Harnessing genetic diversity in papaya: Cluster analysis and its implications for breeding

Introduction

Papaya (Carica papaya L.) is a widely cultivated and consumed fruit in India, known for its rich nutritional and medicinal properties. Native to Central America and southern Mexico, papaya was introduced to India by the Portuguese in the 16 th century (Samaddar, 1985) [15] . Today, India is one of the world's largest producers of papaya, accounting for over 40% of global production (FAO, 2020). Papaya is a versatile fruit that is not only eaten fresh but also used in various culinary preparations, such as juices, jams, and chutneys. In Ayurveda, the traditional system of medicine in India, papaya is considered a valuable fruit for its medicinal properties, including anti-inflammatory, antioxidant, and immunomodulatory effects (Kumar et al., 2017) [7] . In India, papaya is grown in many states, with the major producing states being Andhra Pradesh, Gujarat, Madhya Pradesh, and Maharashtra (Anonymous, 2020). The fruit is available throughout the year, with the peak season being from May to October. Papaya is a diverse crop with numerous varieties, each with its unique caracteristics. Some popular varieties include CO-7, known for its sweet and tender fruit (Sundararajan et al., 2001) [22] , and Arka Prabhat, a hybrid variety developed by the Indian Institute of Horticultural Research, recognized for its high yield and resistance to papaya ringspot virus (Yadav et al., 2017) [23] . Other notable varieties are AC-119 (Singh et al., 2012) [19] , Dwarf Lilly (Kumar et al., 2015) [5] , Red Indian (Rao et al., 2013) [13] , Washington (Patel et al., 2018) [10] , Lucknow (Sharma et al., 2019) [16] , Coorg Honeydew (Kumar et al., 2016) [6] , Pant-2 (Singh et al., 2017) [10] , Shantha (Yadav et al., 2019) [24] , Line-21 (Rao et al., 2020) [14] , CO-8, CO-2, and CO-4 (Sundararajan et al., 2001) [22] , each offering distinct advantages in terms of yield, flavor, and disease resistance. Understanding the relationship between desired breeding populations and genetic diversity in available germplasm derived from Line x Tester mating design is crucial for designing effective breeding programs (Chowdhury et al., 2002) [2] . This knowledge enables breeders to select desirable parents for establishing new breeding populations. Moreover, genetic diversity or similarity information can help sustain long-term selection gain (Chowdhury et al., 2002) [2] . Genetic divergence is a valuable tool for selecting parents for hybridization to develop high-yield potential cultivars (Bhatt, 1973; Chowdhury et al., 2002) [1,2] . Multivariate analysis and generalized distance (D2) can be used to quantify genetic divergence (Bhatt, 1973) [1] . Crosses between genetically diverse parents tend to exhibit more heterosis than those between closely related parents (Singh, 1991; Shukla & Singh, 2002) [21,17] . Papaya germplasm exhibits considerable phenotypic variation for many horticultural traits (Ocampa et al., 2006) [9] . Therefore, this study aimed to investigate the genetic divergence and identify suitable genotypes for use in breeding programs to broaden the genetic base in papaya.

Methods and Materials

A research study was conducted at the Horticultural Research Centre of Sardar Vallabhbhai Patel University of Agriculture and Technology in Modipuram, Meerut, to evaluate the performance of papaya hybrids. The study was aligned with the current climatic and weather data for the Meerut region, which experiences a subtropical climate characterized by significant temperature fluctuations between summer and winter seasons (Kumar et al., 2018) [25] . Ten papaya parent lines, including Arka Prabhat, AC-119, Dwarf Lily, Red Indian, Washington, Pant Papaya-2, Shantha, Line-21, CO-8, and CO-2, were crossed with four testers, CO-7, Lucknow, Coorg Honeydew, and CO-4, using a Line × Tester mating strategy to develop 40 F1 hybrids. These hybrids, along with their parents, were cultivated in a randomized block design with three replications at Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut. Seeds obtained from ICAR-IIHR, Bangalore, were sown in a nursery and later transferred to raised beds after 45-50 days of growth (Rao et al., 2020) [14] . Recommended doses of nitrogen, phosphorus, and potassium were applied, with additional nitrogen sprayed at different growth stages. Frost protection during winter was provided through irrigation and fumigation. The primary observations for the experiment included days to flowering, number of leaves at flowering, and plant height at flowering. At harvest, plant height, stem girth, number of fruits per plant, and fruit yield per plant were recorded. Quality characteristics were assessed and categorized into physical characteristics, such as fruit weight, fruit length, fruit girth, pulp thickness, and breadth of central cavity, and chemical quality, which was measured by total soluble solids (TSS). Genetic diversity among the papaya genotypes was assessed using Mahalanobis' (1936) [8] generalized distance (D2) statistic, as extended by Rao (1952) [12] . The D2 values were utilized to group the genotypes into clusters based on the method proposed by Tocher (Rao, 1952) [12] . Intra-and inter-cluster distances were calculated using the methods described by Singh and Chaudhury (1985) [18] . All statistical analyses were performed using R studio Program and MS Excel.

