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Spectroscopy and Chemometric Analyses

Spectroscopy and Chemometric Analyses is a research topic within Analytical Chemistry. Science Explorer counts 65k research works in it since 1950. 19.5% of them reached the world's top 10% most cited for their field and year.

This cluster of papers covers a wide range of topics in chemometrics, with a focus on applications in analytical chemistry and food technology. It includes methods such as near-infrared spectroscopy, multivariate calibration, hyperspectral imaging, variable selection, and machine vision for quality assessment and food authentication.

  • Near-Infrared Spectroscopy
  • Multivariate Calibration
  • Hyperspectral Imaging
  • Variable Selection
  • Chemometric Tools
  • Quality Assessment
  • Machine Vision
  • Spectral Analysis
  • Food Authentication
  • Principal Component Analysis
Research works
65k
fractional, since 1950
In the world top 10%
13k
per year above
Top-10% rate
19.5%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+36%
the tick is no change

Which countries lead Spectroscopy and Chemometric Analyses research?

By volume, China and India publish the most (4.2k and 2.3k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 4.2k works
  2. 2 India 2.3k works
  3. 3 United States 995 works
  4. 4 Indonesia 539 works
  5. 5 Brazil 432 works
  6. 6 Italy 378 works
  7. 7 Japan 324 works
  8. 8 Türkiye 316 works
  9. 9 Germany 316 works
  10. 10 Spain 315 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 41.5%India: 22.5%United States: 9.9%Indonesia: 5.4%6 others listed: 20.7%42%largest
China4,178 · 41.5%India2,265 · 22.5%United States995 · 9.9%Indonesia539 · 5.4%6 others listed2,081 · 20.7%

Shares of the rows listed above, not of the whole node.

Which institutions lead Spectroscopy and Chemometric Analyses research?

By volume in 2022–2025, Jiangsu University publishes the most Spectroscopy and Chemometric Analyses research, followed by Chitkara University and China Agricultural University.

By volume, 2022–2025

  1. 1 Jiangsu University China 102 works
  2. 2 Chitkara University India 94 works
  3. 3 China Agricultural University China 91 works
  4. 4 Ministry of Agriculture and Rural Affairs China 71 works
  5. 5 SRM Institute of Science and Technology India 66 works
  6. 6 Zhejiang University China 62 works
  7. 7 Vellore Institute of Technology University India 57 works
  8. 8 Saveetha University India 55 works
  9. 9 Graphic Era University India 51 works
  10. 10 Chinese Academy of Sciences China 45 works

Where is Spectroscopy and Chemometric Analyses research done?

The largest centres of Spectroscopy and Chemometric Analyses research in 2022–2025 are Beijing (China), Chennai (India), Hangzhou (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Jinrongjie, Aral and Xiaodian.

Largest cities, 2022–2025

  1. 1 Beijing China 722 works
  2. 2 Chennai India 240 works
  3. 3 Hangzhou China 200 works
  4. 4 Nanjing China 184 works
  5. 5 Shanghai China 158 works
  6. 6 Guangzhou China 143 works
  7. 7 Wuhan China 121 works
  8. 8 Xi'an China 118 works
  9. 9 Zhenjiang China 111 works
  10. 10 Moscow Russia 109 works

Where it is the local speciality

  1. JinrongjieCN · 32.9 works27×
  2. AralCN · 20.5 works21×
  3. XiaodianCN · 27.0 works15×
  4. Lin’an ShiCN · 26.8 works12×
← less than its size predictsmore →

Location quotient: how much more of its research is in Spectroscopy and Chemometric Analyses than the world average.

See Spectroscopy and Chemometric Analyses on the map

Where is the best place to study Spectroscopy and Chemometric Analyses?

Among universities, judged by research, Jiangsu University, China Agricultural University and Chitkara University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%60%mean 43.61%fractional works in this node (log) →share in the world top 10% →Jiangsu University: 102, 55.3%China Agricultural University: 91, 41.8%Chitkara University: 94, 30.6%Daffodil International University: 18, 40.0%Sant Longowal Institute of Engineering and Technology: 8, 56.7%Zhejiang A & F University: 27, 41.8%Northwest A&F University: 38, 41.4%Jimei University: 16, 56.7%King Mongkut's Institute of Technology Ladkrabang: 22, 27.1%Nanjing Agricultural University: 39, 44.7%Jiangsu UniversityChina Agricultural U…Daffodil Internation…Chitkara University
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1Jiangsu University China 78.655.3%9.6×102 +6.1%
2China Agricultural University China 69.241.8%11.6×91 -33.7%
3Chitkara University India 68.530.6%17.1×94
4Daffodil International University Bangladesh 64.140.0%13.4×18
5Sant Longowal Institute of Engineering and Technology India 62.956.7%11.9×8 +70.0%
6Zhejiang A & F University China 62.341.8%12.2×27 +9.2%
7Northwest A&F University China 61.241.4%6.9×38 +81.4%
8Jimei University China 60.156.7%7.1×16
9King Mongkut's Institute of Technology Ladkrabang Thailand 58.327.1%11.8×22 +95.0%
10Nanjing Agricultural University China 57.944.7%7.1×39 -7.5%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Spectroscopy and Chemometric Analyses research growing?

Output in 2018–2022 was 36% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Spectroscopy and Chemometric Analyses.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.