Spatial Distribution Patterns for Identifying Risk Areas Associated with False Smut Disease of Rice in Southern India

False smut disease (FSD) of rice incited by Ustilaginoidea virens is an emerging threat to paddy cultivation worldwide. We investigated the spatial distribution of FSD in different paddy ecosystems of South Indian states, viz., Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana, by considering the exploratory data from 111 sampling sites. Point pattern and surface interpolation analyses were carried out to identify the spatial patterns of FSD across the studied areas. The spatial clusters of FSD were confirmed by employing spatial autocorrelation and Ripley’s K function. Further, ordinary kriging (OK), indicator kriging (IK), and inverse distance weighting (IDW) were used to create spatial maps by predicting the values at unvisited locations. The agglomerative hierarchical cluster analysis using the average linkage method identified four main clusters of FSD. From the Local Moran’s I statistic, most of the areas of Andhra Pradesh and Tamil Nadu were clustered together (at I > 0), except the coastal and interior districts of Karnataka (at I < 0). Spatial patterns of FSD severity were determined by semi-variogram experimental models, and the spherical model was the best fit. Results from the interpolation technique, the potential FSD hot spots/risk areas were majorly identified in Tamil Nadu and a few traditional rice-growing ecosystems of Northern Karnataka. This is the first intensive study that attempted to understand the spatial patterns of FSD using geostatistical approaches in India. The findings from this study would help in setting up ecosystem-specific management strategies to reduce the spread of FSD in India

Timing of oomycete-specific fungicide application impacts the efficacy against fruit rot disease in arecanut

Fungicidal application has been the common and prime option to combat fruit rot disease (FRD) of arecanut (Areca catechu L.) under field conditions. However, the existence of virulent pathotypes, rapid spreading ability, and improper time of fungicide application has become a serious challenge. In the present investigation, we assessed the efficacy of oomycete-specific fungicides under two approaches: (i) three fixed timings of fungicidal applications, i.e., pre-, mid-, and post-monsoon periods (EXPT1), and (ii) predefined different fruit stages, i.e., button, marble, and premature stages (EXPT2). Fungicidal efficacy in managing FRD was determined from evaluations of FRD severity, FRD incidence, and cumulative fallen nut rate (CFNR) by employing generalized linear mixed models (GLMMs). In EXPT1, all the tested fungicides reduced FRD disease levels by &gt;65% when applied at pre- or mid-monsoon compared with untreated control, with statistical differences among fungicides and timings of application relative to infection. In EXPT2, the efficacy of fungicides was comparatively reduced when applied at predefined fruit/nut stages, with statistically non-significant differences among tested fungicides and fruit stages. A comprehensive analysis of both experiments recommends that the fungicidal application can be performed before the onset of monsoon for effective management of arecanut FRD. In conclusion, the timing of fungicidal application based on the monsoon period provides better control of FRD of arecanut than an application based on the developmental stages of fruit under field conditions

Performance of black pepper varieties as intercrop in coconut gardens in the lower Brahmaputra valley of Assam state, India

Black pepper (Piper nigrum) is well habituated as an inter/under/mixed crop in plantation crops. A field experiment was conducted at Horticultural Research Station (AICRP on Palms), Kahikuchi of Assam Agricultural University for 12 consecutive years (2009-2021) for studying the performance of black pepper varieties/hybrids when grown as intercrop in 38 year old Assam Green Tall. Panniyur-1 produced a higher number of laterals with more spread compared to other varieties. Similarly, a significantly higher number of spikes (134.0), spike length (15.0 cm) and number of berries per spike (82.0) were also recorded in Panniyur-1. Sreekara recorded the lowest spike length (9.8 cm), while IISR Malabar Excel recorded the lowest number of spikes (85.0). Six-year mean dry berry yield indicated that the yield was significantly higher with Panniyur-1 (1.60 kg vine-1) followed by Sreekara (1.49 kg vine-1) and average yield of 1.00 kg vine-1 recorded in IISR Malabar Excel, IISR Thevam and IISR Shakthi. The oleoresin content (11.7%) and piperine content (5.2%) was found highest in Panniyur-1, followed by Sreekara (10.9 % and 4.5%) whereas, the lowest oleoresin content (8.8%) and piperine content (2.9%) were recorded in IISR Malabar Excel and IISR Thevam, respectively. Intercropping of black pepper in coconut garden recorded the highest net return (` 237088 ha-1) and B: C ratio (3.48) followed by Sreekara (` 212764 ha-1; B: C ratio 3.12) and the lowest net return (` 177938 ha-1) and B: C ratio (2.61) were obtained in IISR Malabar Excel

