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 >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.

Control Efficiency and Yield Response of Chemical and Biological Treatments against Fruit Rot of Arecanut: A Network Meta-Analysis.

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.

Multigene phylogeny and haplotype analysis reveals predominance of oomycetous fungus, Phytophthora meadii (McRae) associated with fruit rot disease of arecanut in India.

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.

Exploring the Impact of Climatic Variables on Arecanut Fruit Rot Epidemic by Understanding the Disease Dynamics in Relation to Space and Time.

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.

Towards Phytopathogen Diagnostics? Coconut Bud Rot Pathogen Phytophthora palmivora Mycelial Proteome Analysis Informs Genome Annotation.

Planetary agriculture stands to benefit immensely from phytopathogen diagnostics, which would enable early detection of pathogens with harmful effects on crops. For example, Phytophthora palmivora is one of the most destructive phytopathogens affecting many economically important tropical crops such as coconut. P. palmivora causes diseases in over 200 host plants, and notably, the bud rot disease in coconut and oil palm, which is often lethal because it is usually detected at advanced stages of infection. Limited availability of large-scale omics datasets for P. palmivora is an important barrier for progress toward phytopathogen diagnostics. We report here the mycelial proteome of P. palmivora using high-resolution mass spectrometry analysis. We identified 8073 proteins in the mycelium. Gene Ontology-based functional classification of detected proteins revealed 4884, 4981, and 3044 proteins, respectively, with roles in biological processes, molecular functions, and cellular components. Proteins such as P-loop, NTPase, and WD40 domains with key roles in signal transduction pathways were identified. KEGG pathway analysis annotated 2467 proteins to various signaling pathways, such as phosphatidylinositol, Ca2+, and mitogen-activated protein kinase, and autophagy and cell cycle. These molecular substrates might possess vital roles in filamentous growth, sporangia formation, degradation of damaged cellular content, and recycling of nutrients in P. palmivora. This large-scale proteomics data and analyses pave the way for new insights on biology, genome annotation, and vegetative growth of the important plant pathogen P. palmivora. They also can help accelerate research on future phytopathogen diagnostics and preventive interventions.

Xylosandrus crassiusculus (Motschulsky) (Coleoptera: Curculionidae) and Its Fungal Symbiont Ambrosiella roeperi Associated with Arecanut Kernel Decay in Karnataka, India.

Xylosandrus crassiusculus (Coleoptera: Curculionidae: Scolytinae) is reported causing damage to areca palm plantations (Areca catechu L.-Arecaceae) in Karnataka (India). In particular, X. crassiusculus has been observed attacking and successfully reproducing on areca nuts; besides the new host plant record, the data provided here represent the first documented case of spermatophagy for this xyleborine beetle. All infestation symptoms of this polyphagous pest were documented and illustrated. The identity of the scolytid, besides morphologically, was confirmed by its DNA barcoding. Eggs, larvae and pupae were found within the galleries of infested kernels. All galleries of the infested kernels were characterized by the presence of whitish to greyish fungal growth. The fungus was identified as Ambrosiella roeperi, a known symbiont of Xylosandrus crassiusculus. Incidence of this symbiotic insect-fungus complex in the economic part of arecanut, i.e., the kernel, is of serious concern. In a climate change scenario, this beetle with fungal symbionts may pose a serious threat to arecanut production in India and elsewhere.

Data of 16S rRNA gene amplicon-based metagenomic signatures of arecanut rhizosphere soils in Yellow Leaf Disease (YLD) endemic region of India.

Arecanut (Areca catechu L.) is an important plantation crop cultivated predominantly in the Indian states of Karnataka, Kerala, Assam, West Bengal, and Maharashtra in an area of 5.19 lakh ha, with Karnataka State alone accounting for about 68.41% of the area and 79.97% of production. Arecanut production has recently been hampered due to environmental and disease pressures, especially the escalating incidence of Yellow Leaf Disease (YLD). The involvement of phytoplasma as the etiological agent of YLD has been reported. Symptoms include yellowing at the tip of leaflets of two or three fronds of the outer most whorl which gradually spreads to the inner whorl of leaves. As the disease progresses, the entire crown becomes yellow leaving only the spear leaf green. In severe cases, the affected leaves often show necrosis from their tips. In advanced stages, the leaves are reduced in size and become stiff and pointed and the crown ultimately falls off. Degeneration of cortex is commonly observed in the diseased roots. The kernel of affected nuts shows discolouration and later turns blackish. The reduction in yield over a period of three years, immediately after the incidence of the disease, has been estimated to be around 50%. Harnessing the arecanut-microbiome interactions to address the biotic and abiotic stresses of the host plant offers immense opportunity to increase arecanut production sustainably. Here, we report a comprehensive analysis of the structural composition of the arecanut rhizosphere bacterial diversity utilizing next-generation sequencing (NGS) technology. We have used amplicon sequencing (V3-V4 regions of the 16S rRNA gene) of bulk soil and rhizosphere samples collected from YLD endemic regions of Aranthodu, Sullia Taluk, Dakshina Kannada District, Karnataka State, India, to assess the microbial diversity. The results revealed that while there is a great diversity of bacterial communities, relatively few bacterial phyla predominate with higher relative abundance. The phyla viz., Proteobacteria, Bacteroidetes, Firmicutes, Acidobacteria, Planctomycetes, Patescibacteria, Chloroflexi, Actinobacteria, Fusobacteria, and Verrucomicrobia were found to be dominant in the rhizosphere of the arecanut.

