Vis-NIR Spectroscopy for Soil Organic Carbon Assessment: A Meta-Analysis

Abstract: The research papers assessing the content of soil organic carbon with the help of Vis-NIR spectroscopy approaches are systematically analyzed and subject to meta-analysis. This meta-analysis included 134 studies published in 1986–2022 with a total sample of 709 values of quantitative metrics. The papers have been searched for in databases of scientific periodicals (RSCI, Science Direct, Scopus, and Google Scholar) by the key word combination “Vis-NIR spectroscopy AND soil organic carbon”. The meta-analysis using the nonparametric one-sided Kruskal–Wallis variance analysis in conjunction with nonparametric pairwise method shows the presence of a statistically significant difference between the median values of the accepted quantitative metrics of the predictive power of the models, namely, coefficient of determination (R 2cv/val), root mean square error (RMSE), and the ratio of performance to deviation (RPD). The best performance of the preprocessing method for spectral curves is demonstrated and the estimates of soil organic carbon content obtained by laboratory and field spectroscopies are compared. © 2023, The Author(s).

Авторы
Chinilin A.V. , Vindeker G.V. , Savin I.Y.
Журнал
Номер выпуска
11
Язык
Английский
Страницы
1605-1617
Статус
Опубликовано
Том
56
Год
2023
Организации
  • 1 Dokuchaev Soil Science Institute, Moscow, 119017, Russian Federation
  • 2 Ecological Faculty, Peoples’ Friendship University of Russia (RUDN University), Moscow, 115093, Russian Federation
Ключевые слова
algorithm; model calibration; prediction; proximal soil sensing; validation
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