Assessment of the spatial distribution and risk associated with fruit rot disease in Areca catechu L.

Phytophthora meadii (McRae) is a hemibiotrophic oomycete fungus that infects tender nuts, growing buds, and crown regions, resulting in fruit, bud, and crown rot diseases in arecanut (Areca catechu L.), respectively. Among them, fruit rot disease (FRD) causes serious economic losses that are borne by the growers, making it the greatest yield-limiting factor in arecanut crops. FRD has been known to occur in traditional growing areas since 1910, particularly in Malnad and coastal tracts of Karnataka. Systemic surveys were conducted on the disease several decades ago. The design of appropriate management approaches to curtail the impacts of the disease requires information on the spatial distribution of the risks posed by the disease. In this study, we used exploratory survey data to determine areas that are most at risk. Point pattern (spatial autocorrelation and Ripley’s K function) analyses confirmed the existence of moderate clustering across sampling points and optimized hotspots of FRD were determined. Geospatial techniques such as inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) were performed to predict the percent severity rates at unsampled sites. IDW and OK generated identical maps, whereby the FRD severity rates were higher in areas adjacent to the Western Ghats and the seashore. Additionally, IK was used to identify both disease-prone and disease-free areas in Karnataka. After fitting the semivariograms with different models, the exponential model showed the best fit with the semivariogram. Using this model information, OK and IK maps were generated. The identified FRD risk areas in our study, which showed higher disease probability rates (>20%) exceeding the threshold level, need to be monitored with the utmost care to contain and reduce the further spread of the disease in Karnataka

Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in Areca catechu L.

Phytophthora meadii (McRae) is a hemibiotrophic oomycete fungus that infects tender nuts, growing buds, and crown regions, resulting in fruit, bud, and crown rot diseases in arecanut (Areca catechu L.), respectively. Among them, fruit rot disease (FRD) causes serious economic losses that are borne by the growers, making it the greatest yield-limiting factor in arecanut crops. FRD has been known to occur in traditional growing areas since 1910, particularly in Malnad and coastal tracts of Karnataka. Systemic surveys were conducted on the disease several decades ago. The design of appropriate management approaches to curtail the impacts of the disease requires information on the spatial distribution of the risks posed by the disease. In this study, we used exploratory survey data to determine areas that are most at risk. Point pattern (spatial autocorrelation and Ripley’s K function) analyses confirmed the existence of moderate clustering across sampling points and optimized hotspots of FRD were determined. Geospatial techniques such as inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) were performed to predict the percent severity rates at unsampled sites. IDW and OK generated identical maps, whereby the FRD severity rates were higher in areas adjacent to the Western Ghats and the seashore. Additionally, IK was used to identify both disease-prone and disease-free areas in Karnataka. After fitting the semivariograms with different models, the exponential model showed the best fit with the semivariogram. Using this model information, OK and IK maps were generated. The identified FRD risk areas in our study, which showed higher disease probability rates (&gt;20%) exceeding the threshold level, need to be monitored with the utmost care to contain and reduce the further spread of the disease in Karnataka

Insights into the population dynamics of phytophthora species associated with arecanut fruit rot disease

