Journal of Survey in Fisheries Sciences 5(2) 49-63 2019

Discrimination analysis of hybrid hypophthalmus (Sauvage, 1983) (♀) × nasutus (♂) (Bleeker, 1976) and its parental species

Mohamed Yusoff S.F.1; Christianus A.1,2*; Ismail M.F.S.1 ; Esa Y.1 ; Hassan M.D.3 ; Hamid. N.H.3; Siti Nadia A.B.3; Zulkifle M.S. 2

Received: November 2018 Accepted: January 2019

Abstract Comparative analysis was performed to discriminate a hybrid produced from the crossbreed of Pangasianodon hypophthalmus (♀) and Pangasius nasutus (♂) and its parental species based on morphology appearances and morphometric characters. Morphological structures of the vomerin and palatal teeth varied between the hybrid and both parents. Results of the univariate analysis revealed 22 morphometric characters were significantly different between the hybrid and its parental species. Under the stepwise discriminate function analysis, the first Function explained 86.10% of total variations and 13.90% in Function 2. Of the 30 characters, only 10 characters which include prepelvic, caudal peduncle length, length, pectoral fin length, anal fin height, anal fin length, adipose fin length, interorbital length, distant to isthmus, and predorsal length can be used to significantly differentiate these species. The predicted fish groups exhibited characters which 100% differentiate and validate them into their respective group. Examination on vomerin and palatal teeth distinct the hybrid and its parental species.

Keywords: Discriminate function analysis, morphometric, Pangasianodon hypophthalmus, Pangasius nasutus, hybrid

1- Department Aquaculture, Faculty of Agriculture, 2- Institute of Bioscience, 3- Aquatic Health Unit, Faculty of Veterinary Medicine, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor Darul Ehsan, Malaysia. *Corresponding author's Email: [email protected] 50 Mohamed Yusoff et al., Discrimiantion analysis of hybrid Pangasianodon hypophthalmus …

Introduction principal components and discriminant Fish stock can be differentiating based factorial analyses have contributed to on their morphological variation (Sokal the identification of fish stocks et al., 2009). This stock identification is efficiently (Kuszniers et al., 2008; crucial to facilitate the management of Cronin-Fine et al., 2013). domestication, and sustainability of Morphometric and multivariate aquaculture production (Bailey, 1997; statistical procedures are useful Ibánez et al., 2017). According to combination for testing and graphically Ezeafulukwe et al. (2015), display the differences in fish stock determination of phenotypic variation (Baur and Leuenberger, 2011). using morphometric characters and Selection of characters for meristic counts is the most common morphometric analysis is also important method applied in delineating stocks of to maximize the effectiveness of stock fishes. Morphometric characters are discrimination (Begg et al., 1999). useful in biological studies as it allows Multivariate analysis is applied to quantitative descriptions of organisms. reveal the morphometric variables for This quantitative approach allows stock identification (Kusznierz et al., researchers to differentiate the 2008; Specziár et al., 2009; Yakubu and organisms by comparing the body shape Okunsebor, 2011; Cronin-Fine et al., (Gelsvartas, 2005), and combining 2013). Multivariate morphology has descriptions such as colour and size been used in population studies of (Muchlisin, 2013). Morphometric is various fishes for stock discrimination important to distinguish the phenotypic (Tzeng et al. 2001; Tzeng 2004; Von of fish with variability in term of Cramon-Taubadel et al., 2005; Maynou growth, development, and maturation and Sarda, 1997; Anastasiadou and (Begg and Waldman, 1999). Leonardos, 2008; Ezeafulukwe et al., Identification of fish in different 2015; Banerjee et al., 2017). populations using morphometric Particularly with the existence of a new measurement was applied in previous hybrid, description of the studies (Tzeng, 2004; Torres et al., morphological variation becomes 2014; Chen et al., 2015) because of its important. Furthermore, establishment simplicity and direct application of morphological differentiation for (Bronte et al., 1999; Hockaday et al., identification with the least assumption 2000). is possible when using samples of In recent decades, advanced known hybrid (Neff and Smith, 1979). techniques through morphometric Previous studies (Gustiano et al., 2003; methods have successfully discriminate Baharuddin et al., 2014) were able to fish stocks within fish population discriminate the pangasiids species. (Dwivedi and Dubey, 2013), detecting Lack of adequate information on the differences or similarity among groups discrimination of hybrid in the field has (To and Ci, 2015). Statistical tools like led to the current study for the multivariate techniques such as assessment of phenotypic variations Journal of Survey in Fisheries Sciences 5(2) 2019 51 resulting in important characters being Table 1: Description of the characters used in the study. derived for rapid discrimination and Character Landmarks Description of classification. codes characters SL 1 Standard length HL 2 Head length Materials and methods SNL 3 Snout length Fish Samplings ASW 3A Anterior snout width Samples of hybrid (n=30) were from a PSW 3B Posterior snout width HD 4 Head depth local fish farmer in Temerloh, Pahang HW 5 Head width cultured to adult stage (14 month old). PREDL 6 Predorsal length While samples of P. hypophthalmus CPL 7 Caudal peduncle length CPD 8 Caudal peduncle depth (n=40) and P. nasutus (n=10) were PFL 9 Pectoral fin length taken from our collections. PSL 10 Pectoral spine length DFL 11 Dorsal fin length Data Collections DSL 12 Dorsal spine length PEFL 13 length Morphometric measurements were AFH 14 Anal fin height taken according to Gustiano (2003). AFL 15 Anal fin length Thirty parts of the fish body were ADIFH 16 Adipose fin height ADIFW 17 Adipose fin width measured (Fig. 1) and character codes ED 18 Eye diameter and landmarks were employed to MW 19 Mouth width represent the description of characters LJL 20 Lower jaw length (Table 1). Prior to measurement, fish IL 21 Interorbital length DSI 22 Distance snout to were anesthetized using MS 222 (35 isthmus mg/L) then measured on a measurement PL 23 Postocular length MAXBL 24 Maxillary barbell length board. Measurements of characters MANBL 25 Mandibulary barbell were taken using digital vernier calliper length BW 26 Body width to the nearest 0.1 mm. PREPL 27 Prepectoral length PREPEL 28 Prepelvic length

