Description:SYSTEM TO DETERMINE QUALITY PARAMETERS OF AN AGRIPRODUCT
Field of the Invention
[0001] The present disclosure generally relates to agricultural product quality assessment systems. Further, the present disclosure particularly relates to a system to determine quality parameters of an agriproduct.
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Commodity quality assessment plays a significant role in the food industry, where parameters like brix rating, moisture content and acidity are crucial to assess ripeness, sweetness and shelf life. Accurate measurement of these parameters enables producers to ensure the quality and consistency of the commodities before they reach consumers. Traditionally, invasive and destructive methods such as refractometry, oven drying and wet chemistry are employed to determine such parameters. Refractometry is used to measure brix rating by determining the refractive index of a commodity. Oven drying is utilised to calculate moisture content through the loss of mass after drying the commodity. Wet chemistry involves chemical processes to determine acidity levels. These conventional techniques, though widely used, are labour-intensive, time-consuming and require destruction of the commodity sample.
[0004] To address these drawbacks, spectroscopic techniques have been explored as non-invasive alternatives to measure quality parameters. Such techniques use the interaction of light with the commodity sample to assess attributes such as moisture content, acidity and brix rating. Spectroscopic methods include techniques like near-infrared (NIR) spectroscopy, which relies on the absorption and reflection of light at different wavelengths to gather data on the composition of a commodity. However, existing spectroscopic systems suffer from several limitations. One common issue is the lack of accuracy when assessing commodities with thick skin, which can interfere with the passage of light and skew the reflectance and absorbance readings. Another challenge is the inconsistency of measurements in variable environmental conditions, such as changes in temperature, humidity and lighting. These variations affect the interaction between light and the commodity sample, leading to erroneous data.
[0005] Other non-invasive solutions also face problems due to the requirement for stationary and controlled environments, which limits their portability and adaptability across diverse environments and commodity types. Although handheld spectrometers have been developed, their effectiveness is often limited to specific commodities and they struggle to produce consistent results across different agricultural products.
[0006] In light of the above discussion, there exists an urgent need for solutions that overcome the problems associated with conventional systems and/or techniques for accurate, portable and non-destructive commodity quality assessment across various commodity types and environmental conditions.
Summary
[0007] The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later.
[0008] The following paragraphs provide additional support for the claims of the subject application.
[0009] In an aspect, the present disclosure provides a system to determine quality parameters of an agriproduct. The system comprises a light-emitting assembly with a plurality of light-emitting elements positioned to illuminate a sample of the agriproduct. An optical tunnel is disposed beneath the light-emitting assembly and configured to direct light reflected from the sample towards a sensing unit. A transparent surface is disposed beneath the optical tunnel to provide a uniform interface for transmitting reflected light towards the sensing unit. The sensing unit is positioned beneath the transparent surface to detect the reflected light after interaction with molecules in the sample and generate an optical signal. A control unit is also provided, comprising a reflectance-based quality parameter database that contains multiple commodity names, each corresponding to a reflectance value, absorbance value, wavelength range, light intensity, sample thickness and at least one quality parameter. The control unit further includes a processor to acquire the optical signal from the sensing unit, analyse the reflectance-based quality parameter database to develop a machine learning model, apply the developed machine learning model to the acquired optical signal to determine the quality parameters, and transmit the determined quality parameters to a computing device.
[00010] The system improves the accuracy and efficiency of quality parameter measurement for various agriproducts. The system enables the non-invasive assessment of key parameters by leveraging the interaction of light with molecular structures in the sample and machine learning analysis, facilitating faster and more accurate quality determination.
[00011] In another aspect, the present disclosure provides a system wherein the transparent surface is pivotally mounted relative to the optical tunnel to optimize light transmission based on sample positioning. The pivoting mechanism enhances the quality of light reaching the sensing unit, improving the accuracy of the detected signal. The pivotal mounting enables adjustments for optimal light interaction, leading to improved quality parameter determination for samples of varying orientations and thicknesses.
[00012] In another aspect, the present disclosure provides a system wherein the light-emitting assembly comprises a rotation mechanism to rotate the light-emitting elements around the sample, enabling illumination from multiple angles. This rotational movement improves the interaction of light with the sample’s molecular structures, enhancing the accuracy of the quality parameters determined by the system.
[00013] In another aspect, the present disclosure provides a system wherein the light-emitting assembly further includes an array of light diffusers positioned around the light-emitting elements to evenly distribute emitted light across the sample. The light diffusers reduce shadowing effects and ensure uniform light interaction with the sample, resulting in enhanced signal detection and improved measurement accuracy.
[00014] In another aspect, the present disclosure provides a system wherein the transparent surface includes a micro-patterned texture to minimize light scattering and maximize the transmission of reflected light towards the sensing unit. This enhancement ensures more accurate light capture and improves the system’s ability to detect quality parameters.
[00015] In another aspect, the present disclosure provides a system wherein the sensing unit includes a multi-channel detector capable of capturing and analysing multiple wavelengths of reflected light simultaneously. This multi-channel detection enhances the system’s ability to assess various molecular interactions, allowing for accurate determination of multiple quality parameters in a single measurement.
[00016] In another aspect, the present disclosure provides a system wherein the light-emitting assembly includes a tilting mechanism to adjust the angles of the light-emitting elements relative to the sample, enabling optimal light interaction with different surfaces of the agriproduct. The tilting mechanism improves signal detection and ensures accurate quality parameter measurement across different types of samples.
[00017] In another aspect, the present disclosure provides a system wherein the light-emitting assembly includes an automated positioning system to reposition the light-emitting elements based on sample size and orientation, enhancing flexibility and accuracy in measuring a variety of agriproducts.
