CN-121994847-A - Dynamic monitoring method and system for lignin regulation and control of soil Cd bioavailability

CN121994847ACN 121994847 ACN121994847 ACN 121994847ACN-121994847-A

Abstract

The invention belongs to the field of monitoring, and particularly relates to a dynamic monitoring method for lignin regulation and control of the bioavailability of Cd in soil, which comprises the steps of obtaining Micro-XRF element surface distribution data of a soil sample to be detected, calculating a first spatial correlation of a Cd signal gradient and a carbon signal gradient and a second spatial correlation of a gradient of a weighted sum of the Cd signal gradient and a silicon signal, an aluminum signal and a ferric signal in a neighborhood of each pixel point, determining the pixel point as a target Micro-domain when the first spatial correlation is larger than a preset positive threshold and the second spatial correlation is smaller than a preset negative threshold, carrying out nano SIMS analysis on the target Micro-domain to obtain a multidimensional image data cube, carrying out unmixing on the multidimensional image data cube based on a pre-established reference ion mass spectrum library of pure lignin, pure mineral phases and Cd standards to obtain a distribution map of lignin, mineral and Cd in the target Micro-domain, and generating a high-resolution soil Cd abundance map according to the pure distribution map.

Inventors

LI QI
LI YICHUN
LI LINFENG
XIAO ANWEN
ZHENG JIN
TANG MINGDENG

Assignees

广东省农业科学院农业资源与环境研究所

Dates

Publication Date: 20260508
Application Date: 20260304

Claims (10)

