Study on Development of Formulated Feed for Improving Growth and Pigmentation of Koi Carp (Cyprinus carpio L., 1758) Juveniles

Study on Development of Formulated Feed for Improving Growth and Pigmentation of Koi Carp (Cyprinus carpio L., 1758) Juveniles

Nguyen Van Nguyen, Tran Van Khanh, and Pham Duy Hai Research Institute for Aquaculture No. 2, Ho Chi Minh City, Vietnam

Received: March 29, 2014/ Accepted: May 08, 2014 / Published: May 30, 2014.

Abstract: The aim of the present study was to develop a formulated feed for improving skin pigmentation and growth performance of koi carp juveniles. Two experiments were conducted for determination of an optimal dietary astaxanthin and FM (fish meal) ration for koi carp juveniles. In the first experiment, three isonitrogenous and isoenergetic dietary treatments were designed with three different levels of astaxanthin consisted of 60, 80 and 100 mg/kg and a commercial feed served as a control. For the second experiment, four isonitrogenous and isoenergetic dietary treatments were formulated with graded inclusions of dietary FM replaced from 0% to 60% at 20% increments by SM (soybean meal), PBM (poultry by-product meal), and a CD (control diet). Obtained results demonstrated that skin pigmentation of koi carp juveniles fed the diet containing 80 mg/kg astaxanthin, 36.02% protein, 7.78% lipid, 4.20 Kcal/g GE (gross energy) were more better than those at the diet with lower estaxanthin content and commercial diet. Moreover, the highest growth and feed utilization of fish were observed at this diet with WG (weight gain), SGR (specific growth rate) and FCR (feed conversion ratio) were 121.80%, 0.95 (%/day) and 1.6, respectively.

Key words: Formulated feed, pigmentation, fish meal, replacement, koi carp juveniles.

1. Introduction  of fish and shrimp [2-4]. Dietary astaxanthin commonly ranged from 45-100 mg/kg in compounded feeds for

Aquarium fish feed is generally formulated to different aquatic species, but it can be supplemented up satisfy the aquarium hobby of consumers as colour to 2300 mg/kg in the diets for shrimp post larvae [1, 5]. and appearance acceptability, feed cost and minimum Generally, estaxanthin is considered as a very environmental pollution. Feed basically is in associated crucial factor concerning to fish skin pigmentation, with skin pigmentation and well-being and plays a and particularly this ingredient presented in most of very important role in inducing coloration as well as feeds for aquarium fish. However, apart from essential improving the growth of fish. Fish and shrimp use role of estaxanthin, dietary fish meal in the diet for oxygenated carotenoids from the diets to produce aquarium fish is also a high-quality protein relates to pigmentation of their tissue and skin and egg [1]. The well-being, feed efficiency of fish and environmental natural ingredients containing carotenoid pigments are impacts. Today, fish meal replacement in the diets by used as feed additives to enhance skin color of fish as another protein sources for fish and shrimp is red paprika, krill, algae and microorganisms, in which becoming necessary and the main trend for sustainable astaxanthin is considered as a carotenoid pigment aquaculture. In which, SM and PBM are basically widely used in the diets to improve the color intensity considered as the appropriate alternatives of FM in the

diets for many cultured aquatic species [6-12]. In Corresponding author: Nguyen Van Nguyen, Ph.D.,

aquarium fish culture, Koi fish is one of the favorite research fields: fish nutrition and feed technology. E-mail:

nguyenria2@gmail.com. ornamental fish commonly cultured in the world and a

Study on Development of Formulated Feed for Improving Growth and Pigmentation

of Koi Carp (Cyprinus carpio L., 1758) Juveniles

formulated feed has the function of color enhancement

2.2 Experimental Fish and Rearing Conditions and nutritional balance is necessary for most of the

Koi carp juveniles with initial mean body weight people concerning the aquarium fish hobby and

(26.26 ± 1.25 g) were acclimated for 10 days in culture. Development of formulated feed containing a

suitable level of dietary astaxanthin and fish meal to composite tanks prior to start of the feeding trial. Fish improve skin pigmentation and growth performance

were randomly stocked at 30 fishes per tank, three for koi carp juveniles was the aim of this study.

replicates in 12 and 15 units of 500 L composite tanks for the Exp. 1 and Exp. 2, respectively. Fish fed twice

2. Materials and Methods

daily per day to satiation at a feeding rate of 2-4% of

2.1 Diet Preparation body weight for 60 days of Exp. 1 and 90 days of the Exp. 2. After 30 min feeding, siphon and calculate the

For the diet preparation, in the first experiment uneaten feed. Tanks were supplied with sand-filtered

(Exp. 1), three dietary treatments were formulated water in a flow-through system with adequate aeration,

containing different levels of astaxanthin at 60, 80 and and 30% water exchange rate maintained once a week.

100 mg/kg and a control diet (commercial feed-CD) were designed. In the second experiment (Exp. 2), five

2.3 Analytical Procedures

diets were established comprised four isonitrogenous and isoenergetic dietary treatments provided an

2.3.1 Chemical Composition

optimal level of dietary astaxanthin obtained from Exp. Proximate composition of the diets was analysed

1 and different rates (0%, 20%, 40% and 60%) of fish according to the procedures [13]. Fatty acids and meal replaced by SM (soybean meal), PBM (poultry

essential fatty acids including LOA (Linoleic acid), by-product meal), and a CD (control diet). The

LNA (Linolenic acid), ARA (Arachidonic acid); EPA formulated and commercial diets in Exps. 1 and 2 are

(Eicosapentaenoic acid); OHA (ocosahexaenoic acid) shown in Tables 1 and 2.

analyzed by (GC-ISO/CD 5509:94).

Table 1 Formulated diets containing different levels of dietary astaxanthin.

Fish meal

Soybean meal

Corn meal

Cassava meal

Wheat flour

6.00 6.00 6.00 Di-Ca-P 0.50 0.50 0.50 Premix-V&M 0.60 0.60 0.60

Fish oil

Soybean oil

Stay C 35%

Anti-molds & Oxidant

Choline Chloride 60%

Total 100.00 100.00 100.00 Fish meal 65% (Local fish meal-Kien Giang); Soybean meal 46% (India); Fish Oil (Chile fish oil), Lucanthin-pink (Astaxanthin 10%-BASF), Premix V-M [3]: Vitamin A: 8000 IU, vitamin D: 900 I.U, vitamin K: 4; B2: 3.6; Niacin:20; Pantothenic acid: 7; B6: 0.2; B12: 0.005; Mn: 70; Zn: 60; Fe: 20; Cu: 2; I: 1; Co: 0.2.

Study on Development of Formulated Feed for Improving Growth and Pigmentation

of Koi Carp (Cyprinus carpio L., 1758) Juveniles

Table 2 Formulated diets prepared with different levels of dietary FM (fish meal) replacement.

Ingredients D1 D2 D3 D4

(60% Rpl) Fish meal

30.00 24.00 18.00 12.00 Poultry by – product meal

0.00 0.00 0.00 6.80 Soybean meal

28.50 37.20 46.20 44.50 Corn meal

14.00 14.00 14.00 18.00 Cassava meal

10.95 7.80 6.60 6.20 Wheat flour

8.00 8.00 6.00 4.00 Di - Ca - P

0.50 0.50 0.50 0.50 Premix-V & M

0.60 0.60 0.60 0.60 Fish oil

3.00 2.00 2.20 2.00 Soybean oil

1.85 3.00 3.00 2.50 Methionine & Lysine

1.20 1.50 1.50 1.50 Stay C 35%

0.30 0.30 0.30 0.30 Anti-molds & Oxidant

0.15 0.15 0.15 0.15 Astaxanthin

0.08 0.08 0.08 0.08 Choline Chloride 60%

0.15 0.15 0.15 0.15 Total 100.00 100.00 100.00 100.00 Fish meal 65% (Local fish meal–Kien Giang); Poultry by-product meal 65% (Argentina); Soybean meal 46% (India); Fish Oil (Chile fish oil), Lucanthin-pink (Astaxanthin 10%-BASF), Premix V-M [3]: Vitamin A: 8000 IU, vitamin D: 900 I.U, vitamin K: 4; B2: 3.6; Niacin:20; Pantothenic acid: 7; B6: 0.2; B12: 0.005; Mn: 70; Zn: 60; Fe: 20; Cu: 2; I: 1; Co: 0.2.

2.3.2 Color Measurement

3. Results

Colorimeter (NIPPON DENSHOKU NR 300) was

3.1 Experiment 1

used for color measurement of fish skin, the color values indirectly measured and presented by factors

Proximate composition of the diets and colour comprised of L*, a* and b*. In which, L* expresses

values of fish skin are shown in Table 3 and 4. Data in white color with value of 100 and black with 0, a* and

Table 3 illustrated that proximate composition of the b* values display the chromaticity and reflect red

experimental diets are equivalent in nutrients and color with + a* and green with – a* value, whereas, +

energy levels. Chromatic values of fish at the b* value represents for yellow and – b* represents for

treatments were measured and presented in Table 4. blue. The mean values of fish skin color were

The data indicated that there were no any

measured based on 3-4 brilliant points on fish body. significant differences in values of L*, a*, b* of fish at

2.3.3 Calculations the initial stage among treatments. However, the color Parameters used to evaluate growth performance

values of a* and b* of fish skin were slightly increased and feed utilization in the experiments expressed as

and significantly different (P < 0.05) compared to WG (Weight Gain), SGR (Specific Growth Rate),

those at the CD (control diet) during of the experiment, FCR (Feed Conversion Rate) and SUR (Survival Rate)

in which fish fed the diets containing dietary

[1, 3]. estaxanthin observed toward increasing red and

2.3.4 Statistical Analysis yellow coloration of skin. In general, fish fed the diets Statistical software (SPSS version 18) was used for

contained 80 and 100 ppm estaxanthin (DA2, DA3) statistical analysis and data from each treatment diet

had the better chromatic values of a* and b* in were subjected to one-way ANOVA and differences

comparison with those at the DA1 and CD. Especially, were considered significant at P < 0.05.

there were no significant differences in L* values of

Study on Development of Formulated Feed for Improving Growth and Pigmentation

of Koi Carp (Cyprinus carpio L., 1758) Juveniles

Table 3 Proximate composition of the diets in the Exp. 1.

Experimental diets (as fed basis)

Composition DA1 DA2 DA3 CD

Moisture (%)

Crude Protein (%)

Crude Lipid (%)

Crude Ash (%)

Crude Fibre (%)

GE (Kcalg -1 ) 4.17 4.23 4.19 3.94 GE calculated based on 5.64 Kcal/g proteins, 9.44 kcal/g lipids and 4.11 Kcal/g carbohydrates [NRC, 2011].

Table 4 Change of values a*, b* and L* of fish skin during the experiment.

Experimental diets

Color values DA1 DA2 DA3 CD

L* values

Initial

74.01 a ± 2.34 30 days

66.75 a ± 1.52 60 days

67.61 a ± 1.39 a* values Initial

13.55 a ± 1.46 30 days

32.85 a ± 1.62 60 days

34.95 a ± 2.17 b* values Initial

30.94 a ± 2.54 30 days

45.33 a ± 1.98 60 days

44.51 a ± 2.48 Figures are presented as mean ±SE, values in the same row with different superscript letters are significantly different (P < 0.05).

Table 5 Growth and feed utilization of fish fed the experimental diets for 2 months.

Diets WG (%)

SGR (%/day)

FCR

SUV (%)

95.56 a ± 1.93 DA1

CD 66.25 a ± 2.82

0.90 a ± 0.030

1.76 c ± 0.043

94.44 a ± 1.93 DA2

94.44 a ± 1.93 DA3

95.56 a ± 1.93 Figures are presented as mean ±SE, values in the same column with different superscript letters are significantly different (P < 0.05).

fish skin among the treatments during the trial. In showed the lowest FCR. However, there were no any contrast to the formulated feed provided estaxanthin,

significant differences in SUR among the treatments. fish at the control treatment (CD) particularly had a

3.2 Experiment 2

pale skin and less redness. In terms of growth performance, the data in Table 5 showed no

Proximate composition of the diets was mostly significant differences in WG and SGR (%) of fish

equivalent (Table 6) except the CD with a lower lipid, between the DA1 and CD while fish fed DA2 and

fiber and energy and higher NFE, ash content DA3 had a better WG, SGR and FCR. Particularly,

observed, in which the CD had the lowest content

fish at the diet DA2 containing 80 ppm of estaxanthin of lipid (3.23%). The data of fatty acid contents in the

Study on Development of Formulated Feed for Improving Growth and Pigmentation

of Koi Carp (Cyprinus carpio L., 1758) Juveniles

Table 6 Nutrients of the different diets in the experiment 2.

