Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.03.30.646218

Effects of amendments on remediation of heavy metal contaminated soil and accumulation of Cd and Pb in potato

He, R.·Liu, K.·Yang, F.·Feng, S.·Zhang, L.
View original source ↗Export metadata ↓

Abstract

With the development of agriculture and industry, a large amount of heavy metals are loaded into the soil, posing a high ecological and public health risk. Many methods have been proposed to repair heavy metal contaminated soil, such as electroremediation, chemical washing, phytoremediation and in situ fixation. In the above methods, the application of passivators to in-situ immobilization of heavy metals is an environmentally friendly and cost-effective choice. The effects of different amendments on the improvement of heavy metal contaminated soil and the accumulation of Cd and Pb in potato plants were investigated by using attapulgite, diatomite and humic acid as materials.The results showed that soil pH, organic matter content and cation exchange capacity increased after the application of amendments. Under the treatment of attapulgite+humic acid, the soil pH, organic matter content and cation exchange capacity were increased by 0.57units, 10.0 mg/kg and 7.28cmol/kg, respectively, compared with the control. The content of soil hydrolyzable nitrogen increased, and the content of available phosphorus decreased. The application of amendments increased soil enzyme activity; effectively reduce the bioavailability of Cd and Pb in soil ; under the treatment of attapulgite+humic acid, the contents of Cd and Pb in potato plants decreased by 85.50%and 55.54%respectively, and the contents of Cd and Pb in potato tubers decreased to 0.08 mg/kg and 1.41 mg/kg respectively. The application of amendments affected the accumulation and transport of heavy metals Cd and Pb in potato plants to a certain extent and promoted the transformation of Cd and Pb from acid-soluble and reduced states to oxidized and residual states.

Explore related subjects

ecologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

He, R., Liu, K., Yang, F., Feng, S., Zhang, L.. 2025-04-01. Effects of amendments on remediation of heavy metal contaminated soil and accumulation of Cd and Pb in potato. https://doi.org/10.1101/2025.03.30.646218

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Operationalising the context in regenerative agriculture: decision-making and farm variability

Soil degradation is a widespread challenge that requires a broad response at the individual farm level. To ensure effectivity, the practices should be tailored to the farm context: land manager objectives and farm specific challenges. These have however been difficult to quantify. Here we demonstrate that a workable farm context can be created based on a value survey, open satellite and soil data, and published models for vegetation gross primary productivity and soil erosion. Based on the findings, despite individual differences, farmers value profitability and operational efficiency, but also biodiversity and soil health. At least the regenerative farmers surveyed also value working for the greater good more than maintaining tradition or power. In spite of wide differences in farm production orientation, we also found that each farm also had a broad variation in individual fields GPP. Most fields have a stable GPP level, which is either high or low, and that there is a 2-3-fold difference between the weakest and best producing fields indicating the potential for improving GPP by improving the growing conditions on currently weak fields. In addition, soil loss was found to be highly concentrated in critical source areas, where 10% of the field area contributed to 50% of the soil loss. Overall, open data can be linked to modelling workflows to rapidly produce a decision-making context for farmers. This facilitates benchmarking and co-learning as well as enables land managers and advisors to identify the farm context for planning effective responses to soil degradation.

ecology↗
bioRxiv2026

Fly, land, listen: Autonomous intermittent locomotion enables scalable low-noise drone ecoacoustic surveys

Ecoacoustic monitoring is enabling scientists and land managers to monitor and manage biodiversity more effectively and cost-efficiently in the face of human pressures and rapidly changing climates. Currently, most ecoacoustic surveys use manually deployed static sensors to record data, limiting the scale and reach of surveying efforts. Here we present a proof-of-concept autonomous drone platform that can use intermittent locomotion to conduct ecoacoustic surveys using an onboard sensor. Our custom prototype is able to fly, navigate, and avoid obstacles autonomously, land at a pre-determined location, record audio from an onboard microphone whilst static, before taking off and moving to the next sampling site. Autonomous navigation and operation enable greater sampling flexibility, reach, and scalability. Furthermore, by recording audio only whilst landed, noise from the drone's rotors does not mask signals or disturb animals, simplifying signal processing and downstream ecological analyses. We conducted trials in a scrubland habitat at the Knepp Estate in West Sussex, where our prototype demonstrated successful autonomous navigation and obstacle avoidance. Furthermore, we found that avian biodiversity data collected from the drone platform was comparable to that from traditional static acoustic sensor deployments, and that vocalisation patterns were not significantly impacted by the noise of the drone arriving or leaving a site. While scaled deployments of our technology would require further technical and regulatory challenges to be solved, our first demonstration of autonomous intermittent robotics-assisted ecoacoustic surveys lays the foundations for more cost-effective and far-reaching biodiversity surveys, with transformative potential for conservation, agricultural management, biosecurity, and more.

ecology↗
bioRxiv2026

Do higher-order moments improve inference of population dynamics?

Fitting mathematical models of population dynamics to microbial time-series data allows us to estimate the ecological processes and interactions taking place in the microbiome. Repeated experiments of microbial systems yield replicates which slightly differ from each other. Some of this variability arises due to the fact that births and deaths occur at random. Most prior work focuses on fitting a deterministic mathematical model to the average across replicates. We use a stochastic model to fit the variability to the observed variability across replicates. Using a simulation-driven approach, we study the conditions under which our approach allows us to infer a larger fraction of ecological parameters correctly. We observe a substantial improvement in parameter inference. Lastly, our Bayesian approach not only allows us to incorporate prior information about the system, but also provides a distribution of parameters which conveys some idea of the uncertainty of the estimates.

ecology↗