Subscribe Now Subscribe Today
Abstract
Fulltext PDF
References
Research Article
 
Genetic Variability, Heritability and Genetic Advance of Some Haricot Bean (Phaseolus vulgaris L.) Varieties at Bench-Maji Zone, Southwest Ethiopia



Wondwosen Wondimu and Abebe Bogale
 
ABSTRACT
Background and Objective: Assessing variability is fundamental to identify the most important traits in haricot bean improvement program. The objective of the present study was to estimate variability, heritability and genetic advance based on twelve morphological characters of haricot bean (Phaseolus vulgaris L.). Methodology: The experiment was conducted in 2015 and 2016 in main cropping season at 2 locations of Bench-Maji Zone by using randomized complete block design with 3 replications. The data were subjected to one way analysis of variance using SAS. Results: The results revealed significant differences (p<0.05) among genotypes for most characters at both locations. The maximum value between phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) was recorded for number of primary branches (12.6-4.9%) at South bench and plant height (11.6-6.8%) at Menit Shasha. High PCV was recorded for grain yield at both locations and hundred seed weight at South Bench and stand count and number of pod/plant at Menit Shasha. The GCV of high order was observed only for grain yield (20.6%) at South Bench. While, high order of GCV was observed for stand count (20.1%) and number of pod/plant (23.06%) at Menit Shasha. High heritability values were observed on most characters considered at both locations. High heritability coupled high genetic advance (as percentage of the mean) was observed for number of pods/plant, hundred seed weight and grain yield at both locations. Similarly biomass and harvest index at South Bench and primary brunch, stand count at harvest and number of seeds/pod at Menit Shasha were recorded. Conclusion: Therefore, any improvement of these characters would result in a substantial increment on grain yield. Evaluation for variability of haricot bean using conventional approach still could provide vital information but using contemporary molecular genetic analysis approaches such as mapping of quantitative trait loci using molecular markers is helpful to understand variability at molecular level, improve selection knowledge and arrive at more comprehensive conclusions.
Services
Related Articles in ASCI
Similar Articles in this Journal
Search in Google Scholar
View Citation
Report Citation

 
  How to cite this article:

Wondwosen Wondimu and Abebe Bogale, 2017. Genetic Variability, Heritability and Genetic Advance of Some Haricot Bean (Phaseolus vulgaris L.) Varieties at Bench-Maji Zone, Southwest Ethiopia. Asian Journal of Crop Science, 9: 133-140.

DOI: 10.3923/ajcs.2017.133.140

URL: http://scialert.net/abstract/?doi=ajcs.2017.133.140
 
Received: August 15, 2017; Accepted: October 04, 2017; Published: October 17, 2017

INTRODUCTION

Phaseolus vulgaris L. belongs to the family Fabaceae usually called bean, common bean, haricot bean and kidney bean and field beans. In common, it is an annual crop, which thrives, in warm climate. It grows optimally at temperature of 18-24°C1. The crop grows well between 1400 and 2000 m above sea level 2. In East African countries of Burundi, DR. Congo, Ethiopia, Kenya, Rwanda, Tanzania and Uganda, making this the most important region for the crop within the African continent3.

Haricot bean is the most economically important pulse crop grown in Ethiopia. The crop is usually grown by subsistence farmers as a sole crop and/or intercropped with other crops. Considering the production volume and importance, it was noticed as a major pulse crop in many parts of the country. Accordingly, a continuous increase in area and volume of production has been registered. The national production of haricot bean in 2015 cropping season is estimated at over 540.24 thousand t, with a production area of 357.29 thousand hectares and average yield/hectare was about 1.48 t3.

The average yield/hectare of haricot bean in Bench-Maji Zone is 1.796 t ha–1 which was far greater than the national annual average yield3. In reality, the area has possibly the highest potential for haricot bean production than any region in Ethiopia, its productivity has never reached full potential of production that has rated in research center (2.6-3.6 t ha–1)4. Several factors are accountable for this, in which infertility caused by moisture stress, soil reaction, lack improved varieties and biotic factors (disease and pest) are put in the top list5.