[00018] In another aspect, the present disclosure provides a system wherein the optical tunnel comprises adjustable mirrors to redirect and concentrate reflected light towards the sensing unit. These adjustable mirrors ensure maximum light capture with minimal loss, further enhancing the precision of the quality parameter assessment.
Brief Description of the Drawings
[00019] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00020] FIG. 1 illustrates system to determine quality parameters of an agriproduct, in accordance with the embodiments of the present disclosure.
[00021] FIG. 2 illustrates a sequence flow diagram for a system 100 to determine quality parameters of an agriproduct, in accordance with the embodiments of the present disclosure.
[00022] FIG. 3 illustrates multiple views of a system 100 to determine quality parameters of an agriproduct, in accordance with the embodiments of the present disclosure.
Detailed Description
[00023] In the following detailed description of the invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. In the drawings, like numerals describe substantially similar components throughout the several views. These embodiments are described in sufficient detail to claim those skilled in the art to practice the invention. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims and equivalents thereof.
[00024] The use of the terms “a” and “an” and “the” and “at least one” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The use of the term “at least one” followed by a list of one or more items (for example, “at least one of A and B”) is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B), unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including,” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.
[00025] Pursuant to the "Detailed Description" section herein, whenever an element is explicitly associated with a specific numeral for the first time, such association shall be deemed consistent and applicable throughout the entirety of the "Detailed Description" section, unless otherwise expressly stated or contradicted by the context.
[00026] As used herein, the term "system" refers to any assembly of components configured to determine quality parameters of an agriproduct. The system includes a combination of hardware and software elements, including a light-emitting assembly, optical tunnel, transparent surface, sensing unit, and control unit. The system enables non-invasive assessment of various quality parameters by leveraging the interaction of light with molecular structures within the sample. The system is designed to work across a range of agriproduct types, providing accurate and efficient analysis. The "system" as used herein may operate in various environments, allowing for flexibility in its deployment across different agricultural settings. Additionally, the system is not limited to fixed installations but may include portable or hand-held versions, thereby broadening its scope of application. The "system" further includes components for processing the acquired data and communicating results to external devices, ensuring that it is suitable for both standalone use and integration into larger quality control systems.
[00027] As used herein, the term "light-emitting assembly" refers to any assembly comprising a plurality of light-emitting elements positioned to illuminate a sample of an agriproduct. Such an assembly includes a variety of light-emitting elements such as light-emitting diodes (LEDs) or lasers capable of emitting light at different wavelengths. The light-emitting assembly enables the focused illumination of the agriproduct sample, allowing for the reflection and interaction of light with the molecular structures within the sample. The light emitted from the light-emitting assembly can be tailored to specific wavelengths or ranges, facilitating the analysis of different agriproducts with varying thicknesses or compositions. Furthermore, the "light-emitting assembly" as used herein may include additional mechanisms such as rotational elements or diffusers to ensure that the light is uniformly distributed across the sample, thereby enhancing the accuracy and reliability of the reflected light measurements used for quality determination.
[00028] As used herein, the term "optical tunnel" refers to any structure disposed beneath the light-emitting assembly, configured to direct light reflected from the sample towards a sensing unit. The optical tunnel provides a controlled pathway for the light, minimizing external light interference and maximizing the concentration of reflected light onto the sensing unit. The optical tunnel may include a combination of reflective surfaces, lenses, or other optical elements that enhance the accuracy of light redirection. The tunnel ensures that the light's path from the agriproduct sample to the sensing unit remains consistent, thereby improving the precision of the optical signal detection. The "optical tunnel" as used herein may further comprise adjustable components to account for different sample sizes or orientations, allowing for adaptability in various operational conditions. This ensures that the system can accurately assess quality parameters across a wide range of agriproducts.
[00029] As used herein, the term "transparent surface" refers to any surface disposed beneath the optical tunnel, designed to provide a uniform interface for the transmission of reflected light towards the sensing unit. The transparent surface ensures that light passing through it is minimally scattered and remains focused as it moves towards the sensing unit. Such a surface may include materials like glass or acrylic, which are capable of maintaining transparency across a wide range of wavelengths. The "transparent surface" may also be treated or coated to resist contamination or wear, maintaining its effectiveness over extended use. Furthermore, the transparent surface as used herein may be pivotally mounted to adjust its orientation relative to the sample, enhancing light transmission based on sample positioning and thickness. This adjustment facilitates optimized light interaction with the sample, ensuring more accurate quality parameter determination.
[00030] As used herein, the term "sensing unit" refers to any device or assembly positioned beneath the transparent surface, configured to detect light reflected from the sample and generate an optical signal. The sensing unit is capable of capturing the interaction of light with the molecular structures within the agriproduct, which can then be processed to determine various quality parameters. The sensing unit may include components such as photodetectors, spectrometers, or multi-channel detectors capable of capturing multiple wavelengths of reflected light simultaneously. The "sensing unit" as used herein is also responsible for converting the detected light into electrical signals, which are then analysed by the control unit for determining the quality parameters. The unit may be further configured to adapt to different sample sizes and compositions, allowing for precise measurement across a range of agriproducts.
[00031] As used herein, the term "control unit" refers to any assembly comprising a processor and a reflectance-based quality parameter database, used to process the optical signal and determine quality parameters of the agriproduct. The control unit includes a processor capable of acquiring the optical signal from the sensing unit, analysing the signal, and applying machine learning models to derive accurate quality assessments. The "control unit" further comprises a database that stores reflectance values, absorbance values, wavelength ranges, light intensities, and other parameters associated with different commodities. This database is essential for developing and applying machine learning models to assess the quality of the agriproduct. The "control unit" as used herein is also configured to transmit the determined quality parameters to an external computing device, ensuring that the results can be communicated or integrated with other quality control systems.