Phytophthora, a ubiquitous filamentous oomycete, causes huge yield losses and is fatal to arecanut palms in case of severe infection. From 2014 onwards, a severe fruit rot epidemic has been recorded during the South-West monsoon season in major arecanut-growing states of South India. We have assessed the diversity and delineated the population structure of Phytophthora isolates infecting arecanut in India using a combination of morphological traits, multi-gene profiling, haplotype analysis, and pathogenicity. Ninety-eight Phytophthora isolates were obtained from infected samples collected from disease-endemic regions of Karnataka, Kerala, and Goa states in southern India from 2014 to 2019. Morphological traits coupled with phylogenetic analysis using the loci ITS, β-tub, TEF-1α, and Cox-II identified the A2 mating type of P. meadii as the predominant species together with two isolates of homothallic P. heveae. Linkage disequilibrium analysis revealed significant diversity in the form of single nucleotide polymorphisms (SNPs) from the concatenated sequence dataset. Population structure analysis using 590 SNPs demonstrated the existence of four population groups (sub-populations at K = 4 and K = 2) and significant diversity in the geo-distant Phytophthora populations. In summary, 22 haplotypes were identified from the representative 40 isolates with higher haplotype diversity of 1.23 and relatively varying haplotype frequency. Pathogenicity assays confirmed that both the species of Phytophthora were pathogenic to arecanut, while P. meadii coastal region isolates exhibited more virulence compared to others

Mechanisms of Microbial Plant Protection and Control of Plant Viruses

Plant viral diseases are major constraints causing significant yield losses worldwide in agricultural and horticultural crops. The commonly used methods cannot eliminate viral load in infected plants. Many unconventional methods are presently being employed to prevent viral infection; however, every time, these methods are not found promising. As a result, it is critical to identify the most promising and sustainable management strategies for economically important plant viral diseases. The genetic makeup of 90 percent of viral diseases constitutes a single-stranded RNA; the most promising way for management of any RNA viruses is through use ribonucleases. The scope of involving beneficial microbial organisms in the integrated management of viral diseases is of the utmost importance and is highly imperative. This review highlights the importance of prokaryotic plant growth-promoting rhizobacteria/endophytic bacteria, actinomycetes, and fungal organisms, as well as their possible mechanisms for suppressing viral infection in plants via cross-protection, ISR, and the accumulation of defensive enzymes, phenolic compounds, lipopeptides, protease, and RNase activity against plant virus infection

Spatial Distribution Patterns for Identifying Risk Areas Associated with False Smut Disease of Rice in Southern India

False smut disease (FSD) of rice incited by Ustilaginoidea virens is an emerging threat to paddy cultivation worldwide. We investigated the spatial distribution of FSD in different paddy ecosystems of South Indian states, viz., Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana, by considering the exploratory data from 111 sampling sites. Point pattern and surface interpolation analyses were carried out to identify the spatial patterns of FSD across the studied areas. The spatial clusters of FSD were confirmed by employing spatial autocorrelation and Ripley’s K function. Further, ordinary kriging (OK), indicator kriging (IK), and inverse distance weighting (IDW) were used to create spatial maps by predicting the values at unvisited locations. The agglomerative hierarchical cluster analysis using the average linkage method identified four main clusters of FSD. From the Local Moran’s I statistic, most of the areas of Andhra Pradesh and Tamil Nadu were clustered together (at I > 0), except the coastal and interior districts of Karnataka (at I < 0). Spatial patterns of FSD severity were determined by semi-variogram experimental models, and the spherical model was the best fit. Results from the interpolation technique, the potential FSD hot spots/risk areas were majorly identified in Tamil Nadu and a few traditional rice-growing ecosystems of Northern Karnataka. This is the first intensive study that attempted to understand the spatial patterns of FSD using geostatistical approaches in India. The findings from this study would help in setting up ecosystem-specific management strategies to reduce the spread of FSD in India