Experimental diets (as fed basis) Composition

D1 D2 D3 D4 CD (0% Rpl)

Moisture (%) 8.06 8.68 9.12 8.82 9.15 Crude Protein (%)

37.42 36.09 36.23 36.02 36.47 Crude Lipid (%) 8.02 7.96 7.93 7.78 3.23 Crude Ash (%)

9.68 8.43 7.38 7.96 9.76 Crude Fiber (%)

3.86 3.88 4.40 4.38 3.05 NFE (%) 32.96 34.96 34.94 35.04 38.34 GE (kcal/g)

4.22 4.22 4.23 4.20 3.94 GE calculated based on 5.64 kcal/g proteins, 9.44 kcal/g lipids and 4.11 kcal/g carbohydrates [NRC, 2011].

Table 7 Fatty acid composition of the experimental diets (g/100 g sample).

Experimental diets

Fatty acids D1 D2 D3 D4 CD

1.309 C18:2n-6 (LOA)

1.786 C18:3n-3 (LNA)

0.062 C20:4n-6 (ARA)

0.046 C20:5n-3 (EPA)

0.041 C22:6n-3 (DHA)

0.340 0.294 0.323 0.252 Total n-3

0.653 Total n-6

1.832 n-3/n-6 0.426 0.266 0.362 0.297 0.357 EPA/DHA 0.623 0.524 0.813 0.554 0.708

diets (Table 7) indicated that the formulated diets fed diet D4 (60% FM replacement) were significantly contained essential fatty acids with higher content of

different (P < 0.05) in WG, SCR and FCR compared LOA, EPA and DHA and lower content of LNA,

to those at the CD and D1 (0% FM replacement), but ARA compared to the CD. However, the n-3/n-6 ratio

there were no statistically significant differences (P > in all the diets was the same and ranged from 0.266 to

0.05) of WG and FCR in comparison with those at the 0.426.

D2 and D3. In addition, there was no significant For the growth performance and feed utilization, the

difference (P > 0.05) in SUR among treatments and WG and FCR of fish (Table 8) were recorded from

fish fed CD particularly had the lowest WG, SCR and 93.39-121.80%, 0.79-0.95% /day, respectively. Fish

highest FCR.

Study on Development of Formulated Feed for Improving Growth and Pigmentation

of Koi Carp (Cyprinus carpio L., 1758) Juveniles

Table 8 Weight gain, specific growth rate, survival and feed conversion ratio of fish fed the practical diets for 03 months.

Diets

WG (%)

SGR (%/day)

FCR

SUV (%)

95.56 a ± 1.93 D1 (0% Rep.)

CD 93.39 a ± 6.21

0.79 a ± 0.039

1.98 c ± 0.073

94.44 a ± 1.93 D2 (20% Rep.)

94.44 a ± 1.93 D3 (40% Rep.)

95.56 a ± 1.93 D4 (60% Rep.)

95.56 a ± 1.93 Figures are presented as mean ±SE, values in the same column with different superscript letters are significantly different (P < 0.05).

4. Discussion

estaxanthin (50-100 ppm) to induce and maintain threshold of skin pigmentation for aquarium fish [1].

Nutrients of the diets in experiments generally were Concerning to improving and inducing the

nutritional balanced and met nutrition requirement for pigmentation for ornamental fish by using dietary koi carp juveniles except the CD contained a lower pigments, Hancz et al. [18] used paprika as feed lipid (3.23%) and slightly lower gross energy level additive containing high content of capsanthin to (3.94%). According to NRC and Murai et al. [1, 14],

enhance color intensity in koi carp and goldfish. A protein requirement for koi carp fingerlings (0.5-10 g)

similar study of using paprika in the diet of fancy carp, was ranged from 31-38%. Similar with this

it was determined that a formulated diet contained 5% demonstration, Yesilayer et al. and Komaz et al. [15,

carotenoid-rich paprika referred as a suitable rate of 16] were formulated feeds containing around 35%

natural ingredient to improve the coloration of fancy protein, 9% lipid and 4.2 kcal/g GE, 3.0 kcal/g DE for

carp [19]. Yuangsoi et al. [20] demonstrated that the koi fingerlings. Not only proximate chemical

skin redness of fancy carp fed with 25 mg/kg composition of the diets, energy level and ratio of

essential fatty acids of feeds are closely associated astaxanthin diet was similar to the fish fed diets with growth, feed utilization and carcass composition

combined with lutein and β-carotene at 25:25, 50:50 of fish [1, 17]. In contrast to the formulated feeds, the

mg/kg and lutein 50 mg/kg but higher than the control CD had a lower level of lipid and essential fatty acids

contained no supplemented pigments. Today, (LOA, EPA and DPA), consequently and as a result

astaxanthin widely used to induce the pigmentation led to low fish growth and high FCR.

for fish and shrimp. Paripatananont et al. [21] In the first experiment, the results achieved from

demonstrated that the dietary astaxanthin levels of the evaluation of relationship between dietary 36-37 mg/kg were the suitable doses to induce the

estaxanthin and fish skin pigmentation indicated that color intensity of Goldfish Carassius auratus. fish fed the diets containing 80 and 100 ppm dietary

Whereas, Manimegalai et al. [22] found that the estaxanthin showed no statistically significant content of 20-100 ppm dietary astaxanthin was more

differences in chromatic values and growth effective than beta-carotene in producing skin performance, but had a better skin pigmentation than pigmentation of Etroplus Maculatus (E. maculatus).

those at DA1 and CD. Obviously, for the calculation Baron et al. [23] reported that the red coloration of in the aspects of efficiency in fish growth and feed

flame-red male dwarf gourami, Colisa lalia cost, the diet (DA2) contained 80 ppm dietary

significantly increased after 12 weeks of feeding with estaxanthin was considered as the best diet containing

the diet contained 100 ppm synthetic astaxanthin an optimal estaxanthin ration. The level of dietary

(Lucantin Pink). Fish fry (Xiphophorus helleri) fed the estaxanthin observed in this experiment is accordant

diets containing carotenoid pigments extracted rose with recent studies and recommendations for using

rubiginosa petals had a better growth, survival and

Study on Development of Formulated Feed for Improving Growth and Pigmentation

of Koi Carp (Cyprinus carpio L., 1758) Juveniles

skin pigmentation compared to those at the control several plant and animal protein sources can be used diet [24].

for partial and totally fish meal replacement in the In the second experiment, growth performance of

diets for many aquatic species. In which, PBM and fish increased with increasing dietary FM replacement

SM have been commonly used as the suitable sources by SM and PBM. Particularly, fish fed the diet (D4)

to replace FM and other animal protein in the diets for that dietary fish meal replaced up to 60% by SM and

fish and shrimp. Yesilayer et al. [15] found that it had PBM showed the best growth while fish at the CD

no adverse effects on growth performance of koi gave a depression of WG, SGR and highest FCR.

juveniles fed the diets containing 0% FM and 16% Surprisingly, the data illustrated that the more

FM, correspondingly with 45% SM and 22.5% SM in replacement of dietary fish meal, the better fish

the diet. Ismail et al. [25] reported that 100% fish meal growth and feed efficiency (Table 8). Possible reason

in the diet of Malaysian mahseer (Tor tambroides) can for the increasing growth and reduced FCR at the

be replaced by poultry offal meal without adversely increasing content of fish meal replaced in the diets

effects on survival and growth and body composition. may concern to the quality of protein ingredients used

Tri and Davis [26] asserted that dietary FM can be in this study. Quality of ingredients is closely

totally replaced in commercial diets for tilapia associated with the quality of feed and obviously, the

juveniles by de-hulled soybean meal (solvent quality of FM may be a crucial factor and should be

extracted) and expelled soybean meal (pressed) taken account into consideration of quality of the diet

without adversely effects on growth and feed in this experiment. Furthermore, koi cap is utilization. Yang et al. [27] recommended that PBM omnivorous and has probably a good digestibility of

could replace up to 500 g/kg of FM protein in diets for dietary protein sources regardless of animal or plant

gibel carp (Carassius auratus gibelio) without protein in the diets unless the poor quality of protein

negative effects on growth. Likewise, Saadiah and sources and deficiencies of nutrients. In addition, not

Abol-Munafi [28] found 100% dietary FM can be only SM and PBM used for FM replacement in the

replaced by PBM in the diets for cobia, Rachycentron diets, but also corn meal which has been referred as a

canadum without adversely affects on growth palatable ingredient and high coefficient of performance, but an optimal replacement level at digestibility for carp [4]. Concerning to the survival

approximately 60% was recommended for better rate of fish, the data indicated that without significant

growth and efficient feed utilization. Whereas, the difference in SUR among the treatments, this can be

replacement of FM with PBM in the diets for mirror explained by good husbandry and environmental

carp fingerling (Cyprinus carpio) with the range of management during the experiments resulted to high

PBM from 12-36% showed significantly differences survival rate and without significantly differences (P >

and as increasing the PBM content in the diets

0.05) among treatments. resulted in lower WG and higher feed utilization [8]. The replacement of dietary fish meal in the diets of

Not only SM and PBM but also the other protein fish and shrimp by another protein sources derived

sources derived plant and biology have been used as from animal, plant and biology has been considered as

potential protein sources to replace dietary fish meal

a practical solution for sustainable aquaculture for reducing feed cost as well as exhausted development. Thus, the finding of alternatives of fish

exploitation of wild fish. Korkmaz and Cakirogullari meal is absolutely in compliance with the trend of

[16] found that Dried Baker’s Yeast can be used to using another protein sources to replace fish meal in

replace up to 30% dietary fish meal in the diets for koi the diets of aquatic animal. Recent studies proved that

carp fingerlings that did not show significantly

Study on Development of Formulated Feed for Improving Growth and Pigmentation

of Koi Carp (Cyprinus carpio L., 1758) Juveniles

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Mazurkiewicz [29] reported that replacement of

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some plant ingredients as dietary protein sources for common carp (Cyprinus carpio L.) fry, Aquaculture 151

meal) up to 26% in the diets (35% protein, 22% FM)

(1997) 55-70.

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5. Conclusions

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Effect of replacement of dietary fish meal by meat and Tabthipwon, The pigmenting effect of different

bone meal and poultry by-product meal on growth and carotenoids on fancy carp (Cyprinus carpio), Aquaculture

feed utilization of gibel carp, Carassius auratus gibelio. Nutrition 17 (2) (2011) 306-316.

Aquaculture Nutrition 10 (5) (2004) 289-294. [21] T. Paripatananont, J. Tangtrongpairoj, A. Sailasuta, N.

[28] I. Saadiah, A.M.CU Abol-Munafi, Replacement of Chansue, Effect of astaxanthin on the pigmentation of

fishmeal in cobia (Rachycentron canadum) diets using goldfish Carassius auratus, Journal of the World

poultry by-product meal, Aquaculture International 19 (4) Aquaculture Society 30 (1999) 454-460.

(2011) 637-648.

[22] M. Manimegalai, G. Bupesh, M. Mirunalini, S. Vasanth, [29] J. Mazurkiewicz, Utilization of domestic plant S. Karthikeyini, P. Subramanian, Color enhancement

components in diets for common carp, Cyprinus carpio study on Etroplus Maculatus using Astaxanthin and

L., Arch. Pol. Fish 17 (2009) 5-39. β-caroten, International Journal of Environmental Science

[30] S.S. Kim, S. Rahimnejad, K.W. Kim, K.J. Lee, Partial 1 (3) (2010) 403-416.

replacement of fish meal with Spirulina pacifica in diets [23] M. Baron, S. Davıes, L. Alexander, D. Snellgrove, K.A.

for parrot fish (Oplegnathus fasciatus), Turkish Journal Sloman, The effect of dietary pigments on the coloration

of Fisheries and Aquatic Sciences 13 (2013) 197-204.

May 2014, Vol. 8, No. 5, pp. 442-446

Journal of Life Sciences, ISSN 1934-7391, USA

DAVID PUBLISHING

Study of Caspian Goby Neogobius sp. Karyotype Flexibility from Several Biotops

1 1 2 3 Aithazha Bigaliev 1 , Saidina Kobegenova , Viktor Vasil’ev , Elena Vasil’eva , Aiman Imentai and Ashan Shametov 1

1. Department of Molecular Biology and Genetics, Al-Farabi Kazakh National University, Almaty, BOX 050040, Kazakhstan

2. IPEE (Institute of Ecology and Evolution), Russian Academy of Sciences, Russia 3. Zoological Museum, Moscow State University, Moscow, Russia

Received: January 16, 2014 / Accepted: April 21, 2014 / Published: May 30, 2014.

Abstract: The karyotype of Caspian goby was studied, which has been identified as Caspian bighead goby–Neogobius gorlap before. The results of cytogenetic analyses have shown that the diploid set of goby varies from 38 to 40 chromosomes, which is different from bighead goby (2n = 43-46). We assumed that Caspian goby has independence as a species.

Key words: Caspian goby, diploid number of chromosomes, karyotype, cytogenetic, chromosomal mutation, evolution.

