses: The plant-infecting counterparts. Virus Res. 2011, 162, 184–202. [Google Scholar] [CrossRef] [PubMed]
  98. Maliano, M.R.; Macedo, M.A.; Rojas, M.R.; Gilbertson, R.L. Weed-infecting viruses in a tropical agroecosystem present different threats to crops and evolutionary histories. PLoS ONE 2021, 16, e0250066. [Google Scholar] [CrossRef]
  99. Miyake, T.; Haruyama, H.; Ogura, T.; Mitsui, T.; Sakurai, A. Effects of insect juvenile hormone active NC-170 on metamorphosis, oviposition and embryogenesis in leafhoppers. J. Pestic. Sci. 1991, 16, 441–448. [Google Scholar] [CrossRef]
  100. Ooi, A.C. Common insect pests of rice and their natural biological control. J. Agric. Sci. 2015, 1, 49–59. [Google Scholar]
  101. Litsinger, J.A. A farming systems approach to insect pest management for upland and lowland rice farmers in tropical Asia. In Crop Protection Strategies for Subsistence Farmers; CRC Press: Boca Raton, FL, USA, 2019; pp. 45–101. [Google Scholar]
  102. Rashidi, M.; Cruzado, R.K.; Hutchinson, P.J.S.; Bosque-Pérez, N.A.; Marshall, J.M.; Rashed, A. Grassy weeds and corn as potential sources of barley yellow dwarf virus spread into winter wheat. Plant Dis. 2021, 105, 444–449. [Google Scholar] [CrossRef]
  103. Zhao, Y.; Yang, X.; Zhou, G.; Zhang, T. Engineering plant virus resistance: From RNA silencing to genome editing strategies. Plant Biotechnol. J. 2020, 18, 328–336. [Google Scholar] [CrossRef]
  104. Chen, J.; Luo, X.; Chen, Y.; Wang, Y.; Peng, J.; Xing, Z. Recent research progress: Discovery of anti-plant virus agents based on natural scaffold. Front. Chem. 2022, 10, 926202. [Google Scholar] [CrossRef]
  105. Aragão, F.J.L.; Faria, J.C. First transgenic geminivirus-resistant plant in the field. Nat. Biotechnol. 2009, 27, 1086–1088. [Google Scholar] [CrossRef]
  106. Ganesan, U.; Suri, S.S.; Rajasubramaniam, S.; Rajam, M.V.; Dasgupta, I. Transgenic expression of coat protein gene of Rice tungro bacilliform virus in rice reduces the accumulation of viral DNA in inoculated plants. Virus Genes 2009, 39, 113–119. [Google Scholar] [CrossRef]
  107. Verma, V.; Sharma, S.; Devi, S.V.; Rajasubramaniam, S.; Dasgupta, I. Delay in virus accumulation and low virus transmission from transgenic rice plants expressing Rice tungro spherical virus RNA. Virus Genes 2012, 45, 350–359. [Google Scholar] [CrossRef] [PubMed]
  108. Valarmathi, P.; Kumar, G.; Robin, S.; Manonmani, S.; Dasgupta, I.; Rabindran, R. Evaluation of virus resistance and agronomic performance of rice cultivar ASD 16 after transfer of transgene against Rice tungro bacilliform virus by backcross breeding. Virus Genes 2016, 52, 521–529. [Google Scholar] [CrossRef] [PubMed]
  109. Lu, C.; Jin, D.; Zhang, L.; Lu, G.; Ji, Y.; Zhou, Y.; Wang, Y.; Li, S. A rice plant expressing viral glycoprotein NSvc2-NS reduces the transmission of rice stripe virus by the small brown planthopper. Pest Manag. Sci. 2022, 78, 5325–5333. [Google Scholar] [CrossRef] [PubMed]
