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Spatial distribution and risk area assessment of Aphelenchoides besseyi using geostatistical approaches in Giridih district of Jharkhand, India

Sandip Mondal
Sandip Mondal
, 
Matiyar Rahaman Khan
Matiyar Rahaman Khan
 oraz 
Abhishek Mukherjee
Abhishek Mukherjee
   | 23 kwi 2020
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Data publikacji: 23 kwi 2020
Zakres stron: 1 - 16
Otrzymano: 02 wrz 2019
DOI: https://doi.org/10.21307/jofnem-2020-033
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© 2020 Sandip Mondal et al., published by Sciendo.
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1:

Administrative map of India (A), Jharkhand (B), and Giridih (C) district. Grey circles (n = 163) represent the sampling locations of RWTN in Giridih during July to November, 2015.
Administrative map of India (A), Jharkhand (B), and Giridih (C) district. Grey circles (n = 163) represent the sampling locations of RWTN in Giridih during July to November, 2015.

Figure 2:

(A) Box and whisker plot representing population densities (no. of nematode/100 grains) of A. besseyi across different blocks of Giridih. The middle bar = median, box = inter-quartile range (25th-75th percentile), whiskers (error bars) above and below the box represents the 90th and 10th percentiles and the dots are the outlying points. No significant variation in population densities was observed across the block. (B) Agglomerative hierarchical cluster analysis of A. besseyi using average linkage method identifies three main clusters among blocks of Giridih district.
(A) Box and whisker plot representing population densities (no. of nematode/100 grains) of A. besseyi across different blocks of Giridih. The middle bar = median, box = inter-quartile range (25th-75th percentile), whiskers (error bars) above and below the box represents the 90th and 10th percentiles and the dots are the outlying points. No significant variation in population densities was observed across the block. (B) Agglomerative hierarchical cluster analysis of A. besseyi using average linkage method identifies three main clusters among blocks of Giridih district.

Figure 3:

Maps of optimized hotspot analysis of RWTN population density showing significant hotspots (darker color) and cold spots (lighter color) in Giridih district of Jharkhand. Gi Bin values represent those points value showing significant hotspot (red color), cold spot (green color) and points with no significance (blue color). Color coded surface map was prepared using z-score of Getis-Ord Gi statistics through IDW interpolation method for better visualization.
Maps of optimized hotspot analysis of RWTN population density showing significant hotspots (darker color) and cold spots (lighter color) in Giridih district of Jharkhand. Gi Bin values represent those points value showing significant hotspot (red color), cold spot (green color) and points with no significance (blue color). Color coded surface map was prepared using z-score of Getis-Ord Gi statistics through IDW interpolation method for better visualization.

Figure 4:

Interpolated population density maps of RWTN using inverse distance weighting (IDW). Darker to lighter color represents higher to lower population density change. Log(x + 1) transformed data has been used, where x is the actual nematode population density.
Interpolated population density maps of RWTN using inverse distance weighting (IDW). Darker to lighter color represents higher to lower population density change. Log(x + 1) transformed data has been used, where x is the actual nematode population density.

Figure 5:

Semivariogram of RWTN population densities through ordinary kriging (A) and indicator kriging (B). Blue line shows the fitted semivariogram through exponential model. Model parameters have been enlisted in Table 1.
Semivariogram of RWTN population densities through ordinary kriging (A) and indicator kriging (B). Blue line shows the fitted semivariogram through exponential model. Model parameters have been enlisted in Table 1.

Figure 6:

Interpolated map of RWTN distribution in Giridih district through ordinary kriging. Darker to lighter color represent high to low population density of Aphelenchoides besseyi.
Interpolated map of RWTN distribution in Giridih district through ordinary kriging. Darker to lighter color represent high to low population density of Aphelenchoides besseyi.

Figure 7:

Probability distribution map of Aphelenchoides besseyi using indicator kriging. Color map (red to blue) represents probability (high to low) of risk areas infestation with RWTN.
Probability distribution map of Aphelenchoides besseyi using indicator kriging. Color map (red to blue) represents probability (high to low) of risk areas infestation with RWTN.

Figure A1:

Silhouette plot using average linkage method of rice white tip nematode population density among blocks of Giridih. Silhouette width (S i ) determines the wellness of clustering.
Silhouette plot using average linkage method of rice white tip nematode population density among blocks of Giridih. Silhouette width (S i ) determines the wellness of clustering.

Figure A2:

Histogram (A) and normal QQ plot (B) of log(x + 1) transformed data of rice white tip nematode to understand the distribution of data.
Histogram (A) and normal QQ plot (B) of log(x + 1) transformed data of rice white tip nematode to understand the distribution of data.

Figure A3:

Trend analysis of rice white tip nematode data where each stick represents the location and value (height) of RWTN population density. Best fit lines (blue and green) show trends in specific directions.
Trend analysis of rice white tip nematode data where each stick represents the location and value (height) of RWTN population density. Best fit lines (blue and green) show trends in specific directions.

Figure A4:

Semivariogram of different experimental models of RWTN population densities through ordinary kriging (A) and indicator kriging (B). Blue line shows the fitted semivariogram through different models. Model parameters have been enlisted in Table 1.
Semivariogram of different experimental models of RWTN population densities through ordinary kriging (A) and indicator kriging (B). Blue line shows the fitted semivariogram through different models. Model parameters have been enlisted in Table 1.

Semivariogram model parameters and cross-validation results of ordinary kriging and indicator kriging.

Semivariogram model Range (m) Nugget (C o) Partial sill (C) MPE RMSE RMS ASE
Ordinary kriging
 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
Indicator kriging
 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
eISSN:
2640-396X
Język:
Angielski
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Volume Open
Dziedziny czasopisma:
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