Final SPH -JHS Coverpage 17-1 Jan 2022 single 51 J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 This is an open access article d istributed under the terms of Creative Commons Attribution-NonCommer cial-ShareAl ike 4.0 International License, which permits unrestricted non-commercial use, d istribution, and reproduction in any med ium, provide d the original author and source are credited. Original Research Paper INTRODUCTION Squash (Cucurbita pepo L.) is an economically important species of the Cucurbitaceae family that r epr esents one of the most pr imitive gener a (Cucurbita) in the plant kingdom (Tadmor et al., 2005). Squash is monoecious vegetable crop and familiar with its different traditional name like Zucchini (Italy); Cucuzza (Saudi Arabia), Courgette (America); Marrow (Ireland and Britain) and Baby marrow (South Africa). It is grown throughout the temperate, sub-tropical, and tropical regions, native to eastern United States and Mexico and also cultivated worldwide for its fruits (Bisognin, 2002). The major economic value of this crop is based mainly on the culinary use of immature fruits which have relatively high nutritional and medicinal value as compared to other vegetable crops. Its nutritional profile consists of various organic compounds, nutrients, vitamins and minerals, that are responsible for providing all its impressive health benefits (Kulczynski and Gramza- Michałowska, 2019). It is also a very good source of carotenoids, important anti-inflammatory and anti- oxidant compounds (Deppe, 2015) and because of its low caloric value treated as weight loss diets (Fageria et al., 2012). So, keeping its importance in mind, increase the global production is one of the important ways to ensure food security. Bangladesh is one of the most densely populated country in the world having over 160 million people and based on its current growth trends a projected population will be over 200 million by 2050 (USAID, 2017). To meet up the food demand for its uprated population, increasing the crop production in per unit areas of land is the most effective ways to ensure the food security. Squash is one of the important vegetable crops which can assure the nutritional security from its present nutritional shortage (per capita deficiency of vegetables 158 g) in Bangladesh (Anon., 2018). Topographically, Bangladesh has diverse land area Assessing the genetic diversity of squash (Cucurbita pepo L.) genotypes based on agro-morphological traits and genetic analysis Sajid M.B., Sarker K.K., Monshi F.I., Sultana S., Monika M.A. and Bhuiyan M.S.U.* Department of Genetics and Plant Breeding, Faculty of Agriculture Sylhet Agricultural University, Sylhet - 3100, Bangladesh *Corresponding author E-mail: bhuiyanmsu.gpb@sau.ac.bd ABSTARCT An experiment was conducted to estimate the genetic variability of 15 indigenous and exotic squash genotypes assessing 18 quantitative and 8 qualitative traits. Results showed that the accessions have high variability in qualitative traits like fruit size, fruit shape, fruit skin colour, lustre and fruit productivity, which allowed selection for considerable gains in these characteristics. The quantitative traits such as fruits yield per plant, fruit weight, length, diameter and total yield per hectare showed the greater phenotypic coefficient of variation (PCV) along with higher heritability which can helps to identify desirable genotypes. The obtained significant and positive correlation between fruit yield with number of leaves, nodes, fruit length, weight and number could assist in selection to improve this crop. Cluster analysis resulted in the formation of 4 groups, confirming the genetic variability among the studied genotypes. Eventually, the attained PCA analysis result revealed that the number of fruits per plant, fruit yield per plant, fruit length and days to first female flowering are the most discriminating traits which are accelerating the variability in squash genotypes. On the basis of the yield and its attributing traits, First Runner is the best genotype suited in this environment. Keywords: Genetic analysis, genetic variability, heritability, morphological traits and squash 52 Sajid et al J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 which is favorable for the crop diversification and production, however, squash can grow easily in any types of soil even in unproductive and marginal land areas. In addition, more economic growth can be achieved