Data Brief. 2025 Sep 5;62:112030. doi: 10.1016/j.dib.2025.112030. eCollection 2025 Oct.
ABSTRACT
Parthenium hysterophorus (Famine weed) is considered one of the top seven most problematic and devastating weeds in the world. It compromises the integrity of ecosystems, human health, agricultural production and biodiversity. For example, the species releases toxic chemicals such phenolics and lactones which inhibit germination and growth of co-occurring species, leading to declines in pasture production, dry grass biomass and natural habitats and biodiversity. It may also lead to health complications in human populations, declined quality of milk and meat products from cattle and degenerative changes in liver and kidney of sheep and buffalo. Therefore, its early detection and discrimination are critical for facilitating site-specific weed management to avert its adverse impacts. The spectral library datasets that characterize P. hysterophorus spectral properties, critical for its detection, are not available in the public domain. Through this article, we aim to make accessible the first spectral dataset for P. hysterophorus and its co-occurring plant species to the research community to facilitate the development of techniques for effectively identifying and mapping its distribution at various scales, facilitate the development of more robust dimensionality reduction and classification models, and support mapping efforts aiming to scale up to operational analysis with airborne and satellite sensors. The data was collected using the Spectral Evolution spectroradiometer at Ndumo Game Reserve in KwaZulu-Natal province, South Africa. It is made available as Tables (.csv format) containing averaged Raw spectra (per Elementary Sampling Unit [ESU]), pre-processed and multi-sensor resampled data. Moreover, codes are provided in R-Statistical language to replicate the preprocessing and resampling steps. This spectral library dataset for P. hysterophorus is invaluable for aiding early detection and discrimination and evaluating the effectiveness of eradication measures, thus can potentially aid resource allocation and mitigation of severe impacts by the species.
PMID:41143271 | PMC:PMC12545815 | DOI:10.1016/j.dib.2025.112030