[00032] As used herein, the term "reflectance-based quality parameter database" refers to a collection of data stored within the control unit, comprising multiple commodity names, each corresponding to specific reflectance values, absorbance values, wavelength ranges, light intensities, sample thicknesses, and at least one quality parameter. The database is used by the control unit to develop machine learning models that enable the system to accurately determine the quality parameters of different agriproducts. The "reflectance-based quality parameter database" as used herein serves as a reference for the processor when analysing the optical signal captured by the sensing unit. The database may be updated periodically to include new commodities or adjust existing parameters, ensuring the system remains adaptable to various agriproducts and environmental conditions.
[00033] As used herein, the term "processor" refers to any computing device within the control unit, configured to acquire the optical signal from the sensing unit, analyse the reflectance-based quality parameter database, develop machine learning models, and apply said models to determine the quality parameters of an agriproduct. The processor performs the computational tasks necessary to convert the optical signal into meaningful quality assessments. Additionally, the "processor" as used herein is responsible for communicating the determined quality parameters to external devices, allowing for integration with other systems. The processor may include additional components, such as memory units or communication modules, which facilitate its operation within the broader system. The processor enables rapid and accurate processing of large datasets, ensuring that the system can deliver timely and precise quality assessments for various agriproducts.
[00034] FIG. 1 illustrates system to determine quality parameters of an agriproduct, in accordance with the embodiments of the present disclosure. The system 100 to determine quality parameters of an agriproduct includes a light-emitting assembly 102. The light-emitting assembly 102 comprises a plurality of light-emitting elements 104. Said plurality of light-emitting elements 104 is positioned to illuminate a sample of an agriproduct. The light-emitting assembly 102 enables the emission of light at various intensities, wavelengths, or angles depending on the configuration of the plurality of light-emitting elements 104. These elements 104 may include LEDs, lasers, or other suitable light sources, capable of emitting light in various spectra, such as visible, infrared, or ultraviolet. The plurality of light-emitting elements 104 may be arranged in an array, grid, or another formation that facilitates uniform or targeted illumination of the sample. The sample may be positioned underneath or adjacent to the light-emitting assembly 102, depending on the type of agriproduct being tested. The arrangement of the light-emitting elements 104 may be static or adjustable, with possible modifications in light intensity or wavelength based on the specific agriproduct. The emitted light interacts with the surface and internal structures of the agriproduct, such as cellular structures, pigments, or water content. Such light interaction enables the reflection, absorption, or scattering of light from the sample. The plurality of light-emitting elements 104 may be controlled through hardware or software interfaces, allowing for changes in illumination conditions during sample testing. The position and type of the light-emitting elements 104 in relation to the agriproduct sample may also vary depending on the size, shape, or type of agriproduct under analysis. This

configuration enables the capture of reflective data from various surfaces or layers of the agriproduct, aiding in determining its quality parameters through subsequent analysis.
[00035] The optical tunnel 106 is disposed beneath the light-emitting assembly 102 and directs the light reflected from the sample towards a sensing unit 108. The optical tunnel 106 may be designed to optimize the path of the reflected light, preventing the scattering or loss of light during transmission. The inner surface of the optical tunnel 106 may be coated or treated with materials that enhance the reflection or guidance of the light towards the sensing unit 108. Said optical tunnel 106 may be composed of materials such as metal, plastic, or composites that ensure stability and precision in light transmission. The optical tunnel 106 may be constructed in various shapes, including conical, cylindrical, or rectangular, depending on the arrangement of the light-emitting assembly 102 and the sensing unit 108. The optical tunnel 106 may also contain optical elements such as lenses, mirrors, or diffusers that modify or concentrate the reflected light before reaching the sensing unit 108. The alignment of the optical tunnel 106 in relation to the light-emitting assembly 102 and the sensing unit 108 may be calibrated to maximize light capture, minimizing losses due to misalignment or optical aberrations. The positioning of the optical tunnel 106 beneath the light-emitting assembly 102 ensures that the reflected light is transmitted directly from the sample, reducing interference from ambient light or other external sources. The dimensions and design of the optical tunnel 106 may vary depending on the size and type of the agriproduct sample, allowing for adaptability across various types of agriproducts. The construction of the optical tunnel 106 further enables the redirection of the light for optimal interaction with the sensing unit 108.
[00036] A transparent surface 110 is disposed beneath the optical tunnel 106, providing a uniform interface for the transmission of reflected light towards the sensing unit 108. The transparent surface 110 may be constructed from materials such as glass, quartz, or optical-grade plastics that allow for minimal light loss during transmission. The thickness and refractive index of the transparent surface 110 may be selected to minimize distortion or reflection losses of the transmitted light. The transparent surface 110 is positioned to ensure that light reflected from the agriproduct sample passes through the surface with minimal scattering. The surface 110 may be smooth or contain micro-structured textures to reduce reflection losses and optimize light transmission. The material composition and surface properties of the transparent surface 110 may also be chosen based on the spectral range of the light being transmitted, ensuring compatibility with the light wavelengths used in the system 100. The positioning of the transparent surface 110 beneath the optical tunnel 106 enables a clear, uninterrupted path for the reflected light towards the sensing unit 108. The design of the transparent surface 110 may also include anti-reflective coatings or other treatments that further enhance the transmission of light. The transparent surface 110 may also serve as a protective barrier, preventing contamination or physical interference with the optical components, ensuring stable performance during repeated use. The transparent surface 110 ensures that the reflected light is accurately transmitted without significant alteration or loss before reaching the sensing unit 108 for further analysis.