1. Introduction “Karakol”, which is located 10-14 km from Aktau town. Fish was caught by net. The average body

Most of species and subspecies of goby family length of captured specimens ranged from 6.0 to 20 (Gobiidae) are endemic of the Caspian Sea. The sm. Mitotic chromosome preparations were obtained investigation of taxonomical status of the Caspian from a kidney and thymus cell suspension to the gobies attracts researchers to use not only air-drying technique after in vivo colchicines treatment morphological features, but also karyological data [6]. Chromosomes were classified by the criteria of [1-4]. It is assumed that Gobiidae family based on

Levan [7].

karyology is a compact group as most of them have 46 acrocentric chromosomes with 46 NF [5].

3. Results and Discussion

The results of cytogenetic analyses of Caspian goby, The 12 out of 16 specimens’ mitotic plates were which has been collected in August 2012 in the obtained. The karyotypes of studied samples were Caspian Sea near the Aktau town, external signs of significantly different from Caspian goby gorlap which are similar with bighead goby or (Neogobius gorlap). It is considered as subspecies of gorlap–Neogobius gorlap (Fig. 1). Neogobius kessleri (Günther, 1861). Afterwards,

2. Materials and Methods

using the methods of cytogenetic analysis, it was proved that N. kessleri and N. gorlap are different

A total of 16 sexually mature specimens were used species [3, 8-10]. Authors have shown that the number for this study. All specimens were collected from the of chromosomes of N. kessleri from the rivers Dnepr coastal zone of district 9 in the “Buchta” and the gulf and Dnestr was 30 for the female and 29 for the male.

The chromosomal formula for the female was 14 Corresponding author: Aithazha Bigaliev, Ph.D., professor,

metacentric, 2 submeta centric and 2 subtelocentric and research fields: general genetic and ecology, environmental

mutagenesis and ecologically genetic. E-mail:

12 acrocentric chromosomes. The chromosomal formula aitkhazha@gmail.com.

Study of Caspian Goby Neogobius sp. Karyotype Flexibility from Several Biotops

Fig. 1 Caspian goby is collected from the gulf “Karakol”.

Table 1 Chromosome set of Neogobius sp. collected in the coastal area near by Aktau.

No. of fish Sex

Formula of karyotype No. 32.5-1*

Length of fish (mm)

2n

NF

63 40 46 4m + 2sm + 34a No. 38.5-1*

48 38 44 4m + 2st + 32a No. 38.5-4*

48 38 42 1m + 3st + 34a No. 40.5-1*

No. 42.6-1

38 38a

No. 42.6-12 ♂ 38 48 5m + 5st + 28a No. 45.6-7

♀ 39 46 1m + 4st + 2st + 32a No. 50.6-1

♀ 60 38 46 3m + 5st + 30a No. 54.6-2

♂ 69 38 45 1m + 6sm + 31a No. 54.6-7

39 46 3m + 2sm + 2st + 32a No. 54.6-11

47 4m + 3st + 33a No. 54.6-14

39-40

44 1m + 4sm + 34a No. 54.6-15

38-39

38 46 1m + 5sm + 32a

for the male was 15 metacentric, 2 submetacentric and number of chomosome arms as NF = 46 [11, 12].

12 acrocentric chromosomes. However, both sexes had The studied diploid set ranged from 38 to 40 the equal number of chromosome arms as NF = 46. The

chromosomes, while the variability of the cytogenetic structure both of sexes of N. kessleri has

chromosomal formula and the arm number were shown the male heterogeneity and the presence of a

observed (Table 1).

fixed Y-autosomal translocation [3]. The karyotype of The karyotype of syrman goby includes, in the N. gorlap from the downstream of the River Volga and

diploid set, from 32 to 34 chromosomes with the the west-east coast of the Caspian Sea was found 46

number of chromosomes arms as 46 [13]. chromosomes with 2 subtelocentric and 44 acrocentric

According to the table 1, the specimens with the and the arm number as NF = 46 [3]. Further investigation

number 38, 42, 50 have the diploid number 2n = 38, of the diploid number of chromosomes of gorlap from

while the formula of karyotype is different. Therefore, the Caspian Sea (The Rivers Bolshoy and Malyi Uzen)

the arm number also varies. The karyotype of gorlap has shown polymorphism and interpopulation No. 54 includes, in the diploid set, from 32 to 34 variability of karyotypes. There is a variability of

chromosomes and each of the metaphase plate has number of chromosomes from 43 to 46 with the same

different formula (Figs. 2 and 3).

Study of Caspian Goby Neogobius sp. Karyotype Flexibility from Several Biotops

metacentric chromosomes; submetacentric chromosomes;

acrocentric chromosomes.

Fig. 2 Metaphase plate and karyotype of Caspian goby No. 54.6-2 (male 69 mm): 2n = 38.

Fig. 3 Metaphase plate of Caspian goby gorlap No. 54.6-7: 2n = 39.

The first metaphase plate includes: 1 metacentric, 6 length of 170 mm is 2n = 38, include 4 metacentric, 2 submetacentric and 31 acrocentric chromosomes (Fig.

submetacentric, 2 subtelocentric and 30 acrocentric 2). Second metaphase plate includes: 3 metacentric, 2

chromosomes. The arm number NF = 45. submetacentric, 2 subtelocentric and 32 acrocentric

4. Conclusions

chromosomes with the diploid set 2n = 39 (Fig. 3). The karyotype of the female ( № 45.6) with the

Therefore, the investigated gorlap using the diploid

Study of Caspian Goby Neogobius sp. Karyotype Flexibility from Several Biotops

number is completely different from the Caspian Akad. Nauk SSSR 432 (4) (1992) 898-900. (in Russian) [4] D.A. Medvedev, P.A. Sorokin, V.P. Vasil'ev, N.V.

bighead goby (N. gorlap). There are also slightly Chernova, E.D. Vasil'eva, Reconstruction of phylogenetic

differences by morphometric characteristics (13 relations of Ponto-Caspian gobies (Gobiidae, Perciformes) specimens were investigated): the number of rays in

based on mitochondrial genome variation and some the first dorsal fin, -7 (5-8 singly), the second–16-18,

problems of their taxonomy, J. Ichthyology 53 (6) (2013) anal 8-12 and the gorlap has–6, 16-18 and 11-14 rays, 687-698. (in Russian) [5] V.P. Vasiliev, Evolutionary Karyology of Fishes, Nauka,

respectively. However, the external signs of studied

Moscow, 1985.

goby were similar to bighead goby. Gobies with a [6] V.P. Vasiliev, Chromosome polymorphism in Spicara small set of chromosomes, such as the bighead goby N.

smaris (Pisces, Centracanthidae), Zool. Zhurnal 57 (8) kessleri (2n = 29-30), or Caucasian river goby

(1978) 1276-1278. (in Russian) [7] A. Levan, A. Fredga, A. Sandberg, Nomenclature for

Neogobius platyrostris constructor (2n = 38-42) centromeric position on chromosomes, Hereditas 52

belong to the river forms [14-16]. The studied goby

(1964) 201-220.

lived in the eastern part of the Caspian Sea and it [8] K.A. Grigoryan, Population and Species’ Cytogenetic of represented the separate status of species. The

Ponto-Caspian Gobies (Gobiidae, Perciformes), identification requires further morphological and Avtoreferat kandidat Biological Sciences, Publisher of Moscow State University, Russia, 1992. (in Russian)

biological and karyological studies. [9] A.T. Toktosunov, E.U. Mazik, Ecological Cytogenetic of Moreover, it could be assumed that detected

Tyan-shan Fishes, Institute of Biology of Science Kir karyotype differences of goby (N. Gorlap) from

SSR–issue, Ilim, 1991, p. 188. (in Russian) different biotopes with different level of pollution

[10] E.D. Vasil’eva, V.P. Vasil’ev, Neogobius gorlap Iljin in Berg 1949, the Freshwater Fishes of Europe, J.

which could ascribe to the effect of pollutants, the Wiebelsheim: AULA Verlag 8 (I) (2003) 253-264.

variability of karyotypes by genome destabilization. [11] D.V. Prazdnikov, The Evolution of Karyotype of Certainly, further population-genetic research is

Neogobius Gorlap (Pisces: Perciformes: Gobiidae), in: required [17-19].

Chromosome 2012 Materials of International Conference, Novosibirsk, Russia, 2011.

Acknowledgments

[12] D.V. Prazdnikov, V.P. Vasil’ev, E.D. Vasil’eva, Polymorphism and interpopulation variability of the The authors would like to thank the Research

karyotype in the caspian bighead goby Neogobius gorlap Institute of Biology and Biotechnology Directorate for

(Gobiidae, Perciformes), J. Ichthyology 53 (6) (2013) supporting for the studies and former chief of

459-464. (in Russian)

Department of Mangystau natural resources using and [13] E.D. Vasil’eva, D.V. Prazdnikov, V.P. Vasil’ev, First confirmed occurrence of syrman goby Neogobius syrman regulation m-r Zhanburzhin Edil, Dr. Tech. Sci.

(Gobiidae, Perciformes) in Sasyk Lake of the Black Sea Basin and Karyological Characteristic of Syrman goby

References

and Ginger goby N. Eurycephalus, J. Ichthyology 51 (4) [1] E.D. Vasil’eva, The osteological analysis of some

(2011) 472-479. (in Russian)

Caspian tadpole gobies in terms of systematic of genus [14] V.P. Vasil’ev, K.A. Grigoryan, Broad chromosome Benthophilus (Gobiidae), J. Ichthyology 23 (4) (1983)

polymorphism in the Caucasus river goby, Doklady Akad. 544-556. (in Russian)

Nauk. SSSR 311 (6) (1990) 1509-1511. (in Russian) [2] E.D. Vasil’eva, Skull morphology of the ground goby

[15] K.A. Grigoryan, V.P. Vasil’ev, Karyotypes of five species Gobius melanostomus and the syrman goby G. syrman in

of Ponto-Caspian gobies, J. Ichthyology 32 (4) (1992) relation to their position within the genus Gobius

162-166. (in Russian)

sensu lato, J. Ichthyology 29 (2) (1989) 186-197. (in [16] V.P. Vasil’ev, K.A. Grigoryan, Karyology of the gobiidae, Russian)

J. Ichthyology 32 (5) (1992) 27-40. (in Russian) [3] V.P. Vasil’ev, E.D. Vasil’eva, Karyological evidence of

[17] A.B. Bigaliyev, E.T. Zhanburshyn, R.K. Bigaliyeva, A.R. the separate species status of Neogobius kessleri (Günther)

Ryskulova, R.M. Bilydebayeva, Zh. Rakhmanova, et al., and Neogobius gorlap Iljin (Pisces, Gobiidae), Dokl.

Social - economic development of Kazakhstan in present

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and scientific basic of ecological safety, The Journal Remediation, Ottawa, Ontario, Canada, August 17-19, Science and Education a New Dimension 7 (9) (2013)

2011, p. 283.

211-217. [19] N.Sh. Mamilov, E.B. Kozhabaeva, To morphological [18] A.B. Bigaliyev, N.E. Ishanova, R.K. Bigaliyeva, The

alteration of fish Atherina boyeri in Caspian and Aral Ecology-Genetical Evaluation of Ecosystem Status of

Sea on results of polifactory analysis method, J. of Atyrau Oil-Gas Producing Area, in: Proceedings of the

KazNU, Biological Series 5 (51) (2011) 71-75. (in International Conference of Environmental Pollution and

Russian).

May 2014, Vol. 8, No. 5, pp. 447-460

Journal of Life Sciences, ISSN 1934-7391, USA DAVID PUBLISHING

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

1 2 Reuben Omondi 3 , Andrew W. Yasindi and Adiel M. Magana 1. Kenya Marine & Fisheries Research Institute, Kisumu 40100, Kenya

2. Department of Biological Sciences, Egerton University, Egerton 20115, Kenya 3. Department of Biological Sciences, Chuka University College, Chuka 60400, Kenya

Received: October 16, 2013 / Accepted: May 10, 2014 / Published: May 30, 2014.

Abstract: Diel zooplankton samples were obtained at a 4-m-deep central station on two sampling occasions in January and February, 2010 in Lake Baringo. Sampling was done at 1 m interval every four hours for 24 h from 8:00 am to 04:00 am. Ten litres of lake water was collected by a Van Dorn sampler and sieved through a 50 µm mesh sieve and organisms in the entire sample counted. Concurrently, physico-chemical factors including temperature, pH, conductivity and dissolved oxygen were measured at the same depths in situ. In both sampling months, the temperatures were higher during the day when stratification was observed just below the

1 m depth. This was, however, broken by diurnal winds in the evenings. PH and dissolved oxygen values followed the same trend but conductivity was generally uniform. In contrast to what has been observed in clear water lakes, the densities of Lake Baringo zooplankton were generally higher at the surface waters during the day while during the night the organisms were distributed throughout the lake column, a phenomenon which could be attributed to the high waters turbidity. The Proximity of zooplankton to the euphotic zone during the day provides them with feeding opportunities on phytoplankton.