Entomopathogenic Potential of Simplicillium lanosoniveum Native Strain in Suppressing Invasive Whitefly, Aleurodicusrugioperculatus Martin (Hemiptera: Aleyrodidae), Infesting Coconut.

In 2016, infestation of an exotic polyphagous pest, the rugose spiraling whitefly (RSW), Aleurodicus rugioperculatus Martin (Hemiptera: Aleyrodidae), was documented on coconut for the first time in India. Instantaneously, RSW has garnered wide attention owing to its damage severity and rapid spread across the coconut-growing regions of the country. Hence, an attempt was made to devise a sustainable integrated pest management (IPM) module using biological control agents as a mainstay component. The present study documented the identification and characterization of a potential entomopathogenic fungal isolate for the management of RSW. An entomopathogenic fungus isolated from nymphal cadavers of RSW was identified as Simplicillium lanosoniveum based on morphological and phylogenetic analyses. A gradient of five conidial concentrations (1 × 104, 1 × 105, 1 × 106, 1 × 107 and 1 × 108 conidia/mL) of the S.lanosoniveum were tested against eggs, first instars, second to third instars and pupae of RSW. Results revealed that S.lanosoniveum is highly virulent to all developmental stages of RSW by causing mortality rates of 95.20%, 87.33%, 85.38% and 72.85%, in eggs, initial, middle and later instar nymphs of RSW, respectively, at the highest tested concentration (1 × 108 conidia/mL) at seven days after exposure. The LC50 and LT50 values of S.lanosoniveum were 4.72 × 104, 4.94 × 104, 5.11 × 105, 5.92 × 105 conidia/mL and 4.27, 4.86, 4.56, 5.89 days against eggs, initial, middle and later instar nymphs of RSW, respectively. Further, preliminary field trials with S.lanosoniveum strain at 1 × 108 conidia/mL exhibited a significant reduction in the egg and nymphal population by 57.8% and 56.3%, respectively. This report thus demonstrated that the newly isolated S.lanosoniveum is an effective pathogen at suppressing all the developmental stages of RSW. This is the first record of S.lanosoniveum infecting RSW, and it has a great potential to be developed as a mycoinsecticide.

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.

Evidence for genetic isolation and local adaptation in the field cricket Gryllus campestris.

Understanding how species can thrive in a range of environments is a central challenge for evolutionary ecology. There is strong evidence for local adaptation along large-scale ecological clines in insects. However, potential adaptation among neighbouring populations differing in their environment has been studied much less. We used RAD sequencing to quantify genetic divergence and clustering of ten populations of the field cricket Gryllus campestris in the Cantabrian Mountains of northern Spain, and an outgroup on the inland plain. Our populations were chosen to represent replicate high and low altitude habitats. We identified genetic clusters that include both high and low altitude populations indicating that the two habitat types do not hold ancestrally distinct lineages. Using common-garden rearing experiments to remove environmental effects, we found evidence for differences between high and low altitude populations in physiological and life-history traits. As predicted by the local adaptation hypothesis, crickets with parents from cooler (high altitude) populations recovered from periods of extreme cooling more rapidly than those with parents from warmer (low altitude) populations. Growth rates also differed between offspring from high and low altitude populations. However, contrary to our prediction that crickets from high altitudes would grow faster, the most striking difference was that at high temperatures, growth was fastest in individuals from low altitudes. Our findings reveal that populations a few tens of kilometres apart have independently evolved adaptations to their environment. This suggests that local adaptation in a range of traits may be commonplace even in mobile invertebrates at scales of a small fraction of species' distributions.

Loop mediated isothermal amplification (LAMP) assay for detection of coconut root wilt disease and arecanut yellow leaf disease phytoplasma.