by producing vegetables like squash which will ultimately uplift the socio-economic condition of the farmers. Thus, there is urgent need to initiate research on squash especially for its vertical expansion and var ieta l improvement. Although, squash is becoming important vegetable crop in Bangladesh, ther e is little infor ma tion a va ila ble a bout its improvement and till date only a single variety has been recommended for winter season. In Bangladesh, few researchers have taken initiatives for studying its growth and effects of fertilizers on it (Akhter et al., 2018; Baby et al., 2021) but genetic variability study has not been taken up yet. Breeding for high-yielding crops require information available on the germplasm and the relationship among the agronomic traits as well as the degree of environmental influence (El-Hadi et al., 2014). For its crop improvement, determining the extent of genotypic and phenotypic variability among geographical areas is important (Muralidhara and Narasegowda, 2014). Quantitative and qualitative determination (morphological characterization) of the degree of var iation of traits present in genetic resources is important for vegetable breeding programs (Ba lka ya et al. , 2010; Gomes et al. , 2020). Morphological characterization is the first step followed by quantitative traits in the description and classification of genetic resources (Balkaya et al., 2010). However, only a few studies have focused on variability analysis in relation to morphological and yield contributing quantitative traits with squash accessions. Therefore, the present research has been underta ken for the impr ovement of squash by assessing its genetic variability traits. In Bangladesh, squash cultivation in summer season is challenging because of the severe attack of pests and diseases, excessive light and temperature, high rainfall and high labour cost etc. Meanwhile, a very few resear ch works r elating to its ada ptability a nd va riability have been conducted in Bangladesh especially in Sylhet region where huge amount of land has remained fallow (14% of the total land) for a long time (BBS, 2018). So, there is a great opportunity to increase squash production in this region to meet up the vegetable and nutritional requirement of the country. Considering the above points of view, the present study has been under taken to know the extent of genetic variability, heritability and genetic advance for different traits of squash genotypes in Sylhet region. MATERIALS AND METHODS The experiment was conducted at the Research field of the Department of Genetics and Plant Breeding, Faculty of Agriculture, Sylhet Agricultural University, Bangladesh during the period October 2019 to January 2020. Fifteen indigenous and exotic genotypes (Table 1) of squash were used in this experiment that were collected from the different parts of Bangladesh as well as from the other countries. The exper iment was laid out in a Randomized Complete Block Design (RCBD) with thr ee replications. The experiment was divided into three blocks and each consisted of 15 plots. Each unit plot size was 1 x 2.3 m2. Altogether, there were 45 unit plots in experiment and required 300 m2 land. Both row to row and plot-to-plot distances were 0.5 m. The treatments were randomly assigned to each of the block. Each unit plot had 5 pits and in each pit 2 seeds were sown. After germination only one plant was allowed to grow. The land was prepared by ploughing and cross ploughing and different inter cultural oper a tions wer e a ccomplished a ccor ding to recommended BARI Squash variety (BARI, 2018). The data were recorded based on 18 quantitative yield contributing traits i.e. plant height in cm at first harvest (PH), stem diameter in cm at first harvest (SD), number of leaves at first harvest (NL), number of nodes at first harvest (NN), days to flower bud initia tion (DFBI), days to first male flowering (DFMF), days to first female flowering (DFFF), number of male flowers from flowering to last harvest (NMF), number of female flowers from flowering to last harvest (NFF), viable pollen in percentage (VP), days to first harvest (DFH), nodes at first fruit harvest (NFFH), fruit length in cm (FL), fruit diameter in cm (FD), fruit weight in g (FW), number of fruits per plant (NFPP), fruit yield per plant in Kg (FYPP), total yield in t/ha (TY) and 8 qualitative traits i.e. plant vigor, pubescence, stem shape, flower color, fruit size, fruit shape, fruit skin color and luster. The recor ded data on various parameters were analyzed to find out the statistical significance of the experimental results. Mean and standard deviation were calculated using Microsoft Excel software 2010. 