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Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 06 (2018) Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2018.706.171 Genetic Divergence of Maize Genotypes under Normal and Water Stress Conditions K. Vijay Kumar1*, K. V. Radha Krishna2, T. Pradeep3, D. Vishnuvardhan Reddy3 and M. H. V. Bhave4 1 2 Agricultural Research Station, PJTSAU, Mudhol, India Department of Genetics & Plant Breeding, College of Agriculture, PJTSAU), Rajendranagar, Hyderabad-500 030, India 3 PJTSAU, Rajendranagar, Hyderabad, India 4 Department of Mathematics & Statistics, College of Agriculture, PJTSAU, Rajendranagar, Hyderabad, India *Corresponding author ABSTRACT Keywords Maize, genetic diversity, cluster analysis, drought stress Article Info Accepted: xx May 2018 Available Online: xx June 2018 Seventy five maize genotypes were evaluated to study the genetic divergence under two drought stress conditions i.e. moderate stress and severe stress along with well watered conditions. The experiment was carried out at Maize Research Centre, Rajendranagar, Hyderabad, during rabi 2011-12. The seventy five genotypes were grouped into nine distinct clusters. The cluster VII, cluster VIII and cluster VII were the largest and lowest genotypes were included in cluster II, cluster V and clusters V and IX under normal, moderate drought stress and severe drought stress conditions, respectively. The highest inter-cluster distance was observed between, cluster IV and VIII, V and VII and III and V under normal, moderate drought stress and severe drought stress conditions, respectively. Chlorophyll fluorescence and ear weight showed maximum contribution towards total divergence among different characters studied, in all the three water regimes. The cluster IV, cluster V and cluster III showed high mean values for plant height, ear length, ear weight, harvest index and grain yield under normal, moderate drought stress and severe drought stress conditions, respectively. The genotypes with wide genetic diversity can be utilized in future breeding programme to evolve drought tolerant hybrids to mitigate the adverse effects of climate change. Introduction In India Maize (Zea mays L.) has become an important cereal crop after rice & wheat. It is grown in an area of 8.80 million hectares with production of 22.56 million tonnes and productivity of 2680 kg/ha (Centre for Monitoring Indian Economy, 2016). In recent years, the productivity of maize was not increased significantly (2007-08: 2335 kg/ha to 2015-16: 2562 kg/ha), even though 90% of the cultivated area is under high yielding single cross hybrids. The low grain yields can be attributed to a number of constraints which include biotic stress such as diseases, pests and parasitic weeds and abiotic stresses such as low soil fertility and drought. Among them, drought stress or water deficit is an envitable and recurring feature of World Agriculture. It has been estimated that about one third of the world’s potentially arable land suffers water shortage and crop yields are often reduced by 1441 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 drought (Khan et al., 2004). The development of crops with increased tolerance to abiotic stresses especially drought and salinity is much required throughout the world (Denby and Gehring, 2005). Drought remains the most important devastating factor in Maize and it has different effects on the crop depending on the growth stage at which it occurs (Umar et al., 2015). Soil