Sterilization of sea lice eggs with ultraviolet C light: towards a new preventative technique for aquaculture

Evolutionary predictions for a parasite metapopulation: Modelling salmon louse resistance to pest controls in aquaculture

Pests often evolve resistance to pest controls used in agriculture and aquaculture. The rate of pest adaptation is influenced by the type of control, the selective pressure it imposes, and the gene flow between farms. By understanding how these factors influence evolution at the metapopulation level, pest management strategies that prevent resistance from evolving can be developed. We developed a model for the metapopulation and evolutionary dynamics of the salmon louse (Lepeophtheirus salmonis), which is a major parasite affecting salmon aquaculture. Different management scenarios were simulated across a network of salmon farms covering half of Norway, and their effects on louse epidemiology and evolution were investigated. We compared louse controls that differed in how they were deployed through time (discrete vs. continuous), how they impacted the louse life cycle, and in their overall efficacy. We adjusted the strength of selection imposed by treatments, the dominance effect of the resistant allele, and the geographic location at which resistance originated. Continuously acting strategies (e.g., louse-resistant salmon) were generally more effective than discrete strategies at controlling lice, especially when they increased louse mortality during early developmental stages. However, effective strategies also risked imposing frequent and/or strong selection on lice, thus driving rapid adaptation. Resistant alleles were more likely to be lost through genetic drift when they were recessive, had a low-fitness advantage, or originated in low-farm-density areas. The north-flowing current along the Norwegian coastline dispersed resistant genes from south to north, and limited gene flow in the opposite direction. We demonstrate how evolutionary models can produce quantitative predictions over large spatial and temporal scales and for a range of pest control scenarios. Quantitative outputs can be translated into practical management decisions applied at a regional level to minimise the risk of resistance developing.

Sustainable development of factory aquaculture through automation of ultraviolet parasiticide for the prevention and control of cryptocaryoniasis

BACKGROUND

Cryptocaryon irritans infestations on marine teleosts are a considerable burden on factory mariculture. Ultraviolet (UV) light can kill C. irritans under laboratory conditions. However, a rational method for using UV in factory aquaculture to control cryptocaryoniasis has not been developed. This study focused on evaluating the killing effect of UV on protomonts and tomonts of C. irritans and established an automatic UV parasiticide device for the prevention and control of cryptocaryoniasis in marine teleosts.

RESULTS

The survival rate of protomonts and tomonts decreased with an increase in the UV irradiation dose. All the protomonts and tomonts died within 14 and 24 min, respectively. The lowest UV lethal doses of protomonts and tomonts of C. irritans were 2.0 × 10⁶ and 3.5 × 10⁶  μWs cm^-2 , respectively. Exposure of protomonts and tomonts to lethal doses of UV radiation led to shrinkage and severe dissolution of the protoplasm, causing abnormal development of cells. The survival rate of artificially infected Larimichthys crocea (treatment group, group A) was 83.33% at the end of the test (day 14) after disinfection using the automatic UV parasiticide device, whereas that of the control group (group C) was 90.00% (p < 0.05). However, all artificially infected L. crocea without disinfection using the automatic UV parasiticide device (untreated group, group B) died on day 8.

CONCLUSION

The automation of traditional physical methods conforms to the sustainable development of aquaculture and provides a theoretical reference for the prevention and control of cryptocaryoniasis in mariculture. © 2022 Society of Chemical Industry.

Application of wool keratin: an anti-ultraviolet wall material in spray drying

Low-molecular-weight keratin (LMWK) obtained from wool was employed as a wall material for the spray drying encapsulation of fish oil. Microcapsules with different LMWK contents were prepared, and their anti-ultraviolet performance and other features were studied. The results showed that LMWK was able to improve the encapsulation efficiency of fish oil because of its good emulsifying properties. When the LMWK content was increased from 0 to 10, 30 and 50%, the shelf life of the microcapsules under ultraviolet irradiation increased from 48 to 96 h, 144 h and 168 h, respectively. The strongest absorption efficiency of LMWK is shown in the UVc band. The chemical structure of LMWK did not change during an ultraviolet accelerating ageing test.

Perspective: common errors in dose-response analysis and how to avoid them

Dose-response experiments are conducted to determine the toxicity of chemicals on organisms. The relationship between dose and response is described by different statistical models. The four-parameter log-logistic model is widely used in pesticide sciences to derive biologically relevant parameters such as ED₅₀ and resistance index (RI). However, there are some common errors associated with the calculation of ED₅₀ and RI that can lead to erroneous conclusions. Here we discuss five common errors and propose guidance to avoid them. We suggest (i) all response curves must be fitted simultaneously to allow for proper comparison of parameters across curves, (ii) in the case of nonparallel curves absolute ED₅₀ must be used instead of relative ED₅₀ , (iii) standard errors or confidence intervals of the parameters must be reported, (iv) the e parameter in asymmetrical models is not equal to ED₅₀ and hence absolute ED₅₀ must be estimated, and (v) when the four-parameter log-logistic model returns a negative value for the lower asymptote, which is biologically meaningless in most cases, the model should be reduced to its three-parameter version or other types of model should be applied. The mixed-effects model and the meta-analytic approach are suggested as appropriate to average the parameters across repeated dose-response experiments. © 2021 Society of Chemical Industry.