White tip nematode (
Rice white tip nematode completes its life cycle within 8 to 12 days at 30°C. It can survive for three years in a state of anhydrobiosis as adults and fourth stage juveniles in between the lemma and palea of rice grain and as a seed-borne nematode it can survive for several years in storage conditions (Tiwari and Khare, 2003; Khan, 2010). During the initial phase of infection, RWTN feeds on axillary buds of shoot and apical stem while in later phase, they enter into the spikelets before anthesis and feeds on embryo, lodicule, ovaries, and stamens (Bridge et al., 2005). Characteristic attack symptoms include whitening of leaf tips at the vegetative stage and distortion of upper part of the plant including flag leaf and panicle at generative stage. Principal mode of dissemination of RWTN is through infested seeds. However, the nematode can survive in the straw, rice stubbles, wild rice, and some weed species in the rice fields (Sivakumar, 1987; Giuddici et al., 2004, Khan, 2010). While several reports have identified RWTN as a serious threat to rice production in the eastern states of India, as of now, no detail information on its infestation pattern in the state of Jharkhand is available.
To manage RWTN infestation, several control measures like hot water treatment, chemical seed treatment, cultural management, and host plant resistance have been adopted. Pashi
Geostatistical analyses have been used in the field of nematology to evaluate threat of nematode diseases, devise sampling strategy, investigate level of infestation, and to identify infestation hotspots for site-specific nematode management (Dinardo-Miranda and Fracasso, 2009; Ortiz et al., 2010; Contina et al., 2018). Relationships between spatial variability of nematodes and environmental covariates which influence nematode population have also been established using these tools. For example, Gavassoni
As mentioned above, no information exists, to date, on the infestation patterns and population densities of RWTN in Jharkhand. Generating such information would be an important first step in identifying areas where the RWTN population is beyond the ETL (Economic threshold level) (300 nematodes/100 seeds, Fukano, 1962). Though there is considerable ambiguity in available literature regarding the ETL level of
This study was conducted in Giridih district of Jharkhand (Fig. 1), India during
Nematode sampling was conducted across the Giridih during months of October to November, coinciding with the ripening phase of rice. A minimum distance of 1 km was maintained between two sample points. From each block 12 to 18 samples were randomly collected following ‘W’ pattern sample walk method (Karuri et al., 2017). At each site, 30 matured rice panicles were randomly sampled from three adjoining rice fields. Each sampling site was geopositioned and collected panicles were labeled and stored in paper packets before bringing back to the laboratory. In total, 163 samples were collected across the district (Fig. 1C).
Nematodes were isolated using the modified Baermann Funnel method (Schindler, 1961). Briefly, from each sampling site, 100 grains were randomly separated from the collected panicles and pounded with motor and pastel. The grinded material was placed over tissue paper wire gauge assembly placed on a Petri plate filled with water. This assembly was covered with another Petri plate to minimize evaporation loss and kept for 24 hr at room temperature (around 30°C). Extracted nematodes were killed in hot water bath at 65°C for 5 min and fixed in TAF fixative for further analysis (Shepherd, 1970). For identification, fixed nematode samples were processed by Seinhorst’s glycerol-ethanol method (Seinhorst, 1959) and finally mounted on glass slides according to De Grisse (1969). Species identification was done based on morphology and morphometrics key parameters by Khan
Population densities of RWTN collected across different blocks were subjected to the Kruskal–Wallis test in R statistical software (version R-3.6.1) to examine if any significant variation exists between administrative blocks of Jharkhand state. Box and whisker plot representing population densities (no. of nematode/100 grains) of
Spatial pattern of RWTN distribution in Giridih district was characterized by utilizing two different geospatial statistical techniques, point pattern and surface interpolation analyses. First, to identify if any significant hotspots of RWTN infestation exists in the district, point pattern optimized hotspot analysis was carried out. Second, inverse distance weighting (IDW) and Kriging were used to generate continuous map of predicted surface of nematode distribution across Giridih. Finally, risk areas of RWTN (population density > ETL) in the district was delineated by utilizing the indicator kriging (IK) tool, which is also a surface interpolation method. All these operations were performed using ArcMap 10.2, ESRI.