[00037] The sensing unit 108 is disposed beneath the transparent surface 110 and detects the reflected light after interaction with molecules in the agriproduct sample. Said sensing unit 108 generates an optical signal based on the detected light, which is indicative of the molecular composition or quality parameters of the sample. The sensing unit 108 may include photodetectors, spectrometers, or other sensors capable of measuring the intensity, wavelength, or other properties of the reflected light. The sensing unit 108 is positioned to receive the transmitted light through the transparent surface 110 with minimal loss or distortion. The design of the sensing unit 108 may include multiple detectors or channels to capture different aspects of the reflected light, such as wavelength range or intensity variations. The sensors within the sensing unit 108 may be optimized for specific types of agriproducts, allowing for more accurate detection of quality parameters. The sensing unit 108 converts the detected light into an optical signal, which is then processed to determine characteristics of the agriproduct, such as moisture content, ripeness, or nutritional value. The optical signal generated by the sensing unit 108 may also be analyzed in real-time or stored for later processing. The sensing unit 108 may be integrated with other optical components such as filters or lenses that enhance the detection of specific light properties. The placement of the sensing unit 108 beneath the transparent surface 110 ensures that the optical signal is generated based on unaltered light reflected from the sample, providing an accurate representation of the agriproduct's quality parameters.
[00038] The system 100 includes a control unit 112 comprising a reflectance-based quality parameter database 112-A and a processor 112-B. The reflectance-based quality parameter database 112-A stores multiple commodity names, each corresponding to a reflectance value, absorbance value, wavelength range, light intensity, sample thickness, and at least one quality parameter. Said reflectance-based quality parameter database 112-A provides the reference data used by the processor 112-B to compare the optical signal acquired from the sensing unit 108. Each commodity entry in the reflectance-based quality parameter database 112-A includes data collected from various samples of agriproducts, providing a comprehensive range of reflectance and absorbance values for different conditions and quality parameters. The reflectance-based quality parameter database 112-A may be updated with new data over time, ensuring that the control unit 112 remains accurate for a wide range of agriproducts. The data stored in the reflectance-based quality parameter database 112-A may also include environmental factors, such as temperature or humidity, that affect the quality parameters of the agriproducts. The processor 112-B acquires the optical signal generated by the sensing unit 108 and analyzes it using data from the reflectance-based quality parameter database 112-A. The processor 112-B may utilize machine learning models, statistical analysis, or other computational methods to analyze the optical signal and determine the quality parameters of the agriproduct. Said processor 112-B compares the acquired optical signal against the stored reference data to identify patterns or variations that correspond to specific quality parameters, such as moisture content, color, or texture. The processor 112-B applies the machine learning model to the acquired optical signal to improve the accuracy and reliability of the quality parameter determination. The control unit 112 transmits the determined quality parameters to a computing device 114 for display, storage, or further analysis. The computing device 114 may include interfaces that allow for user interaction, report generation, or integration with other systems.
[00039] In an embodiment, the transparent surface 110 is pivotally mounted in relation to the optical tunnel 106. Such a pivotal mounting enables adjustments to the angle of the transparent surface 110, which allows the transparent surface 110 to be optimally aligned based on the position of the sample being analyzed. By altering the angle of the transparent surface 110, the path of the reflected light from the sample can be controlled to ensure that maximum light is transmitted towards the sensing unit 108. This adjustment is particularly beneficial when dealing with samples of varying sizes, shapes, or orientations, where the angle of reflection might differ. The pivotal mechanism may include a hinge or other adjustable connection that permits controlled movement of the transparent surface 110 relative to the fixed optical tunnel 106. The pivotal movement can be manual or automated, depending on the system design, and may include locking mechanisms that fix the transparent surface 110 at a particular angle. The transparent surface 110, when adjusted, aids in maintaining the integrity of the light being transmitted, minimizing losses due to misalignment. Such adjustability optimizes the transmission of light across a wide range of agriproduct samples, enhancing the light interaction necessary for accurate detection by the sensing unit 108. The transparent surface 110 may also return to a default or neutral position when no sample is present, allowing for consistent performance across different operational cycles.
[00040] In an embodiment, the light-emitting assembly 102 further comprises a rotation mechanism that enables rotational movement of the plurality of light-emitting elements 104 around the sample. This rotational movement allows the light-emitting elements 104 to illuminate the sample from multiple angles, which provides a more comprehensive interaction between the emitted light and the sample. The rotation mechanism may include a motorized or manually operated rotating structure upon which the plurality of light-emitting elements 104 is mounted. Such a structure may rotate the light-emitting elements 104 around a central axis, allowing the light to cover the entire surface or different sections of the sample at various angles. The speed and degree of rotation may be adjustable, depending on the specific requirements of the analysis being performed. The rotation mechanism can be synchronized with the sensing unit 108 to ensure that data is captured at specific intervals during the rotation, thus providing a thorough analysis of the sample's optical properties. The interaction of the light from different angles enhances the ability to detect molecular variations or inconsistencies within the sample, such as surface roughness or internal composition. The light-emitting elements 104 may rotate in a continuous manner or may stop at predefined positions to focus light on specific areas of the sample. The rotation mechanism may also include safety features to ensure that the movement does not disrupt other components within the system 100.