1. A dynamic monitoring method for lignin to regulate and control the bioavailability of Cd in soil is characterized by comprising the following steps: Acquiring Micro-XRF element surface distribution data of a soil sample to be detected, wherein the elements comprise Cd, carbon element C representing organic matters and silicon Si, aluminum Al and iron Fe representing minerals; for each pixel point, calculating a first spatial correlation of Cd signal gradient and carbon signal gradient and a second spatial correlation of Cd signal gradient and gradient of silicon, aluminum and iron signal weighted sum in the neighborhood of the pixel point, and determining the pixel point as a target Micro-domain when the first spatial correlation is larger than a preset positive threshold and the second spatial correlation is smaller than a preset negative threshold; Performing NanoSIMS analysis on the target microdomains to obtain a multidimensional image data cube comprising Cd and 28 Si - 、 27 Al 16 O - 、 56 Fe 16 O - ions representing lignin and minerals with 12 C - 、 12 C 14 N - ions representing lignin; unmixing the multidimensional image data cube based on a pre-established reference ion mass spectrum library of pure lignin, pure mineral phases and Cd standard substances to obtain a pure abundance distribution diagram of lignin, minerals and Cd in a target micro-domain; and generating a high-resolution soil Cd occurrence morphology probability map according to the purity abundance distribution map.
2. The method according to claim 1, wherein the generating a high-resolution soil Cd occurrence morphology probability map from the pure abundance distribution map specifically comprises: Calculating Euclidean distance d 1 between each Cd-containing pixel point and the nearest lignin region boundary and Euclidean distance d 2 between each Cd-containing pixel point and the nearest mineral region boundary, constructing a Cd interface retention index I=exp (- (d 1 +d 2 )/L), wherein L is a normalized scale factor, taking the value of the Cd interface retention index I as an interface complexation probability P interface, calculating lignin adsorption probability P Lignin and mineral retention probability P Mineral material according to formulas P Lignin =(1-I)×d 2 /(d 1 +d 2 ) and P Mineral material =(1-I)×d 1 /(d 1 +d 2 ), and generating a high-resolution soil Cd occurrence morphological probability map by combining the Cd pure abundance of each pixel point.
3. The method according to claim 1, wherein the obtaining Micro-XRF element plane distribution data of the soil sample to be measured comprises: The method comprises the steps of drying a collected soil sample in a constant-temperature oven at 40 ℃ to constant weight, removing gravels and root systems with diameters larger than 2mm, placing the processed soil sample in a mould, adding low-melting-point sublimated sulfur or metal indium into the mould, immersing and embedding the soil sample in a vacuum environment, cooling and solidifying the soil sample to form a solidified sample, polishing the surface of the solidified sample step by using diamond grinding paste, sequentially using grinding paste with the diameters of 9 microns, 3 microns, 1 micron and 0.25 micron until the surface roughness Ra is less than 100 nm, setting excitation voltage to be 50 kilovolts, tube current to be 600 microamps, setting scanning step length to be 20 microns, scanning the polished sample surface in the vacuum environment, and respectively collecting characteristic X-ray fluorescence intensities of Cd, C, si, al, fe elements to generate a two-dimensional gray level intensity matrix corresponding to each element.
4. The method of claim 1, wherein for each pixel, calculating a first spatial correlation of the Cd signal gradient and the carbon signal gradient and a second spatial correlation of the Cd signal gradient and the gradient of the weighted sum of the silicon, aluminum, and iron signals in its neighborhood comprises: setting a 5×5 pixel rectangular area with a current pixel point as a center as a neighborhood; carrying out Gaussian smoothing filtering on a two-dimensional gray level intensity matrix of Cd, C, si, al, fe elements; Carrying out convolution operation on the filtered Cd matrix and the filtered C matrix by adopting a Sobel operator to obtain a Cd gradient amplitude vector G Cd and a C gradient amplitude vector G C , and calculating a correlation coefficient between G Cd and G C by utilizing a pearson correlation coefficient formula to be marked as a first spatial correlation; Respectively carrying out maximum normalization treatment on the Si, al and Fe matrixes after filtering, and adding the normalized three matrixes according to equal weights to obtain a mineral signal weighted sum matrix M sum ; and (3) carrying out convolution operation on M sum by adopting a Sobel operator to obtain a mineral comprehensive gradient amplitude vector G min , and calculating a correlation coefficient between G Cd and G min by utilizing a pearson correlation coefficient formula, and marking the correlation coefficient as a second spatial correlation.
5. The method of claim 4, wherein determining the pixel as the target micro-domain when the first spatial correlation is greater than a preset positive threshold and the second spatial correlation is less than a preset negative threshold comprises: Constructing a binarization discrimination matrix, and reserving pixel points meeting the condition that the first spatial correlation is larger than a preset positive threshold and the second spatial correlation is smaller than a preset negative threshold; And performing morphological open operation on the reserved pixel set, removing isolated noise points with the area smaller than 3 pixels, marking the residual connected areas as target Micro-domains to be analyzed, and recording the geometric center coordinates of the target Micro-domains under a Micro-XRF coordinate system and the optical characteristic images for repositioning.
6. The method of claim 1, wherein the NanoSIMS analysis of the target micro-domain to obtain a multidimensional image data cube comprises: Transferring a sample to a sample chamber of a nano secondary ion mass spectrometer, calibrating and positioning the target micro-domain by using an optical microscope and an ion image according to the recorded geometric center coordinate, setting the beam intensity to be 10 picoamperes by using a cesium ion beam as a primary ion source, pre-sputtering the surface of the target micro-domain until the secondary ion yield reaches a steady state, setting the image resolution to be 256 multiplied by 256 pixels, setting the residence time to be 5 milliseconds per pixel, synchronously collecting 12 C - 、 12 C 14 N - 、 28 Si - 、 27 Al 18 O - 、 56 Fe 16 O - and the signal intensity of characteristic secondary ions containing Cd, and constructing the multidimensional image data cube.
7. The method of claim 1, wherein said unmixing the multi-dimensional image data cube comprises: Expanding a multi-dimensional image data cube into a two-dimensional observation matrix Wherein m is the number of ion channels, n is the total number of pixels, constructing a standard mass spectrum feature vector containing pure lignin, pure quartz, pure kaolinite, pure hematite and Cd standard substances, normalizing to be used as an initial value of a base matrix W, randomly initializing a non-negative abundance matrix H, and minimizing an objective function through an iterative updating rule: ; ; outputting an abundance matrix H, and remolding the abundance matrix H into an image size to obtain a pure abundance distribution diagram of lignin, minerals and Cd until the relative change rate of the objective function value is smaller than 10 -5 .
8. The method of claim 2, wherein calculating the euclidean distance d 1 of each Cd-containing pixel from the nearest lignin region boundary and the euclidean distance d 2 of the nearest mineral region boundary comprises: Setting an abundance threshold value to be 0.3, binarizing a pure abundance distribution diagram of lignin and minerals to generate a lignin binary mask M lig and a mineral binary mask M min , respectively calculating the minimum distance from each pixel point to a M lig non-zero area as d 1 and the minimum distance from each pixel point to a M min non-zero area as d 2 by adopting an Euclidean distance conversion algorithm, defining the corresponding distance as 0 if the pixel point is positioned inside the mask, and directly enabling the interface complexation probability P Interface(s) =1, the lignin adsorption probability P Lignin =0 and the mineral retention probability P Mineral material =0 if d 1 =0 of a certain pixel point and d 2 =0 are calculated when the probability is calculated, so as to avoid the singular of zero denominator.
9. The method of claim 8, wherein the generating a high resolution map of soil Cd occurrence morphology by combining Cd pure abundance of each pixel comprises: Setting a normalized scale factor L=50 nanometers, constructing an RGB image matrix by using the calculated P Lignin 、P Mineral material and P Interface(s) for each pixel point containing Cd, mapping P Mineral material to a red channel R, mapping P Lignin to a green channel G and mapping P Interface(s) to a blue channel B, carrying out 8-bit quantization on channel values, and synthesizing a false color image to obtain a soil Cd occurrence morphology probability map showing three morphology distribution probabilities of Cd in lignin adsorption, mineral holding and interfacial complexation.
10. A dynamic monitoring system for lignin to regulate the bioavailability of Cd in soil, comprising the following units: The system comprises a target Micro-domain determining unit, a target Micro-domain determining unit and a target Micro-domain determining unit, wherein the target Micro-domain determining unit is used for acquiring Micro-XRF element surface distribution data of a soil sample to be detected, the elements comprise Cd, carbon C element representing organic matters and silicon Si, aluminum Al and iron Fe element representing minerals; a nano-sims analysis unit for performing nano-sims analysis on the target microdomains to obtain a multi-dimensional image data cube, wherein the data cube comprises Cd and 12 C - 、 12 C 14 N - ions representing lignin and 28 Si - 、 27 Al 16 O - 、 56 Fe 16 O - ions representing minerals; the unmixing unit is used for unmixing the multidimensional image data cube based on a pre-established reference ion mass spectrum library of pure lignin, pure mineral phases and Cd standard substances to obtain a pure abundance distribution diagram of lignin, minerals and Cd in a target micro-domain; and the probability map generating unit is used for generating a high-resolution soil Cd occurrence morphology probability map according to the pure abundance distribution map.

