DESC:FIELD OF THE INVENTION
[0001] The present invention relates to a device, system employing said device and a method of working said system to detect the presence of somatic cells. Particularly, this invention relates to an improved detection of somatic cells in bovine milk samples without the need for a laboratory or skilled persons, a system and method to do the same.

BACKGROUND OF THE INVENTION
[0002] India has approximately 30 crore cattle, of which 25-30% suffer from a condition called mastitis caused especially due to unhygienic conditions of the milk production sites. Needless to say, the demand and production of milk are on a global level irrespective of the race, geographical location, sex or even age of the consumer which ranges from infants to the aged, all have been known to consume bovine milk.

[0003] Traditional methods of milking bovine involve rather unhygienic conditions where bacterial contamination is a prevalent factor, as a solution developed countries and now even some developing countries are adopting automated milk collection systems. However, even here concerns with equipment malfunction or by incorrect procedures or milking settings continue to exist; all of which lead to Bovine mastitis, an inflammatory response of the udder tissue in the mammary gland of the bovine caused due to physical trauma or micro-organism infections. It is considered the most common disease leading to atrophy of bovine mammary glands, a primary reason for the reduction of milk production and economic loss in dairy industries due to reduced yield and poor quality of milk.

[0004] Treatment of active mastitis infection is dependent mainly on antibiotics. However, the extensive use of antibiotics increases concerns about emergence of antibiotic-resistant pathogens. Therefore, the only feasible option is early detection, particularly at the stage of sub-clinical mastitis, which is difficult as detection of early-stage mastitis involves detection of somatic cells in milk which is typically performed in laboratory environment employing methods such as microscopy and flow cytometry, both of which are rather impractical to be adopted at the site of milk production, where such tests are needed.

[0005] As an on-site test, presently used tests involve the California mastitis test (AMT), pH test for alkalinity and the port a SCC strip test. However, the CMT is labor intensive, and the test Suffers from a Subjective interpretation by the individual user and an unacceptably high false negative rate.

[0006] None of the above are capable of quantitatively analyzing milk samples to classify the clinical stage of mastitis in order to accurately offer treatment to the animal. While US Patent 6,709,868 B2 claims to quantifiably detect WBC count in whole milk, the patent focuses on a chemical reaction culminating in a colour change, the quantity of WBC is subjectively detected based on this colour change. This test therefore fails to disclose a system independent of human error in subjectively analyzing the test samples.

[0007] There is, therefore, a need for a detection system, method and device to analyze dairy milk samples for early-stage mastitis independent of human intervention and errors associated with colorimetric readings; and to overcome at least one of the problems stated above.

[0008] For purposes of the present invention, "dairy animal” / “bovine” / “cattle” means any animal from which milk can be obtained. Non limiting examples of dairy animals are cows, sheep, goats, camels, and buffalo (bison). Tests for white blood cells for bovine can be used for other types of dairy animals as well. Thus, when the present Specification uses bovine as an example, the process is not limited to cows but is applicable to all types of dairy animals.

SUMMARY OF THE INVENTION
[0009] An aspect of the present invention relates to a device to quantitatively determine the total somatic cell count, said device comprising:
a. at least one impregnated filter layer (105);
b. an absorptive layer (106,107), to collect the filtrate; and
c. an outer casing (104,108) having a counter reference (101) and
a QR code (103) for correcting any errors in the process of determining the total somatic cell count.

[0010] Another aspect of the present invention relates to a system to accurately determine the Total Somatic Cell count by employing an LED reader, said system comprising:
A.at least a device of the present invention being housed into or onto the LED reader located within a portable device having
i. at least a sensor;
ii. at least two LEDs;
iii. a display screen;
to quantifiably detect somatic cell count in the sample tested on the device, wherein each component is inter connected by means of a wireless communication;
or being imaged or scanned by at least a mobile device having a mobile application enabling the mobile device to quantifiably detect somatic cell count in the sample tested on said device.

[0011] Yet another aspect of the present invention relates to a method of operating the system of the present invention comprising at least the following steps:
i.collecting a sample of milk and dropping it onto the impregnated filter layer of the device through sample well;
ii.adding to the above, running buffer;
iii.Upon complex formation and obtaining a color change to blue, subjecting the device to be analyzed by the present system in the following manner:
a.Subjecting the device to an LED reader or a camera of a mobile device;
b.determining the intensity of the blue color to quantify the total somatic cell count by means of a system using a calibration system;
c.Sending the data including calibrated readings along with sample parameters including location and type of milk sample, to the sub-system.
d. Receiving said data by AI/ML model and processor located in the server and recalculating said result by considering the errors relating to camera imaging by means of a color mat located on the device;
e.Receiving said data by the processor and recalculating said result by considering the errors relating to camera imaging by means of a color mat located on the device;
f.employing by a calibration system present in the mobile application or LED reader, a calibration curve as disclosed by the QR code present in the device of the present invention to further eliminate errors;
g.processing said results and displaying the same to the user interface while storing a copy of the test data within the database of the system.

