18 results about "Soil scientist" patented technology

The present invention discloses a method and system for detecting deep soil organic carbon and microbial carbon metabolic dynamics, which relates to the fields of soil science and environmental science and technology. The method comprises: obtaining the organic carbon content and structural characteristics in the paddy field soil, and determining the composition, function and dynamic response mechanism of the microbial community to environmental changes; setting up a control group and a treatment group, and obtaining the soil organic carbon storage change rate, CO2 emissions and influencing factors in the control group and the treatment group at different time points; constructing a data analysis model based on the soil organic carbon storage change rate, CO2 emissions and influencing factors in the control group and the treatment group at different time points, and generating a comprehensive report on deep soil organic carbon and microbial carbon metabolic dynamics. The present invention provides a scientific basis for optimizing agricultural management and responding to climate change, and reveals the positive effects of biochar addition on soil health, promoting the development of sustainable agriculture.

This invention provides a sampling device for municipal landscaping soil testing, comprising a sampling rod, an outer sleeve, and multiple telescopic sampling mechanisms spaced apart along the axial direction. The outer sleeve is slidably fitted over the sampling rod, and the extension or retraction of the sampling spoon in the telescopic sampling mechanism is controlled by sliding the outer sleeve. During sampling, the outer sleeve moves downward to retract the sampling spoon into the groove. After inserting the device into the soil to the target depth, the outer sleeve is lifted to extend the sampling spoon, which then rotates with the sampling rod to excavate soil, achieving simultaneous collection of soil samples at different depths. This device is compact in structure, easy to operate, and can complete multi-layer soil sampling in one operation, avoiding soil disturbance and sample contamination caused by repeated insertion and removal, thus improving sampling efficiency and accuracy. It is particularly suitable for rapid sampling of vertical soil profiles in municipal landscaping, environmental monitoring, and soil science research.

The utility model provides a cutting ring seal box for measuring saturated hydraulic conductivity, which relates to the field of soil detection and soil scientific experiment equipment and comprises a seal box body, a top cover is mounted at the top of the seal box body, a bottom cover is mounted at the bottom of the seal box body, the seal box body, the top cover and the bottom cover are cylindrical, a water inlet is arranged on one side of the top cover, and a water outlet is arranged on the other side of the bottom cover. A water inlet is formed in one side of the bottom cover, a water outlet is formed in one side of the bottom cover, pipe plugs are connected to the water inlet and the water outlet in a clamped mode, the cutting ring sealing box serves as a key accessory for soil saturation hydraulic conductivity measurement and has the remarkable beneficial effects, multiple functions are creatively integrated, and in a traditional mode, the soil saturation hydraulic conductivity measuring device is convenient to use. Different treatment processes and equipment are often needed for soil saturated hydraulic conductivity measurement and soil moisture characteristic curve measurement through a centrifugal machine, however, according to the sealing box, the cutting ring which is used for extracting undisturbed soil can be directly embedded into the box body, a special cutting ring is not needed for sampling and measurement, and the sampling workload is greatly reduced.

This invention relates to the field of soil science and environmental testing equipment technology, and particularly to a soil profile collection machine, comprising: a collection machine body, a frame fixedly connected to one side of the collection machine body, a vertically arranged chain drive mechanism mounted on the frame, and a soil profiler detachably connected to the chain drive mechanism via a cover plate. This invention achieves automated and standardized profile collection by driving the detachable soil profiler vertically into the soil via the chain drive mechanism. The soil profiler adopts a trapezoidal wedge-shaped entry design, along with built-in springs and liners, effectively reducing the adsorption force and static friction between the sample side and the inner wall of the outer shell, avoiding potential sample structure damage due to excessive friction. Furthermore, the detachable connection design of the cover plate, hook, and hook on the chain drive mechanism allows for rapid separation and connection of the soil profiler and the drive mechanism, improving the convenience of sample handling.