moisture deficit in maize may cause drastic yield reduction, especially if it occurs during the reproductive phase (NeSmith and Ritchie, 1992; Basseti and Westgate, 1993). Banziger (2000) observed that the full sib family selection was the most extensively used at CIMMYT to improve maize populations for drought and low-N tolerance. Precise selection of elite genotypes is very important to breed for any specific area (Ashofteh Beiragi et al., 2010). Several studies on maize have shown that inbred lines from diverse stocks were more productive than crosses of inbred lines from the same variety (Vasal, 1998). Saxena et al., (1998) also reported that manifestation of heterosis usually depends on the genetic divergence of the two parental lines. Multivariate analysis based on Mahalonobis D2 statistic is widely used for effective discrimination of genotypes on the basis of genetic diversity (Murthy and Arunachalam, 1966). Several studies were published on classification of germplasm collections and classification of maize inbreds with comparision of cluster analysis algorithm. The present study was undertaken to evaluate the genetic diversity among the maize genotypes specially for drought tolerance which can be exploited in future maize breeding programmes. from Agricultural Research Station, Karimnagar were included in the present investigation. The experimental material was evaluated under three conditions; one normal (irrigated) and two drought stress conditions viz., moderate drought stress conditions (suspending the irrigation 20 days before flowering and during grain filling stage) and severe drought stress conditions (suspending the irrigation 40 days after sowing). For each condition, the experimental material was sown in randomized block design with two replications. Replication wise, each genotype was sown in a row of 4 m length spaced 75 cm apart with a 20 cm distance between plants with in the row. All the recommended agronomic practices and plant protection measures were taken up in time to raise the crop. Data was recorded on seventeen morpho physiological and yield attributing characters. Observations were recorded on no.of leaves per plant, plant height (cm), ear height (cm), ear length (cm), ear girth (cm), no.of kernel rows per ear, no.of kernels per row, 100 kernel weight (g), ear weight (g), Harvest Index (%) and grain yield per plant (g) on five randomly selected plants for each entry in each replication. Data pertaining to days to 50% tasseling, days to 50% silking and Anthesis-Silking Interval and leaf firing score were recorded on plot basis. The SPAD chlorophyll meter reading and Chlorophyll flourometer readings for leaf chlorophyll content and chlorophyll fluorescence respectively were taken at 90 days after sowing on top third leaf of randomly selected five plants. Mean values were subjected to statistical analysis. Materials and Methods A total of seventy five maize genotypes obtained, of which 42 from Maize Research Centre, Rajendranagar, Hyderabad and 33 Genetic divergence was estimated as per Mahalanobis D2 statistic (1936) and clustering of genotypes was done according to Tocher’s method as described by Rao (1952). 