BRIEF DESCRIPTION OF THE DRAWINGS
[0012] Reference will be made to embodiments of the invention, examples of which may be illustrated in the accompanying figures. These figures are intended to be illustrative, not limiting. Although the invention is generally described in the context of these embodiments, it should be understood that it is not intended to limit the scope of the invention to these particular embodiments.
[0013] FIGURE 1 shows an exploded view of the device 100 in accordance with an embodiment of the present invention;
[0014] FIGURE 2 shows a system architecture 200 of the system in accordance with an embodiment of the present invention and
[0015] FIGURE 3 shows a flowchart 300 of the method in accordance with an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION
[0016] Some embodiments of the present disclosure, illustrating all its features, will now be discussed in detail. It must also be noted that as used herein and in the appended claims, the singular forms "a", "an" and "the" include plural references unless the context clearly dictates otherwise. Although any product and method similar or equivalent to those described herein can be used to optimize the outcome of the present invention.

[0017] Various embodiments of the invention provide an improved system, method and device for accurate quantitative detection of somatic cells in bovine samples based on the principle of colorimetry, particularly overcoming errors associated with human intervention and colorimetry in general.

[0018] In an embodiment, a device to accurately determine the Total SCC count is disclosed, said device comprising:
at least an impregnated filter layer (105), preferably What man grade 2 filter;
at least an absorptive layer (106,107) preferably made of glass fibre being ~0.08mm thick x 3, to collect the filtrate; and
an outer casing (104,108) having a QR code, a color mat, or both; for correcting any errors in the process of determining the total SCC count, wherein the QR code (103) discloses the calibration curve required for a “corrective reading” of the results to negate any erroneous results and the Color mat corrects /counters for any camera imaging errors.
The impregnated filter layer (105) present in the device of the present invention is preferably impregnated with Taloxin, a dye substrate immobilized there in to react with the ester from Somatic Cells (SCC) to form a coloured compound, the colour intensity of which is directly proportionate to the quantity of SCC.

[0019] Referring to FIGURE 1 which shows an exploded view of the device (100) used to quantitatively determine the total somatic cell count, said device comprising:
a.at least one impregnated filter layer (105);
b.an absorptive layer (106,107), to collect the filtrate; and
c.an outer casing (104,108) having a counter reference (101) and a QR code (103) for correcting any errors in the process of determining the total somatic cell count;
wherein the impregnated filter layer (105) is capable of forming a colored compound with the enzyme present in somatic cells, the color intensity of which is directly proportionate to the quantity of somatic cells calculated for a corrective reading of the results in consideration of counter reference (101);
wherein the counter reference is a QR code (103) disclosing calibration details preferably a calibration curve required for a corrective reading of the results to negate any erroneous results and batch code

[0020] Another embodiment of the present invention is to provide a system to determine the Total SCC count by employing a user device, said system comprising:
at least a device of the present invention capable of being housed into / onto the user device, to be able to image said device;
CCD array for image processing built into the user device;
A display screen located on the device for user interface and result display; and
Optionally Onboard other interface(s), all connected to the portable user device interface by means of a wireless communication

[0021] Yet another embodiment of the present invention is to provide a system to determine the Total SCC count by employing an LED reader, said system comprising:
a.at least a device of the present invention capable of being housed into / onto the LED reader;
i.at least a sensor;
ii.at least two LEDs;
iii.a display screen and
iv.Onboard interface(s), all connected to a portable user interface by means of a wireless communication

[0022] Yet another embodiment of the present invention is to provide a system to determine the Total SCC count by employing a portable device employing a user interface selected from but not limited to a mobile phone, tablet, or such alternate devices, said system comprising:
at least a device of the present invention capable of being imaged and scanned by the camera of the portable device;
at least an application preferably a mobile application to enable controlling the camera of said mobile device for imaging, scanning or both purposes, or an application to control the sensor in the portable device and thereafter processing said captured data; and
a central system where the data collected/captured by the portable device is processed, stored, referenced and otherwise used by the present system;

Onboard interface(s), all connected to a portable user interface by means of a wireless communication

[0023] Referring to Figure 2. Which shows a system in accordance to an embodiment of the present invention used for accurately determining the Total Somatic Cell count by employing an LED reader, said system comprising:
at least a device (100):
a.being housed into or onto the LED reader located within a portable device (201b) having
i.at least a sensor;
ii.at least two LEDs;
iii.a display screen;
to quantifiably detect somatic cell count in the sample tested on the device, wherein each component is inter connected by means of a wireless communication;
OR
b.being imaged or scanned by at least a mobile device (201a) having a mobile application enabling the mobile device to quantifiably detect somatic cell count in the sample tested on the device.

