Micro-fluidic chip for agricultural facility environment detection and manufacturing method thereof

Abstract

The invention discloses a micro-fluidic chip for agricultural facility environment detection and a manufacturing method thereof. The micro-fluidic chip comprises a first layer of main body substrate, a third layer of main body substrate, a fifth layer of main body substrate and a sixth layer of main body substrate which are attached together, the first-layer main body substrate comprises an air inlet, a first channel and a second channel which are communicated in sequence, and further comprises a first air outlet; the third layer of main body substrate comprises an SERS substrate placing area for placing the second layer of SERS substrate, a third harmful gas detection area upper gas chamber and a third gas outlet; the fifth layer of main body substrate comprises a fifth harmful gas detection area lower gas chamber for placing the fourth layer of PH response test paper, and a fifth gas outlet; and the sixth layer of main body substrate comprises a sixth harmful gas detection area lower gas chamber and a sixth gas outlet. The content of microorganisms and harmful gas can be synchronously and rapidly detected, and the micro-fluidic chip is simple in structure, convenient to manufacture and low in cost.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring technology for livestock farms, specifically to a microfluidic chip for environmental monitoring of agricultural facilities and its manufacturing method. Background Technology

[0002] With the development of modern animal husbandry, farms have placed higher demands on the speed and accuracy of environmental monitoring. Microorganisms (such as pathogenic bacteria and fungi) and harmful gases (such as ammonia and hydrogen sulfide) in the farm environment are key factors affecting the health of farmed animals, the safety of farm workers, and the quality of the surrounding environment.

[0003] Currently, environmental monitoring in farms uses traditional methods. For example, microbial detection relies on laboratory culture and isolation, which is cumbersome, time-consuming, and requires professional personnel. Harmful gas detection often uses portable gas sensors, which suffer from problems such as susceptibility to environmental interference in detection accuracy, high equipment costs, and inability to achieve multi-point simultaneous deployment and detection. Microfluidic technology boasts advantages such as integration, miniaturization, low sample volume, and high detection speed, showing promising application prospects in environmental monitoring. However, existing microfluidic chips face the following technical challenges in environmental monitoring: First, testing for a single indicator is insufficient to simultaneously meet the needs of farms for the detection of both microorganisms and harmful gases. Second, chip manufacturing relies heavily on complex processes such as photolithography, which are costly and time-consuming, making it unsuitable for large-scale applications. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a microfluidic chip and its manufacturing method for environmental monitoring in agricultural facilities. This chip enables simultaneous and rapid detection of microorganisms and harmful gas content. The microfluidic chip has a simple structure, is easy to manufacture, and has a low cost, providing a novel environmental monitoring method for farms.

[0005] To achieve the above objectives, this invention designs a microfluidic chip for monitoring the environment of agricultural facilities. Its special feature is that it includes a first main substrate, a third main substrate, a fifth main substrate, and a sixth main substrate that are sequentially bonded together from top to bottom, and the first main substrate, the third main substrate, the fifth main substrate, and the sixth main substrate are all made of transparent material. The first layer of the main substrate includes an air inlet, a first channel, and a second channel connected in sequence; the first channel includes a front section of channel one connected to the air inlet, a microbial Raman spectroscopy detection area located in the middle section of channel one, and an airflow bifurcation area located at the end of channel one; the second channel includes a front section of channel two connected to the end of channel one, and an upper air chamber of the first harmful gas detection area connected to the front section of channel two; the first layer of the main substrate also includes a first air outlet; The air inlet extends from the top to the bottom of the first main body substrate; the first channel is excavated from the bottom to the interior of the first main body substrate; the second channel is partially excavated from the bottom to the interior of the first main body substrate; and the first air outlet extends from the top to the bottom of the first main body substrate. The third main substrate includes a SERS substrate placement area corresponding to the microbial Raman spectroscopy detection area, a third harmful gas detection area upper chamber corresponding to the upper chamber of the first harmful gas detection area, and a third gas outlet corresponding to the first gas outlet; the third harmful gas detection area upper chamber extends from the top to the bottom of the third main substrate; the third gas outlet extends from the top to the bottom of the third main substrate. The SERS substrate placement area is provided with a second SERS substrate, which is a SERS film used to enhance microbial metabolites. The fifth main body substrate includes a fifth harmful gas detection area lower chamber corresponding to the upper chamber of the third harmful gas detection area, and a fifth gas outlet corresponding to the third gas outlet; the fifth gas outlet extends from the top to the bottom of the fifth main body substrate. A fourth layer of pH response test paper is provided between the upper air chamber of the third harmful gas detection area and the lower air chamber of the fifth harmful gas detection area. The fourth layer of pH response test paper is a breathable pH response test paper impregnated with a pH indicator. It detects multiple harmful gases by changing color through the reaction of harmful gases with the pH indicator. The sixth main body substrate includes a sixth hazardous gas detection area lower chamber corresponding to the fifth hazardous gas detection area lower chamber, and also includes the rear section of channel two in the second channel, a third channel, and a sixth outlet; the sixth hazardous gas detection area lower chamber and the rear section of channel two are excavated from the top of the sixth main body substrate to the interior; the third channel is a converging channel that converges the rear section of channel two into one section and connects to the sixth outlet, and the converging channel is excavated from the top of the sixth main body substrate to the interior; the sixth outlet corresponds to the fifth outlet and extends from the top of the sixth main body substrate to the interior.

[0006] Furthermore, an equilateral triangular prism array is provided in the microbial Raman spectroscopy detection area, and one side of each triangular prism is perpendicular to the airflow channel, with the lower end of the triangular prism array attached to the second SERS substrate.

[0007] Furthermore, the microbial Raman spectroscopy detection region is an elliptical cylinder, and the major axis of the ellipse is aligned with the airflow direction.

[0008] Furthermore, the upper chamber of the first harmful gas detection area, the upper chamber of the third harmful gas detection area, the lower chamber of the fifth harmful gas detection area, and the lower chamber of the sixth harmful gas detection area are all elliptical cylinders, and the major axis of the ellipse is consistent with the airflow direction.

[0009] Furthermore, a boss is provided at the bottom of the upper chamber of the third hazardous gas detection area, and a groove matching the boss of the upper chamber of the fifth hazardous gas detection area is provided at the top of the lower chamber of the fifth hazardous gas detection area. The fourth layer of pH response test paper is provided between the boss of the upper chamber of the third hazardous gas detection area and the groove of the lower chamber of the fifth hazardous gas detection area.

[0010] This invention also provides a method for fabricating a microfluidic chip for monitoring the environment of agricultural facilities, applicable to the aforementioned microfluidic chip for monitoring the environment of agricultural facilities, characterized by the following steps: S1) Use drawing tools to draw the molds for the first layer main body base, the third layer main body base, the fifth layer main body base, and the sixth layer main body base, and then use a 3D printer to print the molds for the first layer main body base, the third layer main body base, the fifth layer main body base, and the sixth layer main body base; S2) Pour the mixture of PDMS prepolymer and curing agent into the mold in S1), cure and demold to obtain the first main body substrate, the third main body substrate, the fifth main body substrate, and the sixth main body substrate; S3) Prepare a second SERS substrate on the upper surface of the SERS substrate placement area; S4) Prepare the fourth layer of pH response test paper. Place the cut fourth layer of pH response test paper into the lower chamber of the fifth harmful gas detection area. Align and bond the first layer of main substrate, the third layer of main substrate, the fifth layer of main substrate, and the sixth layer of main substrate to obtain the microfluidic chip.

