Prospecting for rare earth element (hyper)accumulators in the Paris Herbarium using X-ray fluorescence spectroscopy reveals new distributional and taxon discoveries.

BACKGROUND: Rare earth elements (REEs) are increasingly crucial for modern technologies. Plants could be used as a biogeochemical pathfinder and a tool to extract REEs from deposits. However, a paucity of information on suitable plants for these tasks exists. METHODS: We aimed to discover new REE-(hyper)accumulating plant species by performing an X-ray fluorescence (XRF) survey at the Herbarium of the Muséum national d'Histoire naturelle (MNHN, Paris, France). We selected specific families based on the likelihood of containing REE-hyperaccumulating species, using known taxa that accumulate REEs. A total of 4425 specimens, taken in the two main evolutionary lineages of extant vascular plants, were analysed, including the two fern families Blechnaceae (n = 561) and Gleicheniaceae (n = 1310), and the two flowering plant families Phytolaccaceae (n = 1137) and Juglandaceae (n = 1417). KEY RESULTS: Yttrium (Y) was used as a proxy for REEs for methodological reasons, and a total of 268 specimens belonging to the genera Blechnopsis (n = 149), Dicranopteris (n = 75), Gleichenella (n = 32), Phytolacca (n = 6), Carya (n = 4), Juglans (n = 1) and Sticherus (n = 1) were identified with Y concentrations ranging from the limit of detection (LOD) >49 µg g-1 up to 1424 µg g-1. Subsequently, analysis of fragments of selected specimens by inductively coupled plasma atomic emission spectroscopy (ICP-AES) revealed that this translated to up to 6423 µg total REEs g-1 in Dicranopteris linearis and up to 4278 µg total REEs g-1 in Blechnopsis orientalis which are among the highest values ever recorded for REE hyperaccumulation in plants. It also proved the validity of Y as an indicator for REEs in XRF analysis of herbarium specimens. The presence of manganese (Mn) and zinc (Zn) was also studied by XRF in the selected specimens. Mn was detected in 1440 specimens ranging from the detection limit at 116 µg g-1 up to 3807 µg g-1 whilst Zn was detected in 345 specimens ranging from the detection limit at 77 µg g-1 up to 938 µg g-1. CONCLUSIONS AND IMPLICATIONS: This study led to the discovery of REE accumulation in a range of plant species, substantially higher concentrations in species known to be REE hyperaccumulators, and records of REE hyperaccumulators outside of the well-studied populations in China.

Reflectance spectroscopy as a promising tool for 'sensing' metals in hyperaccumulator plants.

MAIN CONCLUSION: The VNIR reflectance spectra of nickel hyperaccumulator plant leaves have spectral variations due to high nickel concentrations and this property could potentially be used for discovery of these plants.  Hyperaccumulator plants accumulate high concentrations of certain metals, including manganese, cobalt, or nickel. Of these metals, the divalent ions of nickel have three absorption bands in the visible to near-infrared region which may cause variations in the spectral reflectance of nickel hyperaccumulator plant leaves, but this has not been investigated previously. In this shortproof-of-concept study, the spectral reflectance of eight different nickel hyperaccumulator plant species leaves were subjected to visible and near-infrared and shortwave infrared (VNIR-SWIR) reflectance spectrum measurements in dehydrated state, and for one species, it was also assessed in hydrated state. Nickel concentrations in the plant leaves were determined with other methods and then correlated to the spectral reflectance data. Spectral variations centred at 1000 ± 150 nm were observed and had R-values varying from 0.46 to 0.96 with nickel concentrations. The extremely high nickel concentrations in nickel hyperaccumulator leaves reshape their spectral reflectance features, and the electronic transition of nickel-ions directly contributes to absorption at ~ 1000 nm. Given that spectral variations are correlated with nickel concentrations it make VNIR-SWIR reflectance spectrometry a potential promising technique for discovery of hyperaccumulator plants, not only in the laboratory or herbarium, but also in the field using drone-based platforms. This is a preliminary study which we hope will instigate further detailed research on this topic to validate the findings and to explore possible applications.