53 Assessing the genetic diversity of squash genotypes The significance of the difference between treatment means, coefficient of variation (CV) was calculated by the Least Significance Difference (LSD) test for the interpretation of the results (Gomez and Gomez, 1984). Then the tabulated results were analyzed using one-way analysis of variance (ANOVA) and statistical differences between the means were estimated using Duncan’s multiple range test (DMRT) at 1% or 5% or 0.1% probability with the help of statistical “R” software. Estimation of Genetic parameters Estimation of genotypic and phenotypic variances: Genotypic and phenotypic variances were estimated according to the formula given by Johnson et al. (1955). Estimation of coefficient of variability (genotypic and phenotypic coefficient of variation): Both phenotypic and genotypic coefficient of va riability for a ll characters w estimated using the formula of Burton (1952). PCV and GCV were classified into three categories viz., Low (< 10%), Moderate (10-20%) and High (> 20%) as suggested by Sivasubramanian and Madhavamenon (1973). Heritability in broad sense (h2bs): The broad sense heritability (h2bs) was estimated for all characters as Table 1. Name and source of the Squash genotypes used in the experiment Genotypes Name of the genotypes Origin Remarks G1 First Runner South Korea Indigenous G2 Alaska Australia Indigenous G3 Blossom House Netherlands Indigenous G4 Balam House USA Indigenous G5 Cheonlima South Korea Indigenous G6 Hungnong Squash South Korea Indigenous G7 Runner USA Indigenous G8 SQ-001 Australia Exotic G9 SQ-002 Australia Exotic G10 SQ-003 Australia Exotic G11 SQ-004 Australia Exotic G12 SQ-005 Australia Exotic G13 SQ-006 Australia Exotic G14 SQ-007 Australia Exotic G15 SQ-008 Australia Exotic the ra tio of genotypic var ia nce to the total of phenotypic variance as suggested by Hanson et al., (1956). Heritability estimates in cultivated plants could be placed in the categories viz. as Low (0-30%), Moderate (30-60%) and High (>60%) as suggested by Robinson (1966). Genetic advance (GA): The expected genetic gain or advance for each character was estimated by using the method suggested by Johnson et al., (1955). Genetic advance was classified as high (>20%), moderate (10- 20%) and low (<10%). Further the Genetic advance as per cent of mean was computed by using the formula which was given by Burton (1952). Genetic advance as per cent mean was categorized into groups viz., Low (< 10%), Moderate (10-20%) and High (> 20%) as suggested by Johnson et al. (1955). Correlation estimation Simple correlation coefficient (r) among 12 important parameters of Squash accessions was estimated according to Singh and Chaudhury (1985). Again, cluster analysis (CA) was carried out according to Mahalanobis (1936). It divides genotypes into groups on the basis of a data set into some number of mutually exclusive groups. Furthermore, principal component analysis (PCA) was computed from J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 54 correlation matrix and genotype scores obtained for the first components with roots greater than unit (Jeger et al., 1983). It provides two dimensional plots, which helps in separating different populations involved. Contribution of the different characters towards variability was discussed from the latent vectors of the first three principal components. However, Mean data for each character was subjected to multivariate analysis techniques viz., principal component analysis (PCA), cluster analysis (CA) and also the simple correlation coefficient analysis were done by computer using the STATA 14.0 software. RESULTS AND DISCUSSION Mean performance or genotypes for vegetative characters In this experiment, fifteen indigenous and exotic squash genotypes have been characterized according to morphological traits and genetic analysis. Although morphological characteristics depends on its external factors but it is parallelly important to support these morphological variations along with their genetic studies. Results of mean performance of different squash genotypes based on different agronomic and yield contributing traits indicated that there was a significant difference in