  110. Shan, Q.; Wang, Y.; Li, J.; Zhang, Y.; Chen, K.; Liang, Z.; Zhang, K.; Liu, J.; Xi, J.J.; Qiu, J.-L. Targeted genome modification of crop plants using a CRISPR-Cas system. Nat. Biotechnol. 2013, 31, 686–688. [Google Scholar] [CrossRef] [PubMed]
  111. Paul, N.C.; Park, S.-W.; Liu, H.; Choi, S.; Ma, J.; MacCready, J.S.; Chilvers, M.I.; Sang, H. Plant and fungal genome editing to enhance plant disease resistance using the CRISPR/Cas9 system. Front. Plant Sci. 2021, 12, 700925. [Google Scholar] [CrossRef]
  112. Macovei, A.; Sevilla, N.R.; Cantos, C.; Jonson, G.B.; Slamet-Loedin, I.; Čermák, T.; Voytas, D.F.; Choi, I.-R.; Chadha-Mohanty, P. Novel alleles of rice eIF4G generated by CRISPR/Cas9-targeted mutagenesis confer resistance to Rice tungro spherical virus. Plant Biotechnol. J. 2018, 16, 1918–1927. [Google Scholar] [CrossRef]
  113. Kis, A.; Hamar, É.; Tholt, G.; Bán, R.; Havelda, Z. Creating highly efficient resistance against wheat dwarf virus in barley by employing CRISPR/Cas9 system. Plant Biotechnol. J. 2019, 17, 1004. [Google Scholar] [CrossRef]
  114. Ji, X.; Zhang, H.; Zhang, Y.; Wang, Y.; Gao, C. Establishing a CRISPR–Cas-like immune system conferring DNA virus resistance in plants. Nat. Plants 2015, 1, 15144. [Google Scholar] [CrossRef]
  115. Zhang, T.; Zhao, Y.; Ye, J.; Cao, X.; Xu, C.; Chen, B.; An, H.; Jiao, Y.; Zhang, F.; Yang, X.; et al. Establishing CRISPR/Cas13a immune system conferring RNA virus resistance in both dicot and monocot plants. Plant Biotechnol. J. 2019, 17, 1185–1187. [Google Scholar] [CrossRef]
  116. Muha-Ud-Din, G.; Ali, F.; Hameed, A.; Naqvi, S.A.H.; Nizamani, M.M.; Jabran, M.; Sarfraz, S.; Yong, W. CRISPR/Cas9-based genome editing: A revolutionary approach for crop improvement and global food security. Physiol. Mol. Plant Pathol. 2024, 129, 102191. [Google Scholar] [CrossRef]
  117. Van Esse, H.P.; Reuber, T.L.; van der Does, D. Genetic modification to improve disease resistance in crops. New Phytol. 2020, 225, 70–86. [Google Scholar] [CrossRef]
  118. McDonald, B.A.; Stukenbrock, E.H. Rapid emergence of pathogens in agro-ecosystems: Global threats to agricultural sustainability and food security. Philos. Trans. R. Soc. B Biol. Sci. 2016, 371, 20160026. [Google Scholar] [CrossRef] [PubMed]
  119. Zhan, J.; Thrall, P.H.; Papaïx, J.; Xie, L.; Burdon, J.J. Playing on a pathogen’s weakness: Using evolution to guide sustainable plant disease control strategies. Annu. Rev. Phytopathol. 2015, 53, 19–43. [Google Scholar] [CrossRef] [PubMed]
  120. Al-Ani, R.A.; Adhab, M.A.; El-Muadhidi, M.A.; Al-Fahad, M.A. Induced systemic resistance and promotion of wheat and barley plants growth by biotic and non-biotic agents against barley yellow dwarf virus. Afr. J. Biotechnol. 2011, 10, 12078–12084. [Google Scholar]
  121. Yang, J.G.; Dang, Y.G.; Li, G.Y.; Guo, L.J.; Wang, W.T.; Tan, Q.W.; Lin, Q.Y.; Wu, Z.J.; Xie, L.H. Note: Anti-viral activity of Ailanthus altissima crude extract on Rice stripe virus in rice suspension cells. Phytoparasitica 2008, 36, 405–408. [Google Scholar] [CrossRef]