Key words: Zooplankton, migration, turbid lake.

1. Introduction  planktivorous fishes to spot them. The daily migrations vary from lake to lake and from season to season.

DVM (diel vertical migration) of zooplankton is a Numerous studies on the vertical migration of well studied phenomenon in lentic ecosystems which zooplankton have shown that diel migration in the is believed to be a strategy to reduce the risk of water column is driven largely by responses to light predation [1, 2]. A majority of zooplankton species in [4]. The presences of a thermocline or an oxicline [5], deep lakes undergo diurnal vertical migration in response food concentration [6], and chemical stimuli [7] also to various abiotic and biotic factors. The migration has influence vertical distribution of zooplankton. The been related to the efficient utilization of resources or adaptive significance of this migration is believed to the avoidance of mortality due to predation [3].

be related to the reduction of predation pressure by the Usually, the organisms congregate near the waters visually hunting vertebrate predators [8]. The surface at night and migrate to lower depths during the zooplankton undergo more extensive diurnal vertical day. Ascension enables more abundant food resources migration in clear lakes, where they move to the in the upper strata to be exploited at night, while surface waters at night and remain lower in the water predators can be avoided during the day by descent to column during the day [9]. In contrast, in brown water depths where the light intensity is too low for lakes, the reduced light penetration impairs prey

perception by planktivorous fish thereby releasing Corresponding author: Reuben Omondi, M.Sc., research

large zooplankton species from predation pressure scientist, research field: zooplankton ecology. E-mail:

reubenomondi@yahoo.com. resulting in less extensive migration due to reduced

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

predation threats [10]. Van Dorn water sampler. Ten liters samples from each Some investigations into zooplankton migration in

depth were filtered through a 50 µm sieve and Kenyan clear lakes include those by Worthington,

zooplankton preserved in 4% formalin. In the Ricardo and Mavuti [11, 12] in Lake Naivasha and

laboratory, all the organisms were counted without Worthington, Omondi [13, 14] in Lake Victoria.

sub sampling under a binocular dissecting microscope These studies showed that most of the zooplankters

at  40 magnifications. Zooplankton were identified to tended to concentrate on the upper zones during the

genus and where possible to species level using relevant night and moved to the lower depths during the day.

taxonomic literature. For copepods, identification keys However, some organisms don’t seem to respond to

by Dussart, Defaye were used [16]. The keys by changes and remain at all depths from surface to the

Korovchinsky, Smirnov were used in Cladocera bottom throughout the 24 h regime [13, 14].

identification [17, 18] while Koste, Shiel, and Segers However, no studies on the vertical migration of

were used for the identification of rotifers [19-21]. zooplankton have been carried out in Lake Baringo,

2.3 Data Analysis

which is different from the above studied lakes because of its highly turbid water. Therefore in this

Parametric One-way ANOVA (Analysis of study, the authors determined the migration patterns

Variance) was used to test the differences among the of the zooplankton community in Lake Baringo for

physico-chemical factors and zooplankton abundances comparison with those in the clear water lakes.

on spatial and temporal scales. Pearson correlation analysis was carried out using PAST [22] programme

2. Materials and Methods

to determine the relationship between the

2.1 Study Area environmental variables and species abundance. Lake Baringo, shown in Fig. 1, is a freshwater lake,

3. Results

in the eastern arm of the Great Rift Valley in Kenya. It

is located between latitude 0°30 ′ N and 0°45′ N and longitude 36°00 ′ E and 36°10′ E and lies

3.1 Environmental Factors

In the January of 2010 sampling exercise, the approximately 60 km north of the equator at an

variations in physico-chemical parameters were altitude of 975 m above sea level [15]. The lake has a

shown in Fig. 2. Water temperature was uniform in

the whole water column but increased steadily from catchment of 6,820 km 2 . It has a mean depth of 3 m

surface area of approximately 130 km 2 and a

23 °C to 25 °C at 8:00 am and 12:00 noon, with the deepest point being about 7 m at high water

respectively. In the afternoon there was stratification levels. Diel sampling was carried out C2 (twice at a

with the surface waters reaching 29 °C between noon central sampling station) in the pelagic zone in

and 4:00 pm. At around 6:00 pm there was a

January and February 2010. breakdown of the stratification and temperatures being again uniform in the whole water column with

2.2 Sampling decreasing temperatures from 25 °C at 6:00 pm to

22 °C at 4:00 am. Between 8:00 am and about 10:00 temperature, dissolved oxygen and pH were measured

Physico-chemical parameters including conductivity,

am the pH of the surface waters, above 1 m depth, was in situ using a Surveyor II model hydrolab at each depth

higher than the bottom waters. PH of the lake water before zooplankton samples were taken. The samples

decreased from 8.9 in the surface waters at 8:00 am to were collected from the surface to the bottom at an

8.8 at around 5:00 pm after which there was another interval of 1 m every four hours for 24 h using a 5 L

rise to 8.92 at the surface at 4:00 am. Generally, the

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

Fig. 1 A map of Lake Baringo showing the sampling station (C2).

pH of the surface waters was higher than those at the the water column throughout the 24 h regime. There lower depths.

was, however, a decrease in conductivity from 860 Conductivity of Lake Baringo water during the

µS/cm at 8:00 am to 825 µS/cm at 4:00 am. Dissolved January, 2010 sampling was more or less uniform in

oxygen concentrations were on the other hand

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

h( 26 2 8.84 ept 8.80

8 am 12 Noon

8 pm 12 Mid-night 4 am

8 am 12 Noon

8 pm 12 Mid-night 4 am

Fig. 2 Diurnal variation in (a) temperature, (b) pH, (c) conductivity and (d) dissolved oxygen in Lake Baringo in January 2010.

higher at the surface waters compared to the bottom. uniformly distributed throughout the water column. In The highest concentration of 8 mg/L was attained

the afternoon there was stratification with surface between 12:00 noon and 2:00 pm. The stratification

waters reaching 32 °C while the temperatures of the was broken after 8:00 pm but was followed by another

bottom were 27 °C. After 4 pm, however, it broke after 12:00 mid night.

down the stratification with a decrease in temperature Values of the physical and chemical variables

from 26 °C to 23 °C at 4:00 am. The values of pH during the February 2010 sampling are shown in Fig.

were generally higher during the day with discrete

3. Between 8:00 am and 12:00 noon there was an pH variations within 1 m of surface. The lowest pH of increase in water temperature from 25 °C to 28 °C

8.2 was attained at noon in the surface waters.

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

8 am 12 Noon

8 pm 12 Mid-night 4 am

8 am 12 Noon

8 pm 12 Mid-night 4 am

Fig. 3 Diurnal variation in (a) temperature, (b) pH, (c) conductivity and (d) dissolved oxygen in Lake Baringo in February 2010.

Conductivity values were higher at the surface waters

a clear oxycline between 12:00 noon and 8:00 pm than bottom waters and the values decreased from

followed by uniform levels of dissolved oxygen at all 8:00 am to the end of sampling time. Dissolved

depths. The highest value of dissolved oxygen 9.0 oxygen values were higher in surface waters with an

mg/L was recorded at 4:00 pm at the surface waters increase from 5.0 mg/L at 8:00 am to 9 mg/L at 4:00

while the lowest 3.5 mg/L was found at the bottom of pm followed by a gradual decrease to 5.0 mg/L at 3:00

the lake from 10:00 pm to about 5:00 am. am. At 12:00 noon dissolved oxygen was evenly

ANOVA (Analysis of Variance) showed that there distributed in the water column after which there was

was no significant difference in the mean values of pH

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

(F = 1.68; P = 0.20) and dissolved oxygen (F = 0.72; P (F = 10.06; P < 0.05) between different times of = 0.40) between the two months sampled. There were,

sampling. There was, however, no significant however, significant differences in the mean difference in the mean of pH (F = 1.5; P = 0.21) and temperature (F = 4.86; P = 0.03) and conductivity (F =

conductivity (F = 2.37; P > 0.05). The three groups of 148.0; P < 0.05) between the two months as shown in

sampling times with similar temperatures were 12:00 Table 1. With reference to depth, there were no

noon and 4:00 pm, 8:00 pm and 12:00 midnight, 4:00 significant differences in the mean values of am and 8:00 am while groups of sampling times with temperature (F = 1.5; P = 0.22), pH (F = 1.11; P = 0.36)

similar dissolved oxygen were 12:00 mid night, 4.00 and conductivity (F = 0.24; P = 0.91). There was a

am and 8.00 am and 12.00 noon, 4.00 pm and 8.00 pm. significant difference in the mean values of dissolved

3.2 Zooplankton Diurnal Distribution oxygen concentrations between the different depths (F

= 8.01; P < 0.05). Further analysis using Tukey test The zooplankton species encountered in the study revealed that three groups of depths with similar mean

included the three major groups Copepod, Cladocera dissolved oxygen concentration were 0 m and 1 m, 2 m

and Rotifer. During the January sampling these were and 3 m, 4 m. ANOVA further showed that there

dominated by nauplii, D. barbata and K. tropica, significant differences in the mean values of respectively while in February rotifers were

temperature (F = 28.9; P < 0.05) and dissolved oxygen dominated by F. opoliensis as shown in Table 2.

Table 1 Statistics (F, P) of variation of physic-chemical parameters in relation to month, depth and time of sampling.

Month Depth Time Temperature

2.37, > 0.05 Dissolved oxygen

Table 2 Mean abundance (ind/L) and percentage contribution to total density of the different species of zooplankton recorded in the two DVM sampling dates January and February 2010.

January 2010

February 2010

Mean S.E. (%)

Mean S.E. (%)

Copepoda

Cyclopoida 63.57 7.22 13.16 39.08 5.79 17.45 Nauplii

Cladocera

D. excisum 3.30 0.52 0.68 4.94 0.53 2.20 M. micrura

0.52 0.14 0.11 1.81 0.29 0.81 C. cornuta

2.98 0.33 0.62 5.90 0.38 2.63 D. barbata

6.51 0.52 1.35 7.95 0.55 3.55 M. spinosa

Rotifera

B. angularis 0.08 0.03 0.02 0.27 0.07 0.12 B. calyciflorus

1.47 0.29 0.30 1.81 0.49 0.81 F. opoliensis

8.22 0.88 1.70 22.87 3.28 10.21 K. tropica

17.04 2.37 7.61 Hexarthra sp.

0.16 0.06 0.03 7.53 4.65 3.36 Polyarthra sp.

0.74 0.27 0.15 1.81 0.33 0.81 Lecane spp.

0.01 0.01 0.00 0.50 0.43 0.22 Asplanchna sp.

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

Rotifera was the most species group with 8 species high proportion in the surface waters during the day. while Cladocera had 5 species. The same species of

The highest proportion 28% at the surface was zooplankton were recorded in both months, except

recorded at 12:00 noon while the highest proportion at Asplanchna sp. which was not found in January

the bottom 28% was recorded at 4:00 am as shown in samples. During the period of sampling, no carangids

Fig. 5. A considerable proportion of the cladocerans were recorded in the samples.

was found at the bottom of the lake throughout the In January 2010 DVM sampling the major groups

sampling regime with the least proportion of 13% at of zooplankton were Copepoda, Cladocera and 4:00 pm. Rotifera. They showed similar distribution patterns in

Rotifers presented the most discrete pattern of the water column with higher proportions of the

distribution along the water column in Lake Baringo. organisms occurring in the upper 2 m of the column as

On day break at 8:00 am up to 4:00 pm the highest appears in Fig. 4. The highest proportions of copepods

proportions of rotifers were found at the surface were at the surface at 8.00 am and 12.00 noon with a

waters with proportions of 37%, 36% and 34%, proportion of 27% and 32%, respectively. After 4.00

respectively as shown in Fig. 6. From 8:00 pm there pm the organisms tended to move downwards with a

was a steady movement of the organism towards the peak of 27% at 3 m at 4.00 am afterwards followed by

bottom. The highest proportion 35% of organisms at upward migration towards the surface.

4:00 am was at the 3 m. Between 4:00 pm and 8:00 Unlike Copepoda, Cladocera was fairly well

pm there were no rotifers recorded at the bottom of distributed in the water column but with relatively

the lake.

th -4 p

De 0

Relative abundance

Fig. 4 Vertical distribution (in relative abundance) from surface to 4 m depth of Copepoda in Lake Baringo in January 2010. Each kite represents 100%.

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

th -4 p

De 0

Relative abundance

Fig. 5 Vertical distribution (in relative abundance) from surface to 4 m depth of Cladocera in Lake Baringo in January 2010. Each kite represents 100%.

p th

De 0

Relative abundance

Fig. 6 Vertical distribution (in relative abundance) from surface to 4 m depth of Rotifera in Lake Baringo in January 2010. Each kite represents 100%.