[0011] Furthermore, in S1), high-temperature resistant photosensitive resin is used as the material, and a 3D printer is used to print the first, third, fifth, and sixth main body substrate molds. The printed molds are then ultrasonically cleaned with alcohol and cured a second time to ensure that the photosensitive resin and PDMS do not cause silicone poisoning.

[0012] Furthermore, in S2), the PDMS prepolymer and curing agent are mixed at a mass ratio of 10:1, stirred thoroughly, and then vacuum degassed for 30 minutes. The resulting mixture is poured into the mold in S1), the temperature is fixed at 70°C, the curing time is 1 hour, and the mold is demolded after cooling.

[0013] Further, in S3), the second SERS substrate is synthesized with silver-coated gold nanocubes by seed growth method, and then arranged into a dense and ordered SERS film on the upper surface of the SERS substrate placement area by drip drying self-assembly.

[0014] Further, in S4), the preparation method of the fourth layer of pH-responsive test paper includes the following steps: S41) Cut the filter paper into round pieces, wipe with 70% ethanol, and dry at 60°C for 10 minutes to remove the surface fluorescent whitening agent and residual solvent, ensuring the consistency of subsequent color development; S42) Select various pH indicators, weigh 100 mg of each, dissolve them in 20 ml of anhydrous ethanol to obtain a single mother liquor with a mass percentage of 0.5 wt%; sonicate for 20 min to completely depolymerize the indicators, filter through a 0.22 µm organic syringe filter to remove insoluble impurities, store at 4 ℃ protected from light, shelf life 30 days; S43) Lay the cut quantitative filter paper flat in a petri dish, take 3 ml of single stock solution and inject it vertically into the petri dish with the single stock solution perpendicular to the center of the filter paper, so that the quantitative filter paper is completely soaked with the single stock solution. Then place the petri dish soaked with filter paper on a horizontal wire rack and dry it at 40°C and 30%RH for 2 hours. Then vacuum dry it at 60°C for 15 minutes to completely remove residual ethanol and prevent indicator migration during storage. S44) Remove the dried indicator filter paper, cut it into a shape that matches the SERS substrate placement area (3-1), put it into an aluminum-plastic composite bag, add molecular sieve desiccant, vacuum to −0.08 MPa, fill with N2 and seal, refrigerate at 4℃, shelf life 6 months.

[0015] The advantages of this invention are: 1. The microfluidic chip designed in this invention has two detection areas: the microbial Raman spectroscopy detection area can detect multiple microorganisms at the same time, and the harmful gas detection area can detect multiple harmful gases at the same time.

[0016] 2. To achieve efficient enrichment of microorganisms and harmful gases, this invention employs a multi-layered, three-dimensional design for the microfluidic chip. The microbial Raman spectroscopy detection area is located in the first layer of the microfluidic chip. A triangular prism array design blocks microorganisms in the ambient air within the microbial detection area, and a SERS substrate is attached to the lower end of the triangular prism array to enhance the Raman signal of microbial metabolites. The harmful gas detection area features a sandwich design, with its core consisting of an array of multiple breathable pH-responsive test strips with different indicators. The breathable test strip design facilitates the reaction and color change of harmful gases with pH indicator components. The breathable pH-responsive test strips are sandwiched between the two middle layers of the microfluidic chip. The top and bottom layers of the microfluidic chip include gas inlet / outlet channels. This design improves airtightness, ensuring that harmful gases can fully pass through the pH-responsive test strips.

[0017] 3. The air in the farm flows in through the inlet of the microfluidic chip. It first passes through the microbial Raman spectroscopy detection area, where the microorganisms in the air are intercepted by the triangular prism array. Then, the air is divided into multiple streams by the channels in the microfluidic chip and flows to the harmful gas detection area. In the harmful gas detection area, the air passes through the pH response test paper from top to bottom and then converges into one stream in the microfluidic chip before finally being extracted from the microfluidic chip.

[0018] 4. The microfluidic chip body in this invention is cast from a mold. First, the molds corresponding to each layer of the main substrate are drawn using drawing software. Then, the molds of each layer of the main substrate are printed using a desktop photopolymer 3D printer. The prepared PDMS is then poured into the molds. After high-temperature curing and demolding, each layer of the main substrate of the microfluidic chip is prepared. The desktop photopolymer 3D printer is low in cost and has higher precision than the more common FDM 3D printer on the market, which can ensure that the microfluidic chip produced has accurate dimensions and channel dimensions, and a smooth and transparent surface. PDMS has the characteristics of optical transparency, biocompatibility, chemical stability and corrosion resistance, which is beneficial to the optical detection and visualization detection in this invention.

[0019] 5. The main substrates of the microfluidic chip in this invention are bonded using a plasma cleaner. The plasma cleaner first uses oxygen plasma to oxidize the methyl groups (-CH3) on the PDMS surface into silanol groups (-Si-OH), making the surface change from hydrophobic to hydrophilic. Then, the -OH groups of another PDMS or glass substrate are rapidly dehydrated to form strong Si-O-Si covalent bonds, achieving permanent bonding without glue. Compared with other bonding methods, bonding using a plasma cleaner has the advantages of no glue required, no blockage of microchannels, high bonding strength, and low-temperature non-destructive bonding.

[0020] 6. In this invention, the SERS substrate is first synthesized by seed growth method to form silver-coated gold nanocubes, and then arranged into a dense and ordered SERS film by drip drying self-assembly. The whole process takes into account morphological control, size uniformity and large-area uniform "hot spot" construction, laying the foundation for subsequent high-sensitivity detection. The SERS substrate is placed in the SERS substrate placement area of ​​the third main substrate, and then bonded to the first main substrate by plasma cleaning machine.

[0021] 7. In the fabrication of the pH-responsive test paper in this invention, a rapid quantitative filter paper with good air permeability is selected. The filter paper is impregnated with different dyes, dried, and cut into the size to be tested. The rapid quantitative filter paper has uniform pore size, high air permeability, and high uniformity, providing an excellent carrier for the binding of harmful gases and dyes. The pH-responsive test paper is placed between the upper gas chamber protrusion of the third harmful gas detection area and the lower gas chamber groove of the fifth harmful gas detection area. Then, the upper and lower main body substrates are bonded together by a plasma cleaning machine to ensure the overall airtightness of the microfluidic chip and the integrity of the air flowing through the pH-responsive test paper.

[0022] 8. The detection method of this invention addresses the quantitative analysis needs of microbial surface enhanced Raman spectroscopy (SERS). It innovatively introduces machine learning algorithms to construct a nonlinear correlation model between SERS spectral characteristics and the concentration of microorganisms in the air. In response to the fluorescence interference, noise significance, and high-dimensionality of SERS spectra, a data processing workflow including spectral preprocessing, dataset partitioning, feature extraction, and nonlinear modeling is established. The optimal regression model is selected through comparative analysis of model evaluation indicators.

[0023] 9. The detection method of this invention addresses the quantitative analysis needs of harmful gas concentrations in the air of livestock farms. It innovatively introduces a machine vision-based and ensemble learning regression model to extract deep features from preprocessed images, constructing a nonlinear mapping relationship between the color change of a visual olfactory pH-responsive test strip array and the concentration of harmful gases in the air. The sensor image to be tested is input into the trained model, which directly outputs the predicted harmful gas concentration value. This overcomes the limitations of human eye recognition and traditional image processing methods, achieving accurate and automatic quantitative analysis of harmful gas concentrations. This methodology can be easily extended to the detection of other gases; simply changing the chemical composition of the test strip and selecting a chemical dye sensitive to specific gases is sufficient to detect different gases, demonstrating broad application prospects.