[00041] In an embodiment, the light-emitting assembly 102 further comprises an array of light diffusers positioned around the plurality of light-emitting elements 104 . Such light diffusers are used to distribute the emitted light evenly across the sample, ensuring that the light covers the surface of the sample without creating shadows or areas of uneven illumination. The light diffusers may be constructed from materials such as frosted glass, plastic, or other translucent materials capable of scattering light uniformly. The shape and arrangement of the light diffusers can vary, with options including dome-shaped, planar, or other geometries that promote even light distribution. The light diffusers may be positioned directly in front of each light-emitting element 104 or arranged in a separate structure that encircles the entire light-emitting assembly 102. The use of light diffusers helps in reducing the intensity of the light in certain areas and prevents concentrated beams that could result in misleading reflections or data inaccuracies. The diffused light interacts with the sample in a more uniform manner, ensuring that the sensing unit 108 receives consistent and accurate data regarding the light reflected from the sample. The light diffusers may also be interchangeable or adjustable based on the specific lighting requirements of the agriproduct sample under examination, allowing for versatility in system 100 applications.
[00042] In an embodiment, the transparent surface 110 further comprises a micro-patterned texture. Said micro-patterned texture minimizes light scattering and maximizes the transmission of the reflected light towards the sensing unit 108. The texture may be composed of microscopic ridges, grooves, or other surface modifications designed to channel the reflected light efficiently through the transparent surface 110. The specific pattern of the texture can vary depending on the type of light being transmitted and the nature of the agriproduct sample. The micro-patterned texture may be applied through manufacturing techniques such as etching, embossing, or laser treatment to create uniform surface modifications. These surface modifications help in maintaining the integrity of the transmitted light by reducing any distortions or losses that may occur during the transmission process. The transparent surface 110 with such a texture can reduce glare or internal reflections that could interfere with the sensing unit 108's ability to detect the reflected light accurately. The choice of pattern, spacing, and depth of the micro-patterned texture can be tailored based on the expected light wavelength and sample characteristics, allowing for customization of the system 100 for different agriproducts. The transparent surface 110 remains structurally sound despite the texture, providing both a durable and functional interface for light transmission.
[00043] In an embodiment, the sensing unit 108 further comprises a multi-channel detector. Such a multi-channel detector captures and analyzes multiple wavelengths of the reflected light simultaneously. The multi-channel detector may consist of an array of sensors, each dedicated to detecting specific ranges of wavelengths, including visible, ultraviolet, or infrared light. The arrangement of sensors within the multi-channel detector allows for the simultaneous capture of data from different parts of the light spectrum, providing a more comprehensive analysis of the molecular interactions occurring within the sample. The multi-channel detector may also include filters, prisms, or gratings that separate the reflected light into its component wavelengths before reaching the individual sensors. The data collected from the multiple channels are processed to identify variations in light intensity, absorbance, or reflectance across the different wavelengths, allowing for a more detailed assessment of the sample’s quality parameters. The multi-channel detector may be calibrated to detect specific molecular markers or characteristics within the agriproduct sample, such as moisture content, ripeness, or nutritional value. The sensing unit 108 may also integrate advanced electronics to process the data in real-time, ensuring that the results from the multi-channel detector are available promptly for further analysis by the processor 112-B.
[00044] In an embodiment, the light-emitting assembly 102 further comprises a tilting mechanism that allows the plurality of light-emitting elements 104 to be tilted at variable angles relative to the sample. The tilting mechanism enables the light-emitting elements 104 to be positioned at different angles to achieve optimal light interaction with the surface and internal structures of the agriproduct. The tilting mechanism may include a motorized or manually adjustable system that allows for precise control over the angle of the light-emitting elements 104. The tilting angle can be adjusted based on the type and size of the agriproduct sample, allowing for flexibility in the analysis process. The tilting mechanism may operate in conjunction with the rotation mechanism to provide comprehensive coverage of the sample's surface, ensuring that light reaches all areas of the sample. The tilting of the light-emitting elements 104 enhances the ability of the system 100 to detect subtle variations in the sample’s surface characteristics, as different angles of light can reveal different molecular or structural features. The tilting mechanism may also include sensors that monitor the position of the light-emitting elements 104, ensuring that the correct angle is maintained during the analysis process.
[00045] In an embodiment, the light-emitting assembly 102 further comprises an automated positioning system to reposition the light-emitting elements 104 based on the sample size and orientation. The automated positioning system may include a combination of sensors, motors, and control software that dynamically adjusts the position of the light-emitting elements 104 to ensure optimal illumination of the sample. The sensors within the automated positioning system may detect the dimensions, orientation, or movement of the sample and adjust the light-emitting elements 104 accordingly. The motors within the positioning system allow for fine-tuned adjustments of the light-emitting elements 104, enabling consistent illumination regardless of sample variations. The automated system allows for hands-free operation and can be pre-programmed with specific settings for different types of agriproducts. The automated positioning system may also be integrated with other system 100 components, such as the tilting or rotation mechanisms, to provide a synchronized illumination setup tailored to the specific requirements of each sample.
[00046] In an embodiment, the optical tunnel 106 comprises a series of adjustable mirrors . The adjustable mirrors are used to redirect and concentrate the reflected light towards the sensing unit 108, ensuring maximum light capture with minimal loss. Each mirror within the optical tunnel 106 may be positioned at an angle that directs the reflected light along a controlled path towards the sensing unit 108. The mirrors may be made from materials with high reflectivity, such as polished metal or coated glass, to ensure that light loss is minimized during reflection. The adjustable mirrors may be moved manually or through an automated system to align the reflected light precisely with the sensing unit 108. The series of mirrors within the optical tunnel 106 allows for customization of the light path depending on the sample type, ensuring that the optimal amount of light reaches the sensing unit 108 for analysis.
[00047] In an embodiment, light-emitting assembly 102 comprising a plurality of light-emitting elements 104 positioned to illuminate the sample of the agriproduct provides enhanced control over the illumination process. The plurality of light-emitting elements 104 allows for uniform or selective illumination, depending on the sample's requirements. This arrangement ensures that light penetrates the sample surface and interacts with molecular structures, enhancing the accuracy of reflected light analysis. Such precise illumination improves the interaction between light and the agriproduct's physical and chemical components, facilitating accurate detection by the sensing unit 108. The ability to control light intensity and direction further reduces interference from ambient light and improves the signal-to-noise ratio in the reflected optical signal. By illuminating the sample from various angles and intensities, the system can extract detailed information about the sample's surface and internal characteristics, enabling accurate quality parameter assessment.
