Este proyecto de carácter nacional busca entregar un espacio en la red donde se pueda encontrar las herramientas necesarias para realizar vigilancia, pronóstico, investigación y control de la plaga emergente Drosophila suzukii. Busca articular información técnica, proyectos, artículos de investigación e investigadores. Además entrega información en tiempo real a los beneficiarios, productores, investigadores, asesores, sobre las detecciones validadas a nivel comunal.

El Objetivo del proyecto es mitigar impacto económico mediante difusión y capacitaciones taxonómicas y visuales enfocadas a pequeños productores, logrando un plan de manejo integrado de la plaga.

The field of remote sensing is experiencing an unprecedented acceleration. Besides the large public programs such as Sentinel (see e.g. https://sentinel.esa.int/web/sentinel/missions/sentinel-2), private actors are creating fleets of micro-satellites capable of monitoring of the earth with daily revisits. This abundant and cheap data is creating opportunities for developing novel applications for the monitoring of industrial and agricultural activity. The automatic exploitation of this data is bound to specific application domain knowledge, which requires a mastery of advanced techniques such as computer vision and machine learning, as well as expert knowledge in the field of agriculture. To do this, the team must master earth observation satellites, be able to define the adequate mathematical detection theories, and build on a deep knowledge of satellite image processing, while also including expert knowledge in agriculture. This project aims at uniting competences across the fields of computer vision and machine learning, remote sensing to address emerging applications in agronomy. This project will in addition foster the creation of reproducible research by adopting a reproducible research methodology thus contributing the resulting algorithms to the journal Image Processing On-Line (IPOL). The IPOL journal is an initiative to establish a clear and reproducible state-of-the-art in the domain of image processing and computer vision.

Objetivo General
Desarrollar un kit de qPCR que permita evaluar con precisión la sensibilidad farmacológica de C.
rogercresseyi a tratamientos como inhibidores de quitina mediante asociación estadística entre
frecuencia de marcadores genómicos y eficacia de tratamientos en campo.

Objetivos Específicos
1. Validar estadísticamente la relación entre las variantes genómicas detectadas por el kit de
qPCR y la resistencia a tratamientos con inhibidores de quitina.
2. Establecer un protocolo de buenas prácticas de laboratorio para la correcta aplicación del
kit de qPCR.
3. Implementar capacitaciones para laboratorios y culminar con la certificación de aquellos
aptos para aplicar la técnica con eficacia.

The use of antimicrobials (AMU) in the salmon farming industry in Chile is concentrated in the sea fattening phase of the production cycle. In 2022, 91% of the AMU in fattening farms was for treatment of Piscirickettsia salmonis (Sernapesca, 2023), the main disease-causing pathogen affecting farmed salmon in Chile (Rozas and Enriquez, 2014).

To control P. salmonis, a series of preventive strategies have been adopted. Nevertheless, the incidence of P. salmonis remains high; resulting in high mortality rates (Jakob et al., 2014) and extensive AMU. The use of antimicrobials is exacerbated by current management practices in salmon farms as well as a lack of standardization in treatment guidelines and practices between veterinarians and companies (e.g. treatment of all or selected cages, dosage, etc.), but also because of limited consolidation, communication and use of available AMU data.

The aim of this project is to reduce antimicrobial consumption in salmon farming in Los Lagos and Aysen regions where P. salmonis is a challenge and improve science-based governance of AMU in the salmon farming sector through a surveillance, alert and response system (SVARS). The project will be implemented in two phases. Phase one will focus on increasing the knowledge of AMU drivers by developing a catalog of practices and factors that impact the use of antimicrobials and conduct a cost-effectiveness analysis to assess the more cost efficient alternative methods to AMU practices. The catalog will be compiled in a format that can be used to implement improvements on high AMU farms. Different AMU metrics will be reviewed and selected to differentiate farms with low, medium and high AMU. In addition, the legislative requirements to develop and sustain a surveillance, alert and response system (SVARS) to reduce AMU in Chilean salmon farming will be reviewed. Finally, the infrastructural and operational requirements for the platform will be assessed and the design of the platform will be completed, integrating geospatial and health information.

In phase two, the SVARS will categorize the farms based on their AMU levels. The high use farms will be recruited to a Randomized Controlled Trial where intervention farms will implement practices and methods from the catalog created in phase one to reduce AMU. The outcomes and the effectiveness of the SVARS will be quantitatively and qualitatively assessed. Finally, results and outcomes of establishing and implementing the SVARS will be shared with relevant stakeholders in Chile, to low-and middle-income countries in the region and beyond, e.g. through workshops and education training programs in order to disseminate the results.

Sistema Articulado de Investigación en Cambio Climático y Sustentabilidad de Zonas Costeras de Chile CUECH/RISUE RED21992

Vinculación internacional para la evaluación de la capacidad centinela de moluscos bivalvos filtradores en el monitoreo de contaminantes emergentes en áreas costeras marinas