Rice (Oryza sativa L.) is the most important cereal crop in the world and has been cultivated by mankind for more than 10,000 years.It originated in South East Asia. Rice genome is composed of 12 chromosomes (2n=24) and belongs to the family Gramineae (Poaceae). The genus Oryza consists of 24 species, of which 22 are wild and two are cultivated viz., Oryza sativa and Oryza glaberrima. The sativa rice germplasm of the world is commonly divided into three sub-species i.e., Indica, Japonica and Javanica (Vinoth et al., 2016). Sub species Indica are cultivated in tropical and sub-tropical regions of the globe, subspecies Japonicaare grown throughout the temperate zone and subspecies Javanica are grown mainly in parts of Indonesia (Priya et al., 2017). All germplasm found in Asia, America and Europe belongs to the species Oryza sativa, while in West Africa it belongs to Oryza glaberrima. Rice is a short day autogamous crop and a staple food for about 2/3 of the entire population and plays an important role in the Indian economy (Kumar et al., 2017). Rice is a short day crop and requires a hot and humid climate with an average temperature of 21 to 37 C throughout its life. Rice contains 80% carbohydrates, 7-8% protein, 3% fat and 3% dietary fibre and also contributes, nutritionally, significant amounts of vitamins like thiamine, riboflavin, niacin and zinc (Ray et al., 2016). In India, rice production during 2022-23 was 165.30 million tonnes in an area of 44.10 million hectares with a productivity of 3780 kg/ha (Anonymous, 2022-23). In Rajasthan, rice occupies an area of 0.23 million hectares with the production of 0.66 million tonnes and productivity of 2860 kg/ha (Anonymous, 2022-23). Genetic diversity determines the inherent potential of a cross for heterosis and the frequency of desirable recombinants in advanced generations. Mahalanobis (1936) D2 statistics is a valuable tool used in quantifying the degree of divergence (Ramya and Senthilkumar 2008). It helps the breeder to estimate the genetic divergence in the population for use in plant breeding programmes. Cluster analysis is a statistical approach for converting numerous characteristics of objects into quantitative measures (similarity distance) and, as a result grouping them into clusters at relatively closer distances. By keeping all these considerations in mind, the present experiment was undertaken to study genetic diversity among 25 rice germplasms to identify diverse genotypes for future studies and further crop improvement.

The experiment was carried out with twenty-five of rice along with 4 checks in Randomized Block Design (RBD) with three replications at Agricultural Research Station, Ummedganj, Kota, Rajasthan, during Kharif 2023. The plot size for each genotype was 5m × 1.2 m with a spacing of 20 cm ×10 cm. The observations were recorded on five randomly selected plants per plot for nine characters viz., plant height (cm), number of effective tillers/plant, number of panicle/m2, number of grains/panicle, panicle length (cm), 1000-grain weight (g), grain yield/plant (g), whereas, the observations for days to 50% flowering and days to maturity were recorded on a whole plot basis. Using Mahalanobis D2 statistics, the data on different characters were subjected to an analysis of genetic divergence. The genotypes were then grouped into different intra-cluster and inter-cluster groups using Tocher’s method, as described by Rao (1952). It calculates the relative contributions of each character to the overall divergence and quantifies the variation in intra- and inter-cluster distance.

Table 1: List of twenty five rice genotypes used in the study.

The 25 genotypes were grouped into five clusters based on the Tocher’s method, indicating the average D2 values of intra and inter-cluster distance and the nearest and farthest cluster from each other based on D2 Values that are presented in the Table 3. Among five clusters, cluster I was the biggest with 19 genotypes viz., PR-113, JAYA, IET-31011, IET-28950, DRR Dhan-45, IET-31004, IET-31035, HKR-128, HKR-46, HKR-126, PR-130, PR-129, PR-106, IR-64, IET-28954, IET-28959, PR-124, PR-131 and Govind; cluster II contained 3 genotypes i.e., Chittimuthyalu, DRR Dhan-49 and DRR Dhan-48 while, rest of the clusters contained a single genotype only. Cluster III (HKR-47), cluster IV (IET-29142) and cluster V (BPT-5204) were found to be monogenotypic. The intra-cluster distance ranged from 0.00 (cluster III, IV, V) to 51.5 (cluster II).Cluster II showed maximum intra-cluster distance values (51.5) followed by cluster I (38.14). While cluster III, IV and V reported zero intra-cluster distance, indicating these clusters were monogenotypic in nature. Higher intra-cluster distance displayed that there was greater diversity present among the genotypes assigned to those respective clusters and minimum intra-cluster distance, indicating that genotypes present in cluster were closely related to each other. Similarly, the Inter-cluster distances varied from 82.23 to 249.98. The inter-cluster D2 values was maximum between cluster III and IV(249.98), followed by cluster IV and V (217.18), cluster III and V (201.7), cluster II and III (190.79), cluster I and V(167.55), cluster II and cluster IV (127.21), cluster I and II (114.55), cluster II and cluster V (91.84), cluster I and cluster III (87.13) and cluster I and cluster IV (82.23).Wider genetic diversity among genotypes is indicated by a greater inter-cluster distance between two clusters. Thus, a high heterotic combination would arise from hybridization between genotypes having the maximum inter-cluster distance. The mean values of nine characters for five clusters are presented in Table 3. The cluster IV with genotype IET-29142 was found earliest for days to 50% flowering and days to maturity, while cluster III (HKR-47) had higher cluster mean for plant height (cm), number of effective tillers/plant, number of panicle/m2, number of grains/panicle, panicle length (cm), 1000-grain weight (g) and grain yield/plant (g). Thus, in order to produce better and more desirable recombinants from hybridization programmes, a breeder must carefully integrate all the desired traits of diverse genotypes with high cluster mean values. Similar results were earlier reported by Rathan et al. (2020); Chhodavadiya et al. (2023).

Table 2: Grouping of 25 genotypes of rice into 5 clusters (by Tocher’s method).

Table 3: Average intra and inter-cluster distance based on corresponding D2 values.

Table 4: Mean values of different characters for 25 genotypes of rice grouped in different clusters.

Fig. 1. Graphical representation of clustering by Tocher’s method.

Fig. 2. Diagrammatic representation of intra and inter-cluster distance.

Based on D2 data, the current study aids in the identification of diverse genotypes which is pre-request for any successful breeding programmes for enhancing yield and its contributing attributes.