Using near-infrared spectroscopy to predict nitrogen and phosphorus concentrations of herbarium specimens under different storage conditions

• Published in: Plant methods Vol. 20; no. 1; p. 19
• Main Authors: Kühn, Paul, Proß, Tobias, Römermann, Christine, Wesche, Karsten, Bruelheide, Helge
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 01.02.2024; BioMed Central; BMC
• Subjects: Analysis; Anthropogenic factors; Biodiversity; Biogeography; Calibration; Carbon; Confounding (Statistics); Ecological studies; Environmental changes; Environmental conditions; Eutrophication; Fertilization; Fertilizers; Freezing; Functional traits; Herbaria; Herbarium; Identification and classification; Infrared spectra; Infrared spectroscopy; Leaves; Methods; Near infrared radiation; Near-infrared spectroscopy; Nitrogen; Nondestructive testing; Nutrients; Permethrin; Pesticides; Phosphorus; Plant species; Reliability; Spectrum analysis; Spraying; Storage conditions; Workflow; Iran; Germany; Herbarium; Phosphorus; Functional traits; Fertilization; Nitrogen; Near-infrared spectroscopy
• ISSN: 1746-4811; 1746-4811
• DOI: 10.1186/s13007-024-01146-x

Herbaria are becoming increasingly important as archives of biodiversity, and play a central role in taxonomic and biogeographic studies. There is also an ongoing interest in functional traits and the way they mediate interactions between a plant species and its environment. Herbarium specimens allow tracking trait values over time, and thus, capturing consequences of anthropogenic activities such as eutrophication. Here, we present an open, reproducible, non-destructive workflow to collect leaf trait data from herbarium specimens using near-infrared spectroscopy (NIRS), and a proof of concept for the reliability of this approach. We carried out three experiments to test the suitability of non-destructive NIRS methods to predict leaf traits both for fresh and dried leaves: (1) With a fertilization experiment, we studied whether NIRS was able to capture changes in leaf N and leaf P during a fertilization experiment and we compared contents predicted by NIRS with results obtained from regular wet lab methods. Calibration models for leaf nitrogen and phosphorus contents had a quality of R  = 0.7 and 0.5, respectively. We fitted calibration models for NIRS readings on fresh and dried leaf samples, both of which produced equally precise predictions compared to results from wet lab analyses. (2) We tested the effect of herbarium conservation on NIRS readings by simulating them through the application of six treatments combining freezing, drying and pesticide spraying in a factorial scheme and comparing these with untreated samples. No consistent changes were observed in the spectra quality before and after the simulated herbarium conditions. (3) Finally, we studied the effect of specimen storage duration using specimens from a 2018 study which were re-analyzed and compared with spectra obtained in 2021. No consistent changes in spectra were observed after the storage period. The results demonstrate the reliability of NIRS to measure leaf N and P on herbarium samples. Together with the calibration method and dataset presented here, they provide a toolset allowing researchers to study the development of leaf traits and their response to environmental changes over decades and even centuries in a fast and non-destructive manner.