, Chili pepper (Capsicum annuum) represents one of Indonesia’s principal horticultural crops, valued for its significant role in the national economy and its potential to generate export earnings, especially in high-production regions such as Lampung Province (Amisnaipa et al., 2024; Mariyono, 2019). This commodity holds strategic importance not only as an export product but also as a vital agricultural resource that supports local farmer livelihoods and underpins food security. Price volatility in chili markets has been shown to directly influence food inflation and socioeconomic stability in Indonesia (Sativa et al., 2017; Widodo et al., 2023). Despite its wide-ranging benefits, the optimal production potential of chili has yet to be fully realized due to constraints such as low productivity and suboptimal yields, primarily caused by pests and pathogens, including viral diseases (Ahmad et al., 2024).
Over the past two decades, pepper yellow leaf curl virus (PepYLCV) has emerged as one of the most severe threats to chili production in Indonesia. This virus, classified within the monopartite begomovirus group, is transmitted by the whitefly Bemisia tabaci in a circulative-propagative manner (Fiallo-Olivé et al., 2020; Fouad et al., 2024; Ghosh and Ghanim, 2021; Li et al., 2021; Selangga et al., 2023). The PepYLCV genome consists of a single-stranded DNA molecule of approximately 2.7 kb, encoding essential genes responsible for viral replication, systemic movement, and vector-host interactions (Nigam, 2021; Nova et al., 2018; Paradisa et al., 2022). Infection manifests through symptoms such as leaf curling, size reduction, chlorosis, and severe stunting, often resulting in drastic productivity losses (Dombrovsky et al., 2010; Sayekti et al., 2023; Wahyono et al., 2023). Recent surveillance throughout major chili-producing areas, including Lampung, West Java, and South Sulawesi, has revealed PepYLCV infection rates of 60-80% during the rainy season or in areas with high vector density (Taufik et al., 2023; Wahyono et al., 2023; Widodo et al., 2023). These challenges highlight the urgent need for integrated management strategies involving tolerant cultivars, vector control, and biotechnological as well as biological interventions.
A comprehensive understanding of PepYLCV’s spatial and temporal distribution is crucial for formulating effective disease control strategies. Geographic analysis of virus dissemination facilitates the identification of infection hotspots, mapping of vector transmission zones, and delineation of priority intervention sites (Beard et al., 2018; Palaniyandi et al., 2021; Shen et al., 2025). Distribution mapping underpins targeted management measures such as the adoption of tolerant varieties, optimization of cropping patterns, implementation of field hygiene, and vector suppression, thereby increasing the efficacy and sustainability of chili production systems (Aijaz et al., 2025; Anastasiou et al., 2023). Ultimately, data-driven control strategies offer substantial promise for limiting PepYLCV spread, maintaining chili crop productivity, and strengthening national food security.
Materials and Methods
Sampling and disease intensity assessment
Sampling was conducted in seven major chili-producing districts within Lampung Province, namely Pesawaran, Tanggamus, Pringsewu, South Lampung, North Lampung, West Lampung, and Central Lampung. In each district, five chili fields were surveyed, resulting in a total of thirty-five fields included in this study. A combination of purposive and random sampling techniques was employed to ensure representative data collection within chili fields, following established agronomic sampling protocols (Nyimbili and Nyimbili, 2024). Within each field, five plots were established, and within each plot, 10-20 chili plants were systematically selected and observed for characteristic symptoms of PepYLCV infection, including leaf size reduction, leaf curling, yellow mosaic or chlorosis, and stunted growth (Selangga et al., 2021). Disease incidence was calculated as the proportion (%) of symptomatic plants relative to the total number of plants observed per field.
Disease severity was assessed at the individual plant level using an ordinal symptom severity scale (Table 1), where each plant was assigned a severity score based on symptom intensity (González-Concha et al., 2023; Lestari et al., 2023; Nurulita et al., 2015). Individual plant severity scores were subsequently aggregated at the field level to calculate mean disease severity values, which were used for comparative analysis and spatial mapping. Disease severity (%) was calculated using the following formula:
The disease intensity is estimated by the interval scale assessor based on percentages, as follows:
Disease assessments were conducted by five trained observers using a standardized visual scoring guideline applied consistently across all survey locations to minimize observer bias. Geographic coordinates of each surveyed field were recorded using handheld GPS devices to support subsequent spatial distribution mapping and heatmap analysis (Kerimbek et al., 2025; Malone et al., 1998).
