ABSTRACT
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.
ABSTRACT
Fruit rot disease (FRD) in arecanut has appeared in most of the arecanut growing regions of India in the last few decades. A few comprehensive studies on the management of FRD under field conditions have examined various treatment combinations for disease control and yield response analysis. This study aimed to compare the control efficiencies and yield responses of treatments applied over multiple locations and compute the probable returns of investment (ROIs) for treatment costs. Data were gathered from 21 field trials conducted across five main arecanut growing regions of India in the period 2012−2019. The collected data were subjected to analysis with a multivariate (network) meta-analytical model, following standard statistical protocols. The quantitative, synthesized data were evaluated for the estimated effects of disease pressure (DPLow ≤ 35% of FRDInc in the treatments > DPHigh), mean disease control efficiencies (treatment mean, C), and yield responses (R) corresponding to the tested treatments. Based on disease control efficacy, the evaluated treatments were grouped into three efficacy groups (EGs): higher EGs were observed for the Bordeaux mixture (C, 81.94%) and its stabilized formulation (C, 74.99%), Metalaxyl + Mancozeb (C, 70.66%), while lower EGs were observed in plots treated with Biofight (C, 29.91%), Biopot (C, 25.66%), and Suraksha (C, 29.74%) and intermediate EGs were observed in plots to which microbial consortia (bio-agents) had been applied. Disease pressure acted as a significant moderator variable, influencing yield response and gain. At DPLow, the Bordeaux fungicide mixture (102%, 22% of increased yield) and Metalaxyl + Mancozeb (77.5%, +15.5%) exhibited higher yield responses, with absolute arecanut yield gains of 916.5 kg ha−1 and 884 kg ha−1, while, under DPHigh, Fosetyl-AL (819.6 kg ha−1) showed a yield response of 90.5%. To ensure maximum yield sustainability, arecanut growers should focus on the spraying of fungicides (a mixture of different active ingredients or formulations or products) as a preventative measure, followed by treating palms with either soil microbial consortia or commercial formulations of organic fungicides.
ABSTRACT
An oomycetous fungus Phytophthora causing fruit rot is the most devastating disease of arecanut in different agro-climatic zones of Karnataka with varied climatic profiles. The main aim of this investigation was to characterize the geo-distant Phytophthora populations infecting arecanut using robust morphological, multi-gene phylogeny and haplotype analysis. A total of 48 geo-distant fruit rot infected samples were collected during the South-West monsoon of 2017-19. Pure culture of the suspected pathogen was isolated from the infected nuts and pathogenic ability was confirmed and characterized. Colony morphology revealed typical whitish mycelium with stellate or petalloid pattern and appearance with torulose hyphae. Sporangia were caducous, semipapillate or papillate, globose, ellipsoid or ovoid-obpyriform in shape and sporangiophores were irregularly branched or simple sympodial in nature. Subsequent multi-gene phylogeny (ITS, ß-tub, TEF-1α and Cox-II) and sequence analysis confirmed the identity of oomycete as Phytophthora meadii which is predominant across the regions studied. We identified 49 haplotypes representing the higher haplotype diversity with varying relative haplotype frequency. Comprehensive study confirmed the existence of substantial variability among geo-distant populations (n = 48) of P. meadii. The knowledge on population dynamics of the pathogen causing fruit rot of arecanut generated from this investigation would aid in developing appropriate disease management strategies to curtail its further occurrence and spread in arecanut ecosystem.
ABSTRACT
To understand the spatio-temporal dynamics and the effect of climate on fruit rot occurrence in arecanut plantations, we evaluated the intensity of fruit rot in three major growing regions of Karnataka, India for two consecutive years (2018 and 2019). A total of 27 sampling sites from the selected regions were monitored and the percentage disease intensity (PDI) was assessed on 50 randomly selected palms. Spatial interpolation technique, ordinary kriging (OK) was employed to predict the disease occurrence at unsampled locations. OK resulted in aggregated spatial maps, where the disease intensity was substantial (40.25-72.45%) at sampling sites of the Malnad and coastal regions. Further, Moran's I spatial autocorrelation test confirmed the presence of significant spatial clusters (p ≤ 0.01) across the regions studied. Temporal analysis indicated the initiation of disease on different weeks dependent on the sampling sites and evaluated years with significant variation in PDI, which ranged from 9.25% to 72.45%. The occurrence of disease over time revealed that the epidemic was initiated early in the season (July) at the Malnad and coastal regions in contrary to the Maidan region where the occurrence was delayed up to the end of the season (September). Correlations between environmental variables and PDI revealed that, the estimated temperature (T), relative humidity (RH) and total rainfall (TRF) significantly positively associated (p = 0.01) with disease occurrence. Regression model analysis revealed that the association between Tmax, RH1 and TRF with PDI statistically significant and the coefficients for the predictors Tmax, RH1 and TRF are 1.731, 1.330 and 0.541, respectively. The information generated in the present study will provide a scientific decision support system, to generate forecasting models and a better surveillance system to develop adequate strategies to curtail the fruit rot of arecanut.
ABSTRACT
Rice is a globally important crop and highly vulnerable to rice blast disease (RBD). We studied the spatial distribution of RBD by considering the 2-year exploratory data from 120 sampling sites over varied rice ecosystems of Karnataka, India. Point pattern and surface interpolation analyses were performed to identify the spatial distribution of RBD. The spatial clusters of RBD were generated by spatial autocorrelation and Ripley's K function. Further, inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) approaches were utilized to generate spatial maps by predicting the values at unvisited locations using neighboring observations. Hierarchical cluster analysis using the average linkage method identified two main clusters of RBD severity. From the Local Moran's I, most of the districts were clustered together (at I > 0), except the coastal and interior districts (at I < 0). Positive spatial dependency was observed in the Coastal, Hilly, Bhadra, and Upper Krishna Project ecosystems (p > 0.05), while Tungabhadra and Kaveri ecosystem districts were clustered together at p < 0.05. From the kriging, Hilly ecosystem, middle and southern parts of Karnataka were found vulnerable to RBD. This is the first intensive study in India on understanding the spatial distribution of RBD using geostatistical approaches, and the findings from this study help in setting up ecosystem-specific management strategies against RBD.