mean performance among all the genotypes. This difference could be resulted from the genetic variation a mong the studied squash genotypes which is also supported with the results of other previous studies on squash (Gomes et al., 2020; Tsivelikas et al., 2009; Villanueva-Verduzco et al., 2020). A wide genetic diversity was also reported in the experimental results of Egusi-melon (Olaniyi et al., 2011) and cucumber (Arunkumar et al., 2011). In case of vegetative characters, results showed a great significant variation for all the characters among the squash genotypes (Table 2). The highest plant height at first harvest was found in SQ-002 (36.05 cm) and the lowest was in Balam House (32.17 cm). Diameter of stem during first harvest was highest in First Runner (13 cm) and the lowest was in Balam House (9.21 cm). Number of leaves, considered as an important parameter for fruit yield, was the maximum in two genotypes i.e., Cheonlima (25) and SQ-001 (25). Additionally, the maximum number of nodes per plant was recorded in First Runner (14.3) and the minimum was recorded from Balam House (11.53). Different types of leaves, flowers and fruits were observed in studied squash genotypes those are presented in Figure 1. Therefore, it was observed that, the squash genotypes showed a wide range of variation in their growth-related morphological traits. Variation in morphological (Ozturk et al., 2021) as well as anatomical features (Balkaya et al., 2010) is a common phenomenon among different Cucurbita species. Additionally, Esho and Jasim (2020) found a wide range of variability for number of nodes for the first female flower in Squash. Moreover, considering the reproductive (flowering) characters, the results showed a significant variation on days to flower bud initiation, days to first male and female flowering, number of male and female flowers and viable pollen rate for all the squash genotypes (Table 3). The genotype Runner took minimum days to first flower bud initiation (19.29 days) while the genotypes First Runner took the lowest day to first male flowering (30.54 days) and the genotype Runner was the earliest genotypes to first female flowering (35.73 days). In most of the genotypes, female flowers were emerging before ma le flowers with some exceptions (Table 3). Significant difference for days to female flowering was also reported by Nahar et al., (2016) in sweet gourd genotypes. In addition, the male flower numbers outnumbered the female flower numbers during the experimental period for all the genotypes. Both the male and female flowers formed simultaneously right from the outset. Additionally, pollen viability was of special interest to see the degree of influence it exerts upon fruit and seed setting. The percentage of pollen viability helps us in selecting the parents for crossing in a hybridization program. The mean va lues of fertile (viable) pollen showed statistically almost similar results for all the 15 genotypes (Table 3). This result indicated a high possibility of cross pollination among the genotypes and this could lead a high level to of genetic variability in squash genotypes. Some other yield contributing traits considering the fruiting characters i.e., days to first harvest, number of nodes at first harvest, length and diameter of fruit per plant, fruit weight, number of fruits per plant, fruit yield per plant and total yield showed a significant variation among the genotypes (Table 4). The days to first harvest ranged from 54 to 62.67 days in Runner and Balam House respectively with a mean value of 58.3 days. Low variation was observed among the genotypes with respect to number of nodes at first fruit Sajid et al J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 55 Fig. 1. Variation in leaves, flowers and fruits of fifteen squash genotypes harvest (range: Runner 5.03 to Blossom House 6.5; mean: 5.78). The maximum fruit length was seen in the genotypes First Runner (45.58 cm), Hungnong Squash (45.42 cm) and Cheonlima (44.1 cm) while the minimum length of fruit was observed from SQ- 007 (27.62 cm). Similar findings of significant variation on days to first harvest, number of nodes at first harvest and fruit length were also reported by Esho and Jasim (2020) in squash, Mohsin et al. (2017) in pumpkin and Nahar et al. (2016) in sweet gourd. Significant variation in fruit diameter (range: Alaska 17.47 cm to SQ-003 38.11 cm) was found among squash genotypes. Significant variation was