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Comparative Analysis of Hematological Parameters of some Farmed and Wild Fish Species

PJZ_54_2_591-598

Comparative Analysis of Hematological Parameters of some Farmed and Wild Fish Species

Syed Sikandar Habib1*, Saira Naz2, Sadia Nawaz1, Iqra Ameer1, Ameer Khatoon1, Hameed Ur Rehman3, Sahibzada Muhammad Jawad4 and Haider Ali5

1Department of Zoology, University of Sargodha, Sargodha

2Institute of Molecular Biology and Biotechnology, University of Lahore, Sargodha Campus

3Department of Zoology, Kohat University of Science and Technology, Kohat-26000 4Department of Zoology, Islamia College University, Peshawar

5Department of Chemical and Life Sciences, Qurtuba University of Science and Technology, Peshawar

ABSTRACT

The complete blood count is powerful tool for the aquaculturist to monitor quality of water, related soil and to ensure the health status in response to feed, disease therapy and confirming the maturity. So the present study was designed to determine the hematological parameters of farm and river Chenab (wild) selected fish species including (Labeo rohita, Cirrhinus mrigala, Cyprinus carpio, Hypophthalmichthys molitrix, Ctenopharyngodon idella). Fish species selected for the current study is generally widely cultured in Pakistan and worldwide. Fish sampling was done by using different nets (river and farm) and blood sampling was immediately drawn from caudal peduncle by syringe and added in EDTA containing vial and shake well for proper mixing. Vials stored in ice containing boxes and carried to laboratory for total complete blood count. The water parameter was analyzed in laboratory by taking the sample of water and some (Temperature, DO) was measured in situ. Results of hematological analysis revealed that there is no significant (P > 0.05) difference in packed cell volume, mean cell volume and mean cell hemoglobin of different selected species adapted to similar environmental conditions. However, all other parameters like red blood cells, hemoglobin, mean cell hemoglobin concentration, white blood cells, lymphocytes, mid-range cells, granulocytes and other less important parameters including platelets, red cell distribution width-standard deviation, red cell distribution width-coefficient of variation, platelet distribution width, mean platelet volume, Plateletcrit and Platelet-Large cell ratio are differed significantly (P<0.05). Similar trend was observed in fishes of both selected sites “Farm” and “River. It was concluded that hematological variance can occur between animals of different species and same species of different habitat, but as the water parameter remains the same across the studies so current studies don’t show any significant difference.


Article Information

Received 24 January 2020

Revised 23 May 2020

Accepted 23 June 2020

Available online 21 April 2021

(early access)

Published 07 January 2022

Authors’ Contribution

SSH and SN planned the research work and wrote the manuscript. SN and IA conducted the research work. AK and HUR collected the samples. SMJ and HA analyzed the data.