Data Analyses Data were analysed using univariate and multivariate analyses of variances to test the significance in the morphometric characters. An allometric formula by Elliott et al., (1995) was employed to remove the length effect of the samples due to the morphometric characters (Turan et al., 2005). The

formula was calculated as Madj = M b Figure 1: Measurement of the body (A) and (LS/LO) where, Madj: size adjustment head (B) parts of each species. measurement; M: Original (Source: Gustiano, 2003). measurement; LO: standard length; LS: 52 Mohamed Yusoff et al., Discrimiantion analysis of hybrid Pangasianodon hypophthalmus … overall mean of standard length; b: coloration on the head and upper part of estimated for each character from the body may varies from black to grey for observed data as the slope of the P. hypophthalmus, with merely light regression of LogM on Log LO using all gold for P. nasutus and light green for samples in all groups (species). hybrid. Besides body colour, the For univariate analysis, the size- vomerin and palatal teeth of hybrid was adjusted data were submitted to one- distinctively different from its parents. way analysis of variance (ANOVA) The dentition of P. nasutus shows large followed by post hoc multiple tests and nearly square vomerin, meanwhile using Duncan at 5% significant level to P. hypophthalmus with two palatal compare the variation of each character bands. between species. Multivariate analysis under the discriminate factor analysis (DFA) (Ramsay et al., 2009) was carried out to assess the morphological variation. Discriminate analysis was employed to select more important variables as the predictors for the determination of the hybrid and its parental species. The Mahalanobis squared distance was used in a stepwise method. Functions derived are useful in Figure 2: Morphological appearance and explaining the eigenvalue values that closer look of on the maxillary and classified the components. Wilk’s palatal dentition of (A) Pangasianodon hypophthalmus; (B) lambda was projected to test the Pangasius nasutus (C) hybrid. significant of the combination of the variables in different dimension. It was Univariate Analysis defined based on value close to 1. Univariate analysis demonstrated all of Higher discriminator variables indicates the characters were significantly fish within the same group, while value different (p<0.05) among all three close to 0 shows the variability is due to species except for HL, SNL, ASW, species differences. For visual detection PSW, ED and PPEL (Table 2). Means and classification, scatter plots of sizes of every character varied among canonical scores were constructed. All species and hybrid was closer to P. statistical analyses were performed hypophthalmus as most of the using SPSS software version 20.0 characters seem to be insignificant (p>0.05) between these two species. Results and discussion In general, P. hypophthalmus showed Morphological Appearances longer head parts, in contrast to P. Body colour of hybrid was observed to nasutus which was longer in fin parts. be slightly different as compared to parental species (Fig. 2). Live Journal of Survey in Fisheries Sciences 5(2) 2019 53