Shortage of the improved varieties of common bean was the main problem that aggravates yield reduction in common bean in the study area. For this reason, assessing variability is fundamental to identify important traits for haricot bean improvement. Knowledge of genetic variability, heritability and genetic advance provide more reliable information on variability, heritable trait, nature and level of interrelation ship of haricot bean yield and yield components. Therefore, the present study was conducted to understand the nature and extent of genetic variability, heritability and genetic advance in some important traits of haricot bean genotypes.

MATERIALS AND METHODS

Description of the study areas: The experiments were conducted at two locations in Bench-Maji Zone during the 2015 and 2016 main cropping seasons. Lists of the testing locations in this study with their soil type, altitude, latitude and longitude of locations are presented in Table 1.

Experimental materials: A total, nine haricot bean genotype from Melkasa Agriculture Research Center and one local check were used in this study. List of nine haricot bean genotypes, code and origin are given in Table 2.

Experimental design and procedures: The experiment was laid out in Randomized Complete Block Design (RCBD) with 3 replication and the plot size was 2.1 m×4.8 m. The spacing was 0.4 and 0.1 m intra row and inter- row spacing, respectively and 1.5 m between adjacent blocks and 1 m between plots were left for easy of movement and management activities. Each genotype was sown at seed rate of 85 kg ha–1.

Table 1: Descriptions of soil type, altitude, latitude and longitude of testing locations
Source: Bench Maji zone Agriculture and Natural resource office, 2015 and 2016

Table 2: Description of haricot bean genotypes origin, commercial value and color

The national recommended rates of fertilizer, 46 kg P2O5 ha–1 was used in the form of DAP. The whole dose was applied at planting. All crop management practices was carried out as per the time schedule and existing conditions of the study area.

Coefficient of variation (CV %)=

Statistical analysis:The data were subjected to one way analysis of variance using SAS Version 9.1 software6. The significant difference among genotypes was tested by ‘F’ test at 1 and 5% levels of probability.

The significance was tested by referring the table given by Snecedor7.

Components of variance: The genotypic and phenotypic components of variance were computed according to formulae given by Burton and Devane8 for the observed characters.

Where:
Vg 2g) = Genetic variance
MST = Mean square of treatment
MSE (Ve) = Error variance
r = Number of replications

Genotypic and phenotypic variance:

σ2g = σ2p-σ2e

σ2p = σ2g+σ2e

Where:
σ2g = Genetic variance
σ2p = Phenotypic variance
σ2e = Error variance

Genotypic and phenotypic coefficient of variability: Genotypic and phenotypic coefficients of variability were computed according to the formula stated by Burton and Devane8.

Genotypic coefficient of variability (GCV) =

Phenotypic coefficient of variability (PCV) =

Environmental coefficient of variability (ECV) =

Where:
σ2g = Genotypic variance
σ2p = Phenotypic variance
σ2e = Environmental variance
X = General mean of character

The PCV and GCV values are ranked as low, medium and high by Shivasubramanian and Menon9 as follows: 0-10%-Low, 10-20%-Moderate, >20%-High.

Heritability: Broad sense heritability was estimated based on the ratio of genotypic variance to the phenotypic variance and was expressed in percentage10.

Where:
h2B = Heritability in broad sense
Vg = Genotypic variance
Vp = Phenotypic variance

Heritability values were categorized as low, moderate and high by Robinson et al.11 as follows: 0-30%: Low, 30-60%: Moderate, 60% and above, High.

Genetic advance: The extent of genetic advance is expected by selecting certain proportion of the superior progeny was calculated by using the following formula suggested by Robinson et al.11.

Genetic advance (GA) = kσph2

Where:

k = Intensity of selection at 5% (k-2.06)
σp = Phenotypic standard deviation
h2 = Heritability in broad sense

The value of ‘k’ was taken as 2.06 assuming 5% are selected.

Genetic advance expressed as percentage over mean (GAM):

Where:
GA = Genetic advance
X = General mean of the character

The GAM was categorized as suggested by Johanson et al.12 as: 0-10% = Low, 11-20% = Moderate, >20% and above, High.

RESULTS AND DISCUSSION

The analysis of variance for different characters at South Bench and Menit Shasha locations are presented in Table 3. The results revealed significant differences (p<0.05) among genotypes for most characters at both locations with the exception of day to emergency, days to flowering, day to maturity and number of primary branches at South Bench and day to emergency at Menit Shasha.

