种植者如何应对寄主的抗性?杀菌剂成本节约因果推理的条件高斯贝叶斯网络。

IF 3.1 2区 农林科学 Q2 PLANT SCIENCES
Jae Young Hwang, Sharmodeep Bhattacharyya, Shirshendu Chatterjee, Thomas L Marsh, Joshua F Pedro, David H Gent
{"title":"种植者如何应对寄主的抗性?杀菌剂成本节约因果推理的条件高斯贝叶斯网络。","authors":"Jae Young Hwang, Sharmodeep Bhattacharyya, Shirshendu Chatterjee, Thomas L Marsh, Joshua F Pedro, David H Gent","doi":"10.1094/PHYTO-06-25-0199-R","DOIUrl":null,"url":null,"abstract":"<p><p>The economic value of cultivars resistant to disease is of great interest, but how growers change their fungicide use in response to host resistance may be nuanced. We draw upon a well-described data set of the incidence of hop plants with powdery mildew and associated production meta-data and demonstrate the utility of Bayesian networks as a framework for quantifying causal relationships for fungicides use and cost in response to host resistance. Conditional Gaussian Bayesian network models applied to cultivars differing in race-specific resistance to powdery mildew revealed cultivar resistance to powdery mildew influenced disease levels in early spring, which had causal effect on how often and what fungicides growers later applied. Annual costs depended not only on the number of applications made but the specific types of fungicides growers selected. Fungicide costs were little changed on cultivars that possessed race- specific resistance to only one of two extant strains of the pathogen. For cultivars with resistance to both pathogen strains, annual costs of fungicides were reduced commensurate with the level of resistance. Predicted values from the Bayesian networks and simulation indicate that growers apply a baseline level of fungicide, independent of cultivar resistance. Fungicide cost savings result from how fungicide inputs differentially scale with the incidence of powdery mildew and the type of fungicides used. Our analyses indicate that for a high value crop, deployment of disease resistance may cause complex and unexpected changes in growers' fungicide use patterns that may not be obvious in simplified randomized controlled trials.</p>","PeriodicalId":20410,"journal":{"name":"Phytopathology","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How Do Growers Respond to Host Resistance? A Conditional Gaussian Bayesian Network for Causal Inference of Fungicide Cost Savings.\",\"authors\":\"Jae Young Hwang, Sharmodeep Bhattacharyya, Shirshendu Chatterjee, Thomas L Marsh, Joshua F Pedro, David H Gent\",\"doi\":\"10.1094/PHYTO-06-25-0199-R\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The economic value of cultivars resistant to disease is of great interest, but how growers change their fungicide use in response to host resistance may be nuanced. We draw upon a well-described data set of the incidence of hop plants with powdery mildew and associated production meta-data and demonstrate the utility of Bayesian networks as a framework for quantifying causal relationships for fungicides use and cost in response to host resistance. Conditional Gaussian Bayesian network models applied to cultivars differing in race-specific resistance to powdery mildew revealed cultivar resistance to powdery mildew influenced disease levels in early spring, which had causal effect on how often and what fungicides growers later applied. Annual costs depended not only on the number of applications made but the specific types of fungicides growers selected. Fungicide costs were little changed on cultivars that possessed race- specific resistance to only one of two extant strains of the pathogen. For cultivars with resistance to both pathogen strains, annual costs of fungicides were reduced commensurate with the level of resistance. Predicted values from the Bayesian networks and simulation indicate that growers apply a baseline level of fungicide, independent of cultivar resistance. Fungicide cost savings result from how fungicide inputs differentially scale with the incidence of powdery mildew and the type of fungicides used. Our analyses indicate that for a high value crop, deployment of disease resistance may cause complex and unexpected changes in growers' fungicide use patterns that may not be obvious in simplified randomized controlled trials.</p>\",\"PeriodicalId\":20410,\"journal\":{\"name\":\"Phytopathology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-10-01\",\"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-06-25-0199-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-06-25-0199-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}
引用次数: 0

摘要

抗病品种的经济价值是人们非常感兴趣的,但种植者如何根据宿主的抗性改变杀菌剂的使用可能是微妙的。我们利用酒花植物白粉病发病率的良好描述数据集和相关的生产元数据,并证明贝叶斯网络作为量化杀菌剂使用和成本对宿主抗性的因果关系的框架的效用。将条件高斯贝叶斯网络模型应用于不同品种对白粉病的抗性,结果表明,品种对白粉病的抗性影响早春的病害水平,这对种植者后来使用杀菌剂的频率和种类有因果影响。每年的费用不仅取决于施用的次数,而且取决于种植者选择的特定类型的杀菌剂。在对现存的两种病原菌株中只有一种具有种族特异性抗性的品种上,杀菌剂的成本变化不大。对两种病原菌均有抗性的品种,杀菌剂的年费用随抗性水平的降低而相应降低。贝叶斯网络和模拟的预测值表明,种植者施用的杀菌剂是一个基线水平,与品种的抗性无关。杀菌剂成本的节省是由于杀菌剂的投入与白粉病的发病率和所使用的杀菌剂的类型有不同的比例。我们的分析表明,对于一种高价值作物,抗病性的部署可能会导致种植者的杀菌剂使用模式发生复杂和意想不到的变化,而这种变化在简化的随机对照试验中可能并不明显。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How Do Growers Respond to Host Resistance? A Conditional Gaussian Bayesian Network for Causal Inference of Fungicide Cost Savings.

The economic value of cultivars resistant to disease is of great interest, but how growers change their fungicide use in response to host resistance may be nuanced. We draw upon a well-described data set of the incidence of hop plants with powdery mildew and associated production meta-data and demonstrate the utility of Bayesian networks as a framework for quantifying causal relationships for fungicides use and cost in response to host resistance. Conditional Gaussian Bayesian network models applied to cultivars differing in race-specific resistance to powdery mildew revealed cultivar resistance to powdery mildew influenced disease levels in early spring, which had causal effect on how often and what fungicides growers later applied. Annual costs depended not only on the number of applications made but the specific types of fungicides growers selected. Fungicide costs were little changed on cultivars that possessed race- specific resistance to only one of two extant strains of the pathogen. For cultivars with resistance to both pathogen strains, annual costs of fungicides were reduced commensurate with the level of resistance. Predicted values from the Bayesian networks and simulation indicate that growers apply a baseline level of fungicide, independent of cultivar resistance. Fungicide cost savings result from how fungicide inputs differentially scale with the incidence of powdery mildew and the type of fungicides used. Our analyses indicate that for a high value crop, deployment of disease resistance may cause complex and unexpected changes in growers' fungicide use patterns that may not be obvious in simplified randomized controlled trials.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Phytopathology
Phytopathology 生物-植物科学
CiteScore
5.90
自引率
9.40%
发文量
505
审稿时长
4-8 weeks
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信