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

The three major groups of zooplankton, Copepod shown in Fig. 8. At 8:00 am the highest proportion and Rotifer had similar vertical distribution pattern

(27%) of cladocerans was found at 1 m depth over a 24-hour period. At 8:00 am most copepods

followed by 4 m depth with 20% while the least (13%) (31%) were found at 1 m depth after which there

was recorded at the surface. At 12 noon some seemed to be an upward movement of the organisms

organisms moved to the surface (28%) while others as depicted in Fig. 7. At noon and 4:00 pm the

descended to the bottom of the lake (27%). At 4:00 organisms were concentrated in the two upper layers

pm, there was a general movement of the cladocerans of the water (66% and 72%, respectively) after which

towards the bottom where the highest proportion of the organisms moved downward forming a relatively

32% was attained at 4 am.

homogenous distribution at all depths. During day Rotifers showed a relatively similar pattern of light between 8:00 am and 4:00 pm more copepods

vertical distribution to that of copepods as shown in were found at the surface waters than the bottom

Fig. 9. After day break there was a clear migration of waters while during the night most of the organisms

rotifers towards the surface waters of the lake where a occurred at the mid waters. The highest (50%)

maximum proportion of 50% was reached at noon. proportion of copepods was reduced at the surface

After 12:00 noon there was downward migration to waters at 12:00 noon.

the lower depths. The highest proportion 28% of Cladocerans were fairly distributed at all depths

rotifers at the bottom was recorded at 4 am. with considerable proportion (> 18%) at the bottom of

ANOVA (Analysis of Variance) showed that total the lake throughout the 24-h sampling period as

zooplankton abundance varied significantly between

th -4 p

De 0

Relative abundance

Fig. 7 Vertical distribution (in relative abundance) from surface to 4 m depth of Copepoda in Lake Baringo in February 2010. Each kite represents 100%.

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

p th

De 0

Relative abundance

Fig. 8 Vertical distribution (in relative abundance) from surface to 4 m depth of Cladocera in Lake Baringo in February 2010.

Each kite represents 100%.

th -4 p

De 0

Relative abundance

Fig. 9 Vertical distribution (in relative abundance) from surface to 4 m depth of Rotifera in Lake Baringo in February 2010. Each kite represents 100%.

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

the two months (F = 13.13; P < 0.05) and depth (F = Cladocera (r = -0.159). PH was negatively correlated 8.0; P < 0.05) but not between the different times (F =

with all the three major groups of zooplankton but 0.31; P = 0.90). Non parametric Mann-Whitney U test

only significantly with Cladocera. Conductivity had a further showed that depths 0, 1, 2 and 3 did not vary

significant correlation with all the groups of significantly from one another in terms of zooplankton

zooplankton, positively with Copepoda (r = 0.124) abundance but depth 4 m varied significantly from all

and Rotifera (r = 0.259) but was negatively correlated the other depths.

with Cladocera (r = -0.314). Dissolved oxygen was Data on total zooplankton densities indicated that

also positively significantly correlated with Copepoda during the day most of the organisms occurred in the

(r = 0.563) and Rotifera (r = 0.331) but was negatively, surface waters while during the dark the organisms

but insignificantly, correlated with Cladocera (r = were more or less distributed uniformly in the water

column. Further, by merging of zooplankton densities

4. Discussion

during day (8:00 am to 4:00 pm) and night (8:00 pm to 4:00 am) phases revealed that zooplankton densities

The temporary thermal stratification exhibited in were, generally, higher at the surface waters during

the lake may have been caused by the absorbance of the day than those during the night when the

solar energy by suspended particles in the lake which organisms occurred at higher densities towards the

accentuated the increase in temperature of the surface bottom of the lake as illustrated in Fig. 10.

waters during the day between noon and 4 am. This was broken down in the evening with the surface

3.3 Correlation between Environmental Variables and cooling and wind mixing. This phenomenon of

Zooplankton Distribution thermal stratification during the day and mixing at

The correlated relationships between some night had earlier been reported in the lake by Beadle environmental variables and the distribution of major

[23]. High pH values at the surface waters during the zooplankton groups Copepoda, Cladocera and day were attributed to the use of carbon dioxide Rotifera are shown in Table 3. Temperature was

during photosynthesis process. The opposite was positively correlated with Copepoda (r = 0.48) and

realized during the night, more so, at the bottom of the Rotifera (r = 0.224) but negatively correlated with

lake due to respiration process. Dissolved oxygen

Total abundance (Ind.l -1 ) Total abundance (Ind.l -1 )

h( pt 2 e

e pth (

4 Day

Night

Day Night

Fig. 10 Total abundance of zooplankton in the day and night periods of sampling in January and February 2010.

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

Table 3 Correlation matrix between major groups of zooplankton Copepoda, Cladocera, Rotifera and environmental variables; temperature, pH, conductivity and DO (dissolved oxygen).

Copepoda Cladocera Rotifera Temperature 0.480* -0.159 0.224

pH -0.001 -0.370* -0.248 Conductivity 0.124* -0.314** 0.259** DO 0.563** -0.189 0.331*

Significant at P < 0.05; ** significant at P < 0.001.

concentration distribution in the lake can be explained other physical and biological factors, seems to be with the position of the dominant phytoplankton,

important in initiating, controlling and orientating Microcystis aeruginosa, in the lake [24, 25]. Ganf

zooplankton migration. The organisms move to the found that the buoyant colonies of the phytoplankton

surface for food and migrate to colder temperatures moved to the surface during the day after a period of

where metabolism rates are reduced. The higher dark incubation in Lake George, a similar lake to Lake

densities at the surface during the day could be due to Baringo [26]. This explains the rise in the behavioral changes coinciding with decrease in concentration of dissolved oxygen towards mid-day.

predation pressures from planktivorous fish due to However, this is limited by the high turbid waters.

turbidity. There is presumably no advantage to strong From this study, the relatively homogenous migration during the day since the selective forces of environmental variables could not be used to explain

predation are practically absent. This is the way the distribution of zooplankton in Lake Baringo.

cladocerans avoid predation due to their larger size. Difference in the mean abundance of zooplankton

Similar observation was made in a shallow, in the two sampling dates could have been occasioned

polymictic and eutrophic Lake Vela where most taxa by the difference in environmental factors between the

were homogenously distributed in the water column in two dates. This was supported by statistics which

the turbid phase [27]. Dumont, etc. stressed that in the showed that there was significant correlation in

absence of factors like visual predators and light temperature and conductivity in relation to months.

damage, it would be advantageous to zooplankton not The notable change between the two months was

to descend to the lower depths as this would allow realized in conductivity values which decreased from

them to feed continuously in the euphotic zone [28].

a mean of 844.5 to 830.1 µS/cm, in January and Indeed this seems to be the case in Lake Baringo February 2010, respectively. The population explosion

where visual predation and light damage could have of rotifer K. tropica in January, with 48% of total

been reduced by the turbid waters.

zooplankton, could be explained by such changes. The In our study, migration behavior was different relative higher densities of littoral cladoceran species

between the different zooplankton groups with the Lecane spp in February could be attributed to

tendency to assemble at the surface waters being development of a cyanobacterial bloom.

shown more by copepods and rotifers than in Contrary to the expected maximum zooplankton

cladocerans. This can be attributed to the different concentration near the surface at night and daytime

response to the stimuli by the different species within migration to the lower depths [2], results of this study

the groups [29]. It demonstrated that individual indicate the complete opposite of the same. In our

zooplankton changed their migrating behavior study, zooplankton generally migrated to the surface

depending on the amount of accumulated energy [30]. waters during the day and descended to the mid and

It further showed that the internal condition affected bottom waters during the night. Light, modified by

vertical distribution of zooplankton, which explains

Diel Vertical Distribution of Zooplankton in Lake Baringo, Kenya

variation between individuals of same species. Acknowledgments

Convergence of organisms in the surface waters, in The study was funded by NACOSTI (National my study, during the day puts the organisms in a Council of Science and Technology, Kenya). The habitat with high oxygen concentration and available authors are also grateful to Dick who helped in food arising from photosynthesis. The choice of sampling and analysis and Benjamin who piloted us in optimal habitat by different groups of zooplankton the rough waters of Lake Baringo during the sampling was, however, a function of other factors such as food

exercises.

availability and response to environmental factors. The low proportion of rotifers at the bottom at most of

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May 2014, Vol. 8, No. 5, pp. 461-472

Journal of Life Sciences, ISSN 1934-7391, USA

DAVID PUBLISHING

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

1 1 2 2 2 Abdel Dozic 2 , Vahida Selimbasic , Amira Cipurkovic , Aida Crnkic , Zorica Hodzic and Ilvana Trumic 1. Department of Environmental Protection, Faculty of Technology, University of Tuzla, Tuzla 75000, Bosnia and Herzegovina

2. Department of Chemistry, Faculty of Science, University of Tuzla, Tuzla 75000, Bosnia and Herzegovina

Received: February 11, 2014 / Accepted: April 22, 2014 / Published: May 30, 2014.

Abstract: DD (Dust deposition) was monitored over a 6-month period (April to September, 2011) at four sites located in villages near CADDII (coal ash disposal site Divkovici II), one inside recultivated CADDI (coal ash disposal site Divkovici I) and at one in the middle of forest barrier as control site. The main aim of this paper is to perform monitoring of air dust pollution in the area by measuring of dust deposition, different metals associated with it, and probable adverse effects on human health. Concentrations of metals were measured by using Perkin-Elmer model Inductively Coupled Plasma and statistically evaluated with SPSS 17.0 statistical program. There was a correlation between some metals (Mn, Mo and Pb) and DD distribution. The daily limit values for

concentration of DD proposed by national ″Regulations on air quality″ (200 mg/m 2 d average annual value and 350 mg/m 2 d high value) exceed at three measuring sites. The average maximum content of DD was 684.8 mg/m 2 d downwind of CADDII, and the average minimum was 46.8 mg/m 2 d at measuring site F. Concentrations of pollutants hazardous to the environment as Ni, Cr, Cu, Mo, Mn and Pb vary from one site to another.

Key words: Dust deposition, coal ash disposal site, heavy metals, environment, power plant, atmospheric pollution.

1. Introduction  used and the conditions in which combustion occurs. Other problematic properties of coal ash include

The production and consumption of energy places a extreme pH, increased concentrations of soluble salts, wide range of pressures on the environment and on and physical particle characteristics that make them public health. Energy production from coal affects the easily dispersed by wind. The coal ash disposal sites environment in several ways, particularly through the affect land, air, water, people and animals both emission of harmful pollutants during combustion and

directly and indirectly.

disposal of coal ash. Coal ash has different physical The late 1990s, residents near CAD sites reported and chemical properties depending on the environmental incidences, such as snow turning geochemical properties of the coal being used and ‘black’ and rain leaving a yellowish residue. Local how that coal is burned. Combustion by-products citizens perceive the CAD sites creating a negative include emissions to air, thermal pollution and CCR image of their communities. The interviews with (coal combustion residues), consisting of: BA (bottom local residents illustrated that dust clouds reach their ash), FA (fly ash), FGD (flue gas desulphurization) peak during the spring and summer windy days, waste and boiler slag. These wastes may contain high which affect their lives and can make them feel like concentration of potentially hazardous elements prisoners in their houses. The lack of existing wind depending on the origin and properties of the coal barriers and sparse vegetation, natural characteristic

of CAD site (slope to Spreca valley) dust can travel Corresponding author: Abdel Dozic, Ph.D., assistant

several kilometers before it deposits again. Coal ash professor, research field: environmental protection. E-mail:

abdel.dozic@untz.ba. dust is associated with human health problems,

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

particularly respiratory infections and negative cm 2 /g) and thus they can be dispersed over several impacts on plant and animal health. The EPA has

kilometers by the wind. This is particularly severe found that living next to a coal ash disposal site can

during the hot summer months, when there is little increase risk of cancer or other diseases. According to

rainfall and winds are of higher magnitude. Ash the EPA’s peer-reviewed “Human and Ecological

particles thus affect the surrounding biosphere and Risk Assessment for Coal Combustion Wastes,”

life of local people in the settlements around the people in those circumstances have as much as a 1 in

disposal sites. Dust from ash disposal site consists of

50 chance of getting cancer from drinking water many kinds of particles, ranging from submicron to contaminated by arsenic, one of the most common

several hundreds of microns in diameter with various and dangerous pollutants in coal ash [1]. According to

densities and chemical compositions. Dust deposition the WHO (World Health Organization), 4-8% of

is the carrier of heavy metals and various organic deaths occurring annually in the world are related to

compounds in the atmosphere, according to their air pollution associated with anthropogenic activities

physical and chemical properties, these pollutants are [2, 3]. The TEP (thermo-electric plant) at Tuzla is

partitioned between particulate, liquid, and vapour currently the company’s largest energy production

phases and are subsequently transported to the Earth’s unit with a net production of 3,903.9 GWh in 2011,

surface through dry and wet deposition [5]. In dust which accounts for 53% of the total energy produced

deposition is presented all substances in solid, liquid in BiH [4]. The power plant is fed with raw coal

and gaseous state that are not part of the air, and (75% lignite and 25% black coal) excavated from

deposit itself by the gravity or rinsing rainfalls from mines near Tuzla including the open-cast and

the atmosphere to the ground. Depending of type of underground mines of lignite and black coal in the

adsorbed compounds and chemical composition of nearby municipalities Lukavac, Živinice and DD, the impact of this type of dust may be more or Banovi

ći. TEP produces between 0.4 and 0.9 m 3 of less negative. Except that DD impairs the quality of ash per MWh; at maximum production this would

air, dust constituents pollutants reach and pollute

water, groundwater and soil thus indirectly leads to transportation of bottom ash from the furnaces to the

amounts to approximately 1.7 million m 3 /year. The

the endangerment of the environment. Dust disposal sites is by hydraulic suspension system

deposition leaves inhibit the normal transpiration and mixing water to the solid material in an 11:1 ratio;

photosynthesis of plants; also moisture in the that consumes 37 m 3 per minute of water. These

atmosphere causes their spread partially and get into residues are pumped into settlement ponds in natural

the plant through epithelia. Soil contamination by valleys bordered by dams or backfilled in open cast

heavy metal such as As, B, Cd, Co, Cr, Cu, Hg, coal mine. Five CAD (coal ash disposal) sites,

Mn, Ni and Pb is a matter of great concern because covering an area of approximately 170 ha, have been

of possible influence on the food chain. Recent established around Tuzla: Dreznik, Plane, Divkovici I,

studies, by several researchers, have shown that Divkovici II and Jezero. The disposal uses up huge

deposition, in both urban and rural settings [6-9], can amounts of space and fundamentally alters existing

contribute significantly to soil contamination with landscapes characteristics.

heavy metals.

