Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Microbial production of organic acids: expanding the markets
2008633 citationsMichael Sauer, Danilo Porro et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Danilo Porro's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Danilo Porro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danilo Porro more than expected).
This network shows the impact of papers produced by Danilo Porro. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Danilo Porro. The network helps show where Danilo Porro may publish in the future.
Co-authorship network of co-authors of Danilo Porro
This figure shows the co-authorship network connecting the top 25 collaborators of Danilo Porro.
A scholar is included among the top collaborators of Danilo Porro based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Danilo Porro. Danilo Porro is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Porro, Danilo, et al.. (2006). Ripartizione dell'azoto in diversi organi aerei della vite in relazione a tempo e modalita di somministrazione fogliare. CINECA IRIS Institutional Research Information System (Fondazione Edmund Mach).
11.
Porro, Danilo, et al.. (2002). Fitoregolatori e fitormoni: risposta produttiva ed economica di Golden Delicious. CINECA IRIS Institutional Research Information System (Fondazione Edmund Mach).5 indexed citations
12.
Porro, Danilo. (2001). Lo SPAD nella diagnosi dello stato nutrizionale della vite. CINECA IRIS Institutional Research Information System (Fondazione Edmund Mach). 57(26). 49–55.9 indexed citations
Porro, Danilo, Fulvio Mattivi, Andrea Pitacco, et al.. (2000). Microclima termico e scambi gassosi in vite: influenza sugli aspetti qualitativi del Pinot nero. CINECA IRIS Institutional Research Information System (Fondazione Edmund Mach).
Alberghina, Lilia, et al.. (1997). Flow cytometric analysis of cell size changes during nutritional shifts in budding yeast. European Journal of Cell Biology. 72. 102–102.
17.
Failla, O., et al.. (1995). Indagine sullo stato nutrizionale dei vigneti in alcune zone toscane a denominazione d'origine per una proposta d'interpretazione delle analisi fogliari e del terreno. CINECA IRIS Institutional Research Information System (Fondazione Edmund Mach).3 indexed citations
18.
Iacono, F., Massimo Bertamini, Danilo Porro, & M. Stefanini. (1991). Rapporto tra i livelli di variabilita della struttura vegeto-produttiva della vite e risultati quanti-qualitativi del diradamento. CINECA IRIS Institutional Research Information System (Fondazione Edmund Mach).5 indexed citations
Coraggio, Immacolata, Enzo Martegani, Concetta Compagno, et al.. (1988). DIFFERENTIAL TARGETING AND ACCUMULATION OF NORMAL AND MODIFIED ZEIN POLYPEPTIDES IN TRANSFORMED YEAST. European Journal of Cell Biology. 47(2). 165–172.10 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.