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Seven wild type strains of Agrobacterium tumefaciens were infected to leaf mesophyll, cotyledon, and stem segment tissues of three tomato (Lycopersicon esculentum) cultivars. Tumor formation was most effectively induced by dipping for 5 min in the strain solution and cocultivation for 20 hrs. Tumor formation was vigorous on every tissue infected with C58 or Ach5. The efficiency of tumor formation was higher on the stem segments than on the other tissue segments. Root development was observed after incubation of the tumor mass derived from stem segment on a fresh medium without any plant growth regulator supplemented, and calli were established on the roots.
Binary vectors of Agrobacterium tumefaciens C'482(pTiC58 :: pGA482), C'691(pTiC58 :: pGA691), A'482(pTiBo542 :: pGA482), A'643(pBo542 :: pGA643), A'691(pBo542 :: pGA691) and L'643(pAl4404 :: pGA643) constructed by triparental mating method were used for genetic transformation of tomato plants. All of these strains showed resistant response to the concentration of 100 ㎍/mL kanamycin. Cotyledon, leaf and stem segments of three cultivars of tomato were infected by cocultivation method with A. tumefaciens binary vetor and were cultured on MS medium supplemented with N^6-benzylaminopurine (B/a) 2 ㎎/L, α-naphthalane-acetic acid (NAA) 0.2 ㎎/L, carbenicilline 500 ㎍/mL, cefotaxime 100 ㎍/mL and kanamycin 100 ㎍/mL at 28±2℃. Calli were formed in rate of 1.6 to 1.8% of leaf segments and 1.6 to 1.9% of stem segments that were infected with the binary vectors A'482, A'643 and A'691.
In general, the multi-level multi-item dynamic lot sizing problem is very complicated to solve due to the dependencies among decision variables. A simplification procedure is suggested in order to eliminate the dependencies among decision variables step by step. Firstly, it is shown how the characteristics of the dependencies are analyzed and classified, and assumptions to eliminate the dependencies are introduced. An application case study of the simplification procedure to a real automobile component manufacturer is introduced.
When we try to design a production planning system for a manufacturing company, it is a time consuming task to analyze various planning activities and identify inter-relationship among a lot of decisions made for the production planning. Most of the research efforts have been concentrated to well-organized independent decision-making problems that may usually be identified only after analyzing the characteristics of the decision-making process as a whole in this paper, a methodology is suggested to characterize the whole process of the production planning for a manufacturing company and reduce the complexity of decision-making problem. The methodology is based on an experience of developing a production planning software for an automobile component manufacturer in Korea. First, it is explained how to identify and represent the dependency among various decision-making variables. And a methodology is proposed to analyze the identified dependency among decision variable and identify decision-making process. Lastly, a practical example is provided to illustrate the analysis procedure in this paper.