As the coarse ashes and fine particles settle and In this paper, by comparison of the environment water drains away and evaporate, ash particulates

conditions in the vicinity of CADDII, we attempt to become airborne. These particulates have a small

emphasize the air quality in the surroundings on this specific mass and large specific surface (1500 to 3500

site. The scope of this paper is to provide the results of

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

measurements of the total deposited dust and those elements that are characteristic for coal ash or are particularly ecotoxic: As, B, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Se, V and Zn. The procedure employed for this survey was Standard Method VDI 2119 (Measurement of Dust fall, Determination of Dust fall using Bergerhoff Instrument (Standard Method) German Institute). This measuring method mean continuously measuring DD throughout the year, when establishing the annual trend DD emission concentration, and the measurement was done for a period of six months, since they are intentionally aimed at proving presence of heavy metals in collected dust. The movement and fate as well as deposition rate depends on the natural CAD site characteristics, physical nature of dust and metrological conditions of the surrounding area. Air quality for total dust deposition Pb, Cd, Zn in the study area was evaluated by comparing the mean monthly values with limit values proposed by the Regulations on air quality [10] and German standards [11]. The dust deposition rate was measured by positioning six Bergerhoff dust deposit gauges at strategic locations near the CADDII for a period of 30 ± days. The selection of sampling point locations was completed after consideration of the requirements of VDI 2119 with respect to the location of the samplers relative to buildings and other obstructions, height above ground and sample collection and analysis procedures. Sites were chosen to provide data on dust flux and to answer specific questions about the relations of possible wind erosion of CADDII surface to the total DD emission regarding to the distance from source, climate influence, wind direction, etc. Fall period in samples of DD collected during the spring, summer and autumn was period of six months. After the exposure period was complete, the gauges were removed from the site; the dust deposits in each gauge were determined gravimetrically and expressed

as a dust deposition rate in mg/m 2 /day in accordance

with the relevant standards.

2. Materials and Methods

2.1 Chemicals, Reagents and Glassware All chemicals and reagents were of analytical grade

and were purchased from: (Himedia-India: PAN indicator, Kalcein, Methyl thymol blue, Bromophenol blue, methyl orange), (Riedel de Haën: Barium chloride), (Merck-Alkaloid: Manganese (II) sulfate tetrahydrate), (Lachema-Czech Republic: acetic acid, ammonia), (Semikem-Sarajevo: triethanolamin, potassium hydroxide, hydrogen peroxide, phosphorous acid, sulfuric acid, potassium permanganate), (Zorka-Shabac: sulfosalicil acid, komplexon III, ammonium nitrate, ammonium chloride), (Penta: sodium carbonate, potassium carbonate, chloric acid, nitric acid), (Kemika-Zagreb: ammonium acetate, ammonium thiosulfate, stannous chloride dihydrat, mercury (II) chloride, ammonium oxalate, ammonium hydrogen phosphate, potassium dichromate, silver nitrate). All standards were prepared from reagent grade chemicals (Perkin Elmer Pure-Atomic Spectroscopy Standard). All glassware was rinsed successively with detergent and distilled water three times prior to use.

2.2 Sampling The selections of the sampling sites were based on

several factors including ease of access, safety, minimizing potential for sample contamination, and representativeness. Deposited dust samples were taken from 6 different stations in 6 months (1st April to 30th September, 2011), and could not be taken from October to March because of the rain, snow and climatic conditions. Coordinates were determined by GPS (Global Positioning System). The procedure for dust sampling was Standard Method VDI 2119–‘Measurement of Dust fall, Determination of Dust fall using Bergerhoff Instrument (Standard Method) German Institute’. Gauges were installed in consideration of requirements relating to location of the gauges relative to buildings, trees and other

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

obstructions, height above ground and sample statistical program. Data were statistically ANOVA collection and analysis procedures. Dust samplers,

(analyzed by one factor analysis of variance) followed filled with 250 cm 3 of 10% isopropyl alcohol as

by Tukey HSD post test for multiple comparisons. protection of insects, were used for the monitoring of

Pearson correlation coefficient (r) was used to dust deposition at all locations at an approximate

calculate the degree of linear association between height of 1.5 m above ground. The samples were

different locations and to determine the relative continuously collected monthly for 6 months.

association among and between metals and dust

2.2.1 Determination of Dust Deposition deposition. A two-tailed probability less than 0.05 (< Collected samples were washed up and

0.05) was considered to be significant. vacuum-filtered through Whatman white filter paper,

3. Results and Discussion

and then evaporated at 105 °C until they reached constant weight. Total dust content determined

3.1 Total Content of Dust Deposit gravimetrically after drying. Dried samples were

Heavy metals enter into the environment in a stored in polyethylene bags in desiccators to avoid

variety of ways; dust deposition is of particular contamination throughout the analyses. Results are

concern. Once introduced into the atmosphere,

expressed as a dust deposited rate in mg/m 2 /day in

pollutants adsorbed on dust particle are able to travel accordance with the relevant standard.

long distances from their original source, transferring

2.2.2 Determination of Heavy Metals contaminants to ecosystems and contaminate Dried samples were digested in Teflon cuvette with

agricultural areas. Limit values for dust deposition and

12 mL (concentrated 1/3 HNO 3 + 2/3 HCl) during 16

metal concentrations in it defined by the directives of

h at room temperature. After digesting, extracted “Regulation on limit values of air quality” are showed samples were transferred into glass bottles and diluted

in Table 1. Limit values are those from which are not to a final volume of 50 mL using double distilled

expected to have harmful effect on the environment water. The filtrate was examined for the concentration

but if exposure is the risk.

of metals: As, B, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Monitoring stations are located so that they provide Se, V and Zn by Inductively Coupled Plasma-Optical

data on areas representing typical or maximum

Emission Spectrometer, ICP-OES OPTIMA 2100 DV, concentrations that the population in the area is likely

Perkin-Elmer, with standard of 100 mg/dm 3 for metals.

to be exposed to, directly or indirectly. Six monitoring

sites were selected. Distance between measuring sites presented are average of three replications.

The results were expressed in mg/dm 3 of filtrate. Data

is about 470-2900 m. All the six locations are as: (A)

2.2.3 Ambient Air Quality Monitoring settlement Divkovici–740 m away in south east side, Monitoring meteorological variables and their

(B) settlement Plane–620 m away south west side, (C) significance is important in monitoring air quality.

recultivated coal ash disposal site Plane–780 m away Temperature, relative humidity, wind speed and wind

in south east side, (D) partially recultivated coal ash direction are currently being recorded at an existing

disposal site Divkovici–260 m away south east side, air quality monitoring location on the metrological

(E) settlement Pogorioci–290 m away north and (F) station Bukinje about 2 km distance from coal ash

control monitoring site, field in the middle of forest disposal site Divkovici II. Meteorological parameters

barrier–490 m away west side from coal ash disposal provide correct data for the interpretation of results.

site Divkovici II. Topographically of the study area is

2.2.4 Statistical Analysis shown in Fig. 1, positions of monitoring locations All analysis was performed using the SPSS 17.0

with Gauss-Krüger's coordinate are given in Table 2.

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

Table 1 Locations of measurements sites for dust deposition.

Pollution matter

High level (mg/m 2 d) Dust deposition-total

Period of sampling

The average annual level (mg/m 2 d)

one month

Pb in dust deposition

one month

Cd in dust deposition

350 * Zn in dust deposition

one month

one month

Tl in dust deposition

one month

*applies on the month in the year with the highest value of deposition.

Table 2 Locations of measurements sites for dust deposition.

No. Measurement site x-axis

y-axis height

Fig. 1 Distribution of monitoring sites in the area of

Dust deposition concentrations and distributions at

different monitoring sites are shown graphically in Figs.

Measurement

01.04. ‐30.04.2011. point 02.05. ‐30.05.2011. 01.06. ‐30.06.2011.

2 and 3. During the research period, the daily mean of

2 average temperature in spring ranged between 9.39 °C

Fig. 2 Mean dust deposition concentrations (mg/m day) at

(April) and 13.29 °C (May), in summer 21.66 °C different locations of CADDII.

(June), 22.21 °C (July) and 18.75 °C (August) and in exceeded limit values. Total mass DD at all locations autumn 11.92 °C (September). The prevailing wind

have been arraigned in descending order as: C > B > direction is from the north east (average velocity 0.97

A > D > E > F. Heterogeneous variations in the m/s). Low or zero wind conditions occurr regularly

concentrations of heavy metals prompted us to

more than 45% of time; relative humidity is 88.15%. transform the data DD by using the log 10 to make Calm conditions, light and variable wind velocity are

them homogenous. The transformed data are then likely to cause very high localized concentrations of

submitted to statistical analysis such as ANOVA

pollutants. In Fig. 2, it is obvious that the environment (analysis of variance) and correlation. Equality of in sampling sites A, B and D is polluted and mean differences in DD concentrations of different

total depositions at sampling sites A, B, C and D were locations has been carried out by one-way ANOVA.

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

quality for observed area. During the period of observation the highest DD concentration was in April

(684.8 mg/m 2 d) at location C, when the north wind prevailed with average wind velocity of 0.95 m/s and the temperatures were low. In general, changed in meterological parameters in CADDII can be associated with high degree of monthly variability in DD concentrations. Coal ash disposal site Divkovici II is situated in the narrow valley bordered from east and west with wooded hills. This valley is in slope toward much wide Jala valley. In autumn, winter and spring atmospheric conditions favor the accumulation of pollutants in the valleys, in a phenomenon known as air mass stagnation [12, 13]. The prevailing wind in spring is predominantly from the north-east during hot and windy days when surface water from CADDII away and evaporates, ash particulates become

Fig. 3 Distribution of dust deposition at different locations

airborne they can be dispersed over several kilometers

of CADDII area during six months.

by the very low wind velocity. This information Table 3. Significant (P < 0.05) difference is observed

suggests that the air tend to move towards Jala valley between locations (F = 4.057). A pair wise comparison

but first must circulating downhill through valley with between locations was done by Tukey post hoc test

CADDII, on this way wind raising and moving ash and showed in Table 4 to know which pair differed in

particles toward settlements Divkovici and Plane. As the mean level. Mean concentrations of DD at

per ambient air quality standard in Federation of settlement Plane (monitoring site B) is significantly (P

Bosnia and Herzegovina, the annual average value for < 0.01) higher and different from other locations,

dust deposition is 200 mg/m 2 /day, while mean-year while mean DD in rest of the locations are not

total dust deposition tolerance level is much higher, significantly (P > 0.05) different, i.e. nearly equal, 2 350 mg/m /day. The average values of DD at

except between settlement Divkovici and Pogorioci, measuring sites A, B and C are higher than limit settlement Plane and Pogorioci.

values proposed by Bosnian and German standards.

