Dataset Information

A Framework for Identifying Selective Chemical Applications for IPM in Dryland Agriculture.

ABSTRACT: Shifts to Integrated Pest Management (IPM) in agriculture are assisted by the identification of chemical applications that provide effective control of pests relative to broad-spectrum pesticides but have fewer negative effects on natural enemy (beneficial) groups that assist in pest control. Here, we outline a framework for identifying such applications and apply this framework to field trials involving the crop establishment phase of Australian dryland cropping systems. Several chemicals, which are not presently available to farmers in Australia, were identified as providing moderate levels of pest control and seedling protection, with the potential to be less harmful to beneficial groups including predatory mites, predatory beetles and ants. This framework highlights the challenges involved in chemically controlling pests while maintaining non-target populations when pest species are present at damaging levels.

SUBMITTER: Umina PA

PROVIDER: S-EPMC4693183 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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A Framework for Identifying Selective Chemical Applications for IPM in Dryland Agriculture.

Umina Paul A PA Jenkins Sommer S McColl Stuart S Arthur Aston A Hoffmann Ary A AA

Insects 20151216 4

Shifts to Integrated Pest Management (IPM) in agriculture are assisted by the identification of chemical applications that provide effective control of pests relative to broad-spectrum pesticides but have fewer negative effects on natural enemy (beneficial) groups that assist in pest control. Here, we outline a framework for identifying such applications and apply this framework to field trials involving the crop establishment phase of Australian dryland cropping systems. Several chemicals, whic ...[more]

PMID: 26694469

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Project description:BackgroundResearch in organic chemistry generates samples of novel chemicals together with their properties and other related data. The involved scientists must be able to store this data and search it by chemical structure. There are commercial solutions for common needs like chemical registration systems or electronic lab notebooks. However for specific requirements of in-house databases and processes no such solutions exist. Another issue is that commercial solutions have the risk of vendor lock-in and may require an expensive license of a proprietary relational database management system. To speed up and simplify the development for applications that require chemical structure search capabilities, I have developed Molecule Database Framework. The framework abstracts the storing and searching of chemical structures into method calls. Therefore software developers do not require extensive knowledge about chemistry and the underlying database cartridge. This decreases application development time.ResultsMolecule Database Framework is written in Java and I created it by integrating existing free and open-source tools and frameworks. The core functionality includes:•Support for multi-component compounds (mixtures)•Import and export of SD-files•Optional security (authorization)For chemical structure searching Molecule Database Framework leverages the capabilities of the Bingo Cartridge for PostgreSQL and provides type-safe searching, caching, transactions and optional method level security. Molecule Database Framework supports multi-component chemical compounds (mixtures).Furthermore the design of entity classes and the reasoning behind it are explained. By means of a simple web application I describe how the framework could be used. I then benchmarked this example application to create some basic performance expectations for chemical structure searches and import and export of SD-files.ConclusionsBy using a simple web application it was shown that Molecule Database Framework successfully abstracts chemical structure searches and SD-File import and export to simple method calls. The framework offers good search performance on a standard laptop without any database tuning. This is also due to the fact that chemical structure searches are paged and cached. Molecule Database Framework is available for download on the projects web page on bitbucket: https://bitbucket.org/kienerj/moleculedatabaseframework.

Project description:A challenge for large-scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co-occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure-relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new "Tiered Exposure Ranking" (TiER) framework, developed to support various aspects of risk-relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both "discovery-driven" and "hypothesis-driven" analyses. "Tier 1" applications focus on "exposomic" pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk-relevant exposure metrics for populations and individuals. In this article, "tier 1" applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A "tier 2" application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk-relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.

Dataset Information

A Framework for Identifying Selective Chemical Applications for IPM in Dryland Agriculture.

Publications

A Framework for Identifying Selective Chemical Applications for IPM in Dryland Agriculture.

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