Phenotypic and genotypic variations: The effectiveness of selection in any crop depends on the extent and nature of phenotypic and genotypic variability present in different agronomic traits of the population13. Generally, genetic parameters including genotypic coefficient of variation, heritability and genetic advance are prerequisite for genetic improvement of crops14. High genotypic coefficient of variation indicates availability of high genetic variation. The lower value of variation indicates that selection is not effective for particular character because of the narrow genetic variability15.

According to Burton and Devane8, PCV and GCV values great 20% are regarded as high, whereas values less than 10% are considered to be low and values between 10 and 20% to be moderate. Estimated variance components, PCV and GCV for the characters studied are presented in Table 4 and 5. In this study, PCV ranged from 3.8% for days to maturity to 24.43% for grain yield and the GCV ranged from 3.3% for days to maturity to 12.9% for grain yield at South Bench but at Menit Shasha districts PCV ranged from 4.77% for days to maturity to 24.4% for number of pod/plant and the GCV ranged from 3.13% for days to emergency to 23.06% for number of pod/plant.

Table 3:
Analysis of variance for different characters of haricot bean genotypes at South Bench and Menit Shasha in 2015-16 main cropping season
*Significant at 5% level of probability, **highly significant at 1% level of probability, ns: Not significant, DE: Day to emergency, DF: Days to flowering, DM: Day to maturity, PH: Plant height, PPB: Number of primary branches, SCH: Stand count, NPP: Number of pod/plant, NSPP: Number of seed/pod, BM: Biomass, HI: Harvesting index, HSW: Hundred seed weight and GY: Grain yield

Table 4:
Genotypic, phenotypic and environmental variance genotypic, phenotypic and environmental coefficient of variation, heritability and genetic advance (GA as % of mean) of quantitative traits of 9 genotypes of haricot bean at South Bench in 2015-16 main cropping season
DE: Days to emergency, DF: Days to flowering, DM: Days to maturity, PH: Plant height, PPB: Primary brunch, SCH: Stand count at harvest, NPP: Number of pods per plant, NSPP: Number of seeds per plant, HSW: Hundred seed weight, GY: Grain yield, BMY: Biomass yield, HI: harvest index, GV: Genotypic variance, GCV: Genotypic coefficient of variation, h2: Heritability, PV: Phenotypic variance, PCV: Phenotypic coefficient of variation GAM: Genetic advance as per cent of mean and GA: Genetic advance

The maximum value between PCV and GCV was recorded for number of primary branch (12.6-4.9%) followed by plant height (11.4-6.8%) at South Bench and plant height (11.6-6.8%) at Menit Shasha. It indicates that the expression of character relatively more influenced by environments. In agreement with the present study. Gutu16 reported that the maximum value between PCV and GCV for number of primary branches in French bean.

Generally, the GCV and PCV were similar in magnitude and direction in both locations which indicated that the genotypes were able to express their genetic potential for various traits. GCV of high order was observed only grain yield (20.6%). This result agrees with the findings of More and Borkar17 reported that high genotypic coefficients of variations for grain yield in common beans genotypes. On the other hand, hundred seed weight (18.3%), harvest index (10%), biomass (12%), number of pods/plant (14.6%) had moderate GCV. Earlier researchers also reported relatively moderate for biological yield18 and for hundred seed weight at South Bench, however in Menit Shasha, high order of GCV was observed for stand count (20.1%) and number of pod per plant (23.06%). This result disagrees with the findings18. On the other hand, number of primary branches, number of seed/pod, hundred seed weight, biomass and grain yield had moderate GCV. Earlier researchers also reported relatively moderate for number of seed per pod, biological yield and hundred seed weight18.

Other traits such as days to 50% emergence, days to 50% flowering, days to maturity and plant height, had shown low GCV at both location in addition number of primary branch, stand count at harvest, number of seeds/pod at South Bench and harvesting index at Menit Shasha district had low GCV. Similar results of lower GCV in plant height, days to 50% flowering, days to 90% maturity were also reported by Narayan18. Similarly Plant height, days to maturity and days to flowering low GCV was recorded by Gutu16.

Relatively higher PCV was observed in grain yield at both locations and hundred seed weight at South Bench and stand count and number of pod/plant at Menit Shasha. These findings are in conformity with earlier reports of Narayan18 in number of pod/plant and grain yield and hundred seed weight17. Traits such as biomass, number of primary branch, harvest index and plant height at both locations and number of pods/plant at South Bench and number of seed-pod and hundred seed weight at Menit Shasha had moderate PCV. The moderate value of PCV for the above mentioned characters was reported by Narayan18.

