Publications by authors named "David T Ashton"

Unlabelled: In dioecious crops such as (kiwiberries), some of the main challenges when breeding for fruit characteristics are the selection of potential male parents and the long juvenile period. Currently, breeding values of male parents are estimated through progeny tests, which makes the breeding of new kiwiberry cultivars time-consuming and costly. The application of best linear unbiased prediction (BLUP) would allow direct estimation of sex-related traits and speed up kiwiberry breeding.

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In aquaculture breeding or production programmes, counting juvenile fish represents a considerable cost in terms of the human hours needed. In this study, we explored the use of two state-of-the-art machine learning architectures (Single Shot Detection, hereafter SSD and Faster Regions with convolutional neural networks, hereafter Faster R-CNN) to augment a manual image-based juvenile fish counting method for the Australasian snapper () bred at The New Zealand Institute for Plant and Food Research Limited. We tested model accuracy after tuning for confidence thresholds and non-maximal suppression overlap parameters, and implementing a bias correction using a Poisson regression model.

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Characterizing the genetic variation underlying phenotypic traits is a central objective in biological research. This research has been hampered in the past by the limited genomic resources available for most non-model species. However, recent advances in sequencing technologies and related genotyping methods are rapidly changing this.

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Best use of scientific knowledge is required to maintain the fundamental role of seafood in human nutrition. While it is acknowledged that genomic-based methods allow the collection of powerful data, their value to inform fisheries management, aquaculture, and biosecurity applications remains underestimated. We review genomic applications of relevance to the sustainable management of seafood resources, illustrate the benefits of, and identify barriers to their integration.

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Understanding the genetic basis of phenotypic variation is a major challenge in biology. Here, we systematically evaluate 146 quantitative trait loci (QTL) studies on teleost fish over the last 15 years to investigate (i) temporal trends and (ii) factors affecting QTL detection and fine-mapping. The number of fish QTL studies per year increased over the review period and identified a cumulative number of 3632 putative QTLs.

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