Supawadee Poompuang

Dr. Supawadee Poompuang

Department of Aquaculture, Faculty of Fisheries, Kasetsart University, Chatuchak, Bangkok 10900, Thailand

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 August 2019 in Journal of Fish Diseases
Verified
Journal Article
Closed access
PDF file
WSWasana Suebsong
Wasana Suebsong
Supawadee PoompuangSupawadee Poompuang
Supawadee Poompuang
Prapansak SrisapoomePrapansak Srisapoome
Prapansak Srisapoome
SKSkorn Koonawootrittriron
Skorn Koonawootrittriron
ALAmorn Luengnaruemitchai
Amorn Luengnaruemitchai
MRMorten Rye
Morten Rye

24 October 2017 in Journal of Fish Diseases
Verified
Journal Article
Closed access
PDF file
PWP Wonmongkol
P Wonmongkol
SSS Sukhavachana
S Sukhavachana
KAK Ampolsak
K Ampolsak
Prapansak SrisapoomePrapansak Srisapoome
Prapansak Srisapoome
TST Suwanasopee
T Suwanasopee
Supawadee PoompuangSupawadee Poompuang
Supawadee Poompuang

1 September 2006 in Molecular Ecology Notes
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Journal Article
Closed access
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KCKancee Charoentawee
Kancee Charoentawee
Supawadee PoompuangSupawadee Poompuang
Supawadee Poompuang
UNUthairat Na-Nakorn
Uthairat Na-Nakorn


29 November 2014 in Fish Physiology and Biochemistry
Verified
Journal Article
Closed access
PDF file
PKPoonmanee Kanjanaworakul
Poonmanee Kanjanaworakul
Prapansak SrisapoomePrapansak Srisapoome
Prapansak Srisapoome
OSOrathai Sawatdichaikul
Orathai Sawatdichaikul
Supawadee PoompuangSupawadee Poompuang
Supawadee Poompuang

23 August 2018 in International Aquatic Research
Verified
Journal Article
Open access
PDF file
SYSuthajaree Yenmak
Suthajaree Yenmak
WJWeerakit Joerakate
Weerakit Joerakate
Supawadee PoompuangSupawadee Poompuang
Supawadee Poompuang
The purpose of this study was to develop and validate prediction equations for fillet traits in Asian sea bass. Ninety-day old fish (average weight = 9.48 ± 0.35 g; length = 8.78 ± 0.6 cm) from four hatchery stocks (Chachoengsao, Chon Buri, Chumphon, and Samut Songkram) were raised in earthen ponds. After 300 days, weight and body measurement data of live fish (n = 400) were collected. Mean individual weight was greatest for the Chacheongsao stock (1166.32 ± 23.42 g) and was similar for the other stocks, ranging from 982.96 ± 25.07 to 997.44 ± 24.71 g. Fillet percentage varied slightly from 47.33 to 49.88%. Positive high correlations were observed for weight and body measurements with fillet weight, whereas there were significant but weak correlations for body measurements with fillet yield. Prediction equations developed from body weight using simple linear regression models yielded R2 values of 0.97–0.98 for fillet weight for each stock. Correlations between values predicted from the body weight models and actual values were 0.98–0.99 for fillet weight. Stepwise regression was performed to develop prediction models for fillet yield from body measurements. The best fillet yield prediction models identified length and an additional 2–3 measurement as potential predictors depending on the population. Prediction biases were close to zero despite low to moderate (r values of 0.20–0.51) degrees of predictive power of the models. However, prediction models for fillet yield should be further developed to increase predictability and be applicable to new data.