A bibliometric analysis of research on plant critical dilution curve conducted between 1985 and 2019

作物 油菜 农业工程 环境科学 索引(排版) 农学 作物管理 饲料 地理 生物 计算机科学 工程类 万维网
作者
Rongrong Chen,Yan Zhu,Weixing Cao,Liang Tang
出处
期刊:European Journal of Agronomy [Elsevier BV]
卷期号:123: 126199-126199 被引量:17
标识
DOI:10.1016/j.eja.2020.126199
摘要

The concept of plant critical dilution curve (PCDC) has been studied on several crop species for about four decades, which has been widely applied in studies of crop nutrition evaluation, growth predictions, and fertilization management. This bibliometric analysis comprehensively explores the evolution trends in PCDC research based on literature data retrieved from the Web of Science from 1985 to 2019. The dynamics of the basic characteristics such as outputs, citations, institutions, authors, keywords and research topics of the published papers were studied. The results showed that the outputs and citations remained very low in the early years, then increased gradually, and increased quickly in recent years. INRA from France developed the theory, while research institutions from China and Canada as emerging groups applied the theory in different crops for crop N, growth, and quality indices as well as integrated it with non-destructive tools such as chlorophyll meter and remote sensing technologies in recent years. The frequency of the keywords “nitrogen nutrition index”, “use efficiency”, “management”, “leaf area index” and “vegetation index” in the PCDC study increased over years. The PCDCs along with a number of crops, such as wheat, maize, rice, forage grasses, potato, canola, and tomato, have been widely studied in different countries. Research on PCDC has mainly focused on the theory and development of PCDC, including P, K, S, and their interaction, crop modeling, remote sensing and non-destructive techniques, nutrition diagnosis and fertilization management. Analysis of the published papers revealed that crop modeling and remote sensing are emerging fields. The research trends proposed were: generic PCDCs for crop species, the interaction of N-P-K-S for balanced fertilization, and application of PCDC in crop modeling and remote sensing.
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