Key words

Wild fish, Farm fish, Hematological parameter, Aquaculture, Health status

DOI: https://dx.doi.org/10.17582/journal.pjz/20200124050118

* Corresponding author: Sikandarzoo00@yahoo.com

0030-9923/2022/0002-0591 $ 9.00/0

Copyright 2022 Zoological Society of Pakistan



INTRODUCTION

The hematological parameters can be utilized to monitor the health status of fish as a result of changes associated to diet, water quality, and disease in response to treatment. Since blood is sensitive connective tissue which can be easily affected by the environmental factors, that’s why fishes from different habitat have different blood profile (Fazio et al., 2020; Al-Asgah et al., 2015). Fish lives and totally depend on water, and unfortunately water can be largely contaminated with a wide range of pollutants such as bacterial contamination, oil pollution, contaminants organic and inorganic (Sahiti et al., 2018). Major source of pollution is using the pesticide which have many pathophysiological effects in numerous ways. Many of these pesticides are responsible for serious diseases like atherosclerosis, metabolic syndrome, pathogen invasion and vulnerability to infectious diseases. For example, fipronil the broad spectrum insecticide, seriously effects kidney, gills and even causes death (Lushchak et al., 2018; Fredianelli et al., 2019). The hematology profile of fishes is not only influenced by the pollution alone but may also due to change in feeding behavior and feed type (Parrino et al., 2018; Fazio et al., 2013). At the very beginning fish farmer cultured only native species of Pakistan such as catla (Catla catla), rohu (Labeo rohita), mrigal (Cirrhinus mrigala) and common carp (Cyprinus carpio). These fish species were mostly cultured due to market demand and inexpensive culturing procedure but after a certain time, two fast growing species, the grass carp (Ctenopharyngodon idellus) and silver carp (Hypophthalmichthys molitrix), have been introduced for culture under modern polyculture systems to upsurge the fish yield per unit area. These two species have good commercial values and gained popularity amongst the producers as well as consumers. Besides this two species of trout namely brown trout (Salmo trutta) and rainbow trout (Oncorhynchus mykiss) are also cultured in NWFP, AJK and NA (Laghari, 2018). The main objective of the current study was to determine and compare the hematological parameters of selected species of farm and river (wild).

MATERIALS AND METHODS

Study area specification

River Chenab (320 20’ 16 North, 0730 42’ 36 East) is one of the five major rivers in Punjab Pakistan. It has agri-forest land located adjacent to district Chiniot with diverse flora and fauna. It has moderate climate of having all four seasons with prolonged summer and the maximum temperature varies up to 45 °C (Altaf et al., 2011). Rajpoot fish farm are the public fish farm (Alaph 8 Chak Kotmomin in district Sargodha Punjab, Pakistan) which cover 200 Acers of area. They have semi-intensive aquaculture system. Rice powder and poultry feed was used as fish feed in farm and provided twice a day in morning and evening. Farm was fertilized with diammonium phosphate (DAP) and locally available, Kisan or Babar Sher fertilizer on weekly basis in order to enhance the phytoplankton’s production. Oxygen level was maintained by continues water flow through farm with the help of tube wells.

Fish and water sampling

Five species of fish Labeo rohita (rohu), Cirrhinus mrigala (mori), Cyprinus carpio (gulfam), Hypophthalmichthys molitrix (silver carp) and Ctenopharyngodon idella (grass carp) were selected. Water and fish samples were collected at 11:00 am PST in the month of September to December 2018. Thirty five fish from River Chenab and thirty five fish from a farm were collected with the help of local trained fishermen by using different type of nets including gill net, mesh nets etc. The fish were identified by using identification key (Mirza and Sandhu, 2007). To reduce the stress, fish was handled gently. All specimens were weighed with electric balance and total length was measured by using centimeter scale. Blood (2 ml) was collected from the caudal peduncle vein and transferred in EDTA (anticoagulant) containing vials for analysis of hematology (Shah et al., 2017).

Water samples were collected in sterile bottles for temperature measured with the help of mercury thermometer, dissolve oxygen measured through DO meter (Model: DO-5510), pH measured with the help of pH meter (Jenway model number 3510) and electrical conductivity (uS cm-1) was measured with the help of Conductivity meter (Taiwan, Model # PLC by MBC) (Envi R by 009). All samples were were further analysed in Pakistan Council of Research in Water Resources Water Quality Laboratory, Sargodha and Agriculture Department, Government of Punjab.

Water quality parameters

Hardness (mg/l), alkalinity (mg/l) and chloride (meq L-1) was measured by titrations done with EDTA, H2SO4 and AgNO3 respectively. Nitrate and nitrite (mg/l) was calculated by UV Spectrophotometer (Hitachi 19913-010) (Akbar et al., 2015). Calcium and magnesium (meq L-1) estimation was carried out by complexometric titration (EDTA). Sodium (meq L-1) was determined by flame photometer. Carbonates and bicarbonates (meq L-1) were estimated by titrimetric method. Titration was done with standardized HCl phenolphthalein and methyl orange used as indicator, respectively. Phosphate (mg/l) was determined by spectrophotometer. Chlorine (mg/l) was evaluated by low level amperometric titration method. Sodium adsorption ratio was determined by following equation (Khattak et al., 2012).