The application belongs to the technical field of soil science, and discloses a method for analyzing deformation of soil pore structure under uniaxial compaction, which comprises the following steps: collecting a soil sample; performing CT scanning on the soil sample to obtain a first image slice; performing uniaxial compaction on the soil sample, and performing CT scanning on the compacted soil sample to obtain a second image slice; performing image processing on the first image slice and the second image slice to obtain a binary image, and analyzing changes in soil pore characteristic parameters before and after compaction; obtaining a pre-compaction binary image and a post-compaction binary image of biological pores according to the first image slice and the second image slice; and calculating changes in biological pore characteristic parameters before and after compaction according to the pre-compaction binary image and the post-compaction binary image, and evaluating stability of biological pores in the compaction process. The method can quantitatively analyze deformation of soil pore structure under uniaxial compaction.

The present application relates to the field of soil science, in particular to an agricultural ecological soil quality classification method based on machine learning, wherein the soil physicochemical property evaluation coefficient of each land sub-region is obtained through the soil physicochemical property parameters of each land sub-region, the soil pollution index evaluation coefficient of each land sub-region is obtained through the soil pollution index of each land sub-region, and the soil quality evaluation index of each land sub-region is analyzed and obtained, the environmental impact evaluation coefficient of the soil is analyzed by obtaining the local environmental parameters, the comprehensive evaluation index of the soil of each land sub-region is analyzed according to the soil quality evaluation index and the environmental impact evaluation coefficient of the soil, and the grade of each land sub-region is divided, so that accurate soil quality information can be provided for agricultural production, and the agricultural production efficiency and sustainability are improved.

The invention relates to the technical field of agricultural remote sensing and soil science, in particular to a multi-source fusion hyperspectral soil nutrient remote sensing inversion system. According to the multi-source fusion hyperspectral soil nutrient remote sensing inversion system provided by the invention, through a three-layer architecture of a satellite remote sensing platform (remote sensing satellite), a near-ground air-based platform (unmanned aerial vehicle) and ground sensing equipment, multi-scale soil nutrient monitoring from a region level to a field block level is realized, and the problem of observation blind areas of single satellite data in complex terrains is solved; according to the method, the coverage is improved by more than 40%, meteorological data and topographic data are synchronously acquired, interference of environmental factors such as moisture and illumination on spectral signals is automatically weakened through a dynamic weighting mechanism, the soil organic carbon inversion precision of saline-alkali soil and wet areas is improved by 20%-30% compared with single hyperspectral data, the inversion precision is greatly improved, and the anti-noise capability is remarkably enhanced.

This invention discloses a method for effectively inhibiting the reproduction of fruit fly larvae in the nutrient soil during Arabidopsis thaliana cultivation, relating to the field of soil science. The method includes: ① planting Arabidopsis thaliana seedlings; ② preparation of a non-absorbent material; ③ application of the non-absorbent material; ④ watering in a tray. This invention has the following advantages and positive effects: By preparing a non-absorbent material, this method maintains the continuous dryness of the surface nutrient substrate, effectively inhibiting the reproduction of fruit flies on the surface of the nutrient soil during Arabidopsis thaliana cultivation. This prevents Arabidopsis thaliana seedlings from being eaten by fruit fly larvae, or even the entire plant from being eaten and dying. It also effectively inhibits the outbreak of surface terrestrial fungi, helping researchers using Arabidopsis thaliana as experimental material to efficiently and labor-savingly cultivate plant materials suitable for measuring experimental data in greenhouses.

The invention relates to the technical field of soil science, and discloses a black land ecological geological information decision-making system and method based on big data fusion, and the system comprises a big data service module which is used for obtaining multi-source data associated with a black land, carrying out the preprocessing of the multi-source data, and constructing a digital black land database; black land big data corresponding to the multi-source data are stored in the digital black land database; the multi-source data comprises geochemical data, remote sensing data, shallow drilling data and geophysical prospecting data; associating the multi-source data with five core components of the black land; the application service module is used for carrying out fusion processing on the black land big data and providing a target service corresponding to the black land ecological geological information decision; the target service at least comprises an ecological geology evaluation service, an ecological monitoring service, an ecological problem identification service, an ecological early warning service and a charting service. According to the scheme, the diversified subject requirements for the ecological geological survey of the black land can be met.

This invention relates to the field of soil science technology, specifically a method for calculating the relative spatial distribution of particulate organic matter and pore structure in CT images, comprising the following steps: S1: performing CT scanning on a soil sample and preprocessing the image to obtain a preprocessed CT image; S2: identifying and segmenting particulate organic matter and pore structure from the preprocessed CT image based on machine learning; S3: calculating the morphological characteristics of the pore structure; S4: calculating the morphological characteristics of the particulate organic matter; S5: analyzing the relative spatial distribution of the particulate organic matter and the pore structure, including calculating the distance distribution from the particulate organic matter to the surface of the pore structure. This invention not only calculates the morphological parameters of the pore structure and organic matter, but also calculates the distribution of particulate organic matter relative to the pore structure, as well as the content of particulate organic matter connected to the pores, enabling a direct characterization of the interaction mechanism between the two.

The application is suitable for the field of soil science and technology, and provides a method for estimating the influence degree of fertilization behavior on soil properties across space and time and related equipment, which comprises the following steps: obtaining initial data of a to-be-predicted area; initializing a farmland grid of the to-be-predicted area, and performing data matching and multi-dimensional clustering partitioning on geographic position data, soil data and meteorological data in the initial data and the farmland grid to obtain a plurality of farmland space-time units corresponding to the to-be-predicted area; constructing a quantitative relationship equation of a planting mode corresponding to each farmland space-time unit for replacing the influence of fertilization behavior on soil properties and performing space-time recursion to determine the influence degree prediction result of the fertilization behavior on the soil properties in each farmland space-time unit of the to-be-predicted area at different time periods, and determining the target global prediction result of the to-be-predicted area according to the influence degree prediction result of all farmland space-time units. The application can realize the estimation of the influence degree of the fertilization behavior on the soil properties in each farmland space-time unit at different target time periods.

This invention discloses a method for predicting the optimal phosphorus application rate for Fritillaria cirrhosa seedlings based on multiple soil characteristics. It belongs to the fields of plant nutrition, soil science, and traditional Chinese medicine cultivation. The method includes: obtaining data on Fritillaria cirrhosa yield and corresponding soil physicochemical properties, phosphorus cycle-related enzyme activity, and microbial community structure under different phosphorus application levels; standardizing soil and enzyme activity indicators, and preprocessing and extracting features from microbial data to obtain comprehensive feature variables; constructing a phosphorus application-yield nonlinear response model using phosphorus application rate as the independent variable and yield as the dependent variable; and determining the optimal phosphorus application rate that maximizes the predicted yield based on this model. This invention enables accurate estimation of the phosphorus requirement of Fritillaria cirrhosa, providing personalized phosphorus application schemes for different soil conditions, thereby effectively improving yield and phosphorus fertilizer utilization efficiency.

The invention discloses a method and special equipment for sampling and collecting penetrating rain of shrubs in an arid region, and relates to the technical field of sampling and collecting of penetrating rain. The special equipment comprises a support, a detachable soil sampling barrel, a water funnel and a water tank are integrated on the support, and the soil sampling barrel is controlled by a solenoid and a hand wheel to vertically move and is adaptive to soil sampling; the angle of the water channel can be adjusted, and the water channel can be matched with a water channel tank, so that fixed-point and regional rainwater can be synchronously collected; positioning piles are arranged at the bottom of the bracket to guarantee stability. The sampling method comprises the steps of standardized sampling point selection, equipment layout, process monitoring, soil sampling after raining and sample treatment. Integrated synchronous sampling of multi-dimensional samples is achieved, the problems that a traditional split type instrument is complex in operation and poor in stability are solved, the time-space relevance and data accuracy of the samples are guaranteed through a standardized process, the device adapts to the special habitat of the arid region, the field working efficiency and sampling reliability are improved, and the device is suitable for arid region shrub hydrology and soil science research.

The invention discloses a black soil surveying method based on multichannel ground penetrating radar initial arrival wave signal characteristics, and belongs to the field of metrology soil science, and the method specifically comprises the following steps: arranging multichannel ground penetrating radar survey lines in a target area to collect signals, preprocessing the signals, selecting 15-25 representative point positions for drilling, and obtaining black soil thickness and organic carbon reserve data; extracting radar first arrival wave signal features, training a black soil thickness prediction model by using a PLSR model, and fitting a black soil thickness-organic carbon reserve index conversion model; and finally substituting the radar signal features of the whole area to generate a three-dimensional black soil thickness and organic carbon reserve distribution map. The method only needs a small amount of drilling holes, reduces the cost, improves the exploration precision and efficiency, and is suitable for agricultural investigation, soil fertility evaluation and carbon sink potential estimation in the black soil area.

The application relates to the technical field of soil science, and in particular to a method and device for determining soil components of a to-be-predicted region and a storage medium. The method comprises the following steps: inputting image data into an encoder of an image prediction model to obtain a feature map after down sampling, and inputting the feature map into a decoder and an attention mechanism module respectively; the decoder performs up sampling processing on the feature map after down sampling to obtain a feature map after up sampling; the attention mechanism module identifies effective features and ineffective features in the feature map after down sampling, and inputs the effective features and the ineffective features into the decoder; the decoder fuses the effective features, the ineffective features and the feature map after up sampling to obtain a predicted soil feature map of the to-be-predicted region; and the soil components of the to-be-predicted region are determined according to the predicted soil feature map, so that the soil components of the to-be-predicted region can be determined quickly and accurately, manual participation can be reduced, human cost can be reduced, and identification speed and identification accuracy can be improved.

The invention discloses a black soil degradation real-time monitoring and early warning system and method based on multi-source remote sensing and the Internet of Things, and the system comprises a data sensing layer which is used for receiving the Internet of Things data, satellite image data and unmanned aerial vehicle image data of a research area, constructing a multi-stage land utilization transfer matrix and a geological profile in combination with prior historical data, and carrying out the real-time monitoring and early warning of the black soil degradation. Forming an ecological geological map; the data analysis layer is used for generating an agricultural machinery operation instruction by adopting an enhanced regression tree model fused with a soil science mechanism and a multi-objective optimization algorithm pair according to the ecological geological map so as to realize benefit-ecological balance; and the execution layer is used for receiving and analyzing the agricultural machine operation instruction, downloading and executing the operation parameters, and performing one-way hash on the data for storage after the operation is completed. Through accurate monitoring, optimized operation decision and efficient implementation, sustainable utilization and restoration of the land are supported, black soil resources are protected, the agricultural ecological environment quality is improved, and sustainable development of agriculture is promoted.

The invention discloses an indoor soil permeability coefficient measuring device, and belongs to the technical field of soil science devices.The indoor soil permeability coefficient measuring device comprises an annular groove, an extension cutting ring, a liquid injector arranged above the extension cutting ring, a sample cutting ring and a beaker, the extension cutting ring comprises a cutting ring body and an annular bearing plate arranged on the outer wall of the top of the cutting ring body, the bearing plate is lapped on the inner wall of the annular groove and is used for blocking the hollow part; the extension cutting ring with the annular bearing plate is arranged, the condition flow speed is set in cooperation with the liquid injection device, excessive water can flow out of the periphery of the annular bearing plate into the annular groove, and therefore the liquid injection device can inject water all the time without affecting the height of a water head, the liquid injection device and the annular groove are both provided with the scale marks, and the scale marks are convenient to use. The seepage amount in the time period from water adding to the height of the water head to dropping of the first drop of seepage water can be measured by subtracting the outflow amount of the redundant water from the initial water amount and then subtracting the amount of water in the extending cutting ring, so that the purpose of improving the measurement precision is achieved.

The invention relates to the technical field of crossing of computer vision and soil science, and discloses a soil texture image classification and spatial prediction method and system based on deep learning. The method comprises the steps of standardized image acquisition, multi-scale visual feature recognition network classification, image type judgment and profile layering layer-by-layer texture judgment, environment covariable fusion space prediction and confidence feedback regulation and control. The system comprises a standardized image acquisition module, a soil texture visual feature recognition module, a texture layering recognition module, an environment covariable fusion prediction module and a soil texture archive and drawing output module. According to the method, comprehensive extraction and effective fusion of multi-dimensional visual features such as soil color, structural body form, pore distribution and particle thickness are realized, and the fine granularity distinguishing capability of adjacent transition type soil is remarkably improved.