Table 2: Mean±SD transformed values of morphometric characters of Pangasianodon hypophthalmus, Pangasius nasutus and its hybrid. Morphometric Characters P. hypophthalmus P. nasutus Hybrid (n=40) (n=10) (n=30) Head Length 9.92±0.60 10.02±0.65 9.09±0.74 Snout length 3.94±0.40 4.01±0.39 3.92±0.52 Anterior Snout Width 2.91±0.46 2.98±0.35 2.82±0.70 Posterior snout width 3.86±0.35 3.95±0.27 3.73±0.68 Head depth 4.61±0.66 4.78±0.53 4.62±0.53 Head width 5.66±0.86 a 6.73±0.59 b 5.64±0.55 a Predorsal length 15.73±0.91 a 17.27±0.68 b 15.12±0.79 c Caudal peduncle length 6.38±0.62 a 6.02±0.53 a 5.52±0.87 b Caudal peduncle depth 4.10±0.35 a 3.15±0.21 b 3.46±0.36 c Pectoral fin length 8.52±0.77 a 7.29±0.82 b 6.53±0.49 b Pectoral spine length 7.43±0.71 a 6.58±0.72 b 5.87±0.62 c Dorsal fin length 9.98±0.95 a 8.10±0.59 b 6.87±0.77 c Dorsal spine length 7.62±0.80 a 7.12±0.59 b 6.04±0.54 c Pelvic fin length 7.29±0.49 a 5.00±0.87 b 4.56±0.45 c Anal fin height 6.62±0.94 a 4.22±0.98 b 4.18±0.4 b Anal fin length 14.75±0.99 a 10.68±0.55 b 12.02±0.57 c Adipose fin height 1.58±0.22 a 1.89±0.22 b 2.05±0.45 b Adipose fin width 0.87±0.19 a 0.88±0.16 b 1.14±0.29 b Eye diameter 1.12±0.10 1.08±0.09 1.07±0.10 Mouth width 3.98±0.48 a 4.12±0.36 a 3.70±0.34 b Lower jaw length 2.35±0.30 a 2.52±0.38 a 2.00±0.39 b Interorbital length 5.59±0.53 a 6.10±0.64 b 5.43±0.88 a Distance snout to isthmus 4.75±0.65 a 5.14±0.55 b 4.45±0.4 a Postocular length 4.17±0.41 a 4.73±0.91 b 4.28±0.61 a Maxillary barbell length 2.77±0.92 a 4.65±0.50 b 3.20±0.53 a Mandibular length 1.22±0.67 a 3.54±0.85 b 2.04±0.41 c Body width 7.11±0.57 a 7.89±0.85 b 7.01±0.73 a Prepectoral length 8.73±0.73 9.11±0.98 8.77±0.61 Prepelvic length 18.26±0.94 a 20.25±0.89 b 18.35±0.98 a Values (mean±SD, mm) in the same row with different superscripts are significantly different (p<0.05).