Residual sodium carbonate (meq L-1) was determined by following equation;

RSC=(CO3+HCO3)–(Ca+Mg).

Hematological parameters

Total erythrocyte and leukocyte count was done after diluting the blood samples with dilution solution which contains; sodium citrate 31.3 g, 10 ml volume of 37% formaline, Cresyl brilliant blue 1 g and 1000 ml purified water then analyzed the samples on Neubauer Hemo cytometer. Differential WBCs count was done by Giemsa staining technique (Baghizadeh and Khara, 2015). The amount of hemoglobin was evaluated by cyanmethemoglobin technique by using Drabkins reagent and packed cell volume was calculated by the method of capillary tube micro hematocrit (Mallesh et al., 2015). Erythrocyte indices were calculated by given formulas;

Few others essential blood parameters like Plt, Rdw-sd, Rdw-cv, PDW, MPV, Pct, and Plc-r were also determined (Ashraf et al., 2011).

Statistical analysis

The data obtained for the hematological analysis of wild/farmed fish species and water parameter for both sites were analyzed statistically by using R studio software (version 3.5.3) and applied ANOVA and LSD to determine the differences among the selected parameters of selected species. For water quality parameters the Standard deviation and Mean was determined of both sites.

RESULTS

Table I shows the weight and length of fishes used in this study. Table II shows water quality parameters of farm and river Chenab. The hematological parameters analysis of selected fish species from the farm and wild are given in the Table III and Figures 1 and 2.

 

Table I. Weight (g) and length (cm) of wild and farm fish used in this study.

Name of fish

Wild fish

Farm fish

Weight

Hypophthalmichthys molitrix

1059.67± 122.54

1080.96± 335.46

Labeo rohita

822.1± 100.59

662.04± 132.53

Cyprinus carpio

1024.51± 115.16

881.43± 42.15

Cirrhinus mrigala

861.13 ± 119.50

752.83± 105.94

Ctenopharyngodon idella

552.33± 174

730.5± 32.08

Length

Hypophthalmichthys molitrix

42.9± 4.98

41.42± 7.63

Labeo rohita

34.36± 4.23

26.92± 5.13

Cyprinus carpio

39.83± 4.51

39.28± 1.95

Cirrhinus mrigala

46.07± 6.61

40.87± 5.73

Ctenopharyngodon idella

30.81± 8.93

34.00± 9.27

 

In the present study statistical analysis ANOVA and LSD results reveals that Highest RBC’s was observed in silver and lowest in grass carp. Highest MCHC was observed in silver carp and lowest in rohu and grass carp.


 

 

Higher value of WBC’s observed in rohu and lowest value observed in silver carp. Higher Lymphocytes, Granulocytes and MID was observed in rohu and lowest in silver. Higher Platelets and RDW-SD was observed in silver and lowest in mori. Higher RDW-CV was observed in rohu and lowest in grass carp. Highest MPV, PCT and P-LCR were observed in mori and lowest in grass carp however PDW was highest in silver carp and lowest in grass carp. While on the other hands statistical analysis ANOVA and LSD results for farm fish reveals that Highest RBC’s observed in mori and rohu and lowest in gulfam and grass carp. Highest Hemoglobin observed in silver carp and lowest in gulfam, grass and mori. MCHC and PDW shown highest values in silver and lowest in gulfam fish while white blood cells, lymphocytes and MID shown highest trends in gulfam and lowest in silver carp. Graulocytes shown highest values in gulfam and lowest values in rohu fish. Highest platelets observed in gulfam and lowest in mori. RDW-SD and PDW shown highest values in silver fish while lowest values in mori and gulfam respectively. RDW-CV was highest in gulfam and least value was observed in silver and grass carp. MPV, PCT and P-LCR were observed highest in mori while lowest was observed in gulfam and silver respectively (Table IV).

 

Table II. Comparative water quality parameters (Mean± S.D) of Farm and River Chenab.

