ArticlePloS one2018
Relationship between weight and linear dimensions of Bluefin tuna (Thunnus thynnus) following fattening on western Mediterranean farms.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Article
- Automatic Bluefin Tuna Sizing with a Combined Acoustic and Optical Sensor.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study presents various models based on formulae relating weight and dimensions (length, height and width) of Bluefin tuna, Thunnus thynnus (L.), fattened in captivity. The main aim of establishing these expressions is to design tools for indirectly predicting the weight of a Bluefin tuna from measurements of one or more dimensions obtained using non-invasive methods such as stereoscopic cameras. Measurements of maximum length, height and width following slaughter were taken of fish fattened in captivity (n = 2078). Different relationships drawn from the dimensions of the tuna against their weight are fitted with part of the data collection and later checked against a reserved sample set. The resulting formulae are compared with the formulae most commonly used in the case of wild tuna. The results of this study confirm that, for tuna fattened in cages, the availability of more than one dimension to estimate weight improves the predictive power of the model and reduces error in the estimate.
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