USE OF NON-LINEAR AUTOREGRESSIVE MODEL (NAR) TO FORECAST THE FUTURE HEALTH OF SHRIMP FARM

Microbial load in terms of Total Coliform (TC) and Fecal Coliform (FC) were documented in the water of a shrimp culture farm at Malancha region of North 24 Parganas for a period of 36 years (1984-2019). The region receives the wastewater from the city of Kolkata. A steady hike in the microbial load (comprising of both total and fecal coliform) is noticed. The primary reason behind this rise of the microbial load is the run-off from the nearby landmasses that brings various types of wastes in the shrimp farm under investigation. The sustainability of shrimp farms in this region is under question due to the huge microbial load as revealed from the output of NAR.

First report of the mussel Mytella strigata (Hanley, 1843) in the Venezuelan Caribbean from an invasion in a shrimp farm

Individuals of mussels were collected in ponds from a commercial shrimp farm in the Unare region, Anzoátegui State, Venezuela. Identification was carried out using dichotomous keys and corroborated via analysis of similarities between the sequences of partial mitochondrial DNA of the cytochrome oxidase gene and Mytella strigata (Hanley, 1843) reported in GenBank with 99-100% similarity. Morphological analyses further supported the identification of the specimen. The first report of M. strigata in the Venezuelan Caribbean coast suggests that it could be a transplanted species. Possible negative effects of M. strigata on commercial shrimp production systems are discussed.

Online Analytics for Shrimp Farm Management to Control Water Quality Parameters and Growth Performance

An online analytic service system was designed as a web and a mobile application for shrimp farmers and shrimp farm managers to manage the growth performance of shrimp. The MySQL database management system was used to manage the shrimp data. The Apache Web Server was used for contacting the shrimp database, and the web content displays were implemented with PHP script, JavaScript, and HTML5. Additionally, the program was linked with Google Charts to display data in various graphs, such as bar graphs and scatter diagrams, and Google Maps API was used to display water quality factors that are related to shrimp growth as spatial data. To test the system, field survey data from a shrimp farm in southern Thailand were used. Growth performance of shrimp and water quality data were collected from 13 earthen ponds in southern peninsular Thailand, located in the Surat Thani, Krabi, Phuket, and Satun provinces. The results show that the system allowed administrators to manage shrimp and farm data from the field sites. Both mobile and web applications were accessed by the users to manage the water quality factors and shrimp data. The system also provided the data analysis tool required to select a parameter from a list box and shows the association between water quality factors and shrimp data with a scatter diagram. Furthermore, the system generated a report of shrimp growth for the different farms with a line graph overlay on Google Maps™ in the data entry suite via mobile application. Online analytics for the growth performance of shrimp as provided by this system could be useful as decision support tools for effective shrimp farming.

Risk factors associated with acute hepatopancreatic necrosis disease at shrimp farm level in Bac Lieu Province, Vietnam

Background and Aim: Acute hepatopancreatic necrosis disease (AHPND) is a severe disease in shrimp farms and adversely affected the shrimp industry of Vietnam. So far, the study on risk factors associated with AHPND outbreaks is limited. The objective of this study was to determine the potential risk factors of AHPND at the shrimp farm level in Bac Lieu Province, Vietnam. Materials and Methods: Real-time-Polymerase chain reaction was used to analyze data collected from an active surveillance program of shrimp farms in 2017 in the Vinh Tien and Vinh Lac villages, Vinh Thinh commune, Hoa Binh district in Bac Lieu Province, Vietnam. The matched case-control study selected 20 cases and 20 control farms from 134 shrimp farms. In 2018, face-to-face interviews using structured questionnaires were conducted with the farmers of these selected farms. Results: Of the 59 studied variables, seven had p≤0.2 based on bivariate analyses. The results of multivariable analysis showed that the presence of fish-eating birds on shrimp farms was a significant association with AHPND (odds ratio=8, p=0.049). Conclusion: To reduce the effect of AHPND, farmers should apply effective methods to manage wild animals such as using a grid or net to cover the pond, combined with improved biosecurity.

The rise and demise of the commercial shrimp farm, Amatikulu Prawns (Pty) Ltd., 1989 to 2004 (Kwazulu Natal, South Africa).

Amatikulu Prawns (Pty) Ltd operated as a commercial shrimp farm from 1989 to 2004 when market forces made producing shrimp unviable and the farm closed. The farm established the technical requirements from the existing scientific literature, consultancy, training courses and visits to other commercial farms. The farm had two sites (10 ha and 24 ha), two hatcheries, a HACCP-certified processing plant and a feed mill.