Parameters

Farm water

River water

Temperature (°C)

22.67± 0.58

20.00± 1.00

pH (-log(H))

8.67± 0.21

7.80± 0.006

Dissolved oxygen (mg/l)

6.61± 0.19

6.72± 0.17

Hardness (mg/l)

282.67± 2.52

132.33± 2.52

Alkalinity (mg/l)

222.67± 2.52

121.33± 1.53

Nitrate (mg/l)

13.17± 0.06

5.7± 0.1

Nitrite (mg/l)

3.3± 0.1

1.2± 0.1

Phosphate (mg/l)

0.25± 0.01

0.147± 0.03

Ca and Mg (meq L-1)

5.5± 0.1

2.67± 0.12

Sodium (meq L-1)

2.33± 0.06

0.8± 0.1

Carbonate (meq L-1)

0± 0

0± 0

Bicarbonate (meq L-1 )

3.8± 0.1

2.57± 0.15

Chloride (meq L-1)

3.5± 0.1

1.13± 0.15

Chlorine (meq L-1)

0± 0

0± 0

SAR

1.41± 0.05

0.72± 0.06

RSC (meq L-1)

0± 0

0.033± 0.06

EC (uS cm-1)

780.33± 0.58

363.67± 3.51

 

Abbreviations: SAR, sodium adsorption ratio; EC, electrical conductivity; RSC, residual sodium carbonate; Ca, Calcium; Mg, Magnesium.

DISCUSSION

Present study was conducted to determine the hematological differences among the similar species of River Chenab (wild) and local fish farm of Sargodha. Significant differences were observed among water quality parameters of farm and River Chenab. Oxygen was recorded in higher ratio in the river Chenab as compared to farm water, which may be due to continuous flow of water in river. All other parameters shown higher trend in farm water while chlorine and carbonate were below detection limit in both habitats. However, the water of both localities was suitable for fish growth. All these parameters have great influence on the quality of the blood parameter like it may change RBCs count, leukocyte count and immune response etc. but dissolve oxygen and temperature are the chief parameter that effect the most. Numerous studies were performed to conclude if major difference from standard value of these constraints subsists that might be attributed to any sort of internal or external issue (Sahoo et al., 2008Blanksma et al., 2009; Gorjipour, 2014; Gandotra et al., 2017; Küçükgül et al., 2019).

Zhou et al. (2009) investigated the hematology of wild and cultivated Dojo loach, according to his results cultured Dojo have higher RBC’s count as compared to its wild counterpart, while wild Dojo have higher WBC’s count as compared to cultivated. Similar findings were obtained in present study in terms of RBC’s. Cultured silver, rohu, mori, gulfam and grass carp show higher values of RBC’s as compared to wild silver, rohu, mori, gulfam and grass carp, However, WBC’s results are contrary to present study in some species. Wild rohu and mori have higher WBC’s count, as compared to farmed rohu and mori. No significant difference was observed in WBC’s of wild and farmed silver and grass carp while farmed gulfam shown higher WBC’s as compared to wild counterpart. Higher WBCs count indicate a strong immune system because WBCs are key gears of innate immune-system and leukocytes are the chief component that involved in regulation of immunological function of the organism (Ballarin et al., 2004).

Kumar et al. (2017) reported higher MCV, MCHC, and MCH in mori and highest PLT in rohu and lowest in silver carp, apart from this lowest RBC’s was reported in gulfam. Similar findings were obtained in present research work except MCH and MCV, while highest RDW was reported in rohu. Kumar et al. (2017) reported lowest neutrophil value in gulfam which is contrary to the current study findings. Besides this hemoglobin level showed following trend; rohu˃ silver carp˃ grass carp˃ mori˃ common carp in their study, while our results are little bit contrary to those of Kumar et al. (2017) which show the following trans: silver˃ rohu˃ mori˃ grass carp˃ common carp. These changes may result because of environmental conditions, physical dysfunction, water quality and different types of stresses during handling.