Description

Dynamic monitoring method and system for lignin regulation and control of soil Cd bioavailability Technical Field The application belongs to the field of control, and particularly relates to a dynamic monitoring method and a system for lignin to regulate and control the bioavailability of Cd in soil. Background Soil heavy metal cadmium (Cd) pollution has high toxicity and easy bioaccumulation, and the migration and transformation capacity and bioavailability of cadmium in soil are not only dependent on the total content of the cadmium, but also greatly dependent on the occurrence form of the cadmium in the soil microenvironment. Soil is a complex system formed by minerals, organic matters such as lignin and interaction thereof, lignin is taken as a main product of degradation of plant residues, contains rich oxygen-containing functional groups and is a key component for regulating and controlling the activity of cadmium in the soil. The soil heavy metal morphological analysis method mainly depends on a chemical continuous extraction method such as a BCR method, is a destructive macroscopic statistical means in nature, cannot keep original physical structure and micro-area distribution information of soil, and is easy to cause heavy metal re-adsorption or morphological transformation in the extraction process, so that analysis results are distorted. Furthermore, it is difficult to elucidate the retention behavior of organic substances on cadmium by microscopic mechanisms. With the development of in-situ high-resolution imaging technologies such as synchrotron radiation X-ray fluorescence spectroscopy (Micro-XRF) and nano secondary ion mass spectrometry (nano SIMS), people can directly observe the distribution characteristics of heavy metals on a microscopic scale. In Micro-XRF data, the target microdomains with specific interactions such as organic-inorganic complexes cannot be accurately located, and when NanoSIMS are analyzed with high definition, signals of different components tend to be aliased at the pixel level due to the high complexity of the soil microenvironment, forming mixed pixels, and it is difficult to resolve pure component distribution. The specific adsorption probability and the specific holding strength of cadmium in lignin, mineral and the interface between the lignin and the mineral can not be determined and distinguished, so that the deep research on the microscopic occurrence form of the cadmium in the soil is limited. Disclosure of Invention In order to solve the above problems, in a first aspect, a method for dynamically monitoring the bioavailability of lignin to regulate the Cd in soil is provided, comprising the following steps: Acquiring Micro-XRF element surface distribution data of a soil sample to be detected, wherein the elements comprise Cd, carbon element C representing organic matters and silicon Si, aluminum Al and iron Fe representing minerals; for each pixel point, calculating a first spatial correlation of Cd signal gradient and carbon signal gradient and a second spatial correlation of Cd signal gradient and gradient of silicon, aluminum and iron signal weighted sum in the neighborhood of the pixel point, and determining the pixel point as a target Micro-domain when the first spatial correlation is larger than a preset positive threshold and the second spatial correlation is smaller than a preset negative threshold; Performing NanoSIMS analysis on the target microdomains to obtain a multidimensional image data cube comprising Cd and 28Si-、27Al16O-、56Fe16O- ions representing lignin and minerals with 12C-、12C14N- ions representing lignin; unmixing the multidimensional image data cube based on a pre-established reference ion mass spectrum library of pure lignin, pure mineral phases and Cd standard substances to obtain a pure abundance distribution diagram of lignin, minerals and Cd in a target micro-domain; and generating a high-resolution soil Cd occurrence morphology probability map according to the purity abundance distribution map. In a second aspect, a dynamic monitoring system for lignin to regulate the bioavailability of Cd in soil is provided, comprising the following units: The system comprises a target Micro-domain determining unit, a target Micro-domain determining unit and a target Micro-domain determining unit, wherein the target Micro-domain determining unit is used for acquiring Micro-XRF element surface distribution data of a soil sample to be detected, the elements comprise Cd, carbon C element representing organic matters and silicon Si, aluminum Al and iron Fe element representing minerals; a nano-sims analysis unit for performing nano-sims analysis on the target microdomains to obtain a multi-dimensional image data cube, wherein the data cube comprises Cd and 12C-、12C14N- ions representing lignin and 28Si-、27Al16O-、56Fe16O- ions representing minerals; the unmixing unit is used for unmixing the multidimensional image data cube based on a pre-establish