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  • Influence of satellite-derived oceanographic characteristics on sea truth fishery data of Indian mackerel, Rastrelliger kanagurta

    The study aimed to identify the most relevant variable from remote sensing data that may be utilized to forecast species-specific fish availability. Because of the schooling habits and reliance on surface productivity, the Indian mackerel, Rastrelliger kanagurta, has been suggested as a prospective species for such investigations in tropical waters. The current study showed how a geographic database can aid in focusing attention on key oceanic characteristics that can serve as the most dependable predictors of fish abundance. Generalized Additive Model (GAM) on the GIS platform was used to analyze satellite-derived Chlorophyll (Chl.) data, Sea Surface Temperature (SST) data and geo-referenced catch weights of Indian Mackerel. When comparing moderate and low catch weighting to high catch weighting, the Chl. content was highly significant. SST was important when the catch weighting was high, but not when the catch weighting was moderate or low.

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  • Mitogenomic recognition of incognito lineages in the mud spiny lobster Panulirus polyphagus (Herbst, 1793): A tale of unique genetic structuring and diversification
  • Spatiotemporal analysis in brown seaweed diversity and abundance at selected coastal locations on the Southern coast of Tamil Nadu, India: A way forward for conservation and sustainable utilization
  • New Record of Fanged Seabream, Sparidentex jamalensis (Perciformes: Sparidae) From Indian Waters
  • Spatial variation of the broodstock availability of Acanthopagrus berda (Forsskal 1775) with emphasis on seasonality, lunar periodicity, and sex ratio for facilitating efficient
  • In vitro culture and characterisation of a new brain cell line from the spine cheek anemone fish Premnas biaculeatus
  • Insights into ovarian maturation and reproductive traits of the deep-water penaeid shrimp Metapenaeopsis andamanensis (Wood-Mason in Wood-Mason and Alcock, 1891)
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