Lower PCV was observed for phonological parameters (days to 50% emergence, days to 50% flowering and days to 90% maturity) at both locations. In the same way, stand count at harvest and number of seeds/pod revealed lower PCV value at South Bench. This result was supported by previous findings by Narayan18 and Negash19 who reported lower PCV for days to maturity and days to 50% flowering.

Among all traits, high GCV and PCV values (>20%) were observed for grain yield at South Bench and number of pod/plant and stand count Menit Shasha. Moderate GCV and PCV values (>10%) were observed for hundred seed weight, harvest index, biomass and number of pods/plant at South Bench and number of primary branches, number of seed/pod, biomass and hundred seed weight at Menit Shasha, therefore further selection of these traits could improve the genotype. Similarly, high GCV and PCV value for grain yield reported by Negash19 and on number of pod/plant reported by Prakash et al.20.

On the other hand, low PCV and GCV (<10%) were observed for days to maturity, days to flowering and days to maturity. This traits offered less scope of selection as they under the influence of environments. The current results were supported by previous foundlings reported by More and Borkar17.

Generally, the PCV values were greater than GCV values although the differences were not large suggesting that there was influence of the environment. The environmental coefficients of variation (ECV) of traits were lower than both genotypic and phenotypic coefficient of variations. This implies that the environmental role was less for the expression of such characters. This implies that the environmental role was less for the expression of such characters.

Estimates of heritability (H2B) in broad sense: Information on heritability in broad sense (h2B) and genetic advance of yield attributing traits and their association helps plant breeder to identify characters for effective selection. The concept of heritability explains whether differences observed among individuals rose as a result of differences in genetic makeup or due to environmental forces. According to Robinson et al.11, heritability values are categorized as low from 0-30%, moderate from 30-60% and 60% and above are high. Considering this benchmark, heritability estimate of this study are described as follows.

In this study, heritability (h2B) estimate ranged from 38.9% for primary branch to 86.9% for harvest index (Table 4) at South Bench and from 30.5% for day to emergency to 95.86% for stand count (Table 5) at Menit Shasha.

Table 5:
Genotypic, phenotypic and environmental variance, genotypic, phenotypic and environmental coefficient of variation, heritability and genetic advance (GA as % of mean) of quantitative traits of 9 genotypes of haricot bean at Menit Shasha in 2015-16 main cropping season
DE: Days to emergency, DF: Days to flowering, DM: Days to maturity, PH: Plant height, PPB: Primary brunch, SCH: Stand count at harvest, NPP: Number of pods per plant, NSPP: Number of seeds per plant, HSW: Hundred seed weight GY: Grain yield, BMY: Biomass yield, HI: Harvest index, GV: Genotypic variance, GCV: Genotypic coefficient of variation, h2: Heritability, PV: Phenotypic variance, PCV: Phenotypic coefficient of variation, GAM: Genetic advance as per cent of mean and GA: Genetic advance

Based on the above bench mark days to 90% maturity, stand count at harvest, number of pods/plant, number of seeds/plant, biomass, harvest index, hundred seed weight and grain yield exhibited relatively higher H2B values at both location. Likewise, days to flowering at South Bench and number of primary branches at Menit Shasha showed very high heritability estimates in the broad sense. High heritability values for these traits indicated that the variation observed was mainly under genetic control and was less influenced by the environment and the possibility of progress from selection. This may be attributed due to uniform environmental conditions during the conduct of the experiment. Indicating that the possibility of success in selection. Earlier workers also reported relatively higher broad sense heritability values for days to 90% maturity, days to 50% flowering, plant height, number of seeds/plant and hundred seed weight19. Similarly, Narayan18 reported that number of seeds per pod, harvest index, seed yield/plot and biological yield had high broad sense heritability. Moderately high heritability estimates were obtained from traits like primary branch, plant height and days to 50% emergence at South Bench and day to emergency, days to flowering, plant height and biomass and harvesting index Menit Shasha.