X-ray fluorescence spectroscopy (XRF) for metallome analysis of herbarium specimens.

BACKGROUND: "Herbarium X-ray Fluorescence (XRF) Ionomics" is a new quantitative approach for extracting the elemental concentrations from herbarium specimens using handheld XRF devices. These instruments are principally designed for dense sample material of infinite thickness (such as rock or soil powder), and their built-in algorithms and factory calibrations perform poorly on the thin dry plant leaves encountered in herbaria. While empirical calibrations have been used for 'correcting' measured XRF values post hoc, this approach has major shortcomings. As such, a universal independent data analysis pipeline permitting full control and transparency throughout the quantification process is highly desirable. Here we have developed such a pipeline based on Dynamic Analysis as implemented in the GeoPIXE package, employing a Fundamental Parameters approach requiring only a description of the measurement hardware and derivation of the sample areal density, based on a universal standard. RESULTS: The new pipeline was tested on potassium, calcium, manganese, iron, cobalt, nickel, and zinc concentrations in dry plant leaves. The Dynamic Analysis method can correct for complex X-ray interactions and performs better than both the built-in instrument algorithms and the empirical calibration approach. The new pipeline is also able to identify and quantify elements that are not detected and reported by the device built-in algorithms and provides good estimates of elemental concentrations where empirical calibrations are not straightforward. CONCLUSIONS: The new pipeline for processing XRF data of herbarium specimens has a greater accuracy and is more robust than the device built-in algorithms and empirical calibrations. It also gives access to all elements detected in the XRF spectrum. The new analysis pipeline has made Herbarium XRF approach even more powerful to study the metallome of existing plant collections.

Quantification of spatial metal accumulation patterns in Noccaea caerulescens by X-ray fluorescence image processing for genetic studies.

BACKGROUND: Hyperaccumulation of trace elements is a rare trait among plants which is being investigated to advance our understanding of the regulation of metal accumulation and applications in phytotechnologies. Noccaea caerulescens (Brassicaceae) is an intensively studied hyperaccumulator model plant capable of attaining extremely high tissue concentrations of zinc and nickel with substantial genetic variation at the population-level. Micro-X-ray Fluorescence spectroscopy (µXRF) mapping is a sensitive high-resolution technique to obtain information of the spatial distribution of the plant metallome in hydrated samples. We used laboratory-based µXRF to characterize a collection of 86 genetically diverse Noccaea caerulescens accessions from across Europe. We developed an image-processing method to segment different plant substructures in the µXRF images. We introduced the concentration quotient (CQ) to quantify spatial patterns of metal accumulation and linked that to genetic variation. RESULTS: Image processing resulted in automated segmentation of µXRF plant images into petiole, leaf margin, leaf interveinal and leaf vasculature substructures. The harmonic means of recall and precision (F1 score) were 0.79, 0.80, 0.67, and 0.68, respectively. Spatial metal accumulation as determined by CQ is highly heritable in Noccaea caerulescens for all substructures, with broad-sense heritability (H2) ranging from 76 to 92%, and correlates only weakly with other heritable traits. Insertion of noise into the image segmentation algorithm barely decreases heritability scores of CQ for the segmented substructures, illustrating the robustness of the trait and the quantification method. Very low heritability was found for CQ if randomly generated substructures were compared, validating the approach. CONCLUSIONS: A strategy for segmenting µXRF images of Noccaea caerulescens is proposed and the concentration quotient is developed to provide a quantitative measure of metal accumulation pattern, which can be used to determine genetic variation for such pattern. The metric is robust to segmentation error and provides reliable H2 estimates. This strategy provides an avenue for quantifying XRF data for analysis of the genetics of metal distribution patterns in plants and the subsequent discovery of new genes that regulate metal homeostasis and sequestration in plants.