 

Table III. Hematological parameters of selected fish species (farm and wild).

Para meters

Hypophth almichthys molitrix

Labeo rohita

Cyprinus carpio

Cirrhinus mrigala

Ctenopha ryngodon idella

Farm

Wild

Farm

Wild

Farm

Wild

Farm

Wild

Farm

Wild

RBC (µl ×10^6)

2.36± 0.33

2.16± 0.34

2.30± 0.40

2.14± 0.31

2.07± 0.38

1.87± 0.14

1.81± 0.39

2.16± 0.49

1.76± 0.20

1.48± 1.29

HB (g/dl)

10.89± 1.35

8.63± 1.48

9.75± 1.61

6.19± 0.81

8.58± 1.00

7.25± 0.71

9.50± 1.26

7.80± 1.31

9.29± 0.91

6.78± 0.81

Hct (%)

32.65± 4.16

27.07± 1.98

32.54± 2.13

28.7± 2.11

36.71± 4.38

29.89± 3.34

33.54± 4.52

26.96± 2.97

35.53± 4.07

29.54± 3.18

MCV (Fl)

139.34± 14

176.47± 36.21

146.45± 36.9

170.99± 26.83

164.41± 26.7

173.69± 23.7

147.33± 32.1

166.76± 53.25

177.52± 30.69

218.19± 37

MCH (Pg)

46.32± 2.18

57.32± 17.85

43.61± 11.99

36.78± 5.96

37.27± 7.00

42.05± 4.02

42.30± 11.91

49.11± 20.06

46.00± 4.63

50.18± 8.92

MCHC (g/dl)

33.42± 1.87

31.83± 4.71

30.95± 5.94

21.64± 2.89

22.69± 2.21

24.56± 3.88

28.50± 3.34

29.08± 5.07

26.18± 5.63

23.23± 3.92

WBC (µl×10^3)

29.97± 4.97

33.06± 1.80

41.95± 4.65

63.67± 5.47

79.67± 14.26

53.41± 8.02

38.66± 8.48

48.52± 5.70

53.61± 14.75

50.87± 7.24

Lym (µl ×10^3)

27.79± 3.56

24.61± 1.31

29.55± 2.90

41.86± 4.61

31.58± 13.16

36.49± 6.15

29.05± 6.67

24.41± 4.35

30.88± 13.67

35.96± 4.69

Lym (%)

69.56± 0.56

74.48± 2.21

70.52± 1.63

65.64± 2.26

74.27± 3.45

68.23± 2.78

70.32± 1.37

69.98± 1.44

71.61± 4.04

70.77± 1.03

Gra (µl ×10^3)

3.95± 0.84

3.97± 0.48

3.47± 0.61

8.05± 0.97

6.16± 0.97

5.91± 0.60

3.59± 1.26

3.04± 0.60

4.56± 0.72

5.07± 1.49

Gra (%)

9.1± 0.76

11.98± 1.03

8.23± 0.68

12.68± 1.52

13.78± 0.80

11.17± 1.12

8.23± 1.24

8.69± 0.92

8.98± 2.24

9.78± 1.56

Mid-Range (µl×10^3)

5.23± 0.61

4.48± 0.54

8.93± 1.35

13.76± 0.90

13.90± 0.49

11.00± 2.11

8.74± 1.57

10.80± 1.35

10.16± 1.45

9.83± 1.11

Mid-Range (%)

17.57± 1.05

13.54± 1.24

21.25± 1.34

21.67± 1.33

17.89± 2.92

20.6± 2.21

20.56± 1.54

23.87± 3.35

20.69± 4.47

19.41± 0.87

Plt (µl ×10^3)

60.88± 6.64

63.40± 3.46

38.59± 3.65

44.62± 3.48

86.83± 44.94

46.59± 12.26

32.97± 6.08

32.13± 6.52

50.25± 5.18

43.67± 4.61

Rdw- sd (Fl)