Expected genetic advance (GAM %): The expected genetic advance (GA) values for twelve characters of the genotypes evaluated are presented in Table 4 and 5. These values are also expressed as percentage of the genotypes mean for each character so that comparison could be made among various characters, which had different units of measurement. High H2B along with high GAM is an important factor for predicting the resultant effect of selecting the best individuals. Percentage of mean genetic advance (GAM) estimates varied from for days to 6.8% maturity to 42.2% for grain yield and from 5.1% days to emergency to 48.17% number of pods/plant at South bench and Menit Shasha conditions, respectively. In this study, higher GAM (>20 percent) was recorded for grain yield (42.2%), hundred seed weight (37.7%), number of pods/plant (30.08%), biomass (25.79%) and harvest index (20.65%) at South Bench and number of primary branch/plant (25.3%), stand count (40.5%),number of pod/plant ( 48.17%), number of seed/pod (24.1%), hundred seed weight (23.89%), grain yield (33.86%)at Menit Shasha. This finding is in agreement with Negash19 where 100-seed weight (56.6%) and number of seed/pod 23.71% with Gutu B. 2015 showed a high genetic advance as percent of mean. Similarly the same result was reported by Narayan18 hundred seed weight (57.57%), grain yield (38.56%) and number of pod/plant (24.15%).

The estimates of genetic advance help in understanding the type of gene action involved in the expression of various polygenic characters. High values of genetic advance are indicative of additive gene action whereas low values are indicative of non-additive gene action21. Accordingly, Heritability and genetic advance are important selection parameters. The estimate of genetic advance is more useful as a selection tool when considered jointly with heritability estimates12. High heritability coupled high genetic advance (as percentage of the mean) was observed for number of pods per plant, hundred seed weight and grain yield at both locations, likewise biomass and harvest index at South Bench and number of primary brunch, stand count at harvest and number of seeds per pod at Menit Shasha were exhibited. This reflected that the involvement of additive gene action for the inheritance of these traits and selection would be effective. This finding was similar with the result of Negash19 and Narayan18, respectively opposite to the above mentioned traits, day to 90% maturity at South Bench and Menit Shasha locations showed.

High heritability coupled with low genetic advance as percent of mean compare to the other traits. The traits processing low genetic advance with high heritability which indicates the presence of non additive gene thus, simply selection procedures in early segregating generation will not be effective for screening of desirable traits. Further explanation by Sardana et al.22 suggested that high heritability might not necessarily lead to increased genetic gain, unless sufficient genetic variability existed in the germplasm. In agreement with the current finding, high heritability with low genetic advance were detected by Negash19 for day to maturity in French bean.

Therefore, any improvement of these characters would result in a substantial increment on grain yield. Thus, evaluation for variability of haricot bean using conventional approach still could provide vital information but using contemporary molecular genetic analysis approaches such as mapping of quantitative trait loci using molecular markers is helpful to understand variability at molecular level, improve selection knowledge and arrive at more comprehensive conclusions. Repeating the experiment is advisable to better estimate environmental effects.

CONCLUSION

This study generally indicated that there was genetic variability among the genotypes. Thus, there is enormous opportunity in the improvement of haricot bean genotypes. Therefore, the information generated from this study needs to be used by breeders who are interested both in commercial and food type haricot bean genotypes. Besides, these haricot bean materials need to be tested in similar agro ecologies for their stability.

SIGNIFICANCE STATEMENTS

This study discovers the genetic variability, heritability and genetic of the tested haricot bean varieties. It also indicates yield attribute traits of the haricot bean varieties considered and further selection of this trait could improve the genotypes. Thus, direct selection of these characters and incorporation of selected individuals in breading programs would bring improvement in the genotypes.

ACKNOWLEDGMENTS

Authors luckily acknowledge the massive contribution made by Mizan-Tepi University and Institute of Research and Community Development Support for fully funding the research. Authors would like to thank Mizan Tepi University Income and Revenue Generating Office for their enthusiastic cooperation the field operation. The authors also would like to thanks Melkasa of Agricultural research center for supplying seeds of the genotypes without any cost.

REFERENCES
Arora, P.P., 1991. Genetic variability and its relevance in chickpea improvement. Int. Chickpea Newslett., 25: 9-10.