Hybrid has relatively shorter for most with the percentage of variance at characters but longer in ADIFH and 13.9%. Eigenvalues demonstrated high ADIFW, and with slender body correlation of characters derived from compared to its parents. Function 1 (0.973) than in Function 2 (0.861) which related to canonical Multivariate Analysis correlation, thus important to describe Discriminate Function analysis has the discriminating ability a Function. derived two Functions with eigenvalues Function 1 and 2 were loaded by higher than 1 (Table 3). As illustrated in PREL, CPL, DFL, PFL, AFH, AFL, this table, eigenvalue of 17.71 ADIFL, IL, DSI and PREL. demonstrated 86.1% of variation among In Function 1, highly loaded with the characters loaded in Function 1. ADIFH, IL, DSI, and PREPEL which Meanwhile, the eigenvalue in Function positively related to the Function and 2 was lower than Function 1 (2.854) contribute meaningfully to the species 54 Mohamed Yusoff et al., Discrimiantion analysis of hybrid Pangasianodon hypophthalmus … discrimination since most of the morphometric distinction was also variation occurred in these characters. indicated by Wilks’ lambda criterion As for Function 2, PREDL, DFL, PFL, based on the ratio of distinction within- ADIFL, DSI and PREPEL contributed species variability to total variability for most to the species discrimination in the the discriminator variables. Based on positive direction indicating these the result, the first test presented in characters as good predictors for the Table 4 for Function 1 through 2, hybrid and its parental species. Wilks’ lambda was close to 0, signifying that most of the variables Table 3: Eigenvalues, percentage of variance, captured from Function 1 attributed to cumulative, canonical correlation and standardized canonical the species differences. In Function 2, coefficient of DFA loading of Wilks’ lambda at 0.259 indicates little characters. variability captured by Function 2 that Function 1 2 Eigenvalues 17.71 2.854 contributed to between-species % of variance 86.10 13.90 differences. Furthermore, chi-square Cumulative 86.10 100.00 Canonical 0.973 0.861 values showed the variability for the correlation species differences prior to extraction was statistically significant at 0.05 Standardized canonical coefficient of DFA loading of characters level. Even though there was only small Predorsal length 0.124 0.449 amount of group differences observed Caudal -0.251 -0.517 peduncle depth in Function 2, it is worth consideration Dorsal fin -0.002 0.400 due to the proportion of the group was length statistically significant. Pelvic fin -0.451 0.465 length Anal fin height -0.541 0.036 Table 4: Statistical significance of the Anal fin length -0.769 -0.512 derived discriminate Functions for Adipose fin 0.389 -0.207 Wilks’ Lambda. height Test of Wilks’ Chi- Interorbital 0.443 0.363 Function(s) Lambda square df Sig. length 1 through 2 0.014 310.187 20 0.00 Distance snout 0.684 0.651 2 0.259 97.818 9 0.00 to isthmus Prepelvic length 0.591 0.331 First 2 canonical discriminate Functions were To test the efficacy of a set of Function used in the analysis. based on the ability of the Function to accurately classify the species to their The score of species variability of each respective group is the final determinant Function which captured by the value in this interpretation. The Function of canonical correlation for Function 1 (Table 5) generated in the analysis and 2 are 0.973 and 0.861, respectively, showed that Pangasianodon indicated more important correlation hypophthalmus, P. nasutus and its with larger canonical correlation. hybrid were 100% differentiated and Function 1 exhibited a strong relation validated into their respective group. between score of its Function as compare to Function 2 and species differences. The significance of the Journal of Survey in Fisheries Sciences 5(2) 2019 55

Table 5: Predicted group and cross-validated Pangasianodon hypophthalmus (PH), Pangasius nasutus (PN) and hybrid (HB). Predicted Group membership Fish P. hypophthalmus P. nasutus Hybrid Total (PH) (PN) (HB) Original % PH 100.0 0.0 0.0 100.0 PN 0.0 100.0 0.0 100.0 HB 0.0 0.0 100.0 100.0 Cross-validated % PH 97.5 2.5 0.0 100.0 PN 10.0 90.0 0.0 100.0 HB 10.0 3.3 90.0 100.0 100.0% of original grouped cases correctly classified. Cross-validation is done only for those cases in the analysis. In cross validation, each case is classified by the Function derived from all cases other than that case. 95.0% of cross-validated grouped cases correctly classified.

The predicted fish groups exhibited Morphological appearance of body characters which Cross-validate values colour, vomerin and palatal teeth band indicated that misclassification with can be used to distinguish the hybrid values lower than the original is since rapid diagnostic is needed in common for this classification. identifying fish for stock management. Scatterplot shows there are no The structure of single vomerin and overlapping of characters between palatal teeth band of hybrid differentiate hybrid and its parents evidently showed it from its parental species. Also, this that Function 1 discriminated hybrid method has been used in the and its parents into three separate differentiation of other pangasiids groups (Fig. 3). species (Fumihito et al., 1989; Roberts

