Sandip Mondal, Emile Gluck-Thaler, Cristhian J Grabowski Ocampos, Enrique Hahn Villalba, Terry L Niblack, Aida L Orrego Fuente, Lidia M Pedrozo, Timothy I Ralston, Laura C Soilan, Horacio D Lopez-Nicora
{"title":"地质统计建模改进了对大豆田中相枕虫丰度和分布的预测。","authors":"Sandip Mondal, Emile Gluck-Thaler, Cristhian J Grabowski Ocampos, Enrique Hahn Villalba, Terry L Niblack, Aida L Orrego Fuente, Lidia M Pedrozo, Timothy I Ralston, Laura C Soilan, Horacio D Lopez-Nicora","doi":"10.1094/PHYTO-04-24-0139-R","DOIUrl":null,"url":null,"abstract":"<p><p>Charcoal rot, caused by the soilborne fungus <i>Macrophomina phaseolina</i> (Mp) poses a serious threat to soybean health and harvests at a global scale. Mp exhibits varying distribution patterns across fields, which complicates our ability to predict disease occurrences and outbreaks. Therefore, determining the spatial distribution of Mp abundance and its relation with soil physicochemical properties would help to inform precision management decisions for mitigating charcoal rot. To achieve this, Mp colony forming units (CFU) and edaphic properties were evaluated in 297 soybean fields located in the main soybean growing regions across 7 Departments of Paraguay. A pattern of decreasing CFU density was observed from the south-eastern to the western part of the country. While several edaphic factors are positively correlated with Mp CFU, pH showed a significant negative correlation with CFU. Both spatial and non-spatial model suggest that cation exchange capacity, percentage of clay, and pH could be potential predictors of Mp CFU abundance. Including spatial dependence of edaphic factors improved the prediction of Mp CFU more effectively than classical statistical models. We demonstrated that the occurrence of Mp shows a significant spatial clustering pattern as indicated by Moran's I. Our findings will help growers and policy-makers make informed decisions for managing Mp by improving our ability to predict which agricultural fields and soils are at greatest risk for charcoal rot.</p>","PeriodicalId":20410,"journal":{"name":"Phytopathology","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Geostatistical modelling improves prediction of <i>Macrophomina phaseolina</i> abundance and distribution in soybean fields.\",\"authors\":\"Sandip Mondal, Emile Gluck-Thaler, Cristhian J Grabowski Ocampos, Enrique Hahn Villalba, Terry L Niblack, Aida L Orrego Fuente, Lidia M Pedrozo, Timothy I Ralston, Laura C Soilan, Horacio D Lopez-Nicora\",\"doi\":\"10.1094/PHYTO-04-24-0139-R\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Charcoal rot, caused by the soilborne fungus <i>Macrophomina phaseolina</i> (Mp) poses a serious threat to soybean health and harvests at a global scale. Mp exhibits varying distribution patterns across fields, which complicates our ability to predict disease occurrences and outbreaks. Therefore, determining the spatial distribution of Mp abundance and its relation with soil physicochemical properties would help to inform precision management decisions for mitigating charcoal rot. To achieve this, Mp colony forming units (CFU) and edaphic properties were evaluated in 297 soybean fields located in the main soybean growing regions across 7 Departments of Paraguay. A pattern of decreasing CFU density was observed from the south-eastern to the western part of the country. While several edaphic factors are positively correlated with Mp CFU, pH showed a significant negative correlation with CFU. Both spatial and non-spatial model suggest that cation exchange capacity, percentage of clay, and pH could be potential predictors of Mp CFU abundance. Including spatial dependence of edaphic factors improved the prediction of Mp CFU more effectively than classical statistical models. We demonstrated that the occurrence of Mp shows a significant spatial clustering pattern as indicated by Moran's I. Our findings will help growers and policy-makers make informed decisions for managing Mp by improving our ability to predict which agricultural fields and soils are at greatest risk for charcoal rot.</p>\",\"PeriodicalId\":20410,\"journal\":{\"name\":\"Phytopathology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Phytopathology\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1094/PHYTO-04-24-0139-R\",\"RegionNum\":2,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PLANT SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Phytopathology","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1094/PHYTO-04-24-0139-R","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
Geostatistical modelling improves prediction of Macrophomina phaseolina abundance and distribution in soybean fields.
Charcoal rot, caused by the soilborne fungus Macrophomina phaseolina (Mp) poses a serious threat to soybean health and harvests at a global scale. Mp exhibits varying distribution patterns across fields, which complicates our ability to predict disease occurrences and outbreaks. Therefore, determining the spatial distribution of Mp abundance and its relation with soil physicochemical properties would help to inform precision management decisions for mitigating charcoal rot. To achieve this, Mp colony forming units (CFU) and edaphic properties were evaluated in 297 soybean fields located in the main soybean growing regions across 7 Departments of Paraguay. A pattern of decreasing CFU density was observed from the south-eastern to the western part of the country. While several edaphic factors are positively correlated with Mp CFU, pH showed a significant negative correlation with CFU. Both spatial and non-spatial model suggest that cation exchange capacity, percentage of clay, and pH could be potential predictors of Mp CFU abundance. Including spatial dependence of edaphic factors improved the prediction of Mp CFU more effectively than classical statistical models. We demonstrated that the occurrence of Mp shows a significant spatial clustering pattern as indicated by Moran's I. Our findings will help growers and policy-makers make informed decisions for managing Mp by improving our ability to predict which agricultural fields and soils are at greatest risk for charcoal rot.
期刊介绍:
Phytopathology publishes articles on fundamental research that advances understanding of the nature of plant diseases, the agents that cause them, their spread, the losses they cause, and measures that can be used to control them. Phytopathology considers manuscripts covering all aspects of plant diseases including bacteriology, host-parasite biochemistry and cell biology, biological control, disease control and pest management, description of new pathogen species description of new pathogen species, ecology and population biology, epidemiology, disease etiology, host genetics and resistance, mycology, nematology, plant stress and abiotic disorders, postharvest pathology and mycotoxins, and virology. Papers dealing mainly with taxonomy, such as descriptions of new plant pathogen taxa are acceptable if they include plant disease research results such as pathogenicity, host range, etc. Taxonomic papers that focus on classification, identification, and nomenclature below the subspecies level may also be submitted to Phytopathology.