  122. Farooq, T.; Adeel, M.; He, Z.; Umar, M.; Shakoor, N.; da Silva, W.; Elmer, W.; White, J.C.; Rui, Y. Nanotechnology and Plant Viruses: An Emerging Disease Management Approach for Resistant Pathogens. ACS Nano 2021, 15, 6030–6037. [Google Scholar] [CrossRef]
  123. Dutta, P.; Kumari, A.; Mahanta, M.; Biswas, K.K.; Dudkiewicz, A.; Thakuria, D.; Abdelrhim, A.S.; Singh, S.B.; Muthukrishnan, G.; Sabarinathan, K.G.; et al. Advances in Nanotechnology as a Potential Alternative for Plant Viral Disease Management. Front. Microbiol. 2022, 13, 935193. [Google Scholar] [CrossRef]
  124. Kora, A.J.; Mounika, J.; Jagadeeshwar, R. Rice leaf extract synthesized silver nanoparticles: An in vitro fungicidal evaluation against Rhizoctonia solani, the causative agent of sheath blight disease in rice. Fungal Biol. 2020, 124, 671–681. [Google Scholar] [CrossRef]
  125. Jaithon, T.; Atichakaro, T.; Phonphoem, W.; Jiraroj, T.; Sreewongchai, T.; T-Thienprasert, N.P. Potential usage of biosynthesized zinc oxide nanoparticles from mangosteen peel ethanol extract to inhibit Xanthomonas oryzae and promote rice growth. Heliyon 2024, 10, e24076. [Google Scholar] [CrossRef]
  126. Mankad, M.; Patil, G.; Patel, D.; Patel, P.; Patel, A. Comparative studies of sunlight mediated green synthesis of silver nanoparaticles from Azadirachta indica leaf extract and its antibacterial effect on Xanthomonas oryzae pv. oryzae. Arab. J. Chem. 2020, 13, 2865–2872. [Google Scholar] [CrossRef]
  127. Ito, M.; Oh, J.S.; Ohta, T.; Shiratani, M.; Hori, M. Current status and future prospects of agricultural applications using atmospheric-pressure plasma technologies. Plasma Process. Polym. 2018, 15, 1700073. [Google Scholar] [CrossRef]
  128. Sakudo, A.; Yagyu, Y.; Onodera, T. Disinfection and sterilization using plasma technology: Fundamentals and future perspectives for biological applications. Int. J. Mol. Sci. 2019, 20, 5216. [Google Scholar] [CrossRef] [PubMed]
  129. Hanbal, S.E.; Takashima, K.; Miyashita, S.; Ando, S.; Ito, K.; Elsharkawy, M.M.; Kaneko, T.; Takahashi, H. Atmospheric-pressure plasma irradiation can disrupt tobacco mosaic virus particles and RNAs to inactivate their infectivity. Arch. Virol. 2018, 163, 2835–2840. [Google Scholar] [CrossRef] [PubMed]
  130. Zhan, J.; Thrall, P.H.; Burdon, J.J. Achieving sustainable plant disease management through evolutionary principles. Trends Plant Sci. 2014, 19, 570–575. [Google Scholar] [CrossRef]
Figure 1. Geographic distribution of RSMV infections over most prevalent provinces in southern China during 2015 to 2019. Steric icons; location of RSMV discovery and Solid triangles; location of RSMV undiscovery (data modified from Wang et al. [17]).
Figure 1. Geographic distribution of RSMV infections over most prevalent provinces in southern China during 2015 to 2019. Steric icons; location of RSMV discovery and Solid triangles; location of RSMV undiscovery (data modified from Wang et al. [17]).