75.84± 27.8

66.08± 1.75

10.81± 1.47

14.09± 1.40

67.24± 11.43

13.79± 1.28

14.05± 1.49

10.57± 1.74

58.94± 15.04

43.05± 4.94

Rdw-cv (%)

12.05± 3.26

10.40± 1.08

19.36± 1.22

22.14± 2.74

38.16± 3.82

8.12± 1.84

22.03± 1.80

16.36± 4.68

10.91± 2.05

10.37± 1.55

MPV (Fl)

11.49± 2.05

11.44± 0.56

10.19± 1.61

10.65± 1.51

6.83± 0.60

11.96± 1.70

26.82± 5.11

29.38± 3.89

8.89± 1.87

8.90± 1.71

PDW (%)

14.10± 0.34

13.35± 0.71

10.95± 1.81

11.42± 1.82

8.21± 1.03

14.17± 1.87

10.32± 1.44

10.55± 2.02

11.89± 1.99

11.30± 1.75

Pct (%)

0.05± 0.01

0.05± 0.01

0.02± 0.01

0.04± 0.01

0.08± 0.04

0.07± 0.08

1.14± 0.13

0.21± 0.14

0.04± 0.01

0.04± 0.01

P-lcr (%)

33.19± 9.19

35.21± 1.65

27.02± 2.05

30.43± 2.15

31.32± 2.73

32.98± 5.77

56.32± 12.50

51.37± 6.49

26.01± 7.72

26.02± 3.86

Plt (µl ×103)

60.88± 6.64

63.40± 3.46

38.59± 3.65

44.62± 3.48

86.83± 44.94

46.59± 12.26

32.97± 6.08

32.13± 6.52

50.25± 5.18

43.67± 4.61

Rdw- sd (fl)

75.84± 27.83

66.08± 1.75

10.81± 1.47

14.09± 1.40

67.24± 11.43

13.79± 1.28

14.05± 1.49

10.57± 1.74

58.94± 15.04

43.05± 4.94

Rdw-cv (%)

12.05± 3.26

10.40± 1.08

19.36± 1.22

22.14± 2.74

38.16± 3.82

8.12± 1.84

22.03± 1.80

16.36± 4.68

10.91± 2.05

10.37± 1.55

MPV (fl)

11.49± 2.05

11.44± 0.56

10.19± 1.61

10.65± 1.51

6.83± 0.60

11.96± 1.70

26.82± 5.11

29.38± 3.89

8.89± 1.87

8.90± 1.71

PDW (%)

14.10± 0.34

13.35± 0.71

10.95± 1.81

11.42± 1.82

8.21± 1.03

14.17± 1.87

10.32± 1.44

10.55± 2.02

11.89± 1.99

11.30± 1.75

Pct (%)

0.05± 0.01

0.05± 0.01

0.02± 0.01

0.04± 0.01

0.08± 0.04

0.07± 0.08

1.14± 0.13

0.21± 0.14

0.04± 0.01

0.04± 0.01

P-lcr (%)

33.19± 9.19

35.21± 1.65

27.02± 2.05

30.43± 2.15

31.32± 2.73

32.98± 5.77

56.32± 12.50

51.37± 6.49

26.01± 7.72

26.02± 3.86

 

Abbreviations: RBCs, red blood cells; Hb, hemoglobin; HCT, hematocrit; MCH, mean cell hemoglobin; MCV, mean cell hemoglobin; MCHC, mean cell hemoglobin concentration; WBCs, white blood cells; Lym, lymphocytes), Gra, granulocytes; Mid, Mid-range cells; Plt, platelets; Rdw-sd, red cell distribution width-standard deviation; Rdw-cv, red cell distribution width- coefficient of variation; MPV, mean platelet volume; PDW, platelet distribution width; Pct, plateletcrit; P-lcr, platelet- large cell ratio.

 

Table IV. ANOVA and LSD results of hematology of farm and wild fish species.

