Finding suitable growth models for turbot (Scophthalmus maximus L.) in aquaculture 1 (length application)

Growth data of two different commercial turbot (Scophthalmus maximus) strains reared in recirculating aquaculture systems were analysed with the aim to determine the most suitable model for turbot. To assess the model performance three different criteria were used: (1) The mean percentage deviation between the estimated length and actual length; (2) the residual standard error with corresponding degrees of freedom and (3) the Akaike information criterion. The analyses were carried out for each strain separately, for sexes within strains and for a pooled data set containing both strains and sexes. We tested a pre‐selection of six models, containing three to four parameters. Models were of monomolecular shape or sigmoid shape with a flexible point of inflection including the special case of monomolecular shape in defined cases of their parameters. The 4‐parametric Schnute model achieved best fit in 62% of all cases and criteria tested, followed by the also 4‐parametric generalized Michaelis–Menten equation in 48% and the 4‐parametric Janoschek model (38%). The von Bertalanffy growth function achieved only 29%, Brody 24% and a new flexible function 19% best fit. In a 1–1000 day growth‐simulation sigmoid shaped curves were produced by the Schnute model in 71% of cases. The Janoschek and the Michaelis–Menten model each produced sigmoid curves in 57% of all cases. This indicates that a flexible 4‐parametric function reflects the growth curve of turbot the best and that this curve is rather sigmoid than monomolecular shaped.     

Whitened kernel surface: A fast and reliable method for assessing Fusarium severity on cereal grains by digital picture analysis

Fusarium head blight (FHB) is a cereal disease of major importance responsible for yield losses and mycotoxin contaminations in grains. Here, we introduce a new measurement approach to quantify FHB severity on grains based on the evaluation of the whitened kernel surface (WKS) using digital image analysis. The applicability of WKS was assessed on two bread wheat and one triticale grain sample sets (265 samples). Pearson correlation coefficients between Fusarium‐damaged kernels (FDK) and WKS range from r = 0.77 to r = 0.81 and from r = 0.61 to r = 0.86 for the correlation between deoxynivalenol (DON) content and WKS. This new scoring method facilitates fast and reliable assessment of the resistance to kernel infection and shows significant correlation with mycotoxin content. WKS can be automated and does not suffer from the “human factor” inherent to visual scorings. As a low‐cost and fast approach, this method appears particularly attractive for breeding and genetic analysis of FHB resistance where typically large numbers of experimental lines need to be evaluated, and for which WKS is suggested as an alternative to visual FDK scorings.     

Assessment of the socio-economic impacts associated with the arrival of apple snail (Pomacea canaliculata) in Mwea irrigation scheme,Kenya

Background

In Kenya, rice (Oryza sativa L.) is mainly produced under irrigation by small-scale farmers. Mwea irrigation scheme (MIS) in Kirinyaga County accounts for 80–88% of rice production. Here, rice is the main source of livelihood and a source of revenue generation for the county. However, a recently established invasive freshwater snail, Pomacea canaliculata (Lamarck) (family: Ampullariidae), a species of apple snail, presents a serious threat to rice production.

Results

Household surveys, focus group discussions and key informant interviews highlight apple snail as a serious problem in MIS. Households that observed at least a moderate level of infestation (>20% of cultivated area) experienced significant reductions in rice yield (~14%) and net rice income (~60%). Farmers reported increased use of chemical pesticides for management of apple snail. In addition, the cost of hired labor for physical removal of egg masses and snails is resulting in substantial negative effects on net income. Farmer age, area of land owned, responsibility for decision-making, receipt of extension advice, training, and membership of a farmer organization, were all statistically significant variables to explain farmers awareness of the need for area-wide apple snail management.

Conclusion

Strategies to limit the spread of apple snail are urgently needed. A Multi-Institutional Technical Team (MITT) has been established to spearhead management efforts and consolidate advice to farmers on how to manage apple snail. However, without action to mitigate spread, the consequences could be disastrous for rice production and food security in Kenya, and for other rice growing regions across Africa. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.     

Reproductive characteristics of the fishery important temperate demersal berycid Centroberyx gerrardi indicate greater reproductive output in regions of upwelling

The reproductive biology of Centroberyx gerrardi (Günther) was investigated across ~2,000 km of its southern Australian distribution, encompassing different jurisdictions and varying environmental features. Greater gonad mass and prevalence of spawning fish, along with lower ratios of lengths at maturity:maximum lengths and ages at maturity:maximum ages, were identified at the western‐most (Capes) and eastern‐most (Great Australian Bight; GAB) regions. Across the study region, spawning peaks in summer/autumn, when water temperatures are warmest. Regional differences in potential “reproductive output,” while not consistent with the eastward decline in mean monthly water temperature, may instead be related to summer upwelling in the Capes and GAB, driving greater oceanic productivity prior to peak spawning, supporting larval survival. In autumn, the prevailing southward and eastward flowing, downwelling Leeuwin Current (LC) strengthens, providing a dispersal mechanism along the west and south Australian coasts, but limiting upwelling effects. Predicted changes in environmental conditions and their potential impacts on C. gerrardi are discussed, in particular how these factors may affect recruitment to stocks and fisheries, requiring a better understanding of source‐sink relationships for this species. As environmental changes occur, management strategies to sustain fish resources must adapt to spatially variable and changing reproductive output and be collaborative across jurisdictions.     