[00048] In an embodiment, the optical tunnel 106 is disposed beneath the light-emitting assembly 102 and directs reflected light from the sample towards the sensing unit 108. This arrangement optimizes the pathway of reflected light, minimizing scattering and loss of signal before it reaches the sensing unit 108. The optical tunnel 106 provides a controlled environment where light reflection is focused and guided, resulting in more consistent and accurate data acquisition. The materials and design of the optical tunnel 106 help to preserve the integrity of the reflected light by minimizing external interference and ensuring maximum transmission of light towards the sensing unit 108. The result is a significant reduction in light diffusion, leading to enhanced precision in the quality parameters determined by the system. Furthermore, the optical tunnel 106 ensures that light is consistently directed through the transparent surface 110, improving the overall system accuracy in measuring reflectance-based quality parameters.
[00049] In an embodiment, transparent surface 110 disposed beneath the optical tunnel 106 provides a uniform interface for the transmission of reflected light towards sensing unit 108. The transparent surface 110 facilitates efficient transmission of light without significant scattering or reflection losses, ensuring that the sensing unit 108 receives a clear and undistorted signal. The uniform interface of the transparent surface 110 allows for consistent light transmission across various sample types and conditions, which improves the system's ability to detect subtle variations in the sample’s optical properties. The design of the transparent surface 110 enhances the quality of the transmitted light by preventing external contamination or physical interference, contributing to more accurate measurements of the sample’s molecular interactions. As the light passes through the transparent surface 110, its consistency in transmitting light ensures a more reliable optical signal, which leads to better determination of the sample’s quality parameters.
[00050] In an embodiment, sensing unit 108, disposed beneath the transparent surface 110, detects the reflected light after it interacts with the molecules in the sample. The sensing unit 108 then generates an optical signal based on the detected light, which represents the sample’s molecular composition and physical characteristics. The positioning of the sensing unit 108 directly beneath the transparent surface 110 enables accurate detection of the transmitted light without significant signal degradation. The optical signal generated by the sensing unit 108 captures critical information about the sample's surface and internal structure, enabling further analysis by the control unit 112. The design of the sensing unit 108 may include multiple detectors or channels to capture various wavelengths of reflected light, ensuring comprehensive data collection. The sensing unit 108's ability to detect light with high precision significantly enhances the accuracy of the system in determining quality parameters such as moisture content, nutrient levels, or ripeness.
[00051] In an embodiment, control unit 112 includes a reflectance-based quality parameter database 112-A and a processor 112-B. The reflectance-based quality parameter database 112-A stores detailed information for multiple commodities, such as reflectance values, absorbance values, wavelength ranges, light intensity levels, and quality parameters. This database serves as a reference for the processor 112-B to compare the optical signal acquired from the sensing unit 108. The processor 112-B analyzes the optical signal using data from the reflectance-based quality parameter database 112-A, allowing it to determine the specific quality parameters of the agriproduct. The control unit 112’s ability to store and process large amounts of commodity-specific data ensures that the system can accurately determine quality parameters for a wide variety of agriproducts. The processor 112-B applies a machine learning model to the acquired optical signal, further enhancing the system’s ability to accurately and efficiently assess the quality of the agriproduct.
[00052] In an embodiment, the transparent surface 110 is pivotally mounted in relation to the optical tunnel 106. The pivotal mounting allows for adjustments to the angle of the transparent surface 110, optimizing the transmission of reflected light based on the sample's positioning. This adjustability ensures that the maximum amount of reflected light reaches the sensing unit 108, enhancing the quality of the optical signal. By allowing adjustments to the transparent surface 110, the system accommodates variations in sample size, shape, or placement, ensuring consistent performance across different types of agriproducts. This pivotal mechanism reduces errors due to misaligned light paths and improves the consistency of light transmission, resulting in more reliable quality parameter determinations.
[00053] In an embodiment, the light-emitting assembly 102 further comprises a rotation mechanism that enables rotational movement of the plurality of light-emitting elements 104 around the sample. The rotational movement allows the light-emitting elements 104 to illuminate the sample from multiple angles, improving light interaction with molecular structures within the agriproduct. This enhanced interaction enables the system to capture more comprehensive data, allowing for a detailed analysis of the sample's quality parameters. The rotation mechanism also reduces the likelihood of missing critical information due to uneven illumination, ensuring that the entire sample is uniformly exposed to the emitted light. This approach leads to improved signal detection by the sensing unit 108, which directly contributes to a more accurate determination of quality parameters.
[00054] In an embodiment, the light-emitting assembly 102 further comprises an array of light diffusers positioned around the plurality of light-emitting elements 104. The light diffusers distribute the emitted light evenly across the sample, reducing shadowing effects and improving the uniformity of light interaction with the agriproduct. By ensuring consistent light distribution, the light diffusers improve the accuracy of the optical signal received by the sensing unit 108. The uniform illumination prevents localized variations in light intensity, which can distort the quality parameter measurements. This even distribution of light enhances the system's ability to detect molecular interactions throughout the sample, leading to more precise and reliable determinations of quality parameters.