DNA isolation and molecular detection
Leaf samples exhibiting typical PepYLCV symptoms were collected and transported to the laboratory for analysis. DNA isolation followed the GenAid protocol for plant tissue, involving homogenization and extraction steps. PepYLCV detection was performed via Polymerase Chain Reaction (PCR) amplification using begomovirus-universal primers SPG, targeting conserved genomic regions the AC1/AC2 gene (Selangga et al., 2021). PCR products were electrophoresed on 1.5% agarose gels and purified for subsequent sequencing.
Nucleotide sequence analysis and phylogeny
Raw sequence data were quality-trimmed and assembled into consensus contigs using Geneious Prime (version 2024.0.7) (Biomatters Ltd., Auckland, New Zealand). GenBank BLAST searches facilitated identification of homologous sequences. Multiple sequence alignments employed ClustalW within Geneious Prime, and sequence identity matrices were computed and visualized using Sequence Demarcation Tool (SDT) (Muhire et al., 2014). Phylogenetic trees were constructed using the Neighbor-Joining method with 1000 bootstrap replicates to assess clade support, also within Geneious Prime.
Distribution mapping and heatmap construction
The GIS-based analysis in this study was conducted as an exploratory and descriptive approach to visualize the spatial distribution of PepYLCV incidence and severity, without applying inferential spatial statistics or environmental correlation models. Spatial distribution maps of disease intensity and incidence were created using QGIS version 4.32. Disease observation data, including geographic coordinates, intensity values (%), and incidence percentages (%), were compiled in CSV format and imported as point layers with the WGS 84 coordinate system (EPSG:4326). These layers were saved in GeoPackage (.gpkg) format to facilitate spatial data handling.
Heatmaps were generated using the Heatmap Renderer with Kernel Density Estimation (KDE) to visualize disease density based on intensity or incidence values. Key parameters included a kernel radius of 20-30 km, weight fields corresponding to disease values, and color ramps (Spectral or Viridis) depicting gradients from low to high density. Natural Breaks (Jenks) classification was applied to categorize interpolated values into low, moderate, and high disease levels. Final maps were composed with legends, scale bars, and north arrows to ensure clear spatial visualization of disease patterns across the study region (Kerimbek et al., 2025; Malone et al., 1998).
Separately, pairwise genetic similarity heatmaps among virus isolates were constructed in R Studio (version 4.3.0) utilizing ‘pheatmap’ and ‘ggplot2’ packages. Pairwise sequence identity matrices were subjected to hierarchical clustering to generate color-coded matrices that facilitate visualization of genetic relationships and clustering patterns among isolates (Nelson et al., 1999).
Results and Discussion
Distribution of pepper yellow leaf curl virus in Lampung Province
Field surveys conducted across seven major chili production districts in Lampung Province, Indonesia, revealed substantial variability in the incidence and severity of PepYLCV infections. Typical symptoms observed in chili plants included leaf curling, leaf size reduction, yellow mosaic or chlorotic patches, and stunted plant growth, as illustrated in Fig. 1. The extent of symptom severity varied by location, which may be attributed to differences in chili cultivars, the intensity of viral infection, or local environmental conditions.
Molecular analyses confirmed that PepYLCV was present in all surveyed districts: North Lampung, Central Lampung, South Lampung, West Lampung, Pesawaran, Pringsewu, and Tanggamus, each representing significant centers of chili cultivation (Fig. 2). The geographic distribution pattern highlights that PepYLCV is not confined to isolated localities but is broadly disseminated across lowland and highland agroecosystems in the province. The wide distribution of PepYLCV across all surveyed districts in Lampung Province indicates that virus spread occurs beyond localized infection foci. Although this study did not directly assess vector populations, the observed spatial pattern is consistent with previous reorts describing the role of Bemisia tabaci in begomovirus dissemination. Studies have shown that B. tabaci populations and feeding activity are influenced by host plant morphological traits, including leaf structure and trichome density, which in turn affect virus transmission efficiency (Rodríguez-López et al., 2012)
The heatmap illustrates the distribution of incidence and severity of PepYLCV disease across Lampung Province, revealing varied infection levels among different regions. Districts such as West Lampung, Central Lampung, Pesawaran, and Pringsewu exhibited high infection intensities, indicated by red zones on the map representing infection rates above 76% (Fig. 3). In contrast, areas like North Lampung, South Lampung, and other regions displayed predominantly green zones, reflecting low to moderate disease incidence and severity. The severity map mirrored the incidence pattern, with red hotspots corresponding to areas with higher disease impact, demonstrating consistency between infection rates and disease effects observed in the field. Furthermore, the heterogeneous distribution of PepYLCV incidence and severity among districts corresponds with earlier findings that begomovirus infection levels in the field are closely associated with whitefly feeding behavior and population dynamics, even in the absence of direct vector measurements (Czosnek et al., 2017; Luan et al., 2014). Temaja et al. (2022) demonstrated that viruliferous B. tabaci can sustain virus transmission throughout its lifespan, providing a biological explanation for the extensive and persistent spatial distribution patterns observed in Lampung Province.
