APPLICATION OF ARTIFICIAL INTELLIGENCE IN GRADUATE EDUCATION FOR TROPICAL FOREST TREE GENETIC BREEDING

Authors

  • Jian Wang Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants (Hainan University), Ministry of Education; Key Laboratory of Germplasm Resources of Tropical Special Ornamental Plants of Hainan Province; School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, Hainan, China.
  • MinJie Qian School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.
  • Jie Liu Sanya institute, China Agricultural University, Sanya 572025, Hainan, China.
  • Yan Liu School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.
  • ZhanYing Zhang Sanya institute, China Agricultural University, Sanya 572025, Hainan, China.
  • ZhiQiang Xia School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.
  • ZhiHui Xia School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.
  • ShouChuang Wang School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.
  • YongGang Zhou School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.
  • HongMei Yuan School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.
  • Yan Jing School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.
  • YouGen Wu (Corresponding Author) School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, Hainan, China.

Keywords:

Tropical forest trees, Genetic breeding, Graduate education, Artificial intelligence

Abstract

Tropical forest tree genetic breeding is a fundamental course within forestry disciplines, crucial to sustainable forestry development and the promotion of ecological civilization. However, graduate education in this field faces persistent challenges, including prolonged breeding cycles, the complexity of multi-omics data analysis, and the necessity for deep interdisciplinary theoretical understanding. The integration of artificial intelligence (AI) in higher education offers promising solutions to these challenges. This paper systematically examines the application of AI technologies in graduate teaching of tropical forest tree genetic breeding by focusing on three key approaches: employing AI-driven analysis of genetic big data to enhance students’ ability to interpret complex datasets; utilizing AI-driven virtual simulation experiments to overcome temporal and spatial constraints through accelerated breeding models; and developing AI-based personalized learning and assessment systems tailored to diverse research emphases. To address core obstacles such as insufficient model specialization, limited interpretability of biological processes, and underdeveloped teaching support systems, we propose collaborative strategies including academia-industry partnerships for dedicated system development, interdisciplinary faculty training programs, establishment of standardized resource databases, and the adoption of progressive implementation frameworks. Results indicate that the deep integration of AI with tropical forest tree genetic breeding education can streamline instructional processes, improve the quality of talent development, and provide both theoretical and practical foundations for constructing intelligent educational ecosystems, thereby advancing the cultivation of high-level innovation professionals in forestry.

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Published

2026-03-25

Issue

Vol. 4 No. 3 (2026)

Section

Research Article

DOI:

https://doi.org/10.61784/wjes3152

How to Cite

Jian Wang, MinJie Qian, Jie Liu, Yan Liu, ZhanYing Zhang, ZhiQiang Xia, ZhiHui Xia, ShouChuang Wang, YongGang Zhou, HongMei Yuan, Yan Jing, YouGen Wu. Application Of Artificial Intelligence In Graduate Education For Tropical Forest Tree Genetic Breeding. World Journal of Educational Studies. 2026, 4(3): 40-44. DOI: https://doi.org/10.61784/wjes3152.