The coconut root wilt disease (RWD) and the arecanut yellow leaf disease (YLD) are two major phytoplasma associated diseases affecting palms in South India. Greatly debilitating the palm health, these diseases cause substantial yield reduction and economic loss to farmers. A rapid and robust diagnostic technique is crucial in efficient disease management. We established phytoplasma 16S rDNA targeted loop mediated isothermal amplification (LAMP) and real time LAMP based diagnostics for coconut RWD and arecanut YLD. The LAMP reaction was set at 65 °C and end point detection made using hydroxynaphthol blue (HNB) and agarose gel electrophoresis. Molecular typing of LAMP products were made with restriction enzyme HpyCH4 V. Conventional PCR with LAMP external primers and sequencing of amplicons was carried out. Real time LAMP was performed on the Genei II platform (Optigene Ltd., UK). An annealing curve analysis was programmed at the end of the incubation to check the fidelity of the amplicons. The phytoplasma positive samples produced typical ladder like bands on agarose gel, showed colour change from violet to blue with HNB and produced unique annealing peak at 85 ± 0.5 °C in the real time detection. Restriction digestion produced predicted size fragments. Sequencing and BLASTN analysis confirmed that the amplification corresponded to phytoplasma 16S rRNA gene. LAMP method devised here was found to be more robust compared to conventional nested PCR and hence has potential applications in detection of phytoplasma from symptomatic palm samples and in rapid screening of healthy seedlings.

Rapid and sensitive detection of Phytophthora colocasiae responsible for the taro leaf blight using conventional and real-time PCR assay.

Conventional and real-time PCR assays were developed for sensitive and specific detection of Phytophthora colocasiae, an oomycete pathogen that causes leaf blight and corm rot of taro. A set of three primer pairs was designed from regions of the RAS-related protein (Ypt1), G protein alpha-subunit (GPA1) and phospho-ribosylanthranilate isomerase (TRP1) genes. In conventional PCR, the lower limit of detection was 50 pg DNA, whereas in real-time PCR, the detection limit was 12.5 fg for the primer based on Ypt1 gene. The cycle threshold values were linearly correlated with the concentration of the target DNA (range of R(2) = 0.911-0.999). All the primer sets were successful in detecting P. colocasie from naturally infected leaves and tubers of taro. Phytophthora colocasiae was detected from artificially infested samples after 18 and 15 h of postinoculation in conventional and real-time PCR assay, respectively. The developed PCR assay proved to be a robust and reliable technique to detect P. colocasiae in taro planting material and for assessing the distribution of pathogen within fields, thus aid in mitigating taro leaf blight.

Genetic diversity of Phytophthora colocasiae isolates in India based on AFLP analysis.

Phytophthora colocasiae that causes taro leaf blight is one of the most devastating diseases of taro which is widely distributed in India. Inter and intra-specific genetic diversity among P. colocasiae isolates collected from same field was assessed using amplified fragment length polymorphism (AFLP) marker. Seven primer pairs produced 431 markers, of which 428 (99.2 %) were polymorphic. Considerable genetic variability was displayed by the isolates. The average value of the number of observed alleles, the number of effective alleles, mean Nei's genetic diversity, and Shannon's information index were 1.993, 1.385, 0.261, and 0.420, respectively. Analysis of molecular variance (AMOVA) showed that the majority (85 %) of the diversity were present within populations of P. colocasiae. Dendrogram based on AFLP molecular data using the unweighted pair group method with arithmetic mean (UPGMA) classified the P. colocasiae isolates into two major clusters irrespective of their geographical origin. Clustering was further supported by principle coordinate analysis. Cophenetic correlation coefficient between dendrogram and original similarity matrix was significant (r = 0.816). The results of this study displayed a high level of genetic variation among the isolates irrespective of the geographical origin. The possible mechanisms and implications of this genetic variation are discussed.

Detection and Identification of Dasheen mosaic virus Infecting Colocasia esculenta in India.

Reverse transcription polymerase chain reaction of the infected leaf samples of Colocasia esculenta plants showing severe whitish feathery symptoms were carried out using Potyvirus group specific primers, resulting in an amplicon of 327 bp, encoding the core region of the coat protein gene. Sequencing and BLAST analysis showed that the virus is distinct, closely related to Dasheen mosaic virus (DsMV). Sequence analysis revealed 86 and 96% identity at the nucleotide and amino acid level respectively with the DsMV isolate SY1(accession Number AJ628756). This is the first molecular level characterisation of the DsMV infecting C. esculenta in India.