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学术期刊
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学术著作
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精品图书
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投稿须知
Technological Innovation and Science Management (TISM) June 2026, Vol.2, No.4
Deep Learning Empowered Intelligent Decision-Making Method for Precision Precision Breeding of Barley in Saline-Alkaline Lands
Chengxin Fan
Qingdao Agricultural University, Qingdao, Shandong 266109, China
Abstract: Saline-alkali soil improvement and the breeding of salt-tolerant crops represent critical strategic priorities for ensuring national food security and sustainable utilization of arable land resources. This paper focuses on research into an intelligent decision-making method for precision barley breeding in saline-alkali soils based on deep learning. Building upon an analysis of three fundamental requirements—salt tolerance trait mapping, multi-source data integration, and intelligent breeding processes—the study establishes a technical framework encompassing germplasm resource identification, multi-omics data integration, environmental factor acquisition, and data preprocessing. It further presents phenotypic recognition using Convolutional Neural Network (abbreviated as CNN) gene mining integrating Transformer and GWAS approaches, and multi-omics data integration methodologies. The intelligent decision-making model recommended for genomic selection and G×E breeding aims to establish a theoretical foundation and technical roadmap for precision breeding of barley in saline-alkali soils.
Keywords: deep learning, barley in saline-alkali soils, precision breeding, Intelligent decision-making
