Nematode spatial distribution in the service of biological pest control

被引:3
作者
Abd-Elgawad, Mahfouz M. M. [1 ]
机构
[1] Natl Res Ctr, Plant Pathol Dept, El Behooth St, Giza 12622, Egypt
关键词
Agricultural sustainability; Bioinformatics; Index of dispersion; PCR-based methods; ENTOMOPATHOGENIC NEMATODES; PRATYLENCHUS-PENETRANS; MELOIDOGYNE-HAPLA; PATTERN; AGGREGATION; POPULATIONS; COMMUNITY; FIELDS;
D O I
10.1186/s41938-024-00768-6
中图分类号
Q96 [昆虫学];
学科分类号
摘要
Sound nematode sampling techniques and related measures can gain biocontrol merits from determining their spatial (geographic and temporal) distribution patterns. These latter may be compared to other relevant biotic/abiotic forces to unfold complexities of ecosystem dynamics into quantifiable variables for better development of controlling plant pests/pathogens. Because biotic/abiotic factors are mostly more sensitive in biocontrol tactics than chemical pesticides, it becomes increasingly important to quantify such variables. Herein, pros and cons of common models used to characterize such patterns are reviewed. Adjusting models to acquire more accurate and targeted outputs for cost-effective and reliable plant-parasitic nematode management are presented, e.g., revising optimum sample size. Single models can act for the nematode-count transformation to meet assumptions necessary for parametric statistical analyses and consequently attain valid and accurate treatment comparisons. Yet, it is preferable to use more than one model to demonstrate more aspects of nematode distributions and optimize pest control in integrated pest management (IPM) plans. Harnessing these aspects will enable best seed-location matching, leverage variable rates of the used bionematicides and grasp relationships between beneficial/harmful organisms in space and time for alert IPM. Entomopathogenic nematode spatial (horizontal/vertical) distributions can mirror shifting in their key community dynamics such as parasitism and competition. To overcome limitations related to these models, incorporating emerging innovations like the PCR-based approaches to identify and quantify species (e.g., qPCR versus high-throughput sequencing), bioinformatics and volatile organic compounds as signals for soil inhabitants are discussed.
引用
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页数:9
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