Fluctuations at measurement points of DD The remaining measuring sites D, E and F showed concentrations can be observed. Mean DD lower mean values.

concentrations at location C (296.32 mg/m 2 d), is

3.2 Concentrations and Distribution of Metals in Dust found to be maximum, while the location F registered

2 Deposition

the minimum (67.45 mg/m d). However, DD concentrations were clearly higher at locations A

Dust deposition and corresponding metal

concentrations at different locations are summarized mg/m 2 d) compared to concentrations at locations D

(206.13 mg/m 2 d), B (281.93 mg/m 2 d) and C (296.32

in Table 5 and are shown graphically in Figs. 4 and 5.

Total mass of all the metals in each location and total mg/m 2 d). This suggests that distance is not the only

(140.22 mg/m 2 d), E (125.66 mg/m 2 d) and F (67.45

mass of each metal at all the locations have been factor to be taken into account when evaluating air

arranged in descending order as: Metals: C > B > A >

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

Table 3 Analysis of variance summary–dust deposition.

Source of variation

F Sig. Between groups

Sum of Squares DF Mean square

5 5.689 4.057 0.012 Within groups

Table 4 Comparison of dust deposition by Tukey test (DF = 18).

Comparisons Significance

Settlement Plane

ns

CAD site "Plane"

ns

Settlement Divkovici

CAD site "Divkovici I"

ns

Settlement Pogorioci

Control measuring site

CAD site "Plane"

ns

Settlement Plane

CAD site"Divkovici I"

ns

Settlement Pogorioci

Control measuring site

CAD site "Divkovici I"

CAD site "Plane"

Settlement Pogorioci

Control measuring site

CAD site "Divkovi

ći I" ns

Settlement Pogorioci

Control measuring site

Settlement Pogorioci

Control measuring site

Ns: not significant (P > 0.05); * significant (P < 0.01).

Table 5 Dust deposition and metal concentrations (mg/m 2 d).

A B C D E F Total metal DD 206.13 281.93 296.32 140.22 125.67 67.45 As 0.003 0.002 0.002 0.001 0.002 0.001 0.011

B 0.019 0.020 0.047 0.023 0.014 0.010 0.133 Cd 0.004 0.005 0.005 0.004 0.004 0.004 0.026

Co 0.035 0.048 0.053 0.026 0.016 0.023 0.201 Cr

0.671 0.855 0.735 0.420 0.750 0.585 4.016 Cu

0.954 1.488 1.200 1.359 1.024 0.911 6.936 Hg 0.028 0.019 0.016 0.014 0.014 0.015 0.106

Mn 2.450 3.121 2.880 1.675 0.822 0.450 11.39 Mo

6.771 6.390 7.996 5.553 4.045 4.820 35.57 Ni 3.450 4.080 2.600 3.885 1.325 2.433 17.77 Pb

0.136 0.098 0.159 0.082 0.055 0.061 0.591 Se 0.021 0.035 0.048 0.018 0.062 0.016 0.200 V 0.250 0.143 0.090 0.077 0.041 0.076 0.677 Zn

2.460 1.202 1.664 1.851 1.990 0.768 9.935 Total metal

D > E > F. Metal: Mo > Ni > Mn > Zn > Cu > Cr > V > 2 mg/m /day) at measuring site was the highest and the Pb > Co > Se > B > Hg > Cd > As.

concentration of As (0.001 mg/m 2 /day) at measuring In the light of value of DD and mass of metals, it

site D and F was the least. Correlation of DD with was observed that measuring site C was the most

metals and intercorrelation among metals are shown in polluted and F was the least polluted area near CADII.

Table 6. Correlation of DD with Mn (r = 0.952, P < Total concentration of Mo is the highest and as 0.01), Mo (0.866, P < 0.05) i Pb (0.878, P < 0.05) is

lowest value. Mean concentration of Mo (7.996 found to be positive and significant (Table 6). These

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

Fig. 4 Concentration of B, Cr, Cu, Mn, Mo, Ni, V and Zn Fig. 5 Concentration of As, Cd, Co, Hg, Pb and Se (ppm) (ppm) in dust deposition.

in dust deposition.

Table 6 Correlation matrix.

As B Cd Co Cr Cu Hg Mn Mo Ni Pb Se V Zn DD As 1.000

B 0.167 1.000 Cd 0.171 0.675 1.000

Co 0.032 -0.100 -0.024 1.000 Cr 0.589 0.140 0.643 0.400 1.000 Cu -0.182 0.346 0.625 -0.600 0.134 1.000

Hg 0.821* -0.050 -0.024 -0.487 0.245 -0.211 1.000 Mn 0.545 0.644 0.775 -0.305 0.471 0.615 0.480 1.000 Mo 0.435 0.824* 0.688 -0.510 0.240 0.313 0.446 0.859* 1.000

Ni 0.024 0.122 0.281 -0.736 -0.169 0.650 0.397 0.617 0.472 1.000 Pb 0.585 0.907 0.559 -0.426 0.245 0.134 0.541 0.902 0.968** 0.331 1.000 Se 0.291 0.301 0.340 0.888 0.629 0.048 -0.304 0.089 -0.063 -0.634 0.021 1.000

V 0.744 -0.013 0.038 -0.601 0.187 -0.086 0.985** 0.550 0.510 0.546 0.568 -0.409 1.000 Zn 0.665 0.177 -0.288 0.117 -0.065 -0.143 0.503 0.245 0.180 -0.005 0.373 0.205 0.438 1.000 DD 0.756 0.615 0.668 -0.265 0.542 0.355 0.651 0.952** 0.866* 0.453 0.878* 0.153 0.677 0.401 1.000

*Correlation is significant at the 0.05 level; **Correlation is significant at the 0.01 level.

indicate the linear dependence of metals in DD. In volatile elements with a low boiling point and are other words, increase or decrease in the concentrations

largely associated with fine particles, fly ash and of DD may also increase or decrease the electro filter dust but in this case they were found in concentrations of Mn, Mo i Pb.

ash in CADII and in dust deposit. Metals such as Pb, Correlation of As with Hg (r = 0.821, P < 0.05), B

Cd and Zn can be adsorbed on the surface of with Mo (r = 0.824, P < 0.05), Hg with V (r = 0.985,

particulate matter to make it potentially dangerous P < 0.01), Mn with Mo (r = 0.859, P < 0.05) and Mo

dust for living species. The concentration of Zn in DD with Pb (r = 0.968, P < 0.01) is found to be positive

is over the limit value of 0.4 mg/m 2 /day at all and significant. The positive and significant measuring sites. The results indicate that the association suggests that these metals (and semi-metal

maximum and minimum values of Zn were 2.460

B) are directly related to each other. 2 mg/m /day at settlement Divkovici and 0.768 Toxic metals such as (Hg, As, Pb, Cd and Cr) are

mg/m 2 /day at control point, respectively. These results

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

indicate the presence of high concentration of Zn in areas from < 1 to 5 ng/m 3 ; in industrialized areas from the dust deposition. According to [14], the main cause 3 15-50 ng/m . These concentrations are directly

of the high concentration of Zn in the air is industry, reflected in the precipitation of Cd with yearly coal combustion and traffic. According to the 3 deposition values ranging from 0.15-11 mg/m in

conducted research, the significant sources of air urban areas and 0.007-0.29 in rural areas and 0.25-73 pollution are Zn addition and disposal sites of ashes.

mg/m 3 in industrial areas [26]. On the basis of the The total contribution of these sources, made the Zn

research it can be concluded that the measured mean value reach an average value of 1,655 concentration Cd almost equally spaced measuring

mg/m 2 /day in measured DD at all sites. sites by suggesting that the air over a wide area The concentration of Pb in DD is over the limit

contaminated with this type of pollutants and other value of 0.1 mg/m 2 /day at measuring sites, A (0.136

anthropogenic sources such as coal and fuel oil

2 mg/m 2 /day) and C (0.159 mg/m /day). Main sources combustion processes, metallurgical industry and road of contamination of Pb are furnaces and automobile

transport [27] contribute to increasing concentrations exhaust where Pb is in the form of halide and easily

of Cd and Ni in the air.

converted into oxides, carbonates and sulphates [15]. Metals Mn, Mo and Pb show a linear dependence High concentration of Pb was found in to the soil

on the amount of dust deposit, indicating the along the road sides [16]. The burning of coal, lead

contribution from the same source. Since the low

point of evaporation, Mn regularly accumulates on the particle diameter of 0.2 to 1.0 μm (aerodynamic

occurs in the form of PbCl 2 and in the air is adsorbed

closely to the source, and it was proved, because the diameter) [17-19]. Through the villages Plane and

sites of closest CADII recorded the highest Divkovici passes local travel routes where traffic

concentration of Mn. Nickel is commonly adsorbing intensity is low, others burdened travel routes are in

on fine particle matter fraction of ambient air samples the range of 1000 m; it can be concluded that Pb in

with diameters ranging from 0.6 to 10 nm. Due to DD originating in dust from CADII, and similar

increased emissions from anthropogenic sources results have been received [20].

98000 tons per year [26], the average nickel content in Cadmium in air occurs adsorbed on solid particles

the soils has increasing tendency. At all measuring submicron size (0.5-1.0 µm) [21-24]. The main

sites high concentrations of Ni were recorded in dust chemical forms in which it occur Cd in air emissions

deposit. Maximum values of Ni were 4.080 mg/m 2 d at are: oxides, chlorides, sulfides, as well as in elemental

measuring site B near settlement Plane, and such high form. As oxide (CdO) is usually transmitted from

concentration of Ni may have a negative impact on the anthropogenic sources, the burning of fossil fuels at

health of the local population. On the basis of the high temperature incineration of municipal waste

obtained results, it can be concluded that the air over a occurs in elemental form. In the form of sulfide (CdS)

wide area is polluted with Ni. In industrial area resulting from the burning of coal, cadmium Lukavac with large number of chemical factories concentrations in dust deposit are higher than the limit

about 8 km west from CADDII recorded rich (0.002 mg/m 2 /day) at all measurement locations (A

concentration of Ni [28]. Also, southwest from

2 (0.004 mg/m 2 /day), B (0.005 mg/m /day), C (0.005 CADDII about 1.5 km is thermal power plant Tuzla, mg/m 2 /day), D (0.004 mg/m 2 /day), E (0.004 the highest concentration of Ni was found in the

2 mg/m 2 /day) and F (0.004 mg/m /day). The EC limit smallest particles emitted from coal-fired plant [29].

values for Cd is 5 ng/m 3 [25]. In urban areas, the

Nickel is classified as carcinogenic to harmful effects

yearly average of Cd ranges from 5-15 ng/m 3 ; in rural

on the respiratory system, reproductive system, liver

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

and skin. Manganese shows strong correlations with concentration of Mo was observed at station C, i.e. DD. The concentration of Mn at station B and C was 2 7.996 mg/m d; at stations A and B values were close

to each other. Increase in Mo concentrations can be respectively) where maximum DD values were also

at a maximum (i.e. 3.121 mg/m 2 d and 2.880 mg/m 2 d,

explained by the vicinity of CADDII and wind high. At the remaining stations the Mn concentration

direction. Mercury and arsenic are found in DD.

Because of its low boiling point and high temperature results in the ejection of crustal Mn to the atmosphere

was 0.450-2.450 mg/m 2 d. Combustion of fossil fuels

in combustion processes, Hg leaves plant by the waste in the form of ash in fine-particle range. Its content in

gas in the form of metal vapors and condenses onto coal ranges from 6 µg/g to 100 µg/g [30]. Since it has

the surface of the smallest particles or remains in low volatility, Mn settles mostly in the immediate

vapors phase. The amount of Hg emitted by TEP is vicinity of its source of release. Manganese is not

proportional to the amount of Hg in the fed raw coal classifiable at human carcinogen [31] but it is

due to the volatile nature of mercury. The presence of neurotoxic element that in continuous and prolonged

Hg in the dust deposit may cause its accumulation in exposure causes a neurological disease [30].

the soil. The highest concentrations of Hg were The highest concentration of Cr was measured at

measured at stations A and B (i.e. 0.028 mg/m 2 d and

station B (i.e. 0.855 mg/m 2 d) while at remaining

0.019 mg/m 2 d) while at the remaining stations Hg stations Cr concentrations were 0.585-0.750 mg/m 2 d. levels were close to each other. Measurement stations

The values at stations A, C and E were close to each of A and B, respectively resorts Plane and Divkovici other. Ta Luft limit value for Cr in DD is 250 µg/m 2 d. are between CADDII and TEP, these two sources of

Chromium usually occurs in two forms; chromium (III) pollution affecting the mercury content in the dust and chromium (VI). The natural form is chromium

deposit. The health risks associated with mercury are (III), whereas chromium (VI) is generally by-product

damage to the peripheral nervous system, digestive of industrial activities and considered to be more

and immune systems [30].

mobile and toxic [32]. Bronchial tree is the major

4. Conclusions

target organ for the carcinogenic effects of chromium (VI) compounds [33]. As in the case of Mn, the range

In the present study concentrations of As, B, Cd, Co, of Pb is associated with minimum and maximum

