Study of the spatial variability of the southern root-knot nematode (Meloidogyne incognita) and its impact on cotton yield
Ortiz Uribe, Brenda Valeska
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Site-specific management (SSM) is a promising strategy for reducing yield losses caused by the southern root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) across the U.S Cotton Belt. To address this opportunity, this dissertation addresses the analysis of the spatial variability of RKN and its spatial relationship to edaphic, terrain, and chemical field properties. Additionally, simulations of RKN damage on different cotton biomass components, through adaptations to the CROPGRO-Cotton growth model, were used to estimate the damage of RKN within zones with a high likelihood for high RKN population. The work was conducted in the Tifton-Vidalia Upland (TVU) ecoregion of the southeastern Coastal Plain. Data were collected from eleven producers’ fields and one university-owned field used for a RKN long-term research project during 2005, 2006, and 2007. The fields were located in Colquitt, Tift, and Worth Counties of Georgia, USA. Two different approaches were used to identify field features related to the presence or absence of RKN: (i) geostatistical analyses (factorial kriging) to decompose the variability of RKN and soil properties into different spatial components allowing the computation of correlation coefficients for different spatial scales; and (ii) canonical correlation analyses (CCA) to determine which properties explained the greatest amount of variability in RKN population density. Areas at risk for different levels of RKN population were identified by indicator kriging and fuzzy clustering of canonical predictors derived from the CCA. The simulation of growth and yield of cotton plants infected with RKN was conducted by modifying the Cropping System Model (CSM)-CROPGRO-Cotton. The model was modified by coupling RKN population for removal of daily assimilate and decreasing root length per unit root weight as strategies to mimic RKN damage. This study showed that: (1) small patches with high RKN population were associated with the flat areas within a field and large patches were associated with low values of apparent soil electrical conductivity shallow (ECa-s, 0-30 cm depth) and deep (ECa-d, 0-90 cm depth); (2) areas at risk for RKN population above a threshold value can be delineated from a reduced number of RKN population samples and a dense data set of ECa-d; (3) low values of ECa-d, slope (SL), and NDVI can be associated with areas having high population of RKN; (4) RKN management zones can be delineated from edaphic terrain properties; (5) ECa-s and ECa-d properties offer much more stable information than terrain properties to characterize areas with low and high risk for having presence of RKN population; (6) RKN parasitism reduces cotton growth and development and induces a delay in maturity; (7) the adaptations of the Cropping System Model (CSM)-CROPGRO-Cotton in DSSAT v4.0 by coupling RKN population density and reducing the root length per unit root weight allowed the simulation of growth and yield for the DP 458 BR cotton variety impacted by various levels of RKN population; and (8) the use CSM-CROPGRO-Cotton model to simulate the seed cotton weight for different management zones with various risk levels for RKN allowed the quantification of potential yield losses due to RKN parasitism. Overall, this research contributes to the knowledge of RKN population variability as a function of edaphic and terrain attributes within fields of south Georgia, and develops techniques for applying site specific management to the pervasive problem of the southern root-knot nematode.