Agronomy 14 02442 g001
Figure 2. The geographic spread of RSMV in China. Samples tested positive in the Guangdong, Guangxi, and Hainan provinces from 2015 to 2022. The sample collection areas and total number of positive cases in different regions are shown in (AC). The prevalence of RSMV in China from 2015 to 2022 is demonstrated here (data from Yang et al. [27] and Chen et al. [15]). The PAST 4.10 software was used to prepare the figure Using the URL https://www.downloadcrew.com/article/34304/past (accessed on 10 August 2023).
Figure 2. The geographic spread of RSMV in China. Samples tested positive in the Guangdong, Guangxi, and Hainan provinces from 2015 to 2022. The sample collection areas and total number of positive cases in different regions are shown in (AC). The prevalence of RSMV in China from 2015 to 2022 is demonstrated here (data from Yang et al. [27] and Chen et al. [15]). The PAST 4.10 software was used to prepare the figure Using the URL https://www.downloadcrew.com/article/34304/past (accessed on 10 August 2023).
Agronomy 14 02442 g002
Figure 3. Various phenotypes of RSMV-infected rice plants and symptoms related to yield loss (A); infected plants in the field (B,C); stiff, twisted leaves with mosaic features (D); incomplete heading (E,F); diseased plant with mostly unfilled grains (G); plant height (H); non-functional tiller appearance (I); extent of heading (J); ripened panicles. The healthy plants had long panicles; however, RSMV-infected panicles were small and typically had unfiled grains. The above information is adapted from Yang et al. [4]; Chen et al. [15]; and Wang et al. [17]. Data of the “Nipponbare” rice variety are from Chen et al. [15]. Figures are reprinted with kind permission from Ref. [4], Copyright © 2017 Yang, Huang, Liu, Chen, Zhang and Zhou, Ref. [15], Copyright © 2019 Siping Chen, Weilin Li, Xiuqin Huang, Biao Chen, Tong Zhang & Guohui Zhou, and Ref. [17], Copyright © 2021 Wang Z, Chen B, Zhang T, Zhou G and Yang X.
Figure 3. Various phenotypes of RSMV-infected rice plants and symptoms related to yield loss (A); infected plants in the field (B,C); stiff, twisted leaves with mosaic features (D); incomplete heading (E,F); diseased plant with mostly unfilled grains (G); plant height (H); non-functional tiller appearance (I); extent of heading (J); ripened panicles. The healthy plants had long panicles; however, RSMV-infected panicles were small and typically had unfiled grains. The above information is adapted from Yang et al. [4]; Chen et al. [15]; and Wang et al. [17]. Data of the “Nipponbare” rice variety are from Chen et al. [15]. Figures are reprinted with kind permission from Ref. [4], Copyright © 2017 Yang, Huang, Liu, Chen, Zhang and Zhou, Ref. [15], Copyright © 2019 Siping Chen, Weilin Li, Xiuqin Huang, Biao Chen, Tong Zhang & Guohui Zhou, and Ref. [17], Copyright © 2021 Wang Z, Chen B, Zhang T, Zhou G and Yang X.
Agronomy 14 02442 g003
Figure 4. Infection cycle of RSMV developed based on Chen et al. [15]. Figure is reprinted after modification with kind permission from Ref. [4], Copyright © 2019 Siping Chen, Weilin Li, Xiuqin Huang, Biao Chen, Tong Zhang & Guohui Zhou.
Figure 4. Infection cycle of RSMV developed based on Chen et al. [15]. Figure is reprinted after modification with kind permission from Ref. [4], Copyright © 2019 Siping Chen, Weilin Li, Xiuqin Huang, Biao Chen, Tong Zhang & Guohui Zhou.