Cr, Cu, Hg, Mn, Mo, Ni, Pb, Se, V and Zn in

deposited dust were measured by using ICP-OES respectively. The highest Pb pollution was observed at

values of DD being 0.055 and 0.158 mg/m 2 d,

method. The samples were collected by

Bergerhoff–method around coal ash disposal site downwind direction. Ta Luft limit value for Pb in DD

station C, i.e. 0.159 mg/m 2 d, near CADDII in the

Divkovici II, municipal Tuzla, Bosnia and in averaging period of one year is 100 µg/m 2 d. Herzegovina, during the period April-September,

Emissions of Pb into the atmosphere are associated 2011. As deposited dust mass and its trace metals with coal combustion plants, concentrations of Pb in

concentrations in the ambient air depends upon so coals ranges from 0.7-220.0 µg/g [14]. Depending on

many known and unknown factors, its monitoring is the level of exposure, lead can adversely affect the

very important from the aspect of risk assessment to nervous system, kidney function, immune, human health in the design and choice locations for reproduction, developmental and cardiovascular the future ash disposal sites. The most significant system [34]. Molybdenum is an essential trace

factors for the distribution of pollutants are element but the potential adverse effects of high

meteorological conditions of wind speed and direction concentrations still in the research phase. The highest

as well as landscapes characteristic. Present results

Heavy Metals in Dust Deposition in the Vicinity of Coal Ash Disposal Site Divkovici II

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A Potential Weed Control—Using Robotic Implement

1 1 2 2 3 Kwang Ho Park 3 , Soo Hyun Kim , Young Kuk Kim , Han Jong Joo , Yoon Shik Hong , Jee Hyong Kim and Keun Mo Koo 4

1.Department of Food Crops, Korea National College of Agriculture and Fisheries, Hwaseong 445-760, Republic of Korea 2.Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Republic of Korea 3.Unmanned Technology Research Center, Korea Advanced Institute of Science and Technology, Daejeon 305-701, Republic of Korea 4.Duksan Mecasys Co. Ltd., 7F, 6th Byucksan Digital Valley, 481-4, Gasan-Dong, Geumcheon-Gu, Seoul 153-704, Republic of Korea

Received: March 09, 2014/ Accepted: May 08, 2014 / Published: May 30, 2014.

Abstract: The research was conducted to develop a robot that can navigate a paddy in between rows or hills which were transplanted by the machine transplanter with equal distance. An initial prototype robotic battery-type weeder was manufactured and tested to navigate and control weeds in rice paddy fields, but a speed was so slow, and thus second engine-type prototype was developed. A working acreage for weed control has been attained at and up to 0.8 ha/day. Small and young weed seedlings were uprooted and destroyed by passive devices in between rows as well as hills. This robot was smoothly navigated in between rows on behalf of the guidance under camera and sensor systems and control weeds with mechanical by the use of implements such as passive rotary weeders and then weeds would be cut and buried into the soils. Also muddy water was generated during operation which was none penetrated by light for weed germination to occur. The authors concluded that the robotic was an effective alternative implement to control weeds in lowland rice paddy as long as this tool was systematically introduced into the rice fields at three time intervals, viz. 15-20 days, 25-30days, and 35-40 days after transplanting of rice seedlings.

Key words : Rice, transplanting, weed control, robotic weeder.

1. Introduction  chemically. Yet, the reliance upon chemical weed control has brought previously unknown technical

Rice is the most important staple food crop in the challenges, such as the advent of resistant weeds and republic of Korea. Food safety has been recently adverse environmental impacts [1]. Among the most imposed pressure to shift from chemical control using troublesome weeds that affect rice worldwide, grasses synthetic herbicides of paddy weeds to organic (especially those belonging to the genera Echinochloa farming due to consumer`s request. There were a great and Leptochloa) and weedy rice (O. sativa) have a number of changes of selective control, reasonable substantially negative impact on rice production. cost, without extensive labor input in comparison of Species of Echinochloa, in addition of being conventional weed control with hand pulling method. ubiquitous to rice fields worldwide, were increasingly Thus, weed science research was mainly focused on evolving resistance to rice herbicides [2]. Similarly, herbicide. Most (but surely not all) types of weeds can weedy rice, being the same species as cultivated rice, now be controlled by herbicides, alone or in when present, became the most difficult to control combinations [1].

weed in rice [3].

With the advent of glyphosate and the ALS Moreover, such challenges have contributed to the (acetolactate synthase) inhibitors, there were a few advancement of weed management, including the important weed species that cannot be well-controlled integration of other biological and physical sciences

into the design of weed management programs (John Corresponding author: Kwang Ho Park, Ph.D., professor,

research field: agronomy. E-mail: kh5008@korea.kr. and Masaru 2011). In 21 century, the authors were

st

A Potential Weed Control—Using Robotic Implement

facing the mass production of the agricultural crops For the improvement of the row/column maneuver with organic approaches for the food safety. In

and eco-friendly weeding, this paper was introduced conventional way herbicide based weeding has affected

to the robotic weeding system containing the weeding not only weeds which are herbicide resistant, but also

wheels.

the products which are chemically polluted [4].

2. The robotic weeder : Electrical motor

In order to overcome these side effects,

based system

agrochemical-free cultivation has been applied to the rice fields. Recently, it has been widely used based on

First of all, the authors designed a prototype of the the animals such as duck, carp, and freshwater snail.

system in order to maneuver row and column with However, it has been noted that the cultivation cost

appropriate speed. For satisfying this condition, the and controlling the animal were not the easy solution

authors proposed 4 wheel timing belt system (Fig. 1) of these approach so that it was highly needed to find

for the driving and steering mechanism with gear out a new weeding method.

placement for the steering.

For the alternative solution, there are a few attempts

2.1 System architecture

based on the robotic weeding devices for the physical weeding [1-3, 5, 6]. However, these robots were not

2.1.1 4 Wheel Timing Belt Connected Mechanism available to maneuver the row and column and its

In order to drive robot system in the rice paddy weeding capability was not guaranteed.

environment, the power of the system should be

Driving Motor Timing Belt

Fig. 1 Diagram on the relationship of each mechanical part of the Robotic Weeding System (Electric Motor based).

A Potential Weed Control—Using Robotic Implement

increased by gear placement. In this reason, the

2.2 Weeding Wheel Design

rotational speed of the driving motor was decreased to In order to remove the weeds between column to

the worm gear reduction (50:1) so that the driving column, it was necessary to design the proper weeding

power was fully enough with 1m/s movement in flat wheel equipped on the robot system (Fig. 3). As far field area. In addition, the robot system was ought to

the weeding wheel design requirement, following compact enough to fit in 30 × 15 (cm) rice paddy. In

condition should be satisfied.

order to satisfy this, one single motor was connected  Maximizing Whirlpool Effect to the 4 wheels with timing belt.

 Maximizing Weed Uprooting

2.1.2 Steering Mechanism with Worm Gear In order to fulfill these conditions, the weeding For the steering issue to move the columns of the

must be done with designing specialized wheels. As rice paddy, 2 electric motors were placed in front and

far as the whirlpool effect and weeding uprooting, 4 rear part of the wheel. Due to the high torque

wheels were designed based on triangle-toothed wheel requirement during the wheel rotation, the worm gear

shape. Since the roots of the weeds on the rice plant was set to high reduction ratio (10:1).

were normally 20 mm after the rice-planting, the side

2.1.3 System Controller of the triangle and its included angle were As far as the controller manipulates the system

parameterized as x and  , respectively. When the

remotely, the AVR processor was equipped in the uprooting the weeds are done with driving, it was robot system. This processor (Fig. 2) was designed for

expected that the weight of the weeding wheel was to interacting the remote signal from the OCU (operating

be increased. For minimizing the weight effect of the control unit) with Zegbee protocol. Once the signal of

wheel, the parameters of the wheel was optimized the OCU was recognized, the AVR process was

with Eq. (1).

generated the PWM signal so that the motors were

1 1 2 fx (,)   V  x sin  w

(1) able to rotate.

Fig. 2 Control System Architecture of the Robotic Weeding System (Electric Motor Based).

A Potential Weed Control—Using Robotic Implement

Fig. 3 Basic Concept Design of the Weeding Wheel for the Robotic Weeding System.

Fig. 4 Stress Distribution of the Weeding Wheel.

Based on the calculated mass of the mud, the angle of the triangle were assumed to 30 mm and 120°,

In Eq. (1), two parameters, the side ( x ) and the

simulation of the stress of the wheel was conducted.

respectively. In addition, the width of the wheel ( w )

Assuming that material of the wheel was aluminum (Al was set to 40 mm due to the size of the robot and the

7075), the mass of the wheel was 420 g and the yield maneuvering space on the rice paddy (300 mm). With

stress was 95 MPa. If the mass of the robot has the these facts, it was possible to calculate the mass of the

mass of 20 kg, each wheel was loaded 5 kg, mud jammed in the wheel with assumption that the

respectively. For considering mud stuck in the wheel mud was stuck on the half of the volume of the

(safety factor = 4), each wheel was loaded 200 N for triangle〔Eq. (2)〕.

the stress simulation. The result was shown that the

m increase  V 

1 maximum stress of the wheel was 16.85 MPa which

2 was much smaller than the yield stress. With this result, (  : density of the mud)

the weeding wheel was manufactured (Fig. 4).

A Potential Weed Control—Using Robotic Implement

3. The weeding capability of the robotic

3.2 Results

weeder

3.2.1 Column Direction Weeding by the Designed

3.1 Test Environment

Weeding W*-heel

With the proposed devices, 4 weeding wheels, the In order to verify the weeding capability of the

weeds on the rice paddy were eliminated. As shown in robotic weeding system, the artificial environment

Fig. 5, there were comparisons between the mud was designed to 2500﹡2500 [mm] size. For the

condition before weeding wheel use and the condition consideration of real rice paddy in Korea, the space of

after the wheel use. Based on the figure, the weeding the row and column of the rice paddy were set to 300

wheels physically marked their tread so that weeds mm and 150 mm, respectively. As far as the

were uprooted. In addition, the whirlpool effect was maintaining the size of the rice, the temperature and

followed during the drive because of the triangle light were controlled in PTC greed house.

shape on the wheel.

Fig. 5 Artificial Environment of the Rice Paddy (2500 × 2500 [mm]).

A Potential Weed Control—Using Robotic Implement

3.2.2 Skid Steering Mechanism for Row Direction Weeding After the column weeding is finished, the robot maneuvers itself to the next column position with rotating the wheel. In order to verify this motion, the experiment was conducted after the column weeding. As shown in Fig. 6, the time of the wheel rotation (90°) was made in 22 s without touching the rice plants.

4. Vision system for weeding robot

This section describes the developed vision system

Fig. 7 Sample Paddy Field for Vision System Test.

for the weeding robot. In order to weed using robot wheels, the robot needs to track a row of rice

seedlings. The objective of the vision system was to detect a row of rice seedlings for autonomous navigation. To prevent damage to rice seedlings, the robot was required to track precisely the row of rice seedlings.

The vision system was composed of a general USB camera and a single board computer. The developed vision system was tested on sample paddy field shown in Fig. 7.

Images are acquired by the camera installed on the

Fig. 8 Sample Image Acquired by the Robot (Width: 320

robot with a rate of 15 frames per second. A sample

Pixels, Height: 240 Pixels).

image acquired by the robot was shown in Fig. 8. since surroundings are reflected by water surface of

As they can see in Fig.8, when they use a gray scale the paddy field. So they decided to adopt color image, it will be difficult to classify rice seedlings

information in classification of rice seedlings. The goal of the image processing was the

calculation of a line which fits onto a row of rice seedlings as red line shown in Fig. 9. Once we can accurately calculate the line, the robot can track the row of rice seedlings using the slope and x-intercept of the line on the image plane.

Considering the perspective view of the acquired image, ROI (region of interest) was selected as inside of the triangle which is shown in Fig. 10 using yellow lines.

Applying classification algorithm to the above

image, the authors could obtain the image shown in

Fig. 6 Skid Type Wheel Rotation for the Column

Maneuver

Fig. 11 where rice seedlings were appeared as white

A Potential Weed Control—Using Robotic Implement

color region. Using ROI window, the image shown in Fig. 12 could be obtained.

Fig. 12 Image after Applying ROI.

Fig. 9 An Example of Calculated Line Which Fits on a Row of Rice Seedlings.

Fig. 10 ROI of the Acquired Image.

Fig. 13 Calculated Line(red) after Applying Least Squares Method.

The line fitted into the white region in Fig. 11 was calculated using least squares method. To avoid an infinite slope value in calculation, the image was rotated by 90 degrees counterclockwise before applying least squares method. After application of least squares method, the authors could calculate the red line shown in Fig.13. By rotating 90 degrees clockwise again, they could finally obtain the line

Fig. 11 Classification of Rice Seedlings.

shown in Fig. 9.

480

A Potential Weed Control—Using Robotic Implement

5. Conclusions

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