also observed by Balkaya et al. (2010) in winter squash from the black sea region of Turkey. The individual fruit of First Runner (1165.5 g) had the highest weight followed by SQ-001 (1013.03 g) and Hungnong Squash (1002.08 g). The lowest single fruit weight was recorded in Runner (742.24 g). The variation of fruit weight could be due to the genetical, physiological and environmental influence. Abdein et al. (2021) reported similar results in respect of single fruit weight in summer squash. Number of fruits per plant was the maximum in case of Runner (10.2) proceeded to First Runner (10) and SQ-001 (9.53). Accession Balam House produced the minimum number (6.2) of fruits per plant. Rana et al. (2016) also observed significant va riation in number of fr uits per plant a mong cucumber genotypes. The yield of fruits per plant eventually contributes the total yield of fruit for each genotype. Among the studied squash genotypes, total fruit yield was varied significantly. The maximum total yield of fruit was obtained in First Runner (89.43 t/ ha) preceded to SQ-001 (74 t/ha) and Cheonlima (63.48 t/ha) which was statistically different from other accessions, whereas the minimum total yield of fruit was obtained in case of Balam House (35.78 t/ ha). These results corroborated with the findings of Akhter et al. (2018) in squash and Abdein et al. (2017) in sweet gourd. Uddain et al. (2019) also observed significant variation among the different genotypes of Zucchini squash in respect of weight of fruits per plant. Assessing the genetic diversity of squash genotypes J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 56 Genotypes Plant height Stem diameter Number of Number of (cm) (cm) leaves nodes G1=First Runner 34.13bcde 13a 24.6ab 14.3a G2=Alaska 33.33def 12.13b 22cde 12.93bcd G3=Blossom House 33.68cdef 11.45cde 22.2cde 11.73ef G4=Balam House 32.17f 9.21j 20.27f 11.53ef G5=Cheonlima 33.61cdef 11.6bcd 25a 14.27a G6=Hungnong Squash 32.51ef 11.63bcd 23.27bcd 12.07def G7=Runner 34.69abcd 11.89bc 23.87ab 13.53abc G8=SQ-001 35.11abcd 10.9efg 25a 14ab G9=SQ-002 36.05a 11.29cde 21.2ef 13.93ab G10=SQ-003 34.31abcde 11.36cde 21.67ef 11.87def G11=SQ-004 35.92ab 10.03hi 23.47abc 11.47f G12=SQ-005 34.59abcd 11.05def 21.47ef 11.87def G13=SQ-006 35.23abc 10.48fgh 21.8def 12.6cde G14=SQ-007 34.03cde 9.75ij 21.07ef 13.6abc G15=SQ-008 34.61abcd 10.38jhi 21ef 12.93bcd Mean 34.27 11.08 22.52 12.84 SD 0.99 0.32 0.75 0.54 LSD 1.81 0.66 1.57 1.09 Means followed by the same letter (s) in a column do not differ significantly Table 2. Mean performance of squash genotypes for vegetative characters at first harvest Table 3. Mean performance of squash genotypes for various flowering characters Days to Days to Days to Number Number Viable Genotypes flower bud first male first of male of female pollen initiation flowering femal flowers flowers (%) G1=First Runner 20.86def 30.53f 35.80h 18.73defg 13.13b 91.1abc G2=Alaska 22.20bcd 32.47ef 37.73g 18.4fg 12.87bc 89.75bc G3=Blossom House 23.69ab 31.73ef 40.20cde 18.53efg 10.67ef 87.13d G4=Balam House 24.58a 33.87e 41.80b 18.93defg 10.67ef 84.47e G5=Cheonlima 22.70bc 32.26ef 40.33cde 19.33bcdef 12.8bc 89.89abc G6=Hungnong Squash 22.89abc 33.13e 41bcd 20.6a 10.6ef 89.11cd G7=Runner 19.29f 37.73cd 35.73h 20.13ab 14.13a 90.28abc G8=SQ-001 21.49cde 36.53d 39.93def 18.40fg 12.93bc 90.42abc G9=SQ-002 20.05ef 42.87a 43.06a 20.06abc 12cd 89.88abc G10=SQ-003 22.67bc 43.47a 36h 19.73abcd 11e 92.36a G11=SQ-004 22.08bcd 42.33a 41.2bc 19.6abcd 12.8bc 89.99abc G12=SQ-005 21.99bcd 42.40a 39.06f 19.06cdef 12.53bc 91.02abc G13=SQ-006 22.59bc 39.27c 41.27bc 19.46bcde 12.8bc 91.79ab G14=SQ-007 21.67cde 39.53bc 36.27h 18.73defg 9.87f 89.91abc G15=SQ-008 22.48bcd 41.80ab 39.53f 17.93g 11.27de 89.86abc Mean 22.08 37.33 39.26 19.18 12 89.80 SD 0.92 0.52 0.53 0.53 0.48 1.28 LSD 1.71 2.33 1.07 1.06 0.99 2.54 Means followed by the same letter (s) in a column do not differ significantly Sajid et al J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 57 Table 4. Mean performance of squash genotypes for various fruit characters Genotypes Days to Nodes Fruit Fruit Fruit No of Fruit Total first at first length diameter weight fruits yield yield harvest fruit (cm) (cm) (g) per per plant (t/ha) harvest plant (Kg) First Runner 58.47cde 5.53cde 45.58a 19.67ef 1165.50a 10.2a 11.92a 89.43a Alaska 58.33cde 5.58bcd 34.43b 17.47f 797.60gh 8.90de 7.14efg 53.53ef Blossom House 61.80a 6.50a 31.30de 20.06ef 816.70efg 7.00h 5.73h 