Assefa, T., G. Abebe, C. Fininsa, B.Tesso and A.R.M. Al-Tawaha, 2005. Participatory bean breeding with women and small holder farmers in eastern Ethiopia. World J. Agric. Sci., 1: 28-35.
Direct Link  |  

Burton, W.G. and E.H. Devane, 1953. Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agron. J., 45: 478-481.
CrossRef  |  Direct Link  |  

CSA., 2014. Agricultural sampale survey 2013/14. Report on Area and Production of Major Crops (Private Peasant Holdings, Meher Season), Vol. I, Statistical Bulletin 532, Central Statistics Agency, Addis Ababa, pp: 1-124.

CSA., 2016. Report on area and production of major crops during meher season conducted from September 12 to October 25/2016. Statistical Bulletin 579, Central Statistics Agency, Addis Ababa, pp: 1-113.

Falconer, D.S. and T.F.C. Mackay, 1996. Introduction to Quantitative Genetics. 4th Edn., Benjamin Cummings, London, UK., ISBN-13: 9780582243026, Pages: 464.

Girma, W., M. Yeshialem and B. Tsegaye, 2017. Response of haricot bean (Phaseolus vulgaris L.) to lime application and Rhizobium inoculation on nitosols at Bench-Maji Zone, Southwestern Ethiopia. J. Plant Biol. Soil Health, Vol. 4.

Gutu, B., 2015. Genetic variability and path coefficient analysis for yield and yield related traits in common bean (Phaseolus vulgaris L.). M.Sc. Thesis, Haramaya University, Hararge, Ethiopia.

Johnson, H.W., H.F. Robinson and R.E. Comstock, 1955. Estimates of genetic and environmental variability in soybeans. Agron. J., 47: 314-318.
CrossRef  |  Direct Link  |  

Khorgade, P.W., M.N. Narkhede and S.K. Raut, 1985. Genetic variability studies in chickpea. Int. Chickpea Newslett., 12: 12-13.

More, A.D. and A.T. Borkar, 2016. Analysis of genetic variability, heritability and genetic advance in Phaseolus vulgaris L. Int. J. Curr. Microbiol. Applied Sci., 5: 494-503.
CrossRef  |  Direct Link  |  

Narayan, J., 2013. Variability and correlation analysis in diverse genotypes of French bean (Phaseolus vulgaris L.). M.Sc. Thesis, Banaras Hindu University, Varanasi, India.

Negash, K., 2006. Studies on genetic divergence in commonbean (Phaseolus vulgaris L.) introductions of Ethiopia. M.Sc. Thesis, Addis Ababa University, Ethiopia.

Pandey, R.L. and A.S. Tawari, 1983. Heritability and genetic gain in chickpea. Int. Chickpea Newslett., 9: 5-6.

Prakash, J., R.B. Ram and M.L. Meena, 2015. Genetic variation and characters interrelationship studies for quantitative and qualitative traits in French bean (Phaseolus vulgaris L.) under Lucknow conditions. Legume Res.: Int. J., 38: 425-433.
Direct Link  |  

Robinson, H.F., R.E. Comstock and P.H. Harvey, 1949. Estimates of heritability and the degree of dominance in corn. Agron. J., 41: 353-359.
Direct Link  |  

SAS., 2004. SAS User Guides, Version 9.1. SAS Inc., Cary, North Carolina, USA.

Sardana, S., R.K. Mahajan, N.K. Gautam and B. Ram, 2007. Genetic variability in pea (Pisum sativum L.) germplasm for utilization. SABRAO J. Breed. Genet., 39: 31-41.

Singh, P. and S.S. Narayanan, 1993. Biometrical Techniques in Plant Breeding. 1st Edn., Kalayani Publishers, New Dehli, India.

Sivasubranian, S. and M. Menon, 1973. Heterosis and inbreeding depression in rice. Madras Agric. J., 60: 1139-1144.

Snecedor, G.W., 1946. Statistical Methods. The IOWA State’s College Press, Iowa, USA.

Vakali, C., F. Papathanasiou, I. Papadopoulos and E. Tamoutsidis, 2009. Prelimenary results on a comparative study evaluating landraces of common bean (Phaseolus vulgaris L.) underorganic agriculture in a protected area in Greece. Proceedings of the 2nd Scientific Conference within the Framework of the 9th European Summer Academy on Organic Farming, June 24-26, 2009, Lednicena Morave, Czech Republic -.

©  2017 Science Alert. All Rights Reserved
Fulltext PDF References Abstract