Oilseeds are an important group of crop plants both for humans and livestock. The Brassica group of oilseed crops, commonly known as rapeseed-mustard, are the second largest oilseed crop, next to groundnut, in terms of the area and production in India. Indian mustard accounts for nearly 90% of the area grown for rapeseed-mustard in the country. The available germplasm can serve as the most valuable natural resource in providing donor parents having desirable attributes for engineering varieties with high yield potential. In the present study, 98 germplasm of mustard along with two checks (Kranti and Varuna) were sown in simple lattice design. Data were recorded for 13 different quantitative characters. The principal component analysis was performed using the standard procedure. The first principal component had high eigen root of 3.31, followed by 2.12, 1.32, 1.07, 1.02, 0.82, 0.73, 0.65, 0.56, 0.47, 0.42, 0.31 and 0.21 from second to 13^th principal component. The eigen root of the first principal component accounted for 25.47% of the total variation present in the original data followed by second, third, fourth, fifth and sixth principal components which accounted for 16.29, 10.17, 8.21, 7.82, and 6.29% respectively. The percentage of variations explained by 7^th to 13^th principal components were 5.61, 5.02, 4.33, 3.21, 2.34 and 0.63. The cumulative percent of variation explained by the first 11 principal components which were used for clustering purpose was 96.03%. In the present study, days to flowering initiation, siliqua on main shoot, seeds per siliqua, length of siliqua, seed yield per plant, number of secondary branches per plant and 1000-seed weight proved to be the most important variables since they had high positive and negative eigen values for different principal components.

Oilseeds form the second largest agricultural commodity after cereals in India, sharing 14% of the country's gross cropped area and accounting for nearly 5% of the gross national product and 10% of the value of all agricultural products. India is the largest cultivator of oilseeds in the world, but still has to import large quantities of edible oils to meet its national demand. Annual import is currently 5.0 million tons (approx. 50% of national consumption) valued at £1.5 bn, making India the world's largest importer of vegetable oils. The Brassica group of oilseed crops, commonly known as rapeseed-mustard, is the second largest oilseed crop next to groundnut in terms of area and production in India. Over 12.5% of the World's edible oil now comes from the oilseed Brassica, rapeseed-mustard (Economic Survey, 2000). Of this, Indian mustard Brassica juncea L. Czern and Coss alone accounts for 90% of the area among these crops. Diet surveys by the Indian National Nutrition Monitoring Bureau in 10 States show that the daily visible fat and oil intake ranges from 1-7 kg/person/year in rural India. This is far below the prescribed minimum nutritional norm of 14 kg/person/year. The average production of oilseeds in India is around 0.8 ton/ha, which is far below that of the developed countries (2.5-3.0 tons/ha). The area, production and productivity have declined tremendously in the recent past. Rapeseed-mustard was cultivated in 6.33 million hectares during 2006-07 and 6.69 million tons production was achieved, with the productivity declining to 1,057 kg per hectare, as compared to 1,117 kg per hectare during 2005-06. India holds the premier position in terms of the largest area under oilseeds in the world, still the yield of most of the oilseed crops is less than the world's average (Chahal, 1998). On the other hand, the demand for edible oils has been estimated at 10 million tons for the year 2015 and 11.12 million tons by 2030 (Paroda, 2000). In view of achieving higher production and productivity, genetic improvement through restructuring of plant, both morphologically and physiologically, is needed for developing high-yielding varieties and bridging the gap in the declining production. The available germplasm can serve as the most valuable natural resources in providing donor parents having desirable attributes for engineering varieties with high-yield potential. The success of hybridization in any crop depends primarily on the selection of diverse parents. The basic difficulty, however, has been in recognizing and estimating the diversity without attempting crosses between the lines and evaluating their progenies. For the choice of diverse parents for a hybridization program, multivariate analysis using principal component and cluster analysis has been extensively used as a quantitative measure of genotypic divergence among the parents. The Principal Component Analysis (PCA) is a data analysis tool that is usually used to reduce the dimensionality (number of variables) of a large number of interrelated variables, while retaining as much information (variation) as possible. The PCA calculates an uncorrelated set of variables (factors or pc's). These factors are ordered so that the first few retain most of the variation present in all the original variables. The computation of PCA reduces to an eigenvalue-eigenvector problem. It is a data analytical rather than a statistical procedure.

Genetics & Evolution Journal, Principal Component Analysis, Oilseeds, Mustard, Principal Components, Quantitative Characters, Agricultural Products, Indian National Nutrition Monitoring Bureau, Ethiopian Mustard Genotypes, Genetic Vulnerability, Orthogonal Transformation, Rapeseed-Mustard, Agricultural Commodity.