[00055] In an embodiment, the transparent surface 110 further comprises a micro-patterned texture that minimizes light scattering and maximizes the transmission of reflected light towards the sensing unit 108. The micro-patterned texture directs light more effectively through the transparent surface 110, reducing losses due to scattering and improving the overall quality of the transmitted signal. This textured surface ensures that the light reaching the sensing unit 108 retains its integrity, enabling more accurate detection and analysis of the sample's molecular properties. The reduction in scattering improves the efficiency of light transmission, allowing the system to capture more detailed information about the sample’s quality parameters.
[00056] In an embodiment, the sensing unit 108 further comprises a multi-channel detector capable of capturing and analyzing multiple wavelengths of reflected light simultaneously. This multi-channel capability allows for a more comprehensive analysis of the sample by detecting a wide range of light properties, such as reflectance, absorbance, and wavelength variation. The simultaneous detection of multiple wavelengths enables the system to gather more detailed data about the sample's molecular interactions, leading to more accurate and thorough determinations of multiple quality parameters. The multi-channel detector enhances the system's versatility, allowing it to assess a broader range of agriproducts with varying optical properties.
[00057] In an embodiment, the light-emitting assembly 102 further comprises a tilting mechanism that allows the plurality of light-emitting elements 104 to be tilted at variable angles relative to the sample. By adjusting the angle of the light-emitting elements 104, the system can achieve optimal light interaction with different surfaces of the agriproduct. This adjustability improves the system’s ability to detect variations in surface texture or internal composition, which are critical for determining accurate quality parameters. The tilting mechanism enhances the flexibility of the light-emitting assembly 102, allowing for customized illumination setups depending on the sample’s specific characteristics.
[00058] In an embodiment, the light-emitting assembly 102 further comprises an automated positioning system that repositions the light-emitting elements 104 based on the sample's size and orientation. The automated positioning system ensures that the sample is illuminated appropriately, regardless of its physical dimensions or placement within the system. This automated control reduces the need for manual adjustments, improving the consistency and repeatability of the quality parameter measurements. The ability to dynamically adjust the positioning of the light-emitting elements 104 enhances the system's ability to handle a wide range of agriproducts, ensuring optimal light interaction for accurate detection and analysis.
[00059] In an embodiment, the optical tunnel 106 comprises a series of adjustable mirrors designed to redirect and concentrate the reflected light towards the sensing unit 108. The adjustable mirrors allow for precise control over the path of the reflected light, ensuring that it is directed towards the sensing unit 108 with minimal loss. This arrangement maximizes the amount of light captured by the sensing unit 108, improving the accuracy of the optical signal and the subsequent determination of the sample’s quality parameters. The adjustable mirrors can be repositioned as needed to accommodate different sample types, ensuring optimal light reflection and detection for a wide variety of agriproducts.
[00060] FIG. 2 illustrates a sequence flow diagram for a system 100 to determine quality parameters of an agriproduct, in accordance with the embodiments of the present disclosure. The process begins with the user initiating the quality analysis by interacting with the control unit. Upon receiving the command, the control unit activates the sensing unit, which triggers the emission of light from the light-emitting assembly. The emitted light passes through the optical tunnel and illuminates the sample. The transparent surface ensures uniform transmission of the reflected light, directing it back through the optical tunnel toward the sensing unit. The sensing unit detects the reflected light after it interacts with the sample's molecular structure and generates an optical signal. This optical signal is sent to the control unit, which then retrieves relevant data from the reflectance-based quality parameter database. The control unit analyzes the optical signal using a machine learning (ML) model developed based on the fetched data. The ML model is applied to the acquired optical signal to determine the sample's quality parameters. These quality parameters are then transmitted to a connected computing device for display or further processing, completing the analysis sequence. The diagram highlights the interaction and data flow between the components of the system, enabling precise quality analysis of agriproducts.
[00061] FIG. 3 illustrates multiple views of a system 100 to determine quality parameters of an agriproduct, in accordance with the embodiments of the present disclosure. The system 100 comprises a compact housing that contains various critical components to facilitate the quality analysis of agriproduct samples using optical detection methods. The overall design includes external and internal views, highlighting both the structural configuration and the internal arrangement of components within the system 100.
[00062] The exterior view of the system 100 shows a rectangular housing with rounded edges, designed for ergonomic handling and compactness. The top view illustrates a central tunnel, along with multiple holes positioned symmetrically around the tunnel, intended for LED lamps. The LED lamps are mounted inside these holes to provide illumination for the agriproduct sample placed beneath the system. The light emitted from the LED lamps interacts with the sample, and the reflected light is directed through the tunnel toward a sensing unit (not visible in this figure) for analysis. The housing also features a debossed logo on the top, serving both aesthetic and functional branding purposes.
[00063] The exploded view of the system 100 reveals a detailed breakdown of the internal components. The LED lamps are mounted on the upper section of the chassis, directly facing the glass window that serves as a trans

Claims
I/We Claim:
1. A system to determine quality parameters of an agriproduct, comprising:
a light-emitting assembly comprising a plurality of light-emitting elements positioned to illuminate a sample of said agriproduct;
an optical tunnel disposed beneath said light-emitting assembly, wherein said optical tunnel configured to direct the light reflected from said sample towards a sensing unit;
a transparent surface disposed beneath said optical tunnel to provide a uniform interface for the transmission of reflected light towards said sensing unit;
said sensing unit disposed beneath said transparent surface and configured to detect said reflected light after interaction with molecules in said sample and generate and an optical signal;
a control unit comprising:
a reflectance-based quality parameter database comprising the multiple commodity names, wherein each commodity name corresponds to a reflectance value, an absorbance value, a wavelength range, a light intensity, a sample thickness and at least one quality parameter; and
a processor to:
acquire said optical signal from said sensing unit;
analyse said reflectance-based quality parameter database to develop a machine learning model;
apply said developed machine learning model to said acquired optical signal to determine said quality parameters; and
transmit said determined quality parameters to a computing device.