Result and Discussion

Cluster mean Mahabalanis

The analysis of cluster means among papaya genotypes highlighted several promising traits essential for breeding programs (Table 2). Among these, Cluster IV emerged as the most promising for overall yield, with the highest fruit yield per plant (60.52 kg), heavy fruits (2.48 kg), thick pulp (3.70 cm), and early flowering (108 days). Additionally, Cluster IV had moderate plant height and the largest fruit diameter (55.05 cm), indicating its potential for producing high-quality fruits. For traits such as dwarf plant height and early flowering, Cluster I stood out with the shortest plants (78.38 cm at flowering) and an early flowering time of 95.45 days. This makes Cluster I suitable for developing compact varieties. In terms of high T.S.S., Cluster IV showed slightly superior sweetness levels (12.73), closely followed by Cluster II (12.52). Genotypes with a low central cavity, essential for better fruit quality and consumer preference, were predominantly found in Cluster I and Cluster V, with mean cavity breadths of 8.13 cm and 7.54 cm, respectively. These clusters also exhibited higher pulp thickness, enhancing the overall fruit quality.

Overall, Cluster IV is the most promising for traits like heavy fruit, high yield, and superior quality, while Cluster I offers potential for dwarf plants and early flowering. These clusters, combined with genotypes from other clusters for specific traits like high T.S.S. and low central cavity, present a valuable genetic base for developing improved papaya varieties tailored to diverse agricultural and market needs.

Inter-and Intra-Cluster Distances

The analysis of inter-and intra-cluster distances among papaya genotypes revealed significant variations, indicating the genetic diversity within and between clusters. The intracluster distances, represented by the diagonal values, were relatively low, with cluster IV having the smallest intracluster distance (2.122), suggesting high genetic homogeneity among its genotypes (Table 3). Cluster I also exhibited a low intra-cluster distance (2.363), reflecting moderate genetic similarity. Among the inter-cluster distances, the highest value was observed between clusters I and IV (6.976), highlighting substantial genetic divergence between these groups. Similarly, clusters IV and V showed considerable genetic dissimilarity (6.220), indicating the presence of unique genotypic traits within these clusters. Conversely, the closest relationship was noted between clusters II and III, with an inter-cluster distance of 2.834, suggesting genetic proximity between the genotypes of these groups.

Overall, the findings demonstrate a diverse genetic base among the papaya genotypes, with certain clusters exhibiting greater variability. This genetic diversity provides an excellent opportunity for selecting promising genotypes for hybridization programs to enhance yield, quality, and stress tolerance in papaya breeding.

Number of genotypes in each cluster

The D² Mahalanobis distance analysis grouped the 54 papaya genotypes into five distinct clusters based on genetic diversity, revealing significant variability among the genotypes (Table 4 & Fig. 1). Cluster V was the largest, comprising 18 genotypes, including commercially important varieties such as Arka Prabhat, Washington, and Pant Papaya-2, along with their crosses. This cluster displayed high genetic variability, making it valuable for improving multiple traits such as yield and quality.

Cluster IV was the smallest, consisting of five genotypes, primarily CO-2 and its derived crosses. This cluster exhibited close genetic similarity, making it suitable for specific traits requiring stability and uniformity. Clusters I, II, and III each represented moderate genetic diversity with 11, 11, and 9 genotypes, respectively. Cluster I included key genotypes such as AC-119 and Dwarf Lily, along with their crosses, emphasizing early flowering and dwarf traits. Cluster II grouped genotypes like Shantha and CO-8 with their hybrids, highlighting traits such as high fruit weight and yield potential. Cluster III comprised genotypes like Red Indian and Line-21 with their crosses, showing potential for robust plant height and fruit dimensions.

The distinct genetic grouping highlights the diversity within the papaya genotypes, offering a robust genetic pool for breeding programs. Cluster V genotypes are particularly promising for hybridization programs aimed at improving yield and fruit quality, while Clusters I and IV offer opportunities for breeding compact and early-maturing varieties. Clusters II and III provide intermediate genetic diversity, ideal for combining traits such as plant vigor, high yield, and fruit quality.

Conclusion

The study of inter-and intra-cluster distances, cluster means, and genetic diversity among 54 papaya genotypes revealed significant variations, providing valuable insights for breeding programs. The inter-cluster distances highlighted substantial genetic divergence, with the highest distance observed between Clusters I and IV, indicating the potential for combining genotypes from these clusters to create highly diverse hybrids. The low intra-cluster distances, particularly in Cluster IV, reflected high genetic homogeneity, making it suitable for improving stability and uniformity in specific traits.

Cluster IV emerged as the most promising group, combining traits like the highest fruit yield per plant (60.52 kg), heavy fruit weight (2.48 kg), thick pulp (3.70 cm), and large fruit diameter (55.05 cm). Cluster I stood out for traits like early flowering (95.45 days) and dwarf plant height (78.38 cm), making it ideal for developing compact varieties. Additionally, Cluster V, which housed the largest number of genotypes, offered a diverse genetic base for improving yield and fruit quality, while Clusters II and III presented intermediate diversity for traits such as plant vigor and fruit dimensions.

The findings emphasize the importance of leveraging genetic diversity within and across clusters to develop improved papaya varieties tailored to specific goals, such as high yield, superior fruit quality, compact plant size, and early maturity. By strategically selecting genotypes from different clusters, breeders can achieve targeted improvements, ensuring papaya varieties meet diverse agricultural and market demands.

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