Pine needles as bioindicator and biomagnetic indicator of selected metals in the street dust, a case study from southeastern Iran

Among the different approaches currently being used to evaluate the contamination level of street dust, the magnetic susceptibility of dust and urban tree leaves has received little attention. The key objectives of this study were: (i) to investigate the feasibility of using pine needles as a bioindicator and biomagnetic indicator for estimating the concentration of selected metals in street dust, and (ii) to predict the contamination level of street dust by selected metals using magnetic susceptibility. Street dust and pine tree needle samples were taken from 60 locations in three adjacent cities in Kerman province (Kerman, Rafsanjan, and Sirjan), southeastern Iran. The total concentrations of selected metals, including Cu, Zn, Fe, Mn, Ni, and Pb, and the magnetic susceptibility (χlf and χhf) values of both pine tree needles and street dust samples were determined. Among the three cities studied, samples from Kerman showed the highest magnetic susceptibility and metal concentration values. This could be attributed to the larger size and much higher population density of this city, with more industrial activities and urban traffic than the other two cities investigated. The results also showed that the concentrations of metals in pine needles were strongly correlated (p < 0.01) with those in street dust. The magnetic susceptibility of pine needles and the concentrations of Fe, Pb, Zn, Cu, Ni, and Mn in street dust showed a statistically significant correlation (p < 0.01). A strong and statistically significant correlation (p < 0.01) was also found between magnetic susceptibility and the concentration of metals in pine needles. In conclusion, strong relationships between magnetic properties and metal concentrations of pine needles with those of street dust samples seem to make pine needles a good bioindicator and biomagnetic estimator of the contamination level of metals in street dust.

Chile's agricultural research institute plant tissue analysis dataset

This dataset holds 9,175 entries that report the nitrogen, phosphorus, potassium, calcium, magnesium, zinc, manganese, copper and boron contents of various plant species, with a focus on crops. The dataset accounts data of 94 plant species, and present nutrient concentration of 14 different plant tissues. The data are derived from the Soil and Plant Nutrition Lab of the Chilean Agricultural Research Institute, which provided services to farmers in the Chilean Central Valley between 2006 and 2020. The analytical methods used to generate these data were consistent across all years, ensuring the reliability of the information. Specifically, nitrogen content was determined using the Kjeldahl method, while all other analytes were quantified via colorimetry (phosphorus and boron) or atomic absorption spectrometry following high-temperature oxidation and dilution of the ashes with hydrochloric acid. The dataset has numerous potential applications, including the estimation of crop nutrient extraction rates, the identification of nutrient deficiencies or excesses, and the provision of reference or prior information for researchers studying plant physiology. The dataset includes 21 Chilean endemic species, which might be of particular interest to researchers studying the biodiversity and ecology of Chile's Central Valley.

Laser Ablation Inductively Coupled Plasma Mass Spectrometry Imaging of Plant Materials

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is a sensitive technique which enables fast, spatially resolved analysis of elements at trace concentration levels in a range of solid sample types, including plant materials. Within this chapter, we describe how to prepare leaf material and seeds for elemental distribution imaging, how to embed material in gelatin and epoxy resin, how to produce matrix-matched reference materials, and how to optimize laser ablation methods.

Innovative 3D and 2D machine vision methods for analysis of plants and crops in the field

Machine vision systems offer great potential for automating crop control, harvesting, fruit picking, and a range of other agricultural tasks. However, most of the reported research on machine vision in agriculture involves a 2D approach, where the utility of the resulting data is often limited by effects such as parallax, perspective, occlusion and changes in background light - particularly when operating in the field. The 3D approach to plant and crop analysis described in this paper offers potential to obviate many of these difficulties by utilising the richer information that 3D data can generate. The methodologies presented, such as four-light photometric stereo, also provide advanced functionalities, such as an ability to robustly recover 3D surface texture from plants at very high resolution. This offers potential for enabling, for example, reliable detection of the meristem (the part of the plant where growth can take place), to within a few mm, for directed weeding (with all the associated cost and ecological benefits) as well as offering new capabilities for plant phenotyping. The considerable challenges associated with robust and reliable utilisation of machine vision in the field are also considered and practical solutions are described. Two projects are used to illustrate the proposed approaches: a four-light photometric stereo apparatus able to recover plant textures at high-resolution (even in direct sunlight), and a 3D system able to measure potato sizes in-the-field to an accuracy of within 10%, for extended periods and in a range of environmental conditions. The potential benefits of the proposed 3D methods are discussed, both in terms of the advanced capabilities attainable and the widespread potential uptake facilitated by their low cost.

Effects of soil contamination by trace elements on white poplar progeny: seed germination and seedling vigour

Seed germination is considered a critical phase in plant development and relatively sensitive to heavy metals. White poplar (Populus alba) trees tend to accumulate Cd and Zn in their tissues. We tested if soil contamination can affect P. alba progeny, reduced seed germination and explored the distribution of mineral elements in the seed. For this purpose, fruits and seeds from female P. alba trees were selected from two contaminated and one non-contaminated areas. Seeds from all the sites were germinated using only water or a nutritive solution (in vitro). Concentrations of nutrients and trace elements in the fruits and seeds were analysed. Seedling growth in vitro was also analysed. Finally, a mapping of different elements within the poplar seed was obtained by particle-induced X-ray emission (PIXE). Germination was similar between different progenies, refuting our hypothesis that seeds from a contaminated origin would have reduced germination capacity compared to those from a non-contaminated site. Seedling growth was not affected by the contaminated origin. Cadmium and Zn concentrations in fruits produced by P. alba trees in the contaminated sites were higher than by those from the non-contaminated site. However, the nutritional status of the trees was adequate in both cases. Cd in seedlings was higher in those from contaminated soils although lower than in fruits, indicating a certain exclusion from seeds. Preliminary results of the PIXE technique showed that Al and Zn were distributed uniformly in the seeds (Cd was not detected with this technique), while the nutrients P and S were concentrated in the cotyledons.