Agronomy 14 02442 g004
Figure 5. A phylogenetic tree of RSMV and other plant viruses. The protein sequence was adopted from the NCBI database, URL https://www.ncbi.nlm.nih.gov/ (accessed on 15 November 2023). The multiple sequence alignment of RSMV with other plant viruses was determined utilizing the MEGA-v11.0 software [54] and visualized using TBtools-II-v1.120 software [55]. Firstly, the tree was constructed using the full-length protein sequences of the genes using MEGA-v11.0; then, TBtools was used to predict the segmental and tandem duplications. The multiple sequence alignment of Cluster Omega W was performed. Then, the tree was visualized using the online software iTOL_v5 [56], which was created using the neighbor joining (NJ) and 1000 repeat bootstrap methods, URL (https://itol.embl.de/upload.cgi, accessed on 15 November 2023). The tree is unrooted and the sub-families of RSMV with other plant virus genes are highlighted with different colored backgrounds in the Clade. M, matrix protein; G, glycoprotein; P, phosphoprotein; NC, nucleocapsid protein; and L, immunoglobulin-binding protein. ADV, alfalfa dwarf virus; BYSMV, barley yellow striate mosaic cytorhabdovirus; CBDaV, Colocasia bobone disease-associated virus; CoRSV, coffee ringspot dichorhavirus; LBVaV, lettuce big-vein associated varicosavirus; DYVV, Datura yellow vein nucleorhabdovirus; EMDV, eggplant mottled dwarf nucleorhabdovirus; LNYV, lettuce necrotic yellows virus; LYMoV, lettuce yellow mottle virus; MFSV, maize fine streak nucleorhabdovirus; MIMV, maize Iranian mosaic nucleorhabdovirus; MMV, maize mosaic nucleorhabdovirus; NCMV, northern cereal mosaic cytorhabdovirus; OFV, orchid fleck dichorhavirus; PYDV, potato yellow dwarf nucleorhabdovirus; RYSV, rice yellow stunt nucleorhabdovirus; RPV, pice Peribunya-like virus 1; RLBV, raspberry leaf blotch emaravirus; and RLRV, rose leaf rosette-associated virus.
Figure 5. A phylogenetic tree of RSMV and other plant viruses. The protein sequence was adopted from the NCBI database, URL https://www.ncbi.nlm.nih.gov/ (accessed on 15 November 2023). The multiple sequence alignment of RSMV with other plant viruses was determined utilizing the MEGA-v11.0 software [54] and visualized using TBtools-II-v1.120 software [55]. Firstly, the tree was constructed using the full-length protein sequences of the genes using MEGA-v11.0; then, TBtools was used to predict the segmental and tandem duplications. The multiple sequence alignment of Cluster Omega W was performed. Then, the tree was visualized using the online software iTOL_v5 [56], which was created using the neighbor joining (NJ) and 1000 repeat bootstrap methods, URL (https://itol.embl.de/upload.cgi, accessed on 15 November 2023). The tree is unrooted and the sub-families of RSMV with other plant virus genes are highlighted with different colored backgrounds in the Clade. M, matrix protein; G, glycoprotein; P, phosphoprotein; NC, nucleocapsid protein; and L, immunoglobulin-binding protein. ADV, alfalfa dwarf virus; BYSMV, barley yellow striate mosaic cytorhabdovirus; CBDaV, Colocasia bobone disease-associated virus; CoRSV, coffee ringspot dichorhavirus; LBVaV, lettuce big-vein associated varicosavirus; DYVV, Datura yellow vein nucleorhabdovirus; EMDV, eggplant mottled dwarf nucleorhabdovirus; LNYV, lettuce necrotic yellows virus; LYMoV, lettuce yellow mottle virus; MFSV, maize fine streak nucleorhabdovirus; MIMV, maize Iranian mosaic nucleorhabdovirus; MMV, maize mosaic nucleorhabdovirus; NCMV, northern cereal mosaic cytorhabdovirus; OFV, orchid fleck dichorhavirus; PYDV, potato yellow dwarf nucleorhabdovirus; RYSV, rice yellow stunt nucleorhabdovirus; RPV, pice Peribunya-like virus 1; RLBV, raspberry leaf blotch emaravirus; and RLRV, rose leaf rosette-associated virus.