1442 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 Results and Discussion The analysis of variance revealed highly significant differences among the genotypes for all the studied characters under all three conditions indicating the existence of genetic variability among the experimental material in all the tested water regimes. All the 75 genotypes were grouped into nine clusters each in each condition (Table 1). Clustering pattern of genotypes clearly indicated that majority of the inbred lines showed considerable genetic diversity by occupying different clusters in each condition. A similar study was carried out by Chen FaBo et al., (2007) who grouped 186 genotypes into ten clusters. In normal condition, it was revealed that cluster VII comprised of maximum number (21) of genotypes followed by cluster I and cluster VI with 12 and 9 genotypes, respectively. The lowest (3) number of genotypes were included in cluster II. Whereas under moderate stress condition, cluster VIII was the largest comprised of 18 genotypes followed by clusters I and IX with 14 genotypes. Single genotype was included in the cluster V. The maximum number of genotypes was observed in clusters I and VIII with 15 genotypes followed by cluster VI with 12 genotypes and the lowest (3) was reported in clusters V and IX in case of severe stress condition. The average intra and inter cluster distance values were worked out from divergence analysis for each character (Table 2). The intra cluster distances were lower than the inter cluster distances indicating heterogeneous and homogeneous nature between and within the groups, respectively. The maximum intra cluster distance was observed by cluster VIII under both normal and severe stress conditions and cluster VI in moderate stress condition. Cluster V in moderate stress condition had only a single genotype, hence minimum intra cluster distance was observed. The hybrids are expected to manifest maximum heterosis by involving the parents from most divergent clusters which generates wide variability. This was supported by appreciable amount of variation observed for the cluster means under all the tested conditions. The highest inter cluster distance was observed between clusters IV and VIII (221.29) followed by clusters III and VIII (210.77) under normal conditions. Whereas, the highest distance was obtained by clusters V and VII (237.93) followed by clusters IV and VII (198.41) and clusters V and VI (194.47) in case of moderate stress conditions, while in case of severe stress conditions highest distance was obtained by clusters III and V (164.29), followed by II and V (148.82) and I and V (139.87). This suggests more genetic variability in the genetic architecture of the genotypes included in these clusters under each situation. The genotypes belong to the cluster separated by high statistical distance could be utilized as parents in hybridization programme for yield improvement. The results on the contribution of individual characters towards the total divergence under normal and drought stressed conditions are presented in Table 3. Of the seventeen characters studied, the percent contribution towards total divergence was the highest for chlorophyll fluorescence followed by ear weight in all three water regimes. Mean values of clusters for yield and its contributing characters and physiological parameters are presented in the Table 3. It shows that the genotypes with high values of plant height, ear length, ear weight, harvest index and grain yield were included in cluster IV, cluster V and cluster III under normal, moderate and severe stress conditions, respectively. 