Research Notes: Potential of exotic soybeans in the sub-montane region of Himachal Pradesh (India)

Himachal Pradesh is a hilly state of Northern India , with its global location between 75°45\u27 - 79°04 \u27 E longitude and 30°22\u27 - 33°12\u27 N latitude. In this part of the country, soybean is indigenously grown as a rainy season crop up to an altitude of 1800 m above mean sea level . The indigenous soybean comprise small seeded, twining type low- yielding varieties

Research Notes : India : Genetic variability, interrelationships and path-coefficient analysis of seed technological traits in soybean under different cropping systems

Soybean is generally cultivated in India as a sole or monoculture crop. However, its intercropping with maize is a common practice in some hilly areas of northern India. The practice aims at (1) insuring against total crop fail-ures under abnormal weather conditions, (2) increasing total productivity for unit land area, and (3) equitable and judicious utilization of land resources and farming inputs

Research Notes: Variation for seed yield, its quality and nutritional traits in soybeans

To bring about genetic improvement for any economic trait in economic plants, the foremost prerequisite is the presence of sufficient amount of genetic variability for the trait under improvement in the organism t o be improved. In the present investigation, an attempt has been made to get the information on nature and magnitude of variability for various seed quality traits along with seed yield traits in the soybean germplasm maintained at the Himachal Pradesh Agricultural University, Palampur. Materials and methods: The material for the present study consisted of 250 diverse genotypes of soybeans of both indigenous and exotic origin , and 5 standard checks

Research Notes : Consistency of heritability estimates over environments and crop-ping systems for different groups of traits in soybean

Introduction : Though numerous reports are available on heritability estimates from individual environment, yet information on consistency of heritability over environments is meager (Byth et al., 1969). An attempt has been made in the present communication to understand the influence of en-vironments and cropping system on the heritability estimates in soybean. Materials and methods : The materials and experimental design were same as reported by Gupta et al. (1981)

Research Notes : Correlation among seed yield, seed quality and nutritional traits in soybean

Introduction : In the present communication, the information obtained on correlations among 14 traits related to seed yield, seed quality and nu-trition in soybean germplasm has been discussed, The information on the nature of variation for these traits in the above material has been reported earlier (Rana et al., 1981). Materials and methods : The materials and methods were reported earlier by Rana et al. (1981)

Research Notes : Genotype X Environment interaction in soybean: I. Individual regression analysis.

In this communication, the results obtained from the material given earlier (Gupta et al., 1981) on the basis of individual regression analysis by using Perkins and Jinks (1968) model, have been presented for different traits groupwise. In the individual regression analysis, genotypes having nonsignificant regression m.s. as well as remainder m.s. against error m.s. were described as exhibiting absence of genotype x environment (g x e) interaction, genotypes having regression m.s. significantly different from error m.s. were designated as showing predictable g x e (linear g x e) interaction, and genotypes having only significant remainder m.s. or significant regression m.s. not significantly different from significant remainder m.s. were categorized as genotypes showing unpredictable g x e (nonlinear g x e) interaction. On the basis of this all 40 genotypes were classified into three groups and their distribution with respect to different groups of characters studied is given in Table 1

Research Notes : Factor analysis in F2 generation of soybean crosses

Factor analysis is a technique of reducing a large number of correlated variables to a few main factors. It has been resorted to to overcome the limi-tations of univariate methods of analysis like correlations, path-coefficient and regression analysis (Wright, 1960; Walton, 1972). Besides, Moreno and Cubero (1978) have used it for estimating diversity