2. The system of claim 1, wherein said transparent surface is pivotally mounted in relation to said optical tunnel, said pivotal mounting facilitating adjustments to the angle of said transparent surface to optimize the transmission of reflected light based on sample positioning, enhancing the quality of light reaching said sensing unit.
3. The system of claim 1, wherein said light-emitting assembly further comprises a rotation mechanism enabling rotational movement of said plurality of light-emitting elements around said sample, wherein said sample is illuminated from multiple angles, improving the interaction of light with molecular structures of said agriproduct.
4. The system of claim 1, wherein said light-emitting assembly further comprises an array of light diffusers positioned around said plurality of light-emitting elements, wherein said light diffusers distribute the emitted light evenly across said sample, reducing shadowing effects and improving the uniformity of light interaction with said agriproduct for enhanced signal detection.
5. The system of claim 1, wherein said transparent surface further comprises a micro-patterned texture, said texture configured to minimize light scattering and maximize the transmission of reflected light towards said sensing unit.
6. The system of claim 1, wherein said sensing unit further comprises a multi-channel detector, said detector configured to capture and analyze multiple wavelengths of reflected light simultaneously, enabling enhanced analysis of molecular interactions within said sample for accurate determination of multiple quality parameters.
7. The system of claim 1, wherein said light-emitting assembly further comprises a tilting mechanism that allows said plurality of light-emitting elements to be tilted at variable angles relative to said sample, wherein said light-emitting elements is positioned to achieve optimal light interaction with various surfaces of said agriproduct, enhancing signal detection.
8. The system of claim 1, wherein said light-emitting assembly further comprises an automated positioning system to reposition said light-emitting elements based on sample size and orientation.
9. The system of claim 1, wherein said optical tunnel comprises a series of adjustable mirrors c onfigured to redirect and concentrate reflected light towards said sensing unit, maximizing light capture with minimal loss.

SYSTEM TO DETERMINE QUALITY PARAMETERS OF AN AGRIPRODUCT
Abstract
The present disclosure provides a system to determine quality parameters of an agriproduct. The system comprises a light-emitting assembly with a plurality of light-emitting elements positioned to illuminate a sample of said agriproduct. An optical tunnel is disposed beneath said light-emitting assembly and is configured to direct light reflected from said sample towards a sensing unit. A transparent surface is disposed beneath said optical tunnel to provide a uniform interface for the transmission of reflected light towards said sensing unit. The sensing unit is configured to detect said reflected light and generate an optical signal. A control unit comprises a reflectance-based quality parameter database and a processor configured to acquire said optical signal, analyse the database to develop a machine learning model, apply said model to said optical signal to determine said quality parameters, and transmit said quality parameters to a computing device.
Fig. 1

, Claims:Claims
I/We Claim:
1. A system to determine quality parameters of an agriproduct, comprising:
a light-emitting assembly comprising a plurality of light-emitting elements positioned to illuminate a sample of said agriproduct;
an optical tunnel disposed beneath said light-emitting assembly, wherein said optical tunnel configured to direct the light reflected from said sample towards a sensing unit;
a transparent surface disposed beneath said optical tunnel to provide a uniform interface for the transmission of reflected light towards said sensing unit;
said sensing unit disposed beneath said transparent surface and configured to detect said reflected light after interaction with molecules in said sample and generate and an optical signal;
a control unit comprising:
a reflectance-based quality parameter database comprising the multiple commodity names, wherein each commodity name corresponds to a reflectance value, an absorbance value, a wavelength range, a light intensity, a sample thickness and at least one quality parameter; and
a processor to:
acquire said optical signal from said sensing unit;
analyse said reflectance-based quality parameter database to develop a machine learning model;
apply said developed machine learning model to said acquired optical signal to determine said quality parameters; and
transmit said determined quality parameters to a computing device.
2. The system of claim 1, wherein said transparent surface is pivotally mounted in relation to said optical tunnel, said pivotal mounting facilitating adjustments to the angle of said transparent surface to optimize the transmission of reflected light based on sample positioning, enhancing the quality of light reaching said sensing unit.
3. The system of claim 1, wherein said light-emitting assembly further comprises a rotation mechanism enabling rotational movement of said plurality of light-emitting elements around said sample, wherein said sample is illuminated from multiple angles, improving the interaction of light with molecular structures of said agriproduct.
4. The system of claim 1, wherein said light-emitting assembly further comprises an array of light diffusers positioned around said plurality of light-emitting elements, wherein said light diffusers distribute the emitted light evenly across said sample, reducing shadowing effects and improving the uniformity of light interaction with said agriproduct for enhanced signal detection.
5. The system of claim 1, wherein said transparent surface further comprises a micro-patterned texture, said texture configured to minimize light scattering and maximize the transmission of reflected light towards said sensing unit.
6. The system of claim 1, wherein said sensing unit further comprises a multi-channel detector, said detector configured to capture and analyze multiple wavelengths of reflected light simultaneously, enabling enhanced analysis of molecular interactions within said sample for accurate determination of multiple quality parameters.
7. The system of claim 1, wherein said light-emitting assembly further comprises a tilting mechanism that allows said plurality of light-emitting elements to be tilted at variable angles relative to said sample, wherein said light-emitting elements is positioned to achieve optimal light interaction with various surfaces of said agriproduct, enhancing signal detection.
8. The system of claim 1, wherein said light-emitting assembly further comprises an automated positioning system to reposition said light-emitting elements based on sample size and orientation.
9. The system of claim 1, wherein said optical tunnel comprises a series of adjustable mirrors c onfigured to redirect and concentrate reflected light towards said sensing unit, maximizing light capture with minimal loss.