1443 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 Table.1 Grouping of 75 maize genotypes into clusters under normal, moderate stress and severe stress conditions Cluster Cluster I Cluster II Cluster III Cluster IV Cluster V Cluster VI Cluster VII Cluster VIII Cluster IX Condition N No. of genotypes 12 MS 14 SS 15 N MS SS N MS SS N MS SS 3 3 8 8 5 4 4 7 11 N MS SS N MS SS 5 1 3 9 11 12 N 21 MS SS 2 15 N MS 7 18 SS N MS 4 6 14 SS 3 Genotypes BMLDT-2, BMLDT-64, BMLDT-97, BMLDT-87, BMLDT-16, BMLDT-56, BMLDT-86, BMLDT-27, BMLDT-29, BMLDT-95, BMLDT-134 and BMLDT-38 BMLDT-1, BMLDT-87, BMLDT-5, BMLDT-11, BMLDT-56, BMLDT-2, BMLDT-24, BMLDT-13, BMLDT-88, BMLDT-129, BMLDT-135, BMLDT-97, BMLDT-134, 1063 BMLDT-2, BMLDT-87, BMLDT-1, BMLDT-129, BMLDT-134, BMLDT-56, BMLDT-5, BMLDT-124, BMLDT-11, BMLDT-24, BMLDT-135, BMLDT-97, BMLDT-4, BMLDT-14, 1063 BMLDT-132, BMLDT-133 and BMLDT-131 BMLDT-95, BMLDT-103, BMLDT-82 BMLDT-9, BMLDT-99, BMLDT-38, BMLDT-88, BMLDT-21, BMLDT-34, BMLDT-91 and BMLDT-86. BMLDT-4, BMLDT-45, BMLDT-11, 1063, BMLDT-24, BMLDT-99, BMLDT-124, BMLDT-135 BMLDT-9, BMLDT-34, BMLDT-99, BMLDT-124, BMLDT-86 BMLDT-15, BMLDT-27, BMLDT-29 and BMLDT-45 BMLDT-5, BMLDT-21, BMLDT-15 and BMLDT-91 BMLDT-15, BMLDT-21, BMLDT-27, BMLDT-29, BMLDT-38, BMLDT-45, BMLDT-4 BMLDT-3, BMLDT-17, BMLDT-8, BMLDT-106, BMLDT-7, BMLDT-12, BMLDT-10, BMLDT-110, BMLDT-109, BMLDT-119 and BMLDT108 BMLDT-9, BMLDT-13, BMLDT-129, BMLDT-39 and BMLDT-78 BMLDT-91 BMLDT-101, BMLDT-102 and BMLDT-107 BMLDT-14, BMLDT-88, BMLDT-25, BMLDT-34, BMLDT-18, BMLDT-80, BMLDT-1, BMLDT-36, and BMLDT-37 BMLDT-3, BMLDT-8, BMLDT-108, BMLDT-109, BMLDT-119 BMLDT-10, BMLDT-3, BMLDT-12, BMLDT-17, BMLDT-101, BMLDT-106 BMLDT-16, BMLDT-40, BMLDT-13, BMLDT-25, BMLDT-78 BMLDT-32, BMLDT-112, BMLDT-80, BMLDT-118, BMLDT-37, BMLDT-74 and BMLDT-39. BMLDT-20, BMLDT-103, BMLDT-110, BMLDT-114, BMLDT-57, BMLDT-23, BMLDT-118, BMLDT-32, BMLDT-58, BMLDT-100, BMLDT-112, BMLDT-33, BMLDT-82, BMLDT-40, BMLDT-70, BMLDT-74, BMLDT-26,, BMLDT-6, BMLDT-73, BMLDT-113 and BMLDT-53 BMLDT-102, BMLDT-107 BMLDT-20, BMLDT-23, BMLDT-18, BMLDT-26, BMLDT-36, BMLDT-57, BMLDT-132, BMLDT-53, BMLDT-73, BMLDT-58, BMLDT-70, BMLDT-33, BMLDT-100, BMLDT-113, BMLDT-6, BMLDT-3, BMLDT-12, BMLDT-108, BMLDT-101, BMLDT-106, BMLDT-102 AND BMLDT-107 BMLDT-6, BMLDT-18, BMLDT-132, BMLDT-133,BMLDT-131, BMLDT-32 BMLDT-53, BMLDT-100, BMLDT-113, BMLDT-78 BMLDT112, BMLDT-20,BMLDT-23, BMLDT-57, BMLDT-58, BMLDT-80, BMLDT-33 and BMLDT-110 BMLDT-64, BMLDT-114, BMLDT-131 and BMLDT-133 BMLDT-10, BMLDT-17, BMLDT-8, BMLDT-109, BMLDT-119 and BMLDT-3, BMLDT-14, BMLDT-40, BMLDT-16, BMLDT-25, BMLDT-64, BMLDT-26, BMLDT-36, BMLDT-37, BMLDT-74, BMLDT-114, BMLDT-39, BMLDT-118, BMLDT-70 and BMLDT-73 BMLDT-95, BMLDT-103 and BMLDT-82 Note: N-Normal; MS-Moderate stress; SS-Severe stress. 1444 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 Table.2 Average inter and intra cluster distances (D = √ D2) values under normal, moderate stress and severe stress conditions Cluster Cluster I Cluster II Cluster III Cluster IV Cluster V Cluster VI Cluster VII Cluster VIII Cluster IX Condition N MS SS N MS SS N MS SS N MS SS N MS SS N MS SS N MS SS N MS SS N MS SS Cluster I 56.08 23.91 30.85 Cluster II 77.13 35.59 45.13 37.95 20.48 32.95 Cluster III Cluster IV 78.39 89.05 39.45 64.86 69.42 105.17 106.39 123.03 59.88 85.93 44.89 118.35 106.39 60.03 39.12 24.47 137.70 24.74 45.14 25.56 32.97 Cluster V 87.28 101.70 139.87 98.84 125.45 148.82 74.13 72.11 164.29 111.28 46.95 48.72 47.11 0.00 26.38 Note: Figures in parenthesis indicate D values; Diagonal values indicate intra-cluster distance. N-Normal; MS-Moderate stress; SS-Severe stress. 