Taken together, while vector-related parameters were not quantified in the present study, the spatial distribution of PepYLCV documented here aligns with established epidemiological characteristics of begomovirus transmission mediated by B. tabaci, as reported in previous field-based studies. These findings highlight the need for future investigations integrating virus detection with vector population assessments to further elucidate PepYLCV epidemiology in Indonesia. These findings have significant implications for disease management strategies, especially considering Lampung’s role as a major horticultural hub contributing substantially to Indonesia’s chili supply. Therefore, the spatial distribution mapping of PepYLCV forms a critical basis for designing integrated control measures, including vector management, utilization of mild virus isolates, and development of resistant cultivars (Seal et al., 2006; Varma and Malathi, 2003).
Beyond documenting the widespread occurrence of PepYLCV, the spatially explicit analyses conducted in this study provide enhanced epidemiological resolution by revealing structured patterns of disease aggregation and consistent hotspot formation across districts. The integration of georeferenced field data with GIS-based heatmap visualization enables discrimination between areas characterized by sporadic infection and those experiencing persistent, high-intensity disease pressure. Consequently, this study extends previous regional surveys that primarily reported virus presence by offering a province-wide spatial epidemiological framework for PepYLCV in Lampung Province, thereby generating epidemiologically meaningful insights that can inform targeted surveillance and disease management strategies.
Collectively, these observations confirm the widespread occurrence of PepYLCV across major chili-producing areas of Lampung Province, with consistently higher disease incidence and severity recorded in Tanggamus and West Lampung. These districts constitute important horticultural production centers where chili is cultivated continuously throughout the year, in contrast to other surveyed districts where chili is generally grown as a seasonal or rotational crop.
Continuous host availability in Tanggamus and West Lampung likely plays a central role in sustaining uninterrupted virus circulation and supporting persistent population development of the whitefly vector, B. tabaci. Within this agronomic context, the timing of infection and plant age represent additional, unavoidable factors that further intensify disease incidence. Field observations indicate that chili plants were infected with PepYLCV as early as the initial vegetative stage, creating conditions that allow repeated and continuous virus transmission throughout the plant’s growth cycle. Early-season infections provide the virus with prolonged opportunities to persist within host populations and to be repeatedly acquired and transmitted by vectors as their feeding activity continues. This scenario aligns with previous findings showing that year-round cultivation of suitable host plants enhances whitefly reproduction and persistence, thereby strengthening the efficiency and continuity of begomovirus transmission (Selangga et al., 2023; Temaja et al., 2022).
Although vector abundance and environmental parameters were not quantitatively assessed in the present study, the spatial concentration of PepYLCV infection in Tanggamus and West Lampung is consistent with established epidemiological frameworks linking continuous cropping systems, high vector pressure, and persistent begomovirus epidemics. These findings strengthen the interpretation of heatmap-based spatial patterns and underscore the importance of cropping system structure in shaping PepYLCV distribution in Lampung Province.
Sequence identity and phylogenetic relationship analysis of pepper yellow leaf curl virus
Leaf samples exhibiting leaf curl and yellow mosaic symptoms were collected from all seven surveyed districts in Lampung Province, namely Pesawaran, Pringsewu, West Lampung, North Lampung, Central Lampung, South Lampung, and Tanggamus. All samples were confirmed to be positive for begomovirus infection using universal AC1/AC2 primers (data not shown). Sequence alignment and BLASTn analysis of the partial AC1/AC2 region showed that the Lampung isolates shared 86-94% nucleotide identity with previously reported PepYLCV sequences available in GenBank (Fig. 4).
Phylogenetic analysis based on partial AC1/AC2 nucleotide sequences revealed that all PepYLCV isolates from Lampung clustered within a single major clade with strong bootstrap support (99-100), indicating a close genetic relationship among isolates originating from different districts. Within this clade, Lampung isolates grouped together with other Indonesian PepYLCV reference strains, including kertha, blanga, telaga tawang 1, and ketewel 1, forming a well-supported subcluster (bootstrap values 95-100). This clustering pattern indicates limited sequence divergence among Indonesian PepYLCV isolates within the analyzed AC1/AC2 genomic region.