Par-am eters

Hypophtha lmichthys molitrix

Cirrhinus mrigala

Labeo rohita

Cyprinus carpio

Ctenopha ryngodon idella

P-values

Farm

Wild

Farm

Wild

Farm

Wild

Farm

Wild

Farm

Wild

Farm

Wild

RBC

2.16± 0.34a

2.07± 0.33ab

2.16± 0.49a

2.33± 0.39a

2.14± 0.31a

2.30± 0.40a

1.87± 0.14a

1.76± 0.38b

1.48± 1.29b

1.81± 0.20b

**

*

Hb

8.63± 1.48a

10.89± 1.35a

7.80± 1.31ab

9.50± 1.26b

6.19± 0.81c

9.75± 1.61ab

7.25± 0.71bc

8.58± 1.00b

6.78± 0.81bc

9.29± 0.91b

**

*

Hct

27.07 ±1.98a

32.6 ±4.16a

26.96 ±2.97a

33.54 ±4.52a

28.7 ± 2.11a

32.54 ±2.13a

29.89 ±3.34a

36.7 ± 4.38a

29.54 ±3.18a

35. ±4.07a

0.18

0.21

MCV

176.47 ±36.2b

139.34 ±14b

166.76 ±53.3b

147.33 ±32ab

170.9 ±26.9b

146.45 ±37ab

173.6 ±23.7b

164.4± 27ab

218.1 ± 37a

177.5 ± 31a

0.08

0.11

MCH

57.32± 17.85a

46.32± 2.18a

49.11± 20.1ab

42.30± 12a

36.78± 5.96b

43.61± 12a

42.05± 4.02b

37.27± 7.00a

50.18± 8.92ab

46.0 ±4.6a

0.05

0.29

MCHC

31.83± 4.71a

33.42± 1.87a

29.08± 5.07ab

28.50± 3.3bc

21.64± 2.89c

30.95± 5.94ab

24.56± 3.88bc

22.69± 2.21d

23.23± 3.92c

26.1± 5.6cd

***

***

WBC

33.06± 1.80c

29.97± 4.97d

48.52± 5.70b

38.66± 8.5cd

63.67± 5.47a

41.95± 4.65c

53.41± 8.02b

79.67± 14.5a

50.87± 7.24b

53.6± 14.8b

***

***

Lym

24.61± 1.31c

20.79± 3.56c

24.41± 4.35c

30.05± 6.7bc

41.86± 4.61a

29.55± 2.90bc

36.49± 6.15b

59.58± 13a

35.96± 4.69b

38.8± 13.7b

***

***

Lym%

74.48± 2.21a

69.56± 0.56b

69.98± 1.44bc

70.32± 1.37b

65.64± 2.26d

70.52± 1.63b

68.23± 2.78c

74.27± 3.45a

70.77± 1.03b

71.6± 4ab

***

*

Gra

3.97± 0.48c

3.95± 0.84bc

3.04± 0.60c

3.59± 1.26bc

8.05± 0.97a

3.47± 0.61c

5.91± 0.60b

6.16± 0.97a

5.07± 1.49b

4.56± 0.72b

***

***

Gra%

11.98± 1.03ab

13.1± 0.76a

8.69± 0.92c

8.23± 1.24b

12.68± 1.52a

8.23± 0.68b

11.17± 1.12b

7.78± 0.80b

9.78± 1.56c

8.9 ± 2.24b

***

***

Mid

4.48± 0.54c

5.23± 0.61d

10.80± 1.35b

8.74± 1.57c

13.76± 0.90a

8.93± 1.35bc

11.00± 2.11b

13.90± 0.49a

9.83± 1.11b

10.1± 1.4b

***

***

Mid%

13.54± 1.24d

17.57± 1.05c

23.87± 3.35a

20.56± 1.5ab

21.67± 1.33b

21.25± 1.34a

20.6± 2.21bc

17.89± 2.9bc

19.41± 0.87c

20.6± 4.47ab

***

*

Plt

63.40± 3.46a

60.88± 6.64b

32.13± 6.52c

32.97± 6.08c

44.62± 3.48b

38.59± 3.65bc

46.59± 12.2b

86.83± 44.9a

43.67± 4.61b

50.5± 5.18bc

***

***

Rdw-sd

66.08± 1.75a

75.84± 27.8a

10.57± 1.74d

14.05± 1.49c

14.09± 1.40c

10.81± 1.47c

13.79± 1.28c

67.24± 11ab

43.05± 4.94b

58.9± 15.0b

***

***

Rdw-cv

10.40± 1.08c

12.05± 3.26c

16.36± 4.68b

22.03± 1.80b

22.14± 2.74a

19.36± 1.22b

8.12± 1.84c

38.16± 3.82a

10.3± 1.55c

10.9± 2.05c

***

***

MPV

11.44± 0.56b

11.49± 2.05b

29.38± 3.89a

26.82± 5.11a

10.65± 1.51bc

10.19± 1.61b

11.96± 1.70b

6.83± 0.60c

8.90± 1.71c

8.8 ± 1.87bc

***

***

PDW

13.35± 0.71a

14.10± 0.34a

10.55± 2.02b

10.32± 1.44b

11.42± 1.82b

10.95± 1.81b

14.17± 1.87a

8.21± 1.03c

11.3± 1.75b

11.8± 1.99b

**

***

Pct

0.05± 0.01b

0.05± 0.01b