1445 Cluster VI 74.00 113.35 58.28 68.33 82.16 85.16 82.03 132.99 114.68 121.46 154.18 82.42 63.02 194.47 118.01 45.77 31.70 26.84 Cluster VII 99.41 159.00 70.92 81.05 126.83 96.05 98.50 127.88 123.85 152.18 198.41 65.19 79.60 237.93 99.45 58.37 54.62 33.07 53.04 26.60 23.57 Cluster VIII 198.12 68.53 62.55 159.51 42.30 88.19 210.77 95.25 111.90 221.29 121.74 80.38 168.19 161.81 114.54 159.59 62.82 42.67 156.07 103.57 40.81 71.70 22.75 35.21 Cluster IX 124.29 54.67 43.21 86.62 39.48 60.32 139.59 83.87 85.51 156.31 111.59 73.54 103.97 150.13 107.18 87.29 85.41 43.54 90.62 127.63 43.54 101.10 32.94 47.42 54.76 22.06 27.52 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 Table.3 Cluster means for morpho physiological and yield contributing characters under normal, moderate stress and severe stress conditions Cluster No.of leaves/plant N MS I II 11.97 12.22 11.12 10.44 10.04 77.71 9.57 85.50 68.07 68.83 III 11.94 11.10 10.96 83.19 IV 13.04 12.55 9.88 V 11.43 11.84 VI 11.82 VII Days to 50% silking ASI Plant height (cm) N MS SS N MS SS N MS SS 71.03 69.63 80.71 89.00 72.96 77.33 77.90 75.81 3.08 3.50 4.96 6.17 7.00 6.19 176.42 174.72 134.19 124.44 116.79 119.95 66.30 68.88 86.25 72.00 74.38 3.06 5.50 5.63 147.27 134.10 146.25 74.38 65.93 71.36 76.50 70.21 79.27 2.13 4.29 7.91 189.33 157.79 103.02 9.78 77.90 64.00 71.67 81.10 70.50 84.17 3.20 6.50 12.50 132.15 159.17 101.67 10.94 9.40 78.33 67.32 72.00 81.06 73.27 81.38 2.72 5.95 9.38 147.75 118.12 97.55 11.10 10.17 9.49 80.17 65.25 71.17 83.38 75.75 80.57 3.21 10.50 9.40 132.64 111.58 99.34 VIII 11.19 10.65 9.33 77.00 68.58 72.00 79.79 76.36 81.13 2.79 7.83 9.13 128.81 116.39 132.33 IX 11.78 10.68 9.22 82.08 68.04 72.00 84.75 75.11 80.00 2.67 7.07 8.00 146.94 112.02 110.16 Mean 11.83 11.05 9.74 79.58 66.92 71.08 82.50 73.72 79.40 2.93 6.53 8.35 152.89 129.76 114.12 2 0 796 68 211 0.07 0.00 28.68 2.45 7.60 No. of times appearing first in ranking % of contribution toward total divergence SS Days to 50% tasseling N MS SS 0 0 0 32 0.00 0.00 0.00 1.15 Contribution of each character to the divergence 1 2 0 2 6 0 0.04 0.07 0.00 0.07 0.22 0.00 (Contd…) 1446 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 Cluster Ear height (cm) Ear length (cm) Ear girth (cm) No.of kernel rows/ear No.of kernels/row N MS SS N MS SS N MS SS N MS SS N MS SS I 65.64 51.73 43.47 13.00 12.64 10.82 12.47 11.15 9.71 13.91 12.37 10.53 23.10 20.35 15.96 II 63.06 48.06 42.52 14.15 13.00 12.88 11.13 10.46 10.49 10.78 11.50 11.36 17.83 15.87 20.32 III 52.61 48.57 58.25 12.38 14.10 13.09 11.23 11.77 11.81 12.22 12.08 12.68 19.33 21.59 24.80 IV 80.83 65.38 38.85 16.67 14.61 10.12 13.69 12.27 8.74 14.08 13.70 8.69 33.78 28.79 10.04 V 49.42 65.17 34.83 14.03 15.71 10.52 12.22 11.70 8.61 13.51 13.20 8.87 28.18 28.00 10.30 VI 54.35 46.70 34.13 11.52 11.51 8.74 11.27 9.51 8.37 12.32 10.11 9.54 20.94 13.33 11.71 VII 43.21 35.46 36.71 11.15 11.05 9.30 10.48 9.11 7.62 11.45 9.75 7.45 16.01 12.79 8.90 VIII 38.81 42.45 43.62 12.13 10.25 10.13 11.38 9.33 9.11 11.39 10.37 8.25 17.98 13.89 9.28 IX 60.70 43.30 42.06 12.76 10.13 11.89 11.12 8.82 9.95 11.94 10.31 10.10 18.48 14.04 12.93 Mean 56.51 49.65 41.60 13.09 12.56 10.83 11.67 10.46 9.38 12.40 11.49 9.72 21.74 18.74 13.80 Contribution of each character to the divergence No. of times appearing first in ranking 25 27 23 0 4 14 1 3 0 0 0 2 47 18 0 % of contribution toward total divergence 0.90 0.97 0.83 0.00 0.14 0.50 0.04 0.11 0.00 0.00 0.00 0.07 1.69 0.65 0.00 (Contd…) 1447 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 Cluster 100 kernel weight (g) Ear weight (g) SCMR Chlorophyll fluorescence