and Vidthayanon, 1991; Pouyard et al., 2002; Baharuddin et al., 2014; Dwivedi et al., 2017). In this study, univariate and multivariate analyses employed were able to discriminate and classify the hybrid based on morphometric characters, where hybrid appeared to resemble P. hypophthalmus, evidence Figure 3: Scatterplot of Function 1 against with the mean significant values of Function 2 of the morphometric characters of Pangasianodon univariate analysis closer to P. hypophthalmus, Pangasius nasutus hypophthalmus. There is also no and its hybrid. overlapping of the characters measured The present study revealed the variation between the hybrid and its parents of hybrid and its parental species based related to size as observed in on morphological appearances and scatterplot. Hubb (1955) stated that morphometric characters. hybrid is likely to display the 56 Mohamed Yusoff et al., Discrimiantion analysis of hybrid Pangasianodon hypophthalmus … characteristics of its parents or P. nasutus and its hybrid and the reason immediate traits in the first generation for that presumably P. hypophthalmus (F1) and backcrossing is considered is a benthic species. Therefore it could when hybrid population showed high be part of the adaptation of this species variability. Several hybrids were found since dorsal fin length is related to the displayed intermediate characters of its vertical position of the fish in the water parents. For example intraspecific column, and claimed posteriorly-placed hybridization of native and Thai koi, dorsal fin important for the adaptations Anabas testudineus, interspecific to the surface habitat especially for the hybridization between yellow flounder non-flowing waters (Matthews, 1988). and Winter flounder, Limanda Eyes diameter was larger in P. ferruginea (♀) × Pseudopleuronectes hypophthalmus as compared to P. americanus (♂) (Park et al., 2003), nasutus and its hybrid. While the hybrid between Gibelion catla (♀) × position of eyes of P. hypophthalmus Labeo rohita (♂) (Bhowmick et al., and P. nasutus was expected to be 1981), hybrid between catla and different due to species-specific that fimbriatus, Catla (♀) × Labeo relate to their vertical habitat preference fimbriatus (♂) (Basavaraju et al., 1995) (Turan, 2005). demonstrated immediate characters of This hybrid, however, showed its parents. Similarly, morphological relatively larger ADIFH and ADIFW as characters of hybrids Pangasius compared to its parents, and shorter in djambal and P. hypophthalmus and most part of the characters which means their reciprocal hybrids having this hybrid not only performed intermediate characters except for intermediate shape as anticipated, but number of gill rakers which is less than their characters demonstrated larger or its parental species (Gustiano and smaller than its parents, indicating their Kristanto, 2007). distinctive morphometric characters. In fish population studies, the Duong et al. (2017) stated that hybrid morphology plasticity is commonly could express differently than its occur can be greatly affected by the parents and violated the immediate differences in the environmental assumption. In a more distance reported conditions such as food availability and on hybrid between Clarias variation of water temperature macrocephalus and Pangasius sutchi (Wimberger, 1992). For a hybrid, was successfully produced and yielded morphology of its parents greatly three morphologically different hybrids affected the hybrid characters. It is (Sittikraiwong 1987) and relatively expected that high phenotypic more on Pangasius-like (79.69%), differences of P. hypophthalmus and P. having two dorsal fins, while the second nasutus in the present study as these type showed Clarias-like appearances two species belong to different taxa. It (18.27%) and the third group similar to was observed dorsal fin length was Clarias (2.03%). Similarly, Okomoda et found larger in P. hypophthalmus than al. (2018) reported the hybrid of C. Journal of Survey in Fisheries Sciences 5(2) 2019 57 gariepinus (CG) × P. According to Brown and Wicker hypophthalmus(PH) and its reciprocal (2000), investigators need to have some to be Clarias-like Clariothalmus (CG ♀ indication of the accuracy of the × PH ♂) and Pangapinus progenies (PH Functions derived in classifying the ♀×CG ♂), which were groups and it is important to begin with indistinguishable from their maternal a sample of known group of fish. Most parents and the Panga-like common practice to differentiate the Clariothalmus demonstrated phenotypic unknown individual which could be intermediary of its pure parentage. considered as hybrid is when In multivariate analysis morphometric measurement using interpretation of the results proposed hybrid indices demonstrated immediate that at least 10 characters which are to the value of two parental species prepelvic (PREL), caudal peduncle (Campton, 1987). Therefore, for a length (CPL), dorsal fin length (DFL), proper data collection of hybrid of pectoral fin length (PFL), anal fin known parentage