Crop phenomics enables collection of diverse plant traits for a large number of samples along different time scales, representing a greater data collection throughput compared to the traditional measurements. Most of modern crop phenomics use different sensors to collect reflective, emitted and fluorescence signals etc., from plant organs at different spatial and temporal resolutions. Such multi-modal, high dimensional data not only accelerates basic research on crop physiology, genetics, and whole plant systems modeling, but also supports the optimization of field agronomic practices, internal environments of plant factories, and ultimately crop breeding. Major challenges and opportunities facing the current crop phenomics research community include developing community consensus or standards for data collection, management, sharing, and processing, developing capabilities to measure physiological parameters, and enabling farmers and breeders to effectively use phenomics in the field to directly support agricultural production.

ABSTRACT The field of agronomy and crop science plays a crucial role in ensuring global food security and sustainable agricultural practices. In the realm of scholarly publications, bibliometric indicators have emerged as invaluable tools for quantifying and comparing the impact, reach, and significance of such contributions. Various bibliometric indicators were employed for the study, including Impact Factor, Eigenfactor Score, Cite Score, and h-index. To accomplish this, we compiled a roster of 90 agronomy and crop science journals using the Journal Citation Report (JCR) within the Web of Science (WOS), journal metrics from the Scopus database (Cite Score and SNIP), and h5-index from Google Scholar. The SCImago Journal Ranking (SJR) was obtained from its official website. Subsequently, we conducted Bivariate Pearson’s (r) and Spearman’s (ρ) correlation coefficient tests to assess ranking correlations. The study revealed notable positive correlations particularly, a strong Pearson’s (r) correlation evident between the Impact Factor (JIF) and both the Cite Score (CS) and SCImago Journal Rank (SJR) indicators, yielding values of (r = 0.962) and (r = 0.932), respectively. Interestingly, despite the distinct mathematical foundations underpinning the various citation-based bibliometric indices scrutinized, our findings underscored their robust correlations when it comes to ranking agronomy and crop science journals.