Meta‐analysis of genetic parameters of production traits in cultured shrimp species

Hasan, Md. Mehedi; Tulloch, Rachel L.; Thomson, Peter; Raadsma, Herman W.; Khatkar, Mehar S.

doi:10.1111/faf.12495

Cited by 8 publications

(9 citation statements)

References 115 publications

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“…Heritability of growth traits were moderately high in this study (e.g., 0.27 ± 0.07 for body weight and 0.32 ± 0.08 for body length traits), suggesting selection for these traits will lead to significant response in breeding programs. This finding corroborates with the previous findings, where heritability for growth traits were moderate to high, ranging from 0.23 to 0.69 in P. monodon ( Hasan et al, 2020 ), indicating that these traits will be highly responsive during selection for genetic improvement. Of greater significance in this study is the impact of selection for growth on color traits.…”

Section: Discussionsupporting

confidence: 92%

Genetic parameters of color phenotypes of black tiger shrimp (Penaeus monodon)

et al. 2022

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Black tiger shrimp (Penaeus monodon) is the second most important aquaculture species of shrimp in the world. In addition to growth traits, uncooked and cooked body color of shrimp are traits of significance for profitability and consumer acceptance. This study investigated for the first time, the phenotypic and genetic variances and relationships for body weight and body color traits, obtained from image analyses of 838 shrimp, representing the progeny from 55 sires and 52 dams. The color of uncooked shrimp was subjectively scored on a scale from 1 to 4, with “1” being the lightest/pale color and “4” being the darkest color. For cooked shrimp color, shrimp were graded firstly by subjective scoring using a commercial grading score card, where the score ranged from 1 to 12 representing light to deep coloration which was subsequently found to not be sufficiently reliable with poor repeatability of measurement (r = 0.68–0.78) Therefore, all images of cooked color were regraded on a three-point scale from brightest and lightest colored cooked shrimp, to darkest and most color-intense, with a high repeatability (r = 0.80–0.92). Objective color of both cooked and uncooked color was obtained by measurement of RGB intensities (values range from 0 to 255) for each pixel from each shrimp. Using the “convertColor” function in “R”, the RGB values were converted to L*a*b* (CIE Lab) systems of color properties. This system of color space was established in 1976, by the International Commission of Illumination (CIE) where “L*” represents the measure of degree of lightness, values range from 0 to 100, where 0 = pure black and 100 = pure white. The value “a*” represents red to green coloration, where a positive value represents the color progression towards red and a negative value towards green. The value “b*” represents blue to yellow coloration, where a positive value refers to more yellowish and negative towards the blue coloration. In total, eight color-related traits were investigated. An ordinal mixed (threshold) model was adopted for manually (subjectively) scored color phenotypes, whereas all other traits were analyzed by linear mixed models using ASReml software to derive variance components and estimated breeding values (EBVs). Moderate to low heritability estimates (0.05–0.35) were obtained for body color traits. For subjectively scored cooked and uncooked color, EBV-based selection would result in substantial genetic improvement in these traits. The genetic correlations among cooked, uncooked and body weight traits were high and ranged from −0.88 to 0.81. These suggest for the first time that 1) cooked color can be improved indirectly by genetic selection based on color of uncooked/live shrimp, and 2) intensity of coloration is positively correlated with body weight traits and hence selection for body weight will also improve color traits in this population.

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Section: Discussionsupporting

confidence: 92%

Genetic parameters of color phenotypes of black tiger shrimp (Penaeus monodon)

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“…Overall, moderate to high heritability estimates were recorded for BW (0.32 ± 0.05), BL (0.36 ± 0.06) and BS (0.32 ± 0.05), suggesting substantial potential for genetic improvement of these traits in the P. monodon population studied. All these are growth-related traits and these findings corroborate the previous findings of P. monodon genetic parameter estimates ( Kenway et al, 2006 ; Macbeth et al, 2007 ; Coman et al, 2010 ; Noble et al, 2020b ), although a meta-analysis conducted by Hasan et al (2020) reported the estimates ranged from 0.18 to 0.69. Similarly Noble et al (2020b) reported the heritability estimate of 0.38 for BW trait of P. monodon for a smaller subset of this population.…”