of first filial (F1) height (AFH), anal fin length (AFL), generation is necessary to access the adipose fin length (ADIFL), interorbital accuracy of assumptions of hybrid length (IL), distant to isthmus (DSI) and population in the future (Neff and predorsal length (PREL) were the Smith, 1979). Likewise, result on the strongest components as predictors to cross-validate is crucial if the discriminate these three species which researches intend to classify other occurred largely at the body, head, and samples into the groups of interests and fins parts. The components that derived discrimination based on original or by Functions 1 and 2 are important to cross-validated are the most commonly show the characters that exhibit high used for fish in the wild such as in variation. The total variances shown by different geographical areas the first and second eigenvalues ranged (Ballesteros-córdova et al., 2016; from 86.1 to 13.9% in this study is Banerjee et al., 2017). In cross- important to clarify the variation validation analysis, the construction of occurred on all of the characters discriminant Function is carried out measured. The first eigenvalue showed with multiple repeated analysis by majority of variances were explained in leaving out one individual before Function 1 which indicated a good fit of categorizing this individual according the model derived from the multivariate to their Function which will reduce the allometry to the data (Björklund, 1993), possibility of misjudging the efficacy of and provides information to discriminant Functions to classify the discriminate this hybrid in the future. specimens (Ibánez et al., 2017). The classification based on the In the case of farming in predicted fish groups in the present Vietnam (Legendre and Pariselle, 1998) study was almost perfect with 100.0% and Thailand (Na-Nakorn and of original grouped cases and 95.0% of Kamonrat, 2004; Senanan et al., 2004), cross-validated grouped cases. hybrids detection based on morphology 58 Mohamed Yusoff et al., Discrimiantion analysis of hybrid Pangasianodon hypophthalmus … is only applicable for F1 hybrid as only. This is due to size factor could misclassification beyond F1 or lead to more variations among the set of backcross to its pure parentage occurred variables in morphometric studies quite common (Scribner et al., 2001). (Junquera and Perez-Gandaras, 1993; Mengumphan and Panase (2015) Tzeng and Yeh, 1999). Removing the reported that for hybrids analysis size factor is crucial as it will influence beyond F1 generations, the the morphometric analysis and lead to morphometric and meristic divergent of invalid result (Tzeng, 2004). In the two hybrids beyond F1 generation current study, number of sample for P. which were backcross (BC: F1 hybrid, nasutus n=10, is considerably low. The ♀ × P. gigas ♂) and reciprocal discrimination could be more efficient backcross (RCBC: F1 hybrid ♂ × P. if the samples size of P. nasutus is gigas ♀) derived from the parental of larger. However, according to Brown F1 hybrid (P. gigas ♀ × P. and Wicker (2000), this model of hypophthalmus♂) and maxillary barbell discrimination is still valid as it reflects length and dorsal fin length can be used the real population in the environment to separate these two hybrids from P. since this species is scarce. gigas and P. hypophthalmus. It is important to measure the Conclusions characters with combination of In conclusion, morphological variations conventional and truss network on can be used to differentiate hybrid and different parts of the fish body as it can its parents. Then characters include assist in searching for the most PREL, CPL, DFL, PFL, AFH, AFL, differential characters to differentiate ADIFL, IL, DSI and PREL can be used hybrid. Model derived from as predictors to discriminate hybrid and discriminate Function analysis (DFA) is its parents. The adipose parts in beneficial to facilitate the search for the particular, are larger in hybrid therefore strongest components for the the most favourable characters to be discrimination. Most studies on used for the discrimination. In addition, Pangasiid species used as many as 32 observation on the vomerin and palatal components for discrimination teeth can be used as the most practical (Slembrouck, 2005; Baharuddin et al., method for rapid identification of P. 2014; Dwivedi et al., 2017). Reducing hypophthalmus, P. nasutus and its these components to only those hybrid. contributing most obvious differences will ease the identification of hybrid. In References the current study, result derived from Anastasiadou, C. and Leonardos, the multivariate discriminate analysis I.D., 2008. Morphological variation after removing the size factor was among populations of Atyaephyra favourable as compared to previous desmarestii (Decapoda: Caridea: study when comparison was made Atyidae) from freshwater habitats of based on the ratio of standard length Journal of Survey in Fisheries Sciences 5(2) 2019 59

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