In contrast, PepYLCV isolates from Lampung were clearly separated from begomoviruses originating outside Indonesia, including tomato leaf curl viruses from the Philippines, Thailand, and Vietnam, as well as papaya leaf curl virus and tomato yellow leaf curl virus isolates from China. The phylogenetic tree was rooted using Beet curly top virus (Curtovirus, Geminiviridae) as an outgroup, providing an appropriate taxonomic framework for inferring relationships among begomovirus sequences.
Pairwise sequence identity analysis visualized as a heatmap further supported the phylogenetic reconstruction (Fig. 5). Isolates from West Lampung, Central Lampung, North Lampung, South Lampung, Pesawaran, Pringsewu, and Tanggamus formed a single cluster characterized by consistently high nucleotide similarity, as indicated by the predominance of red coloration in the heatmap. The absence of low-similarity (blue) signals among Lampung isolates reflects minimal variation within the partial AC1/AC2 region analyzed and is consistent with the tight clustering observed in the phylogenetic tree.
Based on the partial AC1/AC2 sequences analyzed in this study, the observed clustering is interpreted as evidence of close genetic relatedness among PepYLCV isolates circulating in Lampung Province. This finding is discussed in the context of regional virus occurrence and spatial distribution, without extending to inferences regarding population-wide evolutionary processes or specific mechanisms of virus dispersal.
The present study demonstrates that PepYLCV is extensively distributed throughout chili cultivation areas in Lampung Province, with the highest disease incidence and severity observed in Tanggamus and West Lampung. Spatial heterogeneity in PepYLCV levels among districts is likely shaped by a combination of epidemiological factors, such as agroecosystem conditions, cropping intensity, host plant availability, and vector dynamics. Previous research indicates that warm, humid environments combined with continuous cultivation provide ideal conditions for the proliferation of Bemisia tabaci, the primary vector of PepYLCV, thereby driving recurrent begomovirus epidemics and high infection rates (Gilbertson et al., 2015; Koeda et al., 2016; Navas-Castillo et al., 2011).
The tight genetic clustering observed among PepYLCV isolates from Lampung in both phylogenetic and heatmap analyses indicates a high degree of sequence similarity within the analyzed AC1/AC2 genomic region. This pattern is consistent with earlier studies reporting limited sequence variation among Indonesian PepYLCV isolates when conserved genomic regions are examined (Selangga et al., 2021; Wahyono et al., 2023). The formation of a distinct Lampung cluster, clearly separated from non-Indonesian begomovirus sequences, reflects regional relatedness among local isolates rather than broad-scale genetic differentiation.
Mapping results also indicate that PepYLCV infection and severity are concentrated in specific hotspots, particularly in districts with intensive chili cultivation such as Tanggamus and West Lampung. This suggests that environmental factors, planting patterns, and possibly active local vector populations contribute to the formation and persistence of disease foci. Targeted control efforts in these high-risk areas should be prioritized to mitigate broader regional impacts on chili production. Furthermore, spatially uneven virus distribution underscores the need for locally adaptive integrated management strategies, including vector population control, crop rotation, deployment of resistant cultivars, and improved sanitary practices (Seal et al., 2006; Shen et al., 2025; Varma and Malathi, 2003).
The identification of infection hotspots highlights the role of continuous cropping systems as reservoirs of PepYLCV. Strategies such as mild strain cross-protection hold biotechnological promise for mitigating severe infections, especially in areas with genetically homogeneous populations. Lampung’s status as a major Indonesian chili-producing region means that these findings contribute substantially to understanding national disease patterns and inform early-warning systems and policy development.
In summary, PepYLCV remains an important constraint to chili production in Lampung Province and other chili-growing regions in Indonesia, as evidenced by its widespread occurrence and consistent detection across major production areas. Molecular characterization based on partial AC1/AC2 sequences indicates a close genetic relatedness among PepYLCV isolates from different districts, reflecting limited sequence variation within the analyzed genomic region.
The combined application of field surveys, molecular detection, and spatial analysis in this study provides a useful framework for understanding the regional distribution and genetic relationships of PepYLCV. These findings contribute baseline information that can support future epidemiological investigations and the development of integrated disease management strategies, particularly when complemented by further studies incorporating whole-genome analyses, environmental factors, and vector population dynamics.
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