Leaf firing score N MS SS N MS SS N MS SS N MS SS N MS SS I II 22.22 29.70 17.80 13.69 16.33 16.98 82.36 51.18 53.07 45.00 47.64 63.71 50.19 41.52 40.15 38.84 36.71 41.39 0.69 0.62 0.64 0.58 0.61 0.61 0.58 0.83 3.93 4.00 5.03 4.38 III 21.39 20.52 19.97 90.04 75.27 81.88 47.42 44.81 43.22 0.71 0.64 0.61 0.88 3.50 4.00 IV 27.13 20.70 12.31 139.81 95.39 23.84 54.86 48.12 33.75 0.70 0.64 0.41 0.50 3.07 7.45 V 21.93 19.81 9.26 90.36 121.24 25.84 48.40 47.85 29.45 0.67 0.69 0.33 0.80 2.50 8.33 VI 19.95 14.61 10.34 60.23 26.60 19.48 49.58 37.19 31.14 0.66 0.43 0.57 0.83 5.91 7.46 VII 20.06 12.26 9.50 41.17 19.65 15.45 44.12 31.64 28.88 0.64 0.35 0.53 1.02 6.00 8.20 VIII 21.77 13.54 10.87 54.06 23.40 20.16 43.56 34.07 27.58 0.46 0.56 0.55 1.36 5.86 7.50 IX 19.97 12.06 12.50 54.26 21.20 36.97 46.04 34.56 33.80 0.56 0.61 0.55 1.08 5.36 6.00 Mean 22.68 16.11 13.12 73.72 53.42 37.22 47.30 39.69 33.99 0.63 0.57 0.53 0.88 4.46 6.48 Contribution of each character to the divergence No. of times appearing first in ranking 1 2 13 498 650 1130 44 45 47 1271 1551 1223 1 0 0 % of contribution toward total divergence 0.04 0.07 0.47 17.95 23.42 40.72 1.59 1.62 1.69 45.80 55.89 44.07 0.04 0 0 (Contd….) 1448 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 Cluster Harvest index (%) Grain yield per plant (g) N MS SS N MS SS I 37.80 27.22 21.80 65.43 39.03 31.17 II 21.83 25.37 29.30 36.83 32.80 48.65 III 39.32 35.30 36.18 70.33 57.23 61.23 IV 44.84 39.52 13.84 118.72 76.78 13.82 V 41.31 43.95 13.70 72.89 99.48 12.56 VI 31.15 16.97 14.81 46.04 18.18 12.61 VII 23.76 13.98 11.41 29.43 12.26 9.69 VIII 32.65 15.63 11.76 40.52 14.97 11.94 IX 27.38 14.97 21.64 38.23 14.15 26.20 Mean 33.34 25.88 19.38 57.60 40.54 25.32 Contribution of each character to the divergence No. of times appearing first in ranking 54 309 79 5 93 25 % of contribution toward total divergence 1.95 11.14 2.85 0.18 3.35 0.90 Note: N- Normal; MS- moderate stress; SS- severe Stress; ASI-Anthesis Silking Interval; SCMR: Spad Chlorophyll Meter Reading 1449 Int.J.Curr.Microbiol.App.Sci (2018) 7(6): 1441-1451 The genotypes with early pollen shedding and silk emergence and less ASI and least leaf firing score were also included in these clusters indicating that these genotypes were believed to be drought tolerant. Per se performance of these genotypes revealed that these genotypes mature earlier before it coincides with drought and high temperatures during flowering and pollination. As the maize production will be reduced when there is increased ASI due to pollen insufficiency during silk emergence (Hall et al., 1982), or due to pollen dammage under hot dry conditions (Schoper et al., 1986). Keeping in view of this and the cluster pattern the genotypes included in clusters IV and VIII, V and VII and III and V with higher inter cluster distance between them could be involved in crossing programme which would give high manifestation of heterosis with drought tolerance. References AshoftehBeiragi, M., SiahSar, B.A., KhavariKhrasani, S., Golbashy, M., Mahdi Nejad, N. and Ali Zade, A. 2010. Effects of genotype by environment interactions on morphological traits, yield and yield components of new grain corn (Zea mays L.) varieties. Journal of Agroecology. 2(1):136-145. 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J. and Vailas, B. L., 1986. Maize pollen viability and ear receptivity under water and high temperature stress. Crop Science. 26:1029-1033. Umar, U. U., Ado, S.G., Aba, D.A. and Bugaje, S.M. 2015. Studies on genetic 1450