42.98h Balam House 62.67a 6.34ab 31.10de 19.39ef 810.10fgh 6.20i 4.77i 35.78i Cheonlima 58.87cd 5.77abc 44.10a 19.72ef 948.90bc 8.90def 8.46c 63.48c Hungnong Squash 59.8bc 5.90abcd 45.42a 19.19ef 1002.80b 7.93g 7.99cde 59.98cd Runner 54.00h 5.03e 27.62f 21.19e 742.24h 10.00ab 7.22efg 54.13ef SQ-001 55.80g 5.19de 32.2cd 25.48cd 1013.00b 9.50bc 9.95b 74.00b SQ-002 61.07ab 5.8abcd 34.4b 21.02e 909.30cd 9.10cd 8.31cd 62.33cd SQ-003 55.93fg 6.06abc 11.84g 38.11a 921.10bcd 8.13g 7.47def 56.05de SQ-004 57.73de 6.28abc 34.48b 24.59d 896.90cde 8.30fg 7.47def 56.05de SQ-005 56.87efg 6.16abc 30.06e 20.99e 822.30efgh 8.27g 6.80fg 51.0fg SQ-006 60.00bc 5.92abc 34.10bc 18.85ef 863.90defg 8.93d 7.90cde 58.88cd SQ-007 55.60gh 5.06e 11.43g 23.77b 873.50defg 7.00h 6.34gh 47.55gh SQ-008 57.53def 5.55bcd 31.7de 27.42c 987.18bc 8.50ef 8.21cd 61.55cd Mean 58.29 5.78 31.97 22.93 904.74 8.46 7.71 57.78 SD 0.84 0.43 0.97 1.18 49.66 0.28 0.55 4.18 LSD 1.69 0.79 1.92 2.65 93.10 0.55 0.92 6.88 Means followed by the same letter (s) in a column do not differ significantly Variability of yield contributing characters The identification and utilization of an extensive germplasm is the prerequisite for improvement of a specific crop by adapting an appropr iate plant breeding program. Regarding these, precise and exhaustive descriptions of the genotypes with the patterns of their genetic diversity can promote the introgression of current squash genetic base. In varia bility studies, high value of coefficient of variation (%CV) was found in number of nodes per plant at first harvest (5.11%), fruit yield per plant (7.13%), fruit diameter (6.89%), and fruit weight (6.14%). On the other hand, the lowest CV value was recorded in days to first female flowering (1.63%). The estimated genotypic variance (σ2g) was higher than their corresponding environmental variances (σ2e) for all the traits, except for plant height and number of nodes at first harvest that was very negligible (Table 5). Among the 15 accessions, the high magnitude of genotypic coefficient of variation (GCV) along with phenotypic coefficient of variation (PCV) were recorded for fruit diameter followed by the fruit yield per plant, total yield/ha and number of female flowers per plant. Very low level of GCV along with PCV was found in case of viable pollen percentage along with plant height at first harvest. Most of the characters had low GCV values than PCV values indicated consider a ble influence of envir onment in the expression of all the traits (Table 6). High GCV indicates the presence of exploitable genetic variability for the tr a its, which ca n fa cilita te selection (Muralidhara and Narasegowda, 2014; Yadav et al., 2009). Heritability estimation gives an insight into the extent of genetic control to express a particular trait and phenotypic reliability in predicting its breeding value (Ndukauba et al., 2015, Nahar et al., 2016). The heritability in combination with genetic advance (GA) Assessing the genetic diversity of squash genotypes J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 58 Table 5. Estimates of genetic parameters for various characteristics in squash genotypes Parameters Mean MSS CV % σ2g σ 2 ph σ 2 e Plant height (cm) 34.27 3.67** 3.16 0.83 2.01 1.17 at first harvest Stem diameter (cm) 11.08 2.90*** 3.55 0.91 1.07 0.16 at first harvest Number of leaves 22.52 7.26*** 4.17 2.13 3.01 0.88 at first harvest Number of nodes 12.84 3.19*** 5.11 0.92 1.35 0.43 at first harvest Days to flower bud 22.08 5.26*** 4.64 1.40 2.45 1.05 initiation Days to first male 37.33 65.33*** 3.73 21.13 23.07 1.94 flowering Days to first female 39.26 17.29*** 1.63 5.63 6.04 0.41 flowering Number of male 19.18 1.71*** 3.29 0.44 0.84 0.40 flowers Number of female 12.00 4.56*** 4.95 1.40 1.76 0.35 aflowers Viable pollen (%) 89.80 10.80*** 1.69 2.83 5.14 2.31 Days to first harvest 58.30 18.23*** 1.74 5.73 6.76 1.03 Nodes at first 5.78 0.63* 8.24 0.14 0.36 0.23 fruit harvest Fruit length (cm) 31.97 96.72*** 3.59 31.8 33.12 1.32 Fruit diameter (cm) 22.93 92.99*** 6.89 30.17 32.67 2.50 Fruit weight (g) 904.74 34814*** 6.14 10573 13668 3095 Number of fruits 8.46 3.74*** 3.87 1.21 1.32 0.11 per plant Fruit yield per 7.71 8.57*** 7.13 2.76 3.06 0.30 plant (Kg) Total yield (t/ha) 57.78 477.72*** 7.12 153.6 170.5 16.93 * Significant at 5% level of probability; ** Significant at 1% level of probability and; *** Significant at 0.1% level of probability. increases the intensity of