Black soils, which play an important role in agricultural production and food security, are well known for their relatively high content of soil organic matter (SOM). SOM has a significant impact on the sustainability of farmland and provides nutrients for plants. Hyperspectral imaging (HSI) in the visible and near-infrared region has shown the potential to detect soil nutrient levels in the laboratory. However, using portable spectrometers directly in the field remains challenging due to variations in soil moisture (SM). The current study used spectral data captured by a handheld spectrometer outdoors to predict SOM, available nitrogen (AN), available phosphorus (AP) and available potassium (AK) with different SM levels. Partial least squares regression (PLSR) models were established to compare the predictive performance of air-dried soil samples with SMs around 20%, 30% and 40%. The results showed that the model established using dry sample data had the best performance (RMSE = 4.47 g/kg) for the prediction of SOM, followed by AN (RMSE = 20.92 mg/kg) and AK (RMSE = 22.67 mg/kg). The AP was better predicted by the model based on 30% SM (RMSE = 8.04 mg/kg). In general, model performance deteriorated with an increase in SM, except for the case of AP. Feature wavelengths for predicting four kinds of soil properties were recommended based on variable importance in the projection (VIP), which offered useful guidance for the development of portable hyperspectral sensors based on discrete wavebands to reduce cost and save time for on-site data collection.

Heavy metal pollution in mine wastelands is quite severe. Iris sibirica L., an emergent wetland plant, is characterized by an ability to survive under high stress of heavy metals. This study aimed to explore the phytoremediation ability of nickel (Ni), cobalt (Co), and lead (Pb) by Iris sibirica L. under hydroponic conditions. A series of tests were conducted at different metal stress conditions to evaluate the phytoextraction and tolerance of Iris sibirica L. The concentrations of Ni, Co, and Pb in plant shoots reached their highest values in 500 mg L⁻¹ treatments, where they were 6.55%, 23.64%, and 79.24% higher than those in 300 mg L⁻¹, respectively. The same concentrations in roots also reached their peak in 500 mg L⁻¹ treatments, where they were 5.52%, 33.02%, and 70.15% higher than those in 300 mg L⁻¹, respectively. Bioconcentration factors (BCF) for Ni, Co, and Pb revealed the phytoextraction ability of Iris sibirica L., and the translocation factors (TCF) showed that Ni may be most easily translocated in the plant, followed by Co and Pb. This study indicates that, compared with Ni and Co, Iris sibirica L. is more suitable for the phytoremediation of Pb-contaminated metal mine wastelands.