Floriculture (kaki) Researcher

かきけんきゅうしゃ

Industry & Occupation

Science & Research

Classification

Summary

Conducts research on floriculture breeding and cultivation techniques, aiming for new variety development and quality improvement as a scientific and technical profession.

Description

Floriculture researchers conduct basic and applied research on floriculture plants such as cut flowers and potted plants. They utilize breeding techniques and molecular biology methods to achieve goals such as disease resistance, environmental tolerance, improvements in color and flowering patterns, and development of long-term preservation technologies. They belong to research institutions, universities, corporate research labs, etc., and handle a wide range of tasks including planning experiments, test cultivation, gene analysis, tissue culture, data analysis, paper writing, and variety registration procedures. Collaboration with industry and farmers, as well as collection of marketing information, is also important.

Future Outlook

Demand for diverse variety development is increasing, and research fields for environmentally adaptive and low-cost production technologies are expanding. Integration with sustainable agriculture is also expected.

Personality Traits

Has attention to detail / Has curiosity and inquisitiveness / Has eagerness to learn / Has patience

Work Style

Academic Society Collaborative Research / Business Trips / Corporate Research Institute / Laboratory Work

Career Path

Researcher → Senior Researcher → Project Leader → Institute Director → University Faculty

Required Skills

Experimental Design / Genetic Marker Analysis / Molecular Biology Techniques / Plant Breeding / Statistical Analysis / Tissue Culture

Recommended Skills

Bioinformatics / English Paper Reading and Writing / GIS Basic Knowledge / Image Analysis

Aptitudes (Strengths Preferred)

Item Description
Analytical & Logical Thinking Multifaceted analysis of experimental data is essential.
Attention to Detail & Accuracy Precise experimental operations and data accuracy are required.
Learning Agility & Knowledge Acquisition Continuous acquisition of new technologies and knowledge is necessary.
Numerical & Quantitative Analysis Statistical analysis is used to evaluate and verify results.
Problem Solving 対応 to experimental troubles and unexpected results is necessary.

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