Agronomy 14 02442 g005
Figure 6. Mechanisms of tripartite interaction between nanoparticles (NPs) in plant-virus-vector systems. Figure and text are reprinted with permission from Ref. [122]. Copyright 2021 American Chemical Society.
Figure 6. Mechanisms of tripartite interaction between nanoparticles (NPs) in plant-virus-vector systems. Figure and text are reprinted with permission from Ref. [122]. Copyright 2021 American Chemical Society.
Agronomy 14 02442 g006
Figure 7. A conceptual diagram describing the practices that can be implemented for RSMV’s disease epidemics and pathogen evolution.
Figure 7. A conceptual diagram describing the practices that can be implemented for RSMV’s disease epidemics and pathogen evolution.
Agronomy 14 02442 g007
Table 1. Selected proteins for PPI networking.
Table 1. Selected proteins for PPI networking.
Sr. NoProtein NameProtein IDGene IDAmino Acids CDS (bp)Chr. Start–End PointDescriptionPutative FunctionsReferences
1L proteinYP_009553369.1NC_040786.1206662016278–12,478RSMVLarge subunit of polymerase (L7), capping mRNA 5′ end, RNA binding, polyadenylation[27,57]
2P6 proteinAPR74653.1NC_040786.1662016005–6205RSMVNon-structural proteins, unknown function[27]
3G proteinAPR74652.1NC_040786.153616114376–5986RSMVGlycoprotein (P5 protein), assemble viral particles and directly interact with M protein, promote viral budding[13,27]
4NC proteinYP_009553363.1NC_040786.1491147690–1565RSMVNucleocapsid, tightly bind to viral gRNA to prevent its cleavage by host cell nucleases[27,58]
5P proteinYP_009553364.1NC_040786.137511281669–2796RSMVPhosphoprotein, cofactor for viral polymerase, mediates correct positioning and connection of the L protein on the N-RNA template.[19,27]
6M proteinYP_009553366.1NC_040786.11745253730–4254RSMVSilencing suppressor, matrix protein (M), affect host antiviral RNA silencing functions[19,27]
7P3 proteinYP_009553365.1NC_040786.11775343006–3539RSMVCell-to-cell movement, nuclear localization signals[4,24,27]
8G proteinKP205452.2NC_028237.2 56414495529–7223ADVP5 protein, assemble viral particles and directly interact with M protein[59]
9P proteinYP_009177016.1NC_028237.23119362060–2995ADVPutative movement protein[59]
10NC proteinYP_009177015.2NC_028237.24821449175–1623ADVNucleocapsid[59]
11L proteinYP_009177231.1NC_028244.1205661716176–12,346BYSMVL protein of Cytorhabdovirus hordei[60]
12G proteinYP_009177229.1NC_028244.147814374504–5940BYSMVForm trans-membrane spikes[60,61]
13M proteinYP_009177228.1NC_028244.11665013916–4416BYSMV Virus assembly, bridge between nucleocapsids and the envelope[60]
14NC proteinALU34429.1NC_034551.14221269178–1446CBDaVNucleocapsid, tightly bind to viral gRNA to prevent its cleavage by host cell nucleases[62]
15GlycoproteinALU34428.1NC_034551.150315123995–5506CBDaVGlycoprotein of Colocasia bobone disease virus[62]
16P proteinALU34424.1NC_034551.1 2808431624–2466CBDaVPhosphoprotein, cofactor for viral polymerase[62]
17ORF5AHH44829.1NC_038756.1 53416054739–6343CoRSV [63]
18NC proteinAHH44825.1NC_038756.14461341105–1445CoRSVNucleocapsid, tightly bind to viral gRNA[63]