Identifying and exploring significant genomic regions associated with soybean yield,seed fatty acids,protein and oil

Soybean [Glycine max (L.) Merrill] yield and seed fatty acids, protein, and oil content are important traits for which an improved understanding of significant genomic regions would be useful. To accomplish this, a soybean population consisting of 203 F5 derived recombinant inbred lines (RILs) was developed and genotyped with 11,633 polymorphic single nucleotide polymorphisms (SNPs). Each RIL was grown in a single plot at Knoxville, TN in 2010; followed by replicated, multi-location field trials in 2013 and 2014. The data from 2010, 2013, and 2014 were analyzed together in order to detect quantitative trait loci (QTL) for these traits, and 30 total QTLs were detected. Five QTLs are candidates for confirmed status and one QTL is a candidate for positional confirmation. Many of the genes with mutations in close proximity to the fatty acid QTLs are involved in biological processes for fatty acids and/or lipids and could be considered possible candidate genes. Similarly, genes with mutations in genomic regions near yield, protein, and oil QTLs were plentiful and may contribute to the variation observed in these traits. Except for yield and stearic acid, each trait displayed pleiotropic effects with other traits in this study. Notable are the pleiotropic effects for oleic and linolenic acid on chromosomes 9, 13, and 19. Overall, the findings from this research contribute new information to the genetic understanding of soybean yield and seed fatty acids, protein and oil content. This understanding will be useful in making trait improvements.     

Segmentation of 3D images of plant tissues at multiple scales using the level set method

Background

Developmental biology has made great strides in recent years towards the quantification of cellular properties during development. This requires tissues to be imaged and segmented to generate computerised versions that can be easily analysed. In this context, one of the principal technical challenges remains the faithful detection of cellular contours, principally due to variations in image intensity throughout the tissue. Watershed segmentation methods are especially vulnerable to these variations, generating multiple errors due notably to the incorrect detection of the outer surface of the tissue.

Results

We use the level set method (LSM) to improve the accuracy of the watershed segmentation in different ways. First, we detect the outer surface of the tissue, reducing the impact of low and variable contrast at the surface during imaging. Second, we demonstrate a new edge function for a level set, based on second order derivatives of the image, to segment individual cells. Finally, we also show that the LSM can be used to segment nuclei within the tissue.

Conclusion

The watershed segmentation of the outer cell layer is demonstrably improved when coupled with the LSM-based surface detection step. The tool can also be used to improve watershed segmentation at cell-scale, as well as to segment nuclei within a tissue. The improved segmentation increases the quality of analysis, and the surface detected by our algorithm may be used to calculate local curvature or adapted for other uses, such as mathematical simulations.

     

Conservation planning with spatially explicit models: a case for horseshoe bats in complex mountain landscapes

Context

Context Bats are considered as an ecological indicator of habitat quality due to their sensitivity to human-induced ecosystem changes. Hence, we will focus the study on two indicator species of bats as a proxy to evaluate structure and composition of the landscape to analyze anthropic pressures driving changes in patterns.

Objectives

This study develops a spatially-explicit model to highlight key habitat nodes and corridors which are integral for maintaining functional landscape connectivity for bat movement. We focus on a complex mountain landscape and two bat species: greater (Rhinolophus ferrumequinum) and lesser (Rhinolophus hipposideros) horseshoe bats which are known to be sensitive to landscape composition and configuration.

Methods

Species distribution models are used to delineate high-quality foraging habitat for each species using opportunistic ultrasonic bat data. We then performed connectivity analysis combining (modelled) suitable foraging habitat and (known) roost sites. We use graph-theory and the deviation in the probability of connectivity to quantify resilience of the landscape connectivity to perturbations.

Results

Both species were confined to lowlands (<1000 m elevation) and avoided areas with high road densities. Greater horseshoe bats were more generalist than lesser horseshoe bats which tended to be associated with broadleaved and mixed forests.

Conclusions

The spatially-explicit models obtained were proven crucial for prioritizing foraging habitats, roost sites and key corridors for conservation. Hence, our results are being used by key stakeholders to help integrate conservation measures into forest management and conservation planning at the regional level. The approach used can be integrated into conservation initiatives elsewhere.