As nematode density data was positively skewed, log(
Gi* is the
Spatial interpolation is a tool to predict the values of a spatial phenomenon at unsampled locations, like if population density of RWTN at locations (
IDW is one of the simplest interpolation techniques where weighted mean of the neighboring observations are taken into consideration. Weights are usually inversely proportional to a power of distance (Burrough, 1986; Watson, 1992) which, at an unsampled location
From theoretical point of view, kriging is the optimal interpolation technique to estimate a random variable
Surface map of population density of RWTN was prepared using ordinary kriging (OK) tool in ArcMap 10.2. As population density data showed strong positive skewness, log(
Spherical model:
Exponential model:
Gaussian model:
Hole effect model:
To identify the areas where population density of RWTN is above the economic threshold level (ETL) level of 300 nematodes/100 seeds, indicator kriging was performed. Indicator kriging was chosen for this purpose because a map showing areas where the population density of RWTN exceeds the ETL would greatly benefit the rice growers. Indicator kriging was performed following steps similar to that mentioned in case of ordinary kriging. Color coded krigged map was generated with contour symbolization delineating high risk areas.
The nematode species was confirmed to be
Moran’s I spatial autocorrelation results suggest presence of significant (
Result of IDW has been depicted through color coded map (Fig. 4), with darker color representing higher population density of RWTN. Of the total interpolated surface, in 2.33% areas, up to 50 nematodes/100 grains was observed. A population density up to 100, 200, and 500 nematodes/100 grain were observed in 30.11%, 48.61%, and 16.94% of the total surface, respectively. In 1.99% of the predicted surface where population density exceeded 500 nematodes/100 grains comprised mainly of Dumri and parts of Giridih and Bengabad blocks. In IDW interpolation techniques, 6.25% of the total interpolated surface was found to possess population density beyond the ETL level.
While the nematode density data were log (
Semivariogram model parameters and cross-validation results of ordinary kriging and indicator kriging.
Semivariogram model | Range (m) | Nugget ( |
Partial sill ( |
MPE | RMSE | RMS | ASE |
---|---|---|---|---|---|---|---|
|
|||||||
Exponential | 7,256.82 | 0 | 0.5544 | 0.0175 | 1.0311 | 0.7257 | 0.6915 |
Circular | 8,166.39 | 0.1730 | 0.3819 | 0.0197 | 1.0661 | 0.7297 | 0.6740 |
Spherical | 8,494.25 | 0.1365 | 0.4178 | 0.0186 | 1.0661 | 0.7287 | 0.6742 |
Gaussian | 6,707.44 | 0.1855 | 0.3682 | 0.0167 | 1.0676 | 0.7330 | 0.6798 |
Hole effect | 14,738.38 | 0.2762 | 0.2762 | 0.0280 | 1.0788 | 0.7356 | 0.6703 |
|
|||||||
Exponential | 8,748.75 | 0 | 0.1897 | 0.0116 | 0.9786 | 0.3896 | 0.3875 |
Circular | 6,641.76 | 0 | 0.1887 | 0.0117 | 1.0759 | 0.4003 | 0.3681 |
Spherical | 7,548.16 | 0 | 0.1887 | 0.0122 | 1.0575 | 0.3977 | 0.3704 |
Gaussian | 5,960.37 | 0.0212 | 0.1672 | 0.0086 | 1.0627 | 0.3967 | 0.3738 |
Hole effect | 13,757.33 | 0.0778 | 0.1103 | 0.0395 | 1.0663 | 0.0140 | 0.3789 |
Indicator kriging was performed similarly like ordinary kriging. Among different experimental models (see Supplementary Fig. A4), here also exponential model was found to be best fitted model. Lag size of 3037 meter was used as in case of ordinary kriging. Semivariogram of exponential model has been shown in Figure 5B. Model parameters and cross-validation results were presented in Table 1. Probability distribution map (Fig. 7) was prepared with the threshold value of 300 nematodes/100 grains. Of total interpolated surface, 58.5% area belongs to low probability (20%) risk areas like Gawan, Deori, Birni, Sariya, Bagodar, and parts of other blocks, whereas up to 50% (medium) and 70% (high) probability to cross the ETL comprised of 29.75% and 7.49% of total interpolated surface. Very high probability (75-100%) to cross the ETL boundary was found in Dumri, Giridih, Gande, Bengabad, and some other fragmented parts of the district which comprised 4.17% of the total interpolated surface.