19ORF3AHH44827.1NC_038756.13289872646–3632CoRSV [63]
20L proteinYP_002308576.1NC_011558.1 20406123339–6461LBVaVLarge subunit of polymerase (L7), RNA binding[64]
21Coat proteinYP_002317202.1NC_011568.1 39711944–1433LBVaV [64]
22GlycoproteinYP_009176976.1NC_028231.1 63018934662–6554DYVVIdentified in Datura yellow vein nucleorhabdovirus, targeted to the endoplasmic reticulum[65]
23P proteinYP_009176973.1NC_028231.1 3279841578–2561DYVVPhosphoprotein, cofactor for viral polymerase[65]
24NC proteinYP_009176972.1NC_028231.1 4501353165–1517DYVVNucleocapsid, tightly bind to viral gRNA [65]
25X proteinYP_009094356.1NC_025389.1 2517561825–2118EMDV [66]
26G proteinYP_009094357.1NC_025389.161518485185–7032EMDVP5 protein, assemble viral particles[66]
27NC proteinYP_009094352.1NC_025389.1 4761431282–1712EMDVTightly bind to viral gRNA to prevent its cleavage [66]
284b proteinYP_425089.1NC_007642.1 3029092720–3765LNYV [67]
29G protein YP_425091.1NC_007642.1 55116564412–6247LNYVAssemble viral particles and interact with M protein[67]
30P proteinYP_425088.1NC_007642.1 3009031631–2712LNYVPhosphoprotein, cofactor for viral polymerase[67]
31L proteinYP_002308376.1NC_011532.1 206862076461–12,667LYMoVRNA binding, polyadenylation[68]
32NC proteinYP_002308371.1NC_011532.1 4521359164–1522LYMoVPrevent cleavage by host cell nucleases[68]
33G proteinYP_002308375.1NC_011532.154816474531–6177LYMoVP5 protein, directly interact with M protein[68]
34L proteinYP_052849.1NC_005974.1194458357657–13,633MFSVCapping mRNA 5’ end, RNA binding, polyadenylation[69]
35NC proteinYP_052843.1NC_005974.14621389254–1642MFSVNucleocapsid, tightly bind to viral gRNA to prevent its cleavage by host cell nucleases[69]
36G proteinYP_052848.1NC_005974.159617915675–7652MFSVAssemble viral particles and interact with M protein[69]
37G proteinYP_009444712.1NC_036390.1 59417854580–6364MIMVAssemble viral particles and interact with M protein[70]
38NC proteinYP_009444708.1NC_036390.1 4451338210–1547MIMVNucleocapsid[70]
39M proteinYP_009444711.1NC_036390.12337023770–4471MIMVSilencing suppressor, matrix protein (M)[70]
40L proteinYP_052855.1NC_005975.1 192257696244–12,039MMVLarge subunit of polymerase (L7), capping mRNA 5′ end, RNA binding, polyadenylation[71]
41G proteinYP_052854.1NC_005975.1 59117764349–6240MMVP5 protein, assemble viral particles and directly interact with M protein[71]
42NC proteinYP_052850.1NC_005975.1 4471344130–1681MMVNucleocapsid[71]
43G proteinNP_057961.1NC_002251.1 46314524996–6447NCMVP5 protein, assemble viral particles [72]
44P proteinNP_057955.1NC_002251.1 2868611568–2428NCMVPhosphoprotein, cofactor for viral polymerase[72]
45NC proteinNP_057954.1NC_002251.1 2651296142–1437NCMVNucleocapsid, tightly bind to viral gRNA to prevent its cleavage by host cell nucleases[72]
46G proteinYP_001294928.1NC_009608.1 54216294549–6265OFVP5 protein, assemble viral particles and directly interact with M protein[73]
47ORF3 proteinYP_001294926.1NC_009608.1 33510082597–3772OFV [73]
48NC proteinYP_001294924.1NC_009608.1 4501353163–1651OFVPrevent its cleavage by host cell nucleases[73]
