Sergio Cubero

60 papers receiving 3.1k citations

Hit Papers

Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why 2025 · 19 citations
192011202620162021100200300400

Peers

Sergio Cubero
Comparison fields: 5 of 123
  • Analytical Chemistry 2.2k
  • Biophysics 362
  • Plant Science 1.6k
  • Biochemistry 246
  • Industrial and Manufacturing Engineering 337
Replace Nuria Aleixos with:
Nuria Aleixos Spain
Haiyan Cen China
Shuxiang Fan China
Min Huang China
Chunjiang Zhao China
Leiqing Pan China
Manuela Zude-Sasse Germany
Fernando Mendoza United States
Qibing Zhu China
Jitendra Paliwal Canada
Sergio Cubero relative to Nuria Aleixos Spain Nuria Aleixos's profile →
Citations per field
00.5×1.5×
Nuria Aleixos · 1×
Citations per year

Countries citing papers authored by Sergio Cubero

Since Specialization
Citations

This map shows the geographic impact of Sergio Cubero'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 Sergio Cubero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergio Cubero more than expected).

Fields of papers citing papers by Sergio Cubero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sergio Cubero. 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 Sergio Cubero. The network helps show where Sergio Cubero may publish in the future.

Co-authors

The 25 scholars most cited alongside Sergio Cubero, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sergio Cubero Line = papers co-authored together Sergio Cubero links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Recent Advances and Applications of Hyperspectral Imaging for Fruit and Vegetable Quality Assessment
Hit paper breakdown →
2011413
2 2010373
3 2019229
4 2014130
5 2011114
6 2008105
7 2012102
8 201691
9 202190
10 201685
11 201373
12 201673
13 200972
14 201571
15 201767
16 201663
17 202061
18 202058
19 201756
20 201256

About Sergio Cubero

Sergio Cubero is a scholar working on Analytical Chemistry, Horticulture, Biochemistry, Plant Science and Biophysics, having authored 61 papers that have together received 3.2k indexed citations. Recurring topics across this work include Spectroscopy and Chemometric Analyses (50 papers), Smart Agriculture and AI (17 papers), Advanced Chemical Sensor Technologies (13 papers), Phytochemicals and Antioxidant Activities (10 papers), Postharvest Quality and Shelf Life Management (9 papers), Horticultural and Viticultural Research (7 papers), Plant Pathogens and Fungal Diseases (7 papers) and Date Palm Research Studies (7 papers). The work is most often cited by research in Analytical Chemistry (2.2k citations), Biophysics (362 citations), Plant Science (1.6k citations), Biochemistry (246 citations) and Industrial and Manufacturing Engineering (337 citations). Sergio Cubero has collaborated with scholars based in Spain, Colombia and Italy. Frequent co-authors include J. Blasco, Nuria Aleixos, Juan Gómez‐Sanchís, Enrique Moltó, Pau Talens, D. Lorente, Victoria Cortés, Sandra Munera, Oscar Leonardo García-Navarrete and J.M. Prats-Montalbán. Their work appears in journals such as Food and Bioprocess Technology, Postharvest Biology and Technology, Journal of Food Engineering, Biosystems Engineering and Computers and Electronics in Agriculture.

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.

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