M. Belayet Hossain
Jabor Hat College, Pirgonj, Thakurgaon
M. A. Karim
Bangabandhu Sheikh Mujibur Rahman Agricultural University, Salna, Gazipur-1706
Mungbean, Water stress, Yield variation
Bangabandhu Shiekh Mujibur Rahman Agricultural University, Gazipur
Variety and Species
Mungbean, Water stress
The experiment was carried out at the experimental field of Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur during the kharif season (April 2004 to June 2004). The experiment was conducted under rain free shed condition. The field was possible to cover by a moving house made by stainless steel frame and transparent polythene sheet was used as shed. The soil type of the experimental field belongs to the Shallow Red Brown Terrace type under Salna Series of Madhupur Tract (Brammer, 1971; Saheed, 1984) of Agro Ecological Zone (AEZ) 28, which is characterized by silty clay with pH value of 6.5. Twenty seven mungbean genotypes collected from Asian Vegetables Research and Development Centre (AVRDC), Taiwan were included in the present investigation. The accession numbers of the genotypes were GK 11, GK 13 GK 15, GK 16, GK 17, GK 18, GK 19, GK 22, GK 23, GK 24, GK 25, GK 26, GK 27, GK 28, GK 29, GK 30, GK 32, GK 33, GK 35, GK 37, GK 38, GK 39, GK 40, GK 42, GK 43, GK 45 and GK 47. The doses of manures and fertilizers were applied as per recommendation of Fertilizer Recommendation Guide 1997. The experimental field was kept weed free by hand weeding. Weeding was done at 15 days interval and it was continued up to pod harvesting stage. The crop was protected from the damage of insect pests by spraying of Malathion 57 EC @ 1 ml/L of water. At physiological maturity, dry pods were harvested at different days after sowing (DAS) for different genotypes. The harvesting was started from 57 DAS and continued up to 68 DAS for different genotypes. The data of different physiomorphological, reproductive, seed yield and related attributes were recorded from the investigation to obtain the precise information pertaining to genotypic differences.
Principal components were computed from the correlation matrix and genotype scores obtained from the first components (which has the property of accounting for maximum variance) and succeeding components with latent roots greater than the unity (Jeger et al., 1983). Clustering was done using non-hierarchical classification. Starting from some initial classification of the genotypes into required group, the algorithm repeatedly transfers genotypes from one group to another so long as such transfers improve the value of criterion. When no further transfer can be found to improve the criterion, the algorithm switches to a second stage which examines the effect of swapping two genotypes of different classes, and so on. Using Canonical Vector Analysis a linear combination of original variability’s that maximize the ratio in between group to with in group variation to be find out and there by giving functions of the original variability’s that can be used to discriminate between groups. The canonical varieties are based on the roots and vectors of W-1B, where W is the pooled within groups covariance matrix and B is the among the groups covariance matrix. When the clusters are formed, the average intra-cluster distance for each cluster was calculated by taking possible D2 values within the members of a cluster obtained from the Principal Coordinate Analysis (PCO). The formula used was D2 /n, where D2 is the sum of distances between all possible combinations (n) of the genotypes included in a cluster. The square root of the average D2 values represents the distance (D) within cluster. Cluster diagram was drawn using the intra and inter cluster distance. It gives a brief idea of the pattern of diversity among the genotypes included in a cluster.
J. Sci. technol. (Dinajpur) Vol. 5: 117-121 (2007) ISSN 1994-0386
Journal