selection in a breeding program. High heritability indicates less environmental influence in the observed variation (Abdein et al., 2017). Thus, genetic advance measures the difference between the mean genotypic values of the original population from which these are selected. Almost all the attributes showed high heritability except nodes at first harvest (38.89%) and plant height (41.49%). The highest estimates of genetic advance (in percent of mean) were determined for total yield/ha, fruit yield per plant, fruit weight, fruit length, fruit diameter and number of fruits per plant (Table 6). Correlation analysis (Table S1), the trait plant height had significant positive correlation with days to first male flowering, number of female flowers, number of fruits per plant, and fruits yield per plant. Other attributes such as number of leaves at first harvest was negatively and significantly correlated with the days to first male flowering. The number of nodes at first harvest showed positive and significant correlation with number of female flowers, single fruit weight, number of fruits per plant and yield of fruits ton per hectare. The number of female flowers per plant had significant and positive correlation with number of Sajid et al J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 59 Table 6. Estimation of heritability and genetic advance (GA) in squash genotypes Parameters GCV PCV ECV Herita- GA GA (% bility (5%) mean) Plant height (cm) at first harvest 2.67 4.14 1.47 41.49 1.21 3.53 Stem diameter (cm) at first harvest 8.61 9.34 0.73 85.05 1.81 16.34 Number of leaves at first harvest 6.48 7.71 1.22 70.76 2.53 11.23 Number of nodes at first harvest 7.47 9.05 1.58 68.15 1.63 12.70 Days to flower bud initiation 5.36 7.10 1.73 57.14 1.84 8.33 Days to first male flowering 12.31 12.87 0.56 91.58 9.07 24.28 Days to first female flowering 6.04 6.26 0.22 93.21 4.72 12.02 Number of male flowers 3.46 4.78 1.32 52.38 0.99 5.16 Number of female flowers 9.86 11.04 1.18 79.73 2.18 18.14 Viable pollen (%) 1.87 2.53 0.65 55.05 2.57 2.86 Days to first harvest 4.11 4.46 0.35 84.76 4.54 7.79 Nodes at first fruit harvest 6.47 10.38 3.91 38.89 0.48 8.31 Fruit length (cm) 17.64 18.00 0.36 96.01 11.38 35.61 Fruit diameter (cm) 23.95 24.93 0.98 92.35 10.87 47.42 Fruit weight (g) 11.37 12.92 1.55 77.36 186.31 20.59 Number of fruits per plant 13.00 13.58 0.58 91.67 2.17 25.64 Fruit yield per plant (Kg) 21.55 22.69 1.14 90.2 3.25 42.16 Total yield (t/ha) 21.45 22.60 1.15 90.07 24.23 41.93 Assessing the genetic diversity of squash genotypes J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 fruits per plant. Fruit length had significant and positive correlation with fruit weight, number of fruits per plant and fruit yield per plant and also significantly and negatively correlated with fruit diameter. One of the most impor ta nt tr a its of fr uit weight wa s significantly and positively correlated with fruit yield per plant. Highly significant and positive association of fruit yield per plant was recorded with the plant height, number of leaves per plant, number of nodes at first harvest, fruit length, fruit weight and number of fruits per plant. Similar findings were noticed by Gomes et al. (2020) in Brazilian germplasm of winter squash and Mohsin et al. (2017) in pumpkin. In cluster analysis (CA), the cluster means of 15 accessions of squash showed that the mean values of the cluster s varied in magnitude for ma ximum characters (Table S2. The cluster II showed the highest total yield value along with the second highest fruit length and fruit diameter value, the highest number of fruits per plant value and the highest yield per plant value, which could contribute to total yield. From the clustering comparison of the means, it was found that cluster II expressed the best agronomic quantitative yield contr ibuting tr a its a nd yield potentia ls. Comparing the means of all clusters it was showed that First Runner from cluster I, Cheonlima and SQ- 001 from cluster II, SQ-008 from cluster IV and SQ- 006 from cluster III expressed the best quantitative and qualitative traits and yield potentials which could be effective for the improvement of yield of squash (Fig. S1). Gomes et al. (2020) reported similar results in Brazilian germplasm of winter squash. Ene et al. (2016) also reported similar findings in cucumber genotypes. This suggests that the genotypes of squash of the same origin have diverse and broad genetic