Spectral Data Preprocessing

Spectral Data Preprocessing is a methodological procedure in process analytical chemistry that comprises a series of signal correction and enhancement techniques applied to raw spectral measurements to reduce instrumental and environmental noise, baseline drift, and scattering effects, thereby improving the quality and interpretability of spectral data for subsequent qualitative or quantitative analysis.

1.4K

Publications

90.4K

Citations

5.4K

Authors

1.6K

Institutions

Publications per year

2017–2026

523

Authors

5.4K

  1. JS
    Jun Sun

    Jiangsu University, China

    16 publications · 596 citations

    15

    h-index

  2. YH
    Yong He

    Zhejiang University, China

    15 publications · 627 citations

    13

    h-index

  3. XW
    Xiaohong Wu

    Jiangsu University, China

    12 publications · 389 citations

    12

    h-index

  4. PM
    Puneet Mishra

    Wageningen University & Research, Netherlands

    11 publications · 1.3K citations

    11

    h-index

  5. JR
    Jean‐Michel Roger

    Technologies & méthodes pour les agricultures de demain, France

    10 publications · 967 citations

    10

    h-index

1–5 of 5.4K

Venues

  1. Applied Spectroscopy

    91 publications · 4.3K citations

    33

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  2. Chemometrics and Intelligent Laboratory Systems

    40 publications · 2.7K citations

    27

    h-index

  3. Analytical Chemistry

    35 publications · 5.1K citations

    25

    h-index

  4. Journal of Agricultural and Food Chemistry

    25 publications · 1.4K citations

    22

    h-index

  5. Journal of Chemometrics

    39 publications · 1.9K citations

    20

    h-index

1–5