The concept of pathogen presence resulting in reduced production performance of livestock and aquatic species has been embodied in text books for decades . Despite this, many shrimp producers often don’t understand and/or have not been able to quantify the true impact of multifactorial pathogen presence , load and prevalence on production. This is understandable when you consider that only until recently were the tools available for accurate multiple pathogen detection at an affordable cost and that shrimp can have any number of 13 commercially relevant (impactful) pathogens , often harbouring 3-4 of these at any one time . Establishing data points that give farmers a quantitative pathogen profile of their crop over time empowers them with data to quantify the true impact of pathogens on culture and on which to make management decisions that can change the outcome and profitability of a crop.
This study will present case studies from around the world on how the application of the multiple pathogen detection platform Shrimp MultiPath has re-defined how farmers think about pathogens, assess pathogen loading and manage pathogens throughout the production cycle .
Materials and methods
Statistically significant sample plans are designed with farmers to allow sampling of appropriate tissue types in a timely manner for testing on the Shrimp MultiPath system. Tissue types that provide accurate detection of virus, bacteria and microsporidians are pooled together for testing. A typical grow out farm samples at postlarvae stage 10, 25 days of culture 50 days of culture and 70 days of culture for early pathogen detection to characterise pathogen presence and prevalence before having clinically sick animals. This provides up to four weeks early warning of pathogen presence and prevenance during which time a farmer can change management protocols to maximise crop outputs and minimise pathogen impact. Management decisions include actions such as increased biosecurity, reduced shrimp stress and feeding of alternative diets depending on the pathogen.
Latin America, for example are using this knowledge and technology as part of their broodstock selection program resulting in a 10-15% improvement in production and a 10% improvement in fertility. Asia-Pacific farmers utilise the technology to monitor pathogen presence and prevalence during grow-out to provide an early warning that allows simple but smarter management practices to be applied on a case-by-case basis.