The spatial point pattern analysis implemented in our study helped to identify the RWTN hotspots in the Giridih district of Jharkhand. In addition, surface analysis of nematode population density data revealed high population density (>100 nematodes/100 grains) of RWTN across the district. These results, being first for this nematode in the district, have important management implications.
Rice is the predominant crop of the Giridih district where most of the fields remain fallow after the harvest of rice till next season. The shattered rice grains and regrowth of rice stubbles as ratoon rice maintain and carry over the nematode population from season to season. Furthermore, RWTN present in rice stubbles in the field after rice harvest and the fungi (
Being a seed-borne pathogen, presence of significant spatial clustering of RWTN infested fields, as shown by the Moran’s I spatial autocorrelation, indicates that exchanges of infected seeds and plant materials like rice husk and plant debris or infected straw might have resulted in the spread of the nematode to the nearby fields from the initial infestation foci (Sivakumar, 1987; Bridge et al., 2005). Infestation hotspots in the Dumri and adjacent blocks could act as sources of future spread of the nematode disease in other areas of the Jharkhand State. Repeated use of infested seed material could lead to high population build-up of nematodes as observed in these locations. Such a scenario of spread of nematode infestation has been referred to as the contagion effect scenario and was previous observed in case of spread of the golden nematode of potato (
Both the surface interpolation techniques, IDW and ordinary kriging, yielded similar prediction surfaces of nematode population density across the district. Experimental variogram for population density of RWTN showed relatively strong spatial correlation indicating the presence of spatial dependency. As spatial dependency is present, kriging is considered as better interpolation tool than IDW due to problems associated with distance-based interpolation methods. The use of ordinary kriging generated map is therefore recommended (Yao et al., 2013; Gong et al., 2014; Shahbeik et al., 2014). In Brazil, a
One of the major drawbacks of using ordinary kriging is that the smoothed map it generates does not capture the extreme population density values (Farias et al., 2002). To avoid this issue, indicator kriging approach was implemented to generate probability risk map of RWTN infestation. This approach corroborates with the study of southern root knot nematode (
The spatial distribution maps generated in our study could be utilized by the farmers and extension agents in devising precautionary measures and formulating management strategies to prevent further spread of this important plant parasitic nematodes in subsequent growing seasons in the district. Management of RWTN could consist of two major strategies: curative and preventative. Disinfection of seed could be a possible means of complete elimination of white tip nematode disease. In high risk areas, curative control measures like sun drying of seeds and pre-soaking seeds in cold water for 18 to 24 hr followed by hot water treatment (51-53°C) for 15 min prior to sowing can be effectively used to minimize the population density build up (Kuriyan, 1995; Bridge et al., 2005; Pashi et al., 2017b). In addition, agronomic practices like early seed bed preparation, irrigation of seed beds immediately after seeding to asynchronies nematode hatching with rice germination, cultivating leguminous crops after rice and destroying crop residues after harvesting could help in decreasing field populations of RWTN (Yamada et al., 1953; Kim et al., 1996).
Like other seed-borne nematodes, establishment of quarantine measures to prevent further spread of RWTN infected seed material from high risk areas could be an effective strategy in stopping the spread of this nematode in low risk areas. This will not only help in reducing the population density load in high risk areas subsequent years, but also reduce the dissemination of the disease in the nearby areas. Use of resistant variety is another eco-friendly management strategy against nematodes. For example, in Russia, resistance screening was conducted with 1,003 rice cultivar against RWTN in glasshouse and three were found to be immune, 10 highly resistant, 164 moderately resistant and rest were susceptible (Popova and Subbotin, 1994; Tülek et al., 2015). However, no studies were conducted so far in India to identify rice cultivars resistant against RWTN, to our knowledge.
Lack of knowledge among farmers regarding this nematode is a crucial factor for wide spread distribution of plant parasitic nematodes in general and RWTN in particular. As nematodes are microscopic and generally do not generate any specific symptoms, farmers often confuse nematode infestation with nutrient or water deficiency. To improve farmers’ perception about RWTN infestation, farmers training workshops can be conducted in agricultural extension centers. Increasing awareness among farmers will reduce the use of contaminated seeds which will help in prevention of spread of RWTN in the district.
In future, the geostatistical methods implemented in our study could be used to generate spatial distribution maps of other agriculturally important plant parasitic nematodes. Beside rice,