Section: Discussionsupporting

confidence: 89%

“…Similarly Noble et al (2020b) reported the heritability estimate of 0.38 for BW trait of P. monodon for a smaller subset of this population. A higher heritability of 0.55 for growth rate (at 54 weeks) and 0.47 body weight were reported by Kenway et al (2006) and Van Sang et al (2020), respectively. However, Sun et al (2015) reported low heritability estimates for body length (0.18) and body weight (0.24) trait of this species.…”

Section: Discussionmentioning

confidence: 65%

“…For example, due to natural curvature seen in the body structure of shrimp, it is difficult to compute body shape indexes, such as the condition factors. It has been demonstrated that landmark-based morphometric distance data derived from shrimp digital images can be used to evaluate and define complex body size and shape traits, such as body size and various aspects of morphological ratios ( Hasan et al, 2020 ). This approach is robust and simple to assess complex traits, which are generally difficult to measure for shrimp, and therefore creates a novel opportunity to evaluate genetic parameters of these traits in shrimp.…”

Section: Introductionmentioning

confidence: 99%

“…G × E reduces the efficiency of selection breeding programs, since the best-performing genotypes in one environment are not necessarily the best in another environment. Meta-analysis studies with both fish and shrimp species have reported the presence of significant G × E for growth traits ( Sae-Lim et al, 2016 ; Hasan et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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Genetic analysis of digital image derived morphometric traits of black tiger shrimp (Penaeus monodon) by incorporating G × E investigations

et al. 2022

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The black tiger shrimp, Penaeus monodon, is the second most economically important aquaculture shrimp species in the world, and in Australia it is one of the most commonly farmed shrimp species. Despite its economic significance, very few studies have reported the genetic evaluation of economically important morphological size and shape traits of shrimp grown in commercial grow-out environments. In this study we obtained genetic parameter estimates and evaluated genotype-by-environment interaction (GxE) for nine body morphological traits of shrimp derived from images. The data set contained image and body weight (BW) records of 5,308 shrimp, from 64 sires and 54 dams, reared in eight grow-out ponds for an average of 133 days. From the images, landmark based morphological distances were computed from which novel morphological traits associated with size and shape were derived for genetic evaluation. These traits included body weight (BW), body length (BL), body size (BS), head size (HS), Abdominal size (AS), abdominal percentage (AP), tail tip (TT), front by back ratio (FBR), condition factor (CF) and condition factor length (CFL). We also evaluated G×E interaction effects of these traits for shrimp reared in different ponds. The heritability estimates for growth related morphological and body weight traits were moderately high (BW: h2 = 0.32 ± 0.05; BL: h2 = 0.36 ± 0.06; BS: h2 = 0.32 ± 0.05; HS: h2 = 0.31 ± 0.05; AS: h2 = 0.32 ± 0.05; and TT: h2 = 0.28 ± 0.05) and low for abdominal percentage and body shape traits (AP: h2 = 0.09 ± 0.02; FBR: h2 = 0.08 ± 0.02; CF: h2 = 0.06 ± 0.02; and CFL: h2 = 0.003 ± 0.004). G × E interaction were negligible for all traits for shrimp reared in different ponds, suggesting re-ranking is not prevalent for this population. Genetic correlations among growth related morphological traits were high ranging from 0.36 to 0.99, suggesting these traits can be simultaneously improved through indirect genetic selection. However, negative genetic correlations were observed for FBR & CF shape traits with major growth traits (ranged −0.08 to −0.95), suggesting genetic selection for rapid growth will likely result in thick/fatty shrimp over generations. Our study showed image-based landmark data can be successfully employed for genetic evaluation of complex morphological traits of shrimp and is potentially amenable to machine-learning derived parameters in semi-automated high volume phenotyping systems needed under commercial conditions.

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