An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027006%3A_____%2F23%3A10176935" target="_blank" >RIV/00027006:_____/23:10176935 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0016706123004019/pdfft?md5=911fd77065613f036d8f6035740f42ed&pid=1-s2.0-S0016706123004019-main.pdf" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0016706123004019/pdfft?md5=911fd77065613f036d8f6035740f42ed&pid=1-s2.0-S0016706123004019-main.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.geoderma.2023.116724" target="_blank" >10.1016/j.geoderma.2023.116724</a>

Result language

angličtina

Original language name

An interlaboratory comparison of mid-infrared spectra acquisition: Instruments and procedures matter

Original language description

Diffuse reflectance spectroscopy has been extensively employed to deliver timely and cost-effective predictions of a number of soil properties. However, although several soil spectral laboratories have been established worldwide, the distinct characteristics of instruments and operations still hamper further integration and interoperability across mid-infrared (MIR) soil spectral libraries. In this study, we conducted a large-scale ring trial experiment to understand the lab-to-lab variability of multiple MIR instruments. By developing a systematic evaluation of different mathematical treatments with modeling algorithms, including regular preprocessing and spectral standardization, we quantified and evaluated instruments&apos; dissimilarity and how this impacts internal and shared model performance. We found that all instruments delivered good predictions when calibrated internally using the same instruments&apos; characteristics and standard operating procedures by solely relying on regular spectral preprocessing that accounts for light scattering and multiplicative/additive effects, e.g., using standard normal variate (SNV). When performing model transfer from a large public library (the USDA NSSCKSSL MIR library) to secondary instruments, good performance was also achieved by regular preprocessing (e. g., SNV) if both instruments shared the same manufacturer. However, significant differences between the KSSL MIR library and contrasting ring trial instruments responses were evident and confirmed by a semi-unsupervised spectral clustering. For heavily contrasting setups, spectral standardization was necessary before transferring prediction models. Non-linear model types like Cubist and memory-based learning delivered more precise estimates because they seemed to be less sensitive to spectral variations than global partial least square regression. In summary, the results from this study can assist new laboratories in building spectroscopy capacity utilizing existing MIR spectral libraries and support the recent global efforts to make soil spectroscopy universally accessible with centralized or shared operating procedures.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

40106 - Agronomy, plant breeding and plant protection; (Agricultural biotechnology to be 4.4)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

GEODERMA

ISSN

0016-7061

e-ISSN

—

Volume of the periodical

440

Issue of the periodical within the volume

DEC 2023

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

14

Pages from-to

116724

UT code for WoS article

001129663100001

EID of the result in the Scopus database

2-s2.0-85178668878