basis. Principal component analysis (PCA) is an important multivariate technique used to examine associations between cha r a cter s a nd mea sur es the genetic variability of genotypes (Balkaya et al., 2010; Ene et al., 2016). The three principal components (PC1, PC2 and PC3) can be retained to describe the variability among the squash genotypes (Table S3). The first three components explain 63% of the total genetic variation 60 Sajid et al J. Hortl. Sci. Vol. 17(1) : 51-62, 2022 while the first two principal components accounted for 53% and first component accounted for 32.4% of the total genetic variation among the 18 a ttributes describing 15 different genotypes. The first component (PC1) described 32.4% of the total variation, second component (PC2) explained 20.6% of the total variability and the third component (PC3) evaluated only 10.02% of the total variation. The PC1 was positively and strongly associated with the plant height (0.18), stem diameter (0.29), number of leaves (0.29), number of nodes (0.28), number of female flower (0.30), viable pollen percentage (0.25), fruit length (0.13), fruit weight (0.21), number of fruits per plant (0.39) and fruit yield per plant ( 0.36). The PC2 was positively and highly associated to days to first harvest (0.36) and fruit length (0.47). In case of PC3, it was strongly associated with plant height (0.47), days to first male flowering (0.39), days to first female flowering (0.49), number of male flower (0.31), number of female flowers (0.24) and fruit length (0. 16). Wher ea s, mor phologica l (qua lita tive) characterization showed that limited variability present in the genotypes in respect of some characters viz., plant vigor, stem and leaf pubescence, and flower colour. Significant variability was observed in case of fruit shape, fruit size, fruit skin color and luster respectively. This finding corroborated with the findings of El-Hadi et al. (2014) in squash and partly agrees with the results by Khawla et al. (2019) in Tunisian squash and Nahar et al. (2016) in sweet gourd. Qualitative characterization Selection of qualitative traits is also very important in successful crop breeding program. Significant variation was found under this research in relation to different qualitative traits of squash accessions. Most significant variation was found in fruit size, fruit shape and fruit skin color followed by lustre (Table S4). The fruit colour, size, shape was morphologically different because of the genetic makeup present in the studied genotypes (Fig. 1). A similar morphological variation of qualitative traits was reported by Uddain et al. (2019) in Zucchini squa sh, Mur a lidha r a a nd Narasegowda (2014) in pumpkin, Nahar et al. (2016) in sweet gourd and Ene et al. (2016) in cucumber. CONCLUSION High heritability coupled with high genetic advance observed for total yield/ha, fruit yield per plant, fruit weight, fruit length and fruit diameter in this set of germplasm indicated that, these traits will be the main contributing factors for further crop improvement programme. Significant and positive association of fruit yield per plant with number of leaves per plant, number of nodes at first harvest, fruit length, fruit weight and number of fruits per plant suggested that, these tr aits were inter-related a nd collectively contributed to the final yield of squash. The principal component analysis showed that number of fruits per plant, fruit yield per plant, fruit length and days to first female flowering were the most discriminating factors that accounted for the genetic diversity of squash and would be considered for squash improvement program. 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(Received: 24.112021; Revised: 06.03.2022; Accepted :10.03.2022) 00 A Final SPH -JHS Coverpage First 2 pages.pdf 00 Content and in this issue.pdf 01 Mohan Kumar G N.pdf 02 Meera Pandey.pdf 03 Biradar C.pdf 04 Varalakshmi B.pdf 05 Vijayakumari N.pdf 06 Barik S.pdf 07 Sajid M B.pdf 08 Ranga D.pdf 09 Usha S.pdf 10 Manisha.pdf 11 Amulya R N.pdf 12 Akshatha H J.pdf 13 Adak T.pdf 14 Sujatha S.pdf 15 Gowda P P.pdf 16 Subba S.pdf 17 Dhayalan V.pdf 19 Ahmed S.pdf 20 Vishwakarma P K.pdf 21 Deep Lata.pdf 22 Udaykumar K P.pdf 23 Nayaka V S K.pdf 24 Sahel N A.pdf 25 Bayogan E R V.pdf 26 Rathinakumari A C.pdf 27 Yella Swami C.pdf 28 Saidulu Y.pdf 29 Sindhu S.pdf 30 Neeraj.pdf 31 Sivaranjani R.pdf 32 Rashied Tetteh.pdf 34 Sangeetha G.pdf 35 Shareefa M.pdf 36 Last Pages.pdf