49G proteinADE45273.1NC_016136.1 60718244953–6844PYDVAssemble viral particles and interact with M protein[74]
50M proteinADE45272.1NC_016136.1 2537624051–4948PYDVSilencing suppressor, matrix protein (M), affect host antiviral RNA silencing functions[74]
51NC proteinADE45268.1NC_016136.1 4721419154–1671PYDVNucleocapsid, tightly bind to viral gRNA [74]
52G proteinNP_620500.1NC_003746.166920105127–7284RYSVAssemble viral particles and interact with M protein[75]
53M proteinNP_620499.1NC_003746.1 2627894209–5121RYSVAffect host antiviral RNA silencing functions[75]
54NC proteinNP_620496.1NC_003746.15211566207–1920RYSVNucleocapsid, tightly bind to viral gRNA [75]
55Large proteinNP_620502.1NC_003746.1 196759047860–13,847RYSV [75]
56RNA polymeraseQKN84393.1-21376414-RPV [76]
57P4 proteinYP_009237267.1NC_029560.1 3731122473–1594RLBVPhosphoprotein, cofactor for viral polymerase[77]
58RdRp proteinYP_009058929.1NC_024906.1 47714348417–9850RLBV [78]
RSMV, rice stripe mosaic virus; ADV, alfalfa dwarf virus; BYSMV, barley yellow striate mosaic cytorhabdovirus; CBDaV, Colocasia bobone disease-associated virus; CoRSV, coffee ringspot dichorhavirus; LBVaV, lettuce big-vein associated varicosavirus; DYVV, Datura yellow vein nucleorhabdovirus; EMDV, eggplant mottled dwarf nucleorhabdovirus; LNYV, lettuce necrotic yellows virus; LYMoV, lettuce yellow mottle virus; MFSV, maize fine streak nucleorhabdovirus; MIMV, maize Iranian mosaic nucleorhabdovirus; MMV, maize mosaic nucleorhabdovirus; NCMV, northern cereal mosaic cytorhabdovirus; OFV, orchid fleck dichorhavirus; PYDV, potato yellow dwarf nucleorhabdovirus; RYSV, rice yellow stunt nucleorhabdovirus; RPV, rice Peribunya-like virus 1; RLBV, raspberry leaf blotch emaravirus.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Mas-ud, M.A.; Chowdhury, M.R.; Juthee, S.A.; Rabbee, M.F.; Matin, M.N.; Kang, S.G. Unravelling the Current Status of Rice Stripe Mosaic Virus: Its Geographical Spread, Biology, Epidemiology, and Management. Agronomy 2024, 14, 2442. https://doi.org/10.3390/agronomy14102442

AMA Style

Mas-ud MA, Chowdhury MR, Juthee SA, Rabbee MF, Matin MN, Kang SG. Unravelling the Current Status of Rice Stripe Mosaic Virus: Its Geographical Spread, Biology, Epidemiology, and Management. Agronomy. 2024; 14(10):2442. https://doi.org/10.3390/agronomy14102442

Chicago/Turabian Style

Mas-ud, Md. Atik, Md. Rayhan Chowdhury, Sadiya Arefin Juthee, Muhammad Fazle Rabbee, Mohammad Nurul Matin, and Sang Gu Kang. 2024. "Unravelling the Current Status of Rice Stripe Mosaic Virus: Its Geographical Spread, Biology, Epidemiology, and Management" Agronomy 14, no. 10: 2442. https://doi.org/10.3390/agronomy14102442

APA Style

Mas-ud, M. A., Chowdhury, M. R., Juthee, S. A., Rabbee, M. F., Matin, M. N., & Kang, S. G. (2024). Unravelling the Current Status of Rice Stripe Mosaic Virus: Its Geographical Spread, Biology, Epidemiology, and Management. Agronomy, 14(10), 2442. https://doi.org/10.3390/agronomy14102442

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop