天津农业科学2026，Vol.32Issue(8)：55-64,10.DOI:10.3969/j.issn.1006-6500.2026.08.008
拉曼光谱结合智能算法在耐盐碱粳稻鉴定中的研究进展
Research Progress on the Identification of Salt-Alkali Tolerant Japonica Rice Using Raman Spectroscopy Combined with Intelligent Algorithms
摘要
Abstract
Saline-alkali cropland constrains grain productivity,and precise screening of saline-alkali-tolerant japonica rice germplasm in cold regions is a core step in expanding arable land resources.Traditional field phenotyping and molecular marker-assisted breed-ing have limitations such as long cycles,high costs,and low throughput,making them inadequate for large-scale rapid germplasm screening.Raman spectroscopy offers advantages including non-destructive and rapid detection,clear molecular fingerprinting,and no complex pretreatment requirement.Coupled with machine learning,it enables high-throughput intelligent discrimination of saline-al-kali tolerance in japonica rice and has become a frontier technology for crop stress-resistance germplasm identification.This paper systematically retrieved 59 publications in Chinese and English from the past 20 years,with clearly defined search strategies and in-clusion/exclusion criteria.Focusing on the coupling of Raman spectroscopy with intelligent algorithms for saline-alkali tolerance iden-tification in japonica rice,it reviewed three types of technical systems for identifying saline-alkali tolerance in japonica rice;described standardized workflows for spectral acquisition,preprocessing,and feature extraction;summarized the applicable scenarios,advan-tages,and limitations of mainstream machine learning recognition algorithms,and compared their performance;highlighted key bottle-necks such as insufficient spectroscopy-imaging fusion,poor small-sample generalization,and lack of field-portable detection sup-port;and envisioned directions including multiband Raman imaging,conversion of one-dimensional spectra into two-dimensional rep-resentations,lightweight deep learning models,and intelligent in situ field detection.Overall,Raman spectroscopy coupled with intel-ligent algorithms has demonstrated the foundational performance required for high-throughput preliminary screening of saline-alkali tolerant japonica rice germplasm,enabling rapid and non-destructive elimination of a large number of sensitive accessions at early stages of breeding in cold regions.关键词
耐盐碱粳稻/拉曼光谱/机器学习/种质鉴定/智能育种Key words
saline-alkali tolerant japonica rice/Raman spectroscopy/machine learning/germplasm identification/intelligent breeding分类
农业科技引用本文复制引用
马波,王兴宇,胡继芳,杜浩强,刘蕊,李宸珲..拉曼光谱结合智能算法在耐盐碱粳稻鉴定中的研究进展[J].天津农业科学,2026,32(8):55-64,10.基金项目
农业科技创新跨越工程(CX23ZD02-03) （CX23ZD02-03）
黑龙江省重点研发计划(创新基地)(JD2023GJ04) （创新基地）
黑龙江省优秀青年教师基础研究支持计划(YQJH2023065) （YQJH2023065）
黑龙江省自然科学基金(LH2024F046) （LH2024F046）
