Introduction
Horse gram (Macrotyloma uniflorum (Lam.) Verd.) is an arid food legume known to grow well in diverse environmental conditions (poor soils, low rainfall, soil pH from 5 to 7.5, 1800 masl altitude; Duke, Reference Duke1981). The species is widely grown as a pulse, fodder crop, green manure crop and medicinal crop. In the Indian state of Andhra Pradesh, horse gram is grown in all eco-geographical regions, including Telangana, Rayalaseema and the Coastal region. Significant variability was observed within the germplasm grown in these areas. Seed colour ranges from black to chocolate brown, and protein content from 20 to 25%. The identification and development of high-yielding varieties are key for the full exploitation of this dryland crop. Hence, an attempt was made to study the genetic diversity and geographical distribution within the germplasm collected from Andhra Pradesh.
Experimental
A set of 20 accessions, based on field performance in previous years, along with two controls (varieties Palem-1 and Palem-2 released by the state agricultural university) were evaluated to study the extent of diversity, identify diverse accessions for breeding programmes and identify geographical areas for future germplasm collection efforts. Each accession was planted in three 3 m rows, with an inter-row spacing of 60 cm and an inter-plant spacing of 10 cm. Recommended cultural practices were followed to grow the crop (Anonymous, Reference Anonymous1992). The accessions were grown during the post-rainy (rabi) season of 2005–2006. The experimental design was a randomized complete block design with three replications. Nine morphological, phenological and reproductive characters (Table 1) were measured from five randomly selected plants at maturity. Mean trait values were used to derive Mahalanobis (Reference Mahalanobis1936) D 2 statistics using the Windostat statistical package. The D 2 values were treated as generalized distances to cluster the populations following Tocher's optimization method, as described by Rao (Reference Rao1952). Latitude and longitude at the collection site were recorded using a handheld global positioning system (Garmin, GPS 12). The quantitative and GPS data were used for mapping the accessions based on their traits using DIVA-GIS software v5.2.
Table 1 Cluster composition and cluster means based on D 2 values in horse gram
Discussion
On the basis of the D 2 analysis, the 20 accessions were grouped into five clusters (Table 1). Cluster I was the largest group, containing seven entries, followed by clusters III and V with five entries each, and IV and II with, respectively, three and two entries. The range of intra- and inter-cluster distances was 4.06–7.41 (Table 1) and 8.9–22.2, respectively. The greatest inter-cluster distance separated clusters II and V, followed closely by clusters IV and V, and III and IV, indicating that these clusters were genetically the most outlying. The geographical origins of the entries along with a grid map generated using DIVA-GIS for seed yield per plant are provided in Fig. 1. Entries sharing a similar geographical origin grouped into different clusters, indicating that geographical distribution and genetic divergence are not related. Thus, collection should be based on agromorphological characterization and standard sampling procedures (Brown and Marshall, Reference Brown, Marshall, Guarino, Ramanatha Rao and Reid1995). The clustering of the entries suggested that the exchange of genetic stocks, genetic drift, spontaneous variation and natural and artificial selections applied for developing varieties suited to local needs may all have played an important role in generating genetic diversity (Arunachalam and Ram, Reference Arunachalam and Ram1967; Dhobal and Rana, Reference Dhobal and Rana1994). Entries in cluster IV were the best performing in terms of yield and the number of primary branches. Those in cluster III had high seed weight, seed number per pod and earlier days to flowering, while those in cluster II tended to have more pods per plant and a shorter plant height. Crop improvement is most likely to be achieved if parental combinations involve entries belonging to different outlying groups (clusters II and V, II and IV and III and IV).
Fig. 1 Distribution and grid map showing the diversity index of horse gram accessions for seed yield per plant in Andhra Pradesh (India).
The DIVA-GIS grid map revealed that entries from the Rayalaseema region were the most diverse for seed yield per plant (Fig. 1), days to flowering and to maturity.
Acknowledgements
The authors thank Dr S. K. Sharma (Director, NBPGR, New Delhi) for providing the facilities for the study and Dr Ravi Khetarpal (Head, Plant Quarantine Division, NBPGR) for his encouragement.
