Analysis on Research Situation of Soybean Quality Evaluation Based on Bibliometrics.

IF 2 4区计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Big Data Pub Date : 2025-12-01 Epub Date: 2025-12-04 DOI:10.1177/2167647X251399053

Yanxia Gao, Pengju Tang, Xuhong Tang, Dong Wang, Jiaqi Luo, JiaDong Wu

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引用次数: 0

Abstract

Soybeans are a high-quality vegetable protein resource and a fundamental strategic material integral to the national economy and public livelihood. To investigate the research status of soybean quality evaluation, this study analyzes relevant literature from Web of Science and China Knowledge Network (2000-2024). Using bibliometric methods with Excel and VOSviewer, we examined publication years, keywords, authors, sources, countries/regions, and institutions, generating visualizations to intuitively illustrate the field's developmental status. Results indicate that over the past 25 years, soybean quality evaluation research has emerged as a focal point in crop science, with institutions predominantly located in China and the United States. Key journals in this domain include Food Chemistry, Frontiers in Plant Science, and Soybean Science, among others. Research primarily focuses on soybean physical characteristics and the component-quality relationship. Interdisciplinary advancements have positioned spectral analysis, intelligent systems, and multitechnology fusion as innovative frontiers in this field. These findings enhance researchers' understanding of current trends and support evidence-based decision-making in soybean quality evaluation.

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基于文献计量学的大豆品质评价研究现状分析。

大豆是一种优质植物蛋白资源，是关系国计民生的基础性战略物资。为了了解大豆品质评价的研究现状，本研究分析了Web of Science和中国知识网（2000-2024）的相关文献。利用文献计量学方法，结合Excel和VOSviewer，对论文的出版年份、关键词、作者、来源、国家/地区和机构进行了统计分析，生成了可视化图，直观地说明了该领域的发展状况。结果表明，在过去的25年中，大豆质量评价研究已成为作物科学的一个焦点，研究机构主要集中在中国和美国。该领域的主要期刊包括《食品化学》、《植物科学前沿》和《大豆科学》等。研究主要集中在大豆的物理特性和成分与品质的关系。跨学科的进步将光谱分析、智能系统和多技术融合定位为该领域的创新前沿。这些发现增强了研究人员对当前趋势的理解，并为大豆质量评价的循证决策提供了支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

9.10

自引率

2.20%

发文量

期刊介绍： Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions. Spanning a broad array of disciplines focusing on novel big data technologies, policies, and innovations, the Journal brings together the community to address current challenges and enforce effective efforts to organize, store, disseminate, protect, manipulate, and, most importantly, find the most effective strategies to make this incredible amount of information work to benefit society, industry, academia, and government. Big Data coverage includes: Big data industry standards, New technologies being developed specifically for big data, Data acquisition, cleaning, distribution, and best practices, Data protection, privacy, and policy, Business interests from research to product, The changing role of business intelligence, Visualization and design principles of big data infrastructures, Physical interfaces and robotics, Social networking advantages for Facebook, Twitter, Amazon, Google, etc, Opportunities around big data and how companies can harness it to their advantage.