[0024] 10. The detection method of the present invention only requires a microfluidic chip and any tool that can generate negative pressure, such as a syringe, a bulb syringe, or a handheld compressor, to collect on-site environmental samples in a farm.

[0025] This invention relates to a microfluidic chip and its manufacturing method for environmental monitoring in agricultural facilities. It can simultaneously and rapidly detect the content of microorganisms and harmful gases. The microfluidic chip has a simple structure, is easy to manufacture, and has a low cost, which is conducive to large-scale application. Attached Figure Description

[0026] Figure 1 This is a top view of the microfluidic chip in this invention; Figure 2 This is an exploded view of the substrate of each layer of the microfluidic chip in this invention; Figure 3 for Figure 2 A schematic diagram of the bottom structure of the first layer of the main substrate; Figure 4 This is the integrated pH-responsive test paper component of the fabricated microfluidic chip; Figure 5 This is a flowchart of the fabrication method of the microfluidic chip in this invention; Figure 6 The flowchart shows the method for detecting the environmental conditions of agricultural facilities based on a dual-index microfluidic chip according to the present invention. Figure 7 This is the user interface of the MATLAB GUI-based spectral analysis software in this embodiment of the invention. Figure 8 This is the user interface of the machine vision and ensemble learning regression software in this embodiment of the invention; In the diagram: First layer: Main substrate 1; Second layer: SERS substrate 2 (not shown in the diagram); Third layer: Main substrate 3; Fourth layer: pH response test paper 4; Fifth layer: Main substrate 5; Sixth layer: Main substrate 6. The first main body substrate 1 includes: an air inlet 1-1, a microbial Raman spectroscopy detection area 1-2, an upper air chamber 1-3 for the first harmful gas detection area, and a first air outlet 1-4; The third main substrate 3 includes: SERS substrate placement area 3-1, upper air chamber of the third harmful gas detection area 3-2, and third air outlet 3-3; The fifth main body substrate 5 includes: the lower air chamber 5-1 of the fifth harmful gas detection area and the fifth air outlet 5-2; The sixth layer of the main substrate 6 includes: the lower air chamber 6-1 of the sixth hazardous gas detection area and the sixth air outlet 6-2. Detailed Implementation

[0027] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0028] In the description of this invention, it should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention.

[0029] like Figure 1 and 2 As shown, the present invention provides a microfluidic chip for monitoring the environment of agricultural facilities, comprising a first main substrate 1, a third main substrate 3, a fifth main substrate 5, and a sixth main substrate 6 bonded together from top to bottom, wherein the first main substrate 1, the third main substrate 3, the fifth main substrate 5, and the sixth main substrate 6 are all made of transparent material.

[0030] The first layer of the main body substrate 1 includes an air inlet 1-1, a first channel, and a second channel connected in sequence; the first channel includes a front section of channel one connected to the air inlet 1-1, a microbial Raman spectroscopy detection area 1-2 located in the middle section of channel one, and an airflow bifurcation area located at the end of channel one; the second channel includes a front section of channel two connected to the end of channel one, and an upper air chamber 1-3 of the first harmful gas detection area connected to the front section of channel two; the first layer of the main body substrate 1 also includes a first air outlet 1-4.

[0031] The air inlet 1-1 extends from the top to the bottom of the first main body substrate 1, the first channel is excavated from the bottom of the first main body substrate 1 to the interior, the second channel is partially excavated from the bottom of the first main body substrate 1 to the interior, and the first air outlet 1-4 extends from the top to the bottom of the first main body substrate 1.

[0032] In this embodiment, the microfluidic chip is designed with three air inlets and outlets that communicate with the outside world: two air inlets located on the left side of the chip, and a first air outlet located on the right side of the chip.

[0033] Air from the farm enters the microfluidic chip through the inlet and first flows into the elliptical microbial Raman spectroscopy detection area 1-2 via the front section of channel one. The rear section of channel one is a bifurcation area. This rear section divides into two equal channels, then into four equal channels, connecting to the second channel. After exiting the microbial Raman spectroscopy detection area 1-2, the air splits into four streams, flowing into the four second channels respectively, and then into the upper air chamber 1-3 of the first hazardous gas detection area. Each of the four second channels has an elliptical area in the middle for detecting hazardous gases. After passing through the hazardous gas detection area, the air flows through the third channel, where the four streams converge into two streams, then into one stream, and finally are extracted from the first outlet 1-4.

[0034] In this embodiment, the microfluidic chip has an overall length of 65mm, a width of 25mm, and a height of 8mm. The first main substrate 1 has a length of 65mm, a width of 25mm, and a thickness of 2mm, and is divided into two identical detection channels. From left to right, these channels are: air inlet 1-1, the front section of channel one, the microbial Raman spectroscopy detection area 1-2, the end section of channel one, the front section of channel two, the upper air chamber of the first harmful gas detection area 1-3, and the first air outlet 1-4 at the far right of the microfluidic chip.

[0035] The air inlet 1-1 has a diameter of 1.5 mm and a height of 2 mm. The front section of channel one has a width of 1.5 mm and a height of 1 mm. The microbial Raman spectroscopy detection area 1-2 is an elliptical cylindrical region with a major semi-axis of 3 mm, a minor semi-axis of 1.5 mm, and a height of 1 mm, the details of which are as follows... Figure 3 The ellipse's major axis aligns with the flow direction, its inlet and outlet tangents are continuous, and its curvature gradually changes. Compared to circular or rectangular detection areas, it completely eliminates the low-velocity stagnation zone caused by right angles or acute angles. Within this area, equilateral triangular prisms with sides of 0.4 mm and a height of 1 mm are densely packed, with a spacing of 0.2 mm between the prisms. One side of each prism is perpendicular to the channel, allowing for better interception of airborne microorganisms. The gas bifurcation channels at the end of the channel all have an angle of 120° and a height of 1 mm.

[0036] The width and height of the second channel in the fourth section are 1mm. The upper air chamber 1-3 of the first hazardous gas detection area consists of four elliptical cylinders in two rows, with a major axis of 2.5mm, a minor axis of 1.1mm, and a height of 1mm. The first air outlet 1-4 has a diameter of 4mm and a height of 2mm.

[0037] The third layer substrate 3 includes a SERS substrate placement area 3-1 corresponding to the microbial Raman spectroscopy detection area 1-2, a second harmful gas detection area upper chamber 3-2 corresponding to the upper chamber 1-3 of the first harmful gas detection area, and a third gas outlet 3-3 corresponding to the first gas outlet 1-4; the second harmful gas detection area upper chamber 3-2 extends from the top to the bottom of the third layer substrate 3, and a boss is provided at the bottom of the second harmful gas detection area upper chamber 3-2; the third gas outlet 3-3 extends from the top to the bottom of the third layer substrate 3.

[0038] In this embodiment, the third-layer substrate 3 has a length of 65mm, a width of 25mm, and a thickness of 1.8mm. The middle of the chip is the upper gas chamber 3-2 of the second hazardous gas detection area, and the rightmost end is the third gas outlet 3-3, concentric with the first gas outlet 1-4. The upper gas chamber 3-2 of the second hazardous gas detection area consists of two rows of eight elliptical cylindrical spaces penetrating the third-layer substrate 3. The major axis of each elliptical cylinder is 2.5mm, the minor axis is 1.1mm, and the height is 3mm (including the boss height). The boss is a concentric elliptical cylinder with an outer perimeter of 3.2mm major axis and 1.7mm minor axis, an inner perimeter of 2.5mm major axis and 1.1mm minor axis, and a height of 1.2mm. The edges of the boss are chamfered to facilitate the mating of the third-layer substrate 3 and the fifth-layer substrate 5. The third gas outlet 3-3 has a diameter of 4mm and a height of 1.8mm.

[0039] The SERS substrate placement area 3-1 is provided with a second SERS substrate 2, which is a dense and ordered SERS film.

[0040] The fifth layer main body substrate 5 includes a fifth harmful gas detection area lower chamber 5-1 corresponding to the upper chamber 3-2 of the third harmful gas detection area, and a fifth gas outlet 5-2 corresponding to the third gas outlet 3-3; the top of the fifth harmful gas detection area lower chamber 5-1 is provided with a groove that matches the protrusion of the upper chamber 3-2 of the third harmful gas detection area, and the fifth gas outlet 5-2 extends from the top to the bottom of the fifth layer main body substrate 5.

[0041] In this embodiment, the fifth-layer substrate 5 has a length of 65mm, a width of 25mm, and a thickness of 2.2mm. The lower chamber 5-1 of the fifth hazardous gas detection area is located in the middle of the chip, and the fifth outlet 5-2, concentric with the third outlet 3-3, is located at the rightmost end. The lower chamber 5-1 of the fifth hazardous gas detection area corresponds to the upper chamber 3-2 of the third hazardous gas detection area, and also consists of two rows of eight elliptical cylindrical spaces penetrating the fifth-layer substrate 5. The major axis of the elliptical cylinder is 2.5mm, the minor axis is 1.1mm, and the height is 2.2mm. On the upper surface of the fifth-layer substrate 5, each elliptical cylinder has a groove at its upper end corresponding to the protrusion of the upper chamber 3-2 of the third hazardous gas detection area. The outer periphery of the groove is an ellipse with a major axis of 3.2mm, a minor axis of 1.7mm, and a depth of 1.2mm. The outer periphery of the groove is also chamfered. The fifth outlet 5-2 has a diameter of 4mm and a height of 2.2mm.

[0042] A fourth layer of pH-responsive test paper 4 is provided between the upper air chamber 3-2 of the third harmful gas detection area and the lower air chamber 5-1 of the fifth harmful gas detection area. The fourth layer of pH-responsive test paper 4 is a breathable pH-responsive test paper impregnated with dye. It detects multiple harmful gases by reacting with the impregnated dye and changing color.

[0043] The main function of the third and fifth main substrate layers 3 and 5 of the microfluidic chip is to fix the fourth pH response test paper 4 located between the two layers using a stepped design, providing a sealed channel for gas flow and preventing air from leaking out from the edge of the fourth pH response test paper 4.

[0044] The sixth-layer main body substrate 6 includes a sixth harmful gas detection area lower chamber 6-1 corresponding to the fifth harmful gas detection area lower chamber 5-1, and also includes a second channel section, a third channel, and a sixth outlet 6-2 in the second channel; the sixth harmful gas detection area lower chamber 6-1 and the second channel section are excavated from the top of the sixth-layer main body substrate 6 to the interior; the third channel is a converging channel that merges the second channel section into one section and connects to the sixth outlet 6-2, and the converging channel is excavated from the top of the sixth-layer main body substrate 6 to the interior; the sixth outlet 6-2 corresponds to the fifth outlet 5-2 and extends from the top of the sixth-layer main body substrate 6 to the interior.

[0045] In this embodiment, the main function of the sixth-layer substrate 6 is to converge eight streams of air into a single stream for extraction from the microfluidic chip. The sixth-layer substrate 6 is 65mm long, 25mm wide, and 2mm thick. From left to right, the center of the chip contains eight lower air chambers 6-1 for the sixth hazardous gas detection area. To the right, eight channels converge, forming four channels, then two more, and finally one channel. The converging channel is symmetrical to the air dispersion channel in the first-layer substrate 1. The rightmost end is the sixth air outlet 6-2, concentric with the fifth air outlet 5-2. The lower air chamber 6-1 for the sixth hazardous gas detection area is an elliptical cylindrical region with a major axis of 2.5mm, a minor axis of 1.1mm, and a height of 1mm. The widths of the converging channels on the right are 1mm, 1.5mm, and 2mm, respectively, and the height is 1mm. The angle between the converging channels is 120°. The sixth air outlet 6-2 has a diameter of 4mm and a height of 1mm.

[0046] like Figure 5 As shown, the present invention also designs a method for fabricating a microfluidic chip for monitoring the environment of agricultural facilities, applicable to the above-mentioned microfluidic chip for monitoring the environment of agricultural facilities, comprising the following steps: S1) Use drawing tools to draw structural diagrams of the first layer main body base 1, the third layer main body base 3, the fifth layer main body base 5, and the sixth layer main body base 6, and then use a 3D printer to print the molds of the first layer main body base 1, the third layer main body base 3, the fifth layer main body base 5, and the sixth layer main body base 6.

[0047] Specifically, using high-temperature resistant photosensitive resin as the material, a 3D printer is used to print the first layer main substrate 1, the third layer main substrate 3, the fifth layer main substrate 5, and the sixth layer main substrate 6 molds. The printed molds are then ultrasonically cleaned with alcohol and cured a second time to ensure that the photosensitive resin and subsequent PDMS will not cause silicone poisoning.

[0048] In this embodiment, SolidWorks was used to draw the structural diagrams of each layer of the chip, including the corresponding negative mold diagrams of the channel layer, detection area, gas inlet and outlet, and test paper fixing groove. To facilitate fabrication, each layer of the microfluidic chip in this invention is designed as a single-sided protruding or recessed mold, making it easy to create a casting mold. A desktop photopolymerization 3D printer, ELEGOO Mars5, was used with a high-temperature resistant photosensitive resin from Sanlv as the material to print the molds for each layer of the microfluidic chip's main substrate.

[0049] S2) Pour the mixture of PDMS prepolymer and curing agent into the mold in S1), cure and demold to obtain the first main body substrate 1, the third main body substrate 3, the fifth main body substrate 5, and the sixth main body substrate 6.

[0050] PDMS (polydimethylsiloxane) is a polymer material with applications in multiple fields, and its molecular formula is (C2H6OSi). n It consists of a main chain composed of silicon-oxygen bonds (Si-O) and side chains of methyl groups, forming a flexible polymer chain. After cross-linking, it becomes a hydrophobic elastomer with low surface energy and 100% light transmittance.

[0051] Specifically, the PDMS prepolymer and curing agent are mixed at a mass ratio of 10:1, stirred thoroughly, and then vacuum degassed for 30 minutes. The mixture is then poured into mold S1, the temperature is fixed at 70℃, the curing time is 1 hour, and after cooling, the mold is removed to obtain a chip layer with a complete structure.

[0052] S3) A second SERS substrate 2 is prepared on the upper surface of the SERS substrate placement area 3-1.

[0053] Specifically, the second SERS substrate 2 is synthesized using a seed growth method to produce silver-coated gold nanocubes, which are then arranged into a dense and ordered SERS film on a PDMS substrate through drop-dry self-assembly. This film is used to enhance the Raman signal of microbial metabolites. The fabrication method consists of four steps: Step 1, 11nm Au seed crystal synthesis: Add 10 mL of 1 mmol·L⁻¹ Au seed crystals to… -1 Add 10 mL of 0.2 mol·L⁻¹ solution to HAuCl₄. - 1 CTAB was rapidly injected at 0.6 mL in an ice-water bath at 30°C, using 0.01 mol·L⁻¹ solution. -1 NaBH4 was stirred for 2 min and allowed to stand for 2 h to obtain a brownish-yellow 3 nm gold seed solution; then 1.2 mL of the 3 nm seed solution was injected into 100 mL of 0.5 mmol·L⁻¹ solution. -1 HAuCl4 / 0.05mol·L -1 CTAC / 0.8mmol·L -1 The ascorbic acid (L-AA) growth medium was allowed to stand at 30°C for 3 hours, and the solution changed from light pink to wine red. After centrifugation at 8000 rpm for 10 min, the supernatant was discarded to obtain 11 nm Au seed crystals.

[0054] The second step, silver cube growth (Au@AgNCs): 11 nm Au seeds were redispersed in 100 mL of 0.5 mmol·L⁻¹ water. -1 AgNO3 / 0.05mol·L -1 CTAC / 1mmol·L -1 L-AA growth medium was allowed to stand at 30℃ for 4 hours, and the solution changed from red to yellow. After centrifugation at 7000 rpm for 8 minutes, monodisperse Au@Ag nanocubes with an average side length of 42.7 nm were obtained.

[0055] The third step, purification and phase transfer: extract three times with CHCl3 at a volume ratio of 1:1 to remove excess CTAC; then add 20 mL of 0.5 wt% PVP (MW≈40 k) methanol solution and sonicate for 10 min to form an organically stable Au@AgNCs colloid.

[0056] Step 4, self-assembly into a film: The PDMS substrate was treated with oxygen plasma for 30 seconds (power 40W) to hydrophilize the surface; then 50µL of Au@AgNCs colloid was dropped into the center of the substrate, and then covered with 20µL of deionized water to form a water / CHCl3 liquid-liquid interface; the mixture was allowed to stand at room temperature for 2 hours to evaporate, and the nanocubes shrank and arranged tightly on the water surface; after the CHCl3 was completely evaporated, it was gently blown with N2 to obtain a small piece of Au@AgNCs close-packed film with a mirror-like gloss.

[0057] S4) Prepare the fourth layer of pH response test paper 4, place the cut fourth layer of pH response test paper 4 into the lower gas chamber 5-1 of the fifth harmful gas detection area, and align and bond the first layer of main substrate 1, the third layer of main substrate 3, the fifth layer of main substrate 5, and the sixth layer of main substrate 6 to obtain a microfluidic chip.

[0058] In this embodiment, the cut fourth layer of pH response test paper 4 is placed into the groove of the lower chamber 5-1 of the fifth harmful gas detection area. Then, each main substrate layer is treated with oxygen plasma using a plasma cleaner for 30 seconds at a power of 40W. The main substrate layers treated with oxygen plasma are aligned and bonded together to complete the fabrication of the microfluidic chip.

[0059] The plasma cleaner first uses oxygen plasma to oxidize the methyl groups (-CH3) on the surface of PDMS into silanol groups (-Si-OH), making the surface change from hydrophobic to hydrophilic. Then, it rapidly dehydrates the -OH groups of another PDMS or glass sheet, forming a strong Si-O-Si covalent bond, achieving permanent bonding without glue. Compared with other bonding methods, bonding with a plasma cleaner has the advantages of no glue required, no blockage of microchannels, high bonding strength, and low-temperature non-destructive bonding.

[0060] The fourth layer pH-responsive test paper 4 in this invention is made by combining dye and filter paper to create a visual pH-responsive test paper. Specifically, the preparation method of the fourth layer pH-responsive test paper 4 includes the following steps: S41) Substrate preparation: Cut the filter paper into round pieces, wipe with 70% ethanol, and dry at 60℃ for 10 minutes to remove surface fluorescent whitening agents and residual solvents, ensuring consistent color development in the subsequent process. The filter paper used is a high-grade quantitative rapid filter paper that is bio-inert, low-cost, highly permeable, and highly uniform; cut into 50mm diameter round pieces; and wiped on one side with 70% ethanol in a clean bench.

[0061] S42) Preparation of color-sensitive mother liquor: Select multiple pH indicators, weigh 100mg of each, and dissolve them in 20ml of anhydrous ethanol to obtain a single mother liquor with a mass percentage of 0.5wt%; sonicate for 20min (40 kHz, 100 W) to completely depolymerize the indicators, filter through a 0.22µm organic syringe filter to remove insoluble impurities, store at 4 ℃ protected from light, shelf life 30 days.

[0062] In this embodiment, eight pH indicators were selected: thymol blue, cresol red, bromophenol blue, bromocresol green, methyl red, bromocresol purple, brilliant yellow, and bromothymol blue.

[0063] S43) Soaking and Drying: Lay the cut quantitative filter paper flat in a petri dish, take 3 ml of single stock solution and inject it vertically into the petri dish with the center of the filter paper to completely soak the quantitative filter paper with the single stock solution. Then place the petri dish soaked in the filter paper on a horizontal wire rack and dry it at 40°C and 30%RH for 2 h. Then vacuum dry it at 60°C for 15 min to completely remove residual ethanol and prevent indicator migration during storage.

[0064] S44) Test paper cutting: Take out the dried indicator filter paper, cut it into a shape that matches the SERS substrate placement area (3-1), put it into an aluminum-plastic composite bag, add molecular sieve desiccant, vacuum to −0.08 MPa, fill with N2 and seal, refrigerate at 4℃, shelf life is 6 months.

[0065] In this embodiment, a desktop laser cutter was used to cut the dye-impregnated filter paper into elliptical pieces with a long axis of 2.5 mm and a short axis of 1.1 mm. To avoid the influence of chromatographic and edge effects on color uniformity, only the central 30 mm diameter circular area of ​​the 50 mm diameter disc was cut. Ten pH-responsive test strips were placed in an aluminum-plastic composite bag, 1 g of molecular sieve desiccant was added, and the bag was vacuumed to −0.08 MPa and then sealed with N2. The bag was refrigerated at 4°C and had a shelf life of 6 months. Before use, the bag was allowed to equilibrate at room temperature for 30 minutes before opening to prevent condensation from hydrolyzing the dye.

[0066] The prepared microfluidic chip was placed in the environmental monitoring area of ​​the breeding farm to collect samples. Specifically, a certain amount of air was drawn in through the air inlet 1-1. The air first passed through the microbial Raman spectroscopy detection area 1-2, where microorganisms in the air were intercepted by the triangular prism array. Then, the air was divided into multiple streams by the channels within the microfluidic chip and flowed towards the harmful gas detection area. In the harmful gas detection area, the air passed from top to bottom through the fourth layer of pH response test paper 4, then converged into one stream within the microfluidic chip. Finally, the air was extracted from the microfluidic chip and flowed out from the first air outlet 1-4.

[0067] The collected microfluidic chip was placed into a Raman spectrometer to detect the microbial concentration (CFU / m³).3 The risk level was determined by placing the collected microfluidic chip in a dark box and taking a picture of the fourth layer of pH response test paper to analyze the harmful gas pollution index.

[0068] like Figure 6 As shown, the present invention discloses an agricultural facility environmental monitoring method based on a dual-index microfluidic chip, comprising the following steps: S1) Several sampling points are set up in the agricultural facility environment.

[0069] Specifically, the sampling points include the center of the livestock shed, the exhaust vent, the feed area, the manure area, and the clean area upwind.

[0070] In this embodiment, based on the factory layout and the prevailing wind direction, one sampling point is set up in the center of the livestock shed, the exhaust vent, the feed area, the manure area, and the clean area upwind. Each sampling point is labeled with a number and attached to the edge of the dual-index microfluidic chip.

[0071] S2) Take out the dual-index microfluidic chip and place it flat at the sampling point.

[0072] Connect the air inlet of the air extraction device to the first air outlet 1-4 of the dual-index microfluidic chip, extract a set amount of air, and seal the air inlet 1-1 and the first air outlet 1-4 of the dual-index microfluidic chip after the air extraction is completed.

[0073] Preferably, an air pump is used to extract 400~800ml of air from the first air outlet 1-4.

[0074] In this embodiment, a handheld air pump is connected to the first air outlet 1-4, and the piston is pulled at a constant speed to extract a total of 500ml of air.

[0075] S3) Test the sealed dual-index microfluidic chip within 4 hours, and ensure that the dual-index microfluidic chip is at 0~5℃ before testing.

[0076] In this embodiment, immediately after the air extraction is completed, the air inlet 1-1 and the first air extraction port 1-4 are sealed with airtight tape. Then, the sealed dual-index microfluidic chip is placed separately in a sealed bag to ensure no air leakage. It is returned to the testing laboratory within 4 hours. The transport box contains ice packs to prevent dye deliquescence and continued microbial metabolism.

[0077] S4) Place the sealed dual-index microfluidic chip into the Raman spectrometer, collect the Raman spectral signals of the microbial Raman spectral detection region 1-2, input the Raman spectral data into the self-built spectral analysis model based on MATLAB GUI, and output the microbial concentration and risk level of the sampling point.

[0078] Meanwhile, the sealed dual-index microfluidic chip is placed in a dark box, and images of the fourth layer of pH response test paper after the reaction are collected. The image data is then input into a self-built regression model based on machine vision and ensemble learning to output the concentration of harmful gases.

[0079] Specifically, in S4), when collecting the Raman spectral signal of the microbial Raman spectral detection area 1-2, the light spot is aligned with the center of the microbial Raman spectral detection area 1-2, and the Raman spectral signal is collected 4 to 8 times, with an offset of 0.5 mm each time. After averaging the spectrum, it is exported as a CSV format.

[0080] In this embodiment, the Raman spectrometer was configured with the following parameters: laser power 50 mW, integration time 2 s, 3 accumulations, 10 objective lenses, and the light spot aligned with the center of the microbial Raman spectroscopy detection area 1-2. Raman signals from this area were acquired 5 times, with each acquisition offset by 0.5 mm. The 5 spectra were averaged and saved as a *.csv file, named "Sampling Point-Time-Chip Number".

[0081] Import the above spectral files into the MATLAB GUI-based spectral analysis software described below, and select the preset preprocessing and feature extraction workflow (such as MSC+airPLS+CARS / UVE, etc.). The software automatically performs baseline correction, noise filtering, and feature peak extraction, and calls the built-in PLSR or LSSVM model for inference, outputting the corresponding concentration of microorganisms in the air (e.g., CFU / m³). 3 The results, along with the risk level, can be used to generate reports based on the sampling point number for assessing microbial contamination in farms.

[0082] Specifically, in S4), the self-built spectral analysis model based on MATLAB GUI includes a spectral data acquisition and import module, a spectral data preprocessing module, a peak detection and feature extraction module, a training set and test set partitioning module, and a model encapsulation module.

[0083] The spectral data acquisition and import module includes exporting the acquired Raman spectra as CSV or TXT files, loading spectra once or in batches, automatically selecting the target wavenumber range, and establishing a spectral matrix. In this embodiment, the "Import" button in the software described below is used to load spectra once or in batches, automatically select the target wavenumber range, and establish a spectral matrix.

[0084] The spectral data preprocessing module includes using SG smoothing to remove high-frequency noise, then employing SNV to suppress scattering effects and instrument drift, and finally using airPLS baseline correction to eliminate fluorescence background.

[0085] In this embodiment, the user selects the desired preprocessing method in the software interface below, and the software calls the corresponding algorithm module to complete the process. The preprocessed spectrum is then overlaid and displayed in real time on the "Baseline Correction Spectrum" coordinate axis for easy inspection.

[0086] The peak detection and feature extraction module includes automatically extracting the position and height of candidate feature peaks from the preprocessed spectrum, and then calling CARS and UVE algorithms to further screen feature wavelengths related to concentration enhancement across the entire spectrum to reduce redundant variables.

[0087] In this embodiment, after the user clicks the "Auto Peak Finding" button in the software, the software executes the peak detection algorithm to automatically extract the position and height of candidate characteristic peaks from the preprocessed spectrum and display them in a table.

[0088] The training and test set partitioning module includes using the Kennard-Stone algorithm to uniformly select samples in the feature space, dividing a portion of the samples into a training set and another portion into a test set, ensuring coverage of all concentration gradients; constructing PLSR and LSSVM regression models based on the full spectrum or characteristic wavelengths respectively, and comparing their performance with the test set using cross-validation to calculate R. 2 RMSE and RPD indicators were used to screen for the optimal regression model.

[0089] In this embodiment, 70% of the samples are divided into the training set and 30% of the samples are divided into the test set.

[0090] The model encapsulation module includes writing the parameters of the best-performing regression model into a configuration file or encapsulating them in the form of a MAT file, which is automatically loaded by the software upon startup.

[0091] In this embodiment, targeting the high-dimensionality and noisy characteristics of microbial SERS spectra in microbial Raman spectroscopy detection regions 1-2, a MATLAB GUI-based spectral analysis software was developed. The interface includes a raw spectrum display window, a baseline-corrected spectrum window, a spectral data table area, and a results display area. Buttons such as "Import," "Baseline Correction," "Automatic Peak Finding," "Save Spectrum," "Prediction Results," and "Clear" are configured to enable one-click operation from data import to concentration prediction. Figure 7 As shown.

[0092] The MATLAB GUI's spectral analysis software is divided into the following modules: 1. User Interface Module: Responsible for drawing the graphical interface and the button response logic.

[0093] 2. Data Processing Module: Enables batch import and selective cropping of spectral files (.txt, .csv, .xlsx, etc.) (e.g., fingerprint region 600–1800 cm). -1) and data caching.

[0094] 3. Algorithm Module: Integrates preprocessing algorithms such as SG smoothing, multivariate scattering correction (MSC), standard normal variable transformation (SNV), and adaptive iterative reweighted penalized least squares (airPLS), as well as feature wavelength screening algorithms such as CARS and UVE.

[0095] 4. Model Prediction Module: Encapsulates pre-trained Partial Least Squares Regression (PLSR) and Least Squares Support Vector Machine (LSSVM) models to realize the transformation from spectral input to microbial concentration output.

[0096] 5. File I / O module: Responsible for saving and exporting spectra and processing results.

[0097] 6. Visualization module: Used to draw the original / corrected spectra, label peak positions, and display prediction results.

[0098] In routine testing, users only need to import new SERS spectra and click "Predict Results". The system can then complete preprocessing, feature extraction, and model inference, outputting the corresponding microbial concentration values ​​and risk levels, and supporting the saving of the results as a report file.

[0099] Specifically, in S4), when collecting the image after the reaction of the fourth layer of pH response test paper (4), the image resolution is not less than 1920×1080.

[0100] In this embodiment, the collected microfluidic chip sample was placed in a 30cm×30cm×30cm dark box. A circular hole was made at the top of the dark box to fix the imaging equipment. A 6500 K LED ring light was used for supplemental lighting, illuminating the chip from the side at a 45° angle, with a constant brightness of 800 lx. An 18% gray card was attached to the inner wall of the dark box for white balance. Five frames of the microfluidic chip were continuously captured, and the third frame was used for analysis.

[0101] In this embodiment, the hazardous gas detection area is used to detect ammonia, a typical hazardous gas in the air. This area consists of two rows of elliptical colorimetric test strip windows, four in each row, for a total of eight. Each test strip changes color upon exposure to the gas, and its color characteristics are related to the gas concentration. This embodiment uses machine vision and an ensemble learning regression model to achieve automatic image recognition and concentration prediction, replacing the traditional manual colorimetric method.

[0102] After automatically performing color correction and white balance and extracting the rectangular ROI where the test strip array is located, the machine vision and ensemble learning regression software uses Hough circle transform to locate two rows of eight test strip windows and draws recognition circles and numbers in the image display area, realizing the visualization of "input image - automatic frame drawing".

[0103] The self-built machine vision and ensemble learning regression model includes an automatic test strip window recognition algorithm module, a color feature extraction module, and a concentration prediction module.

[0104] The automatic identification algorithm module for the test strip window includes identifying the outer boundary of the microfluidic chip, then automatically cropping the rectangular ROI containing the test strip area, then performing elliptical ROI edge detection and elliptical center coordinate sorting, and finally extracting the center region of the elliptical ROI.

[0105] In this embodiment, since the harmful gas detection area of ​​the chip consists of two rows of regularly arranged elliptical mask areas, image processing methods are used to achieve automatic detection. 1. ROI extraction: The outer boundary of the microfluidic chip is identified by grayscale, threshold segmentation and morphological closing operation, and then a rectangular ROI containing the two rows of test strips is automatically cut out.

[0106] 2. Ellipse detection and sorting: In this embodiment, an ellipse detection algorithm based on Hough transform is adopted. The steps are as follows: First, Gaussian smoothing and edge detection are performed within the ROI. Then, multi-threshold and multi-scale ellipse detection is used. Finally, the ellipse centers are clustered into two rows of four ellipses each, and sorted from left to right. If some ellipse edges are incomplete due to lighting or shooting angle, the system automatically interpolates the position based on the geometric layout to ensure that eight detection windows are identified.

[0107] 3. Central Region Extraction: To reduce false color differences caused by uneven adsorption at the test strip edges, this embodiment generates a proportionally shrunk mask (generally 40%–50% of the major and minor axes of the ellipse) in the central region of each ellipse. Then, the average color value is calculated within this central region. This method ensures stable identification of 8 test strip windows under various environments, improving the automation level of the detection.

[0108] The color feature extraction module includes extracting the RGB mean, HSV mean, and CIE Lab three-channel mean (L, a, b) from each elliptical test paper area to obtain a multidimensional color feature vector.

[0109] The Lab color space is more robust to changes in illumination, so the concentration prediction model in this embodiment mainly uses the 3D Lab features of each test strip. Ultimately, a single chip image yields an 8 × 3 = 24-dimensional color feature vector.

[0110] The concentration prediction module includes acquiring a large number of chip images under a known concentration of harmful gas, extracting multi-dimensional color feature vectors, and constructing a training set; it also employs a Random Forest Regressor as the concentration prediction model, outputting R0... 2MAE and RMSE are indicators of harmful gas concentration.

[0111] In this embodiment, ammonia prediction is used as an example. A large number of chip images are acquired under ammonia concentrations (0–30 ppm), and 24-dimensional Lab characteristics are extracted using the method described above to construct a training set. A Random Forest Regressor is used as the concentration prediction model, which has advantages including: not requiring a large amount of training data, insensitivity to noise, ability to handle nonlinear relationships, and strong interpretability (feature importance can be viewed). Finally, 5-fold cross-validation is used to evaluate the model performance, and the output R0 is calculated. 2 Indicators such as MAE and RMSE.

[0112] In this embodiment, an independent graphical user interface (GUI) was developed. The interface consists of three parts, such as... Figure 8 As shown: 1. Original image display area (left side): Used to display the imported chip image.

[0113] 2. Elliptical window recognition and labeling area (right side): Automatically recognizes 8 elliptical test strip areas on the chip and labels them with outlined elliptical frames.

[0114] 3. Concentration Result Output Area (Bottom): Displays the concentration of harmful gases (ppm) predicted by the model.

[0115] The graphical user interface has three main function buttons at the bottom: ① Import Image (Load Image): The user selects any PNG / JPG image, and the software previews and displays the image.

[0116] ② Automatic identification and labeling (Detect): The software automatically detects the eight elliptical test strip windows in the chip's hazardous gas detection area, performs positioning, geometric correction and labeling, and extracts color features at the same time.

[0117] ③ Predict concentration: Input the extracted color features into the pre-trained random forest regression model and output the corresponding harmful gas concentration value.

[0118] In the graphical user interface (GUI), after the user clicks the "③ Predict Concentration" button, the system extracts 24-dimensional Lab features from the current image, calls the built-in random forest model to perform concentration prediction, and the model outputs the concentration value (ppm) of ammonia harmful gas in the air at the corresponding sampling point, which is displayed in the "Prediction Results" area. At the same time, it provides the concentration range, the warning of exceeding the standard, and a simple pollution index.

[0119] The above-mentioned detection methods not only establish a unified detection standard, but also enable the simultaneous and rapid detection of microbial and harmful gas content.

[0120] This invention relates to a microfluidic chip and its manufacturing method for environmental monitoring in agricultural facilities. It can simultaneously and rapidly detect the content of microorganisms and harmful gases. The microfluidic chip has a simple structure, is easy to manufacture, and has a low cost, which is conducive to large-scale application.