0.21± 0.14a

1.14± 0.13a

0.04± 0.01b

0.02± 0.01b

0.07± 0.08b

0.08± 0.04ab

0.04± 0.01b

0.04± 0.0b

***

**

P-lcr

35.21± 1.65b

33.19± 9.19b

51.37± 6.49a

56.32± 12.5a

30.43± 2.15bc

27.02± 2.05b

32.98± 5.77b

31.32± 2.73b

26.02± 3.86c

26.0 ± 7.72b

***

***

 

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1. Values in a row with different superscripts are significantly different from each other.

For abbreviations, see Table III.

Afkhami et al. (2011) reported that C. idella and H. molitrix have higher blood parameters, Hb, PCV, RBC’s, WBC’s as compared to grass carp, Hb, PCV, RBC’s, WBC’s. Similar findings for RBC’s and Hb were obtained in present research silver carp shows higher Hb and RBC’s as compared to grass carp. However, PCV and WBC’s results are contrary to our findings because of various environmental factors. Kandeepan (2014) reported that rohu has higher RBC’s, WBC’s and PCV as compared to C. carpio RBC’s, WBC’s and PCV. According to present research result rohu shown higher value of RBC’s as compared to gulfam which is similar to the above mention study. However, in other three parameters the present research results are contrary to the Kandeepan (2014) study. This difference may arise due to different environmental and living conditions. Feed composition, feed quantity and feeding habits also affect the energy, metabolic pathways and in turn the physical health and hematological parameter of fish. Several studies had been carried out to evaluate the effects of the different feed on the blood parameter of fish like Kondera et al. (2017) reported that starvation or low nutrient feed can reduce erythroblast frequency, result in low frequency of neutrophilic lineage, low oxygen consumption rate. But they did not find any effect on immune response but record reduced haematopoietic activity, which was directly related to the metabolic rate. Another study by Iqbal et al. (2017) in which they used selenium fortified feed in different doses and conclude that different dose of selenium in feed can effects the counts of WBC’s, neutrophils, RBC’s and hemoglobin. In the current study feed availability was different in composition and even quantity in both of the habitat. So this may result in difference in blood parameter values.

CONCLUSION

It is concluded that hematological parameters of farm fish were influenced by some water quality parameters such as water temperature, dissolved oxygen, pH, calcium, magnesium and nitrate values or may be due to feed composition as compared to the wild. However, it is necessary to consider the age and size of the fish, breeding periods, gender, seasons, physiology of the fish, habitat and environmental conditions.

Statement of conflict of interest

The authors have declared no conflict of interest.

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Pakistan Journal of Zoology

February

Vol. 54, Iss. 1, Pages 1-501

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