[0121] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A microfluidic chip for environmental monitoring in agricultural facilities, characterized in that: It includes a first main body substrate (1), a third main body substrate (3), a fifth main body substrate (5), and a sixth main body substrate (6) that are attached together from top to bottom, and the first main body substrate (1), the third main body substrate (3), the fifth main body substrate (5), and the sixth main body substrate (6) are all made of transparent material; The first layer of the main body substrate (1) includes an air inlet (1-1), a first channel, and a second channel connected in sequence; the first channel includes a front section of channel one connected to the air inlet (1-1), a microbial Raman spectroscopy detection area (1-2) located in the middle section of channel one, and an airflow bifurcation area located at the end of channel one; the second channel includes a front section of channel two connected to the end of channel one, and an upper air chamber (1-3) of the first harmful gas detection area connected to the front section of channel two; the first layer of the main body substrate (1) also includes a first air outlet (1-4). The air inlet (1-1) extends from the top to the bottom of the first main body substrate (1), the first channel is excavated from the bottom of the first main body substrate (1) to the interior, the second channel is excavated from the bottom of the first main body substrate (1) to the interior, and the first air outlet (1-4) extends from the top to the bottom of the first main body substrate (1). The third main body substrate (3) includes a SERS substrate placement area (3-1) corresponding to the microbial Raman spectroscopy detection area (1-2), a third harmful gas detection area upper chamber (3-2) corresponding to the upper chamber (1-3) of the first harmful gas detection area, and a third gas outlet (3-3) corresponding to the first gas outlet (1-4); the third harmful gas detection area upper chamber (3-2) extends from the top to the bottom of the third main body substrate (3); the third gas outlet (3-3) extends from the top to the bottom of the third main body substrate (3); The SERS substrate placement area (3-1) is provided with a second SERS substrate (2), which is a SERS film used to enhance microbial metabolites; The fifth layer main body substrate (5) includes a fifth harmful gas detection area lower chamber (5-1) corresponding to the upper chamber (3-2) of the third harmful gas detection area, and a fifth air outlet (5-2) corresponding to the third air outlet (3-3); the fifth air outlet (5-2) extends from the top end to the bottom end of the fifth layer main body substrate (5); A fourth layer of pH response test paper (4) is provided between the upper air chamber (3-2) of the third harmful gas detection area and the lower air chamber (5-1) of the fifth harmful gas detection area. The fourth layer of pH response test paper (4) is a breathable pH response test paper impregnated with pH indicator. It detects a variety of harmful gases by reacting with the pH indicator and changing color. The sixth layer main body substrate (6) includes a sixth harmful gas detection area lower chamber (6-1) corresponding to the fifth harmful gas detection area lower chamber (5-1), and also includes a second channel section, a third channel, and a sixth outlet (6-2) in the second channel; the sixth harmful gas detection area lower chamber (6-1) and the second channel section are excavated from the top of the sixth layer main body substrate (6) to the interior; the third channel is a converging channel that converges the second channel section into one section and connects to the sixth outlet (6-2), and the converging channel is excavated from the top of the sixth layer main body substrate (6) to the interior; the sixth outlet (6-2) corresponds to the fifth outlet (5-2) and extends from the top of the sixth layer main body substrate (6) to the interior.

2. The microfluidic chip for monitoring the environment of agricultural facilities according to claim 1, characterized in that: An equilateral triangular prism array is provided in the microbial Raman spectroscopy detection area (1-2), and one side of each triangular prism is perpendicular to the airflow channel. The lower end of the triangular prism array is attached to the second layer SERS substrate (2).

3. The microfluidic chip for monitoring the environment of agricultural facilities according to claim 2, characterized in that: The microbial Raman spectroscopy detection area (1-2) is an elliptical cylinder, and the major axis of the ellipse is consistent with the direction of airflow.

4. The microfluidic chip for monitoring the environment of agricultural facilities according to claim 3, characterized in that: The upper chamber (1-3) of the first hazardous gas detection area, the upper chamber (3-2) of the third hazardous gas detection area, the lower chamber (5-1) of the fifth hazardous gas detection area, and the lower chamber (6-1) of the sixth hazardous gas detection area are all elliptical cylinders, and the major axis of the ellipse is consistent with the airflow direction.

5. The microfluidic chip for monitoring the environment of agricultural facilities according to claim 1, characterized in that: The bottom of the upper chamber (3-2) of the third hazardous gas detection area is provided with a boss, and the top of the lower chamber (5-1) of the fifth hazardous gas detection area is provided with a groove that matches the boss of the upper chamber (3-2) of the third hazardous gas detection area. The fourth layer of pH response test paper (4) is provided between the boss of the upper chamber (3-2) of the third hazardous gas detection area and the groove of the lower chamber (5-1) of the fifth hazardous gas detection area.

6. A method for fabricating a microfluidic chip for monitoring the environment of agricultural facilities, applicable to the microfluidic chip for monitoring the environment of agricultural facilities as described in claims 1-5, characterized in that, Includes the following steps: S1) Use drawing tools to draw the molds of the first layer main body base (1), the third layer main body base (3), the fifth layer main body base (5), and the sixth layer main body base (6), and then use a 3D printer to print the molds of the first layer main body base (1), the third layer main body base (3), the fifth layer main body base (5), and the sixth layer main body base (6); S2) Pour the mixture of PDMS prepolymer and curing agent into the mold of S1), cure and demold to obtain the first main body substrate (1), the third main body substrate (3), the fifth main body substrate (5), and the sixth main body substrate (6). S3) Prepare a second SERS substrate (2) on the upper surface of the SERS substrate placement area (3-1); S4) Prepare the fourth layer of pH response test paper (4), put the cut fourth layer of pH response test paper (4) into the lower air chamber (5-1) of the fifth harmful gas detection area, and align and bond the first layer of main body substrate (1), the third layer of main body substrate (3), the fifth layer of main body substrate (5) and the sixth layer of main body substrate (6) to obtain the microfluidic chip.

7. The method for fabricating a microfluidic chip for monitoring the environment of agricultural facilities according to claim 6, characterized in that: In S1), high-temperature resistant photosensitive resin is used as the material. The first layer of the main body substrate (1), the third layer of the main body substrate (3), the fifth layer of the main body substrate (5), and the sixth layer of the main body substrate (6) are printed by a 3D printer. The printed molds are then ultrasonically cleaned with alcohol and cured a second time to ensure that the photosensitive resin and PDMS will not cause silicone poisoning.

8. The method for fabricating a microfluidic chip for monitoring the environment of agricultural facilities according to claim 7, characterized in that: In step S2), the PDMS prepolymer and curing agent are mixed at a mass ratio of 10:

1. After thorough stirring, the mixture is degassed under vacuum for 30 minutes. The resulting mixture is then poured into the mold in step S1. The temperature is fixed at 70°C, and the curing time is 1 hour. After cooling, the mixture is demolded.

9. The method for fabricating a microfluidic chip for monitoring the environment of agricultural facilities according to claim 6, characterized in that: In S3), the second layer SERS substrate (2) is synthesized with silver-coated gold nanocubes by seed growth method, and then arranged into a dense and ordered SERS film on the upper surface of the SERS substrate placement area (3-1) by drip drying self-assembly.

10. The method for fabricating a microfluidic chip for monitoring the environment of agricultural facilities according to claim 6, characterized in that: In S4), the preparation method of the fourth layer pH-responsive test paper (4) includes the following steps: S41) Cut the filter paper into round pieces, wipe with 70% ethanol, and dry at 60°C for 10 minutes to remove the surface fluorescent whitening agent and residual solvent, ensuring the consistency of subsequent color development; S42) Select various pH indicators, weigh 100 mg of each, dissolve them in 20 ml of anhydrous ethanol to obtain a single mother liquor with a mass percentage of 0.5 wt%; sonicate for 20 min to completely depolymerize the indicators, filter through a 0.22 µm organic syringe filter to remove insoluble impurities, store at 4 ℃ protected from light, shelf life 30 days; S43) Lay the cut quantitative filter paper flat in a petri dish, take 3 ml of single stock solution and inject it vertically into the petri dish with the single stock solution perpendicular to the center of the filter paper, so that the quantitative filter paper is completely soaked with the single stock solution. Then place the petri dish soaked with filter paper on a horizontal wire rack and dry it at 40°C and 30%RH for 2 hours. Then vacuum dry it at 60°C for 15 minutes to completely remove residual ethanol and prevent indicator migration during storage. S44) Remove the dried indicator filter paper, cut it into a shape that matches the SERS substrate placement area (3-1), put it into an aluminum-plastic composite bag, add molecular sieve desiccant, vacuum to −0.08 MPa, fill with N2 and seal, refrigerate at 4℃, shelf life 6 months.

Images