[0024] Further referring to FIGURE 2 which shows the inter connection of various components of the system (200) of the present invention, said system comprising
A.at least a portable device (201b) or a mobile device (201a) having a camera capable of imaging and scanning the device locally present and connected by wireless connection (202) with a central sub-system (203);
B.at least a mobile application to enable controlling the camera of said mobile device for imaging, scanning or both purposes, and thereafter processing said captured data, wherein the mobile devise (201a) is selected from a mobile phone, tablet, laptop, smart watch, or such alternate device; and
C.a central sub-system where the data captured by the portable device (201b) or the mobile device (201a) is processed, stored, referenced and otherwise used by the system (203).
wherein the central system employs an algorithm, a controller, a processor (204), sub-systems (203), a user application preferably being a mobile or web application onboarded onto one or more user device (201a,201b), a server being physical (203a) or cloud based(203b) and an AI/ML block, each communicating vide wireless connection (202) and wherein the processor configured to an inbuilt correction model is configured to an AI/ML model containing a training model such that the AI/ML model is provided with preset training data which is updated by the training model, said AI/ML model attempts to map various corrective algorithms onto the type of sample and infers to confirm if the data fits the trained AI model so as to improve accuracy with each test performed.
wherein the sensor may be a color sensor or a CCD sensor and wherein the LED reader or the mobile application has a calibration system which is updated periodically or in real time, from the backend server (203).

[0025] In another embodiment, a method of operating the present system is disclosed, said method comprising at least the following steps:
a.Collecting a sample size of ~40l of whole milk and dropping it onto the 1st layer of the device of the present invention through sample well;
b.Adding to the above, 160l of running buffer, preferably TRIS (pH 10) to assist with developing the complex faster;
c.Upon a color change to blue (due to complex formation), subjecting the device to be analyzed by the present system in the following manner;
d.Determining the intensity of the blue color to quantify the total SCC count by means of a user device;
e.Recalculating said result by considering the errors relating to camera imaging by means of a color mat;
f.Employing a calibration curve as disclosed by the QR code present in the device of the present invention to further eliminate errors.
g.Processing said results and displaying the same to the user interface while storing a copy of the test data within the database of the system

[0026] Referring to FIGURE 3 which shows a flow chart (300) depicting a method in accordance with an embodiment of the present invention the method including the following steps:
i.collecting a sample of milk and dropping it onto the impregnated filter layer of the device through sample well (102);
ii.adding to the above, running buffer, preferably TRIS at pH 10 to assist with developing the complex faster;
iii.Upon complex formation and obtaining a color change to blue, subjecting the device to be analyzed by the present system in the following manner:
a.Subjecting the device to an LED reader or a camera of a mobile device;
b.determining the intensity of the blue color to quantify the total somatic cell count by means of a system;
c.Sending the data including readings along with sample parameters including location and type of milk sample, to the sub-system (203).
d.Receiving said data by AI/ML model which attempts to map various corrective algorithms onto the type of sample and infers to confirm if the data fits the trained AI model so as to improve accuracy with each test performed
e.Receiving said data by the processor and recalculating said result by considering the errors relating to camera imaging by means of a color mat located on the device;
f.employing by a calibration system present in the mobile application or LED reader, a calibration curve as disclosed by the QR code present in the device of the present invention to further eliminate errors;
g.processing said results and displaying the same to the user interface while storing a copy of the test data within the database of the system.

[0027] In yet another embodiment, a system comprising at least one device of the present invention is disclosed, wherein said system further employs an algorithm, a controller, a processor, at least a display screen, a user application and user device, a wireless connection and ancillary parts, a server (selected from physical, cloud based, etc.) an AI/ML block, sub-systems.

[0028] In an embodiment of the present invention the AI/ML block includes a trained AI model loop which may be provided with training data set so to try various corrective algorithms based on the type of sample and infer if the data fits the trained AI model so as to improve accuracy of the testing method. The iterative feedback loop increases the accuracy as well as eliminates manual intervention and for any data set, the ratio is identified automatically by intelligently learning from the provided data for providing best accuracy.

[0029] In an embodiment aspect of the present invention the AI/ML block includes a task executor wherein an input dataset may be provided to or received by a task executor. The task executor, may be configured to forward the input dataset to the trained model. The trained model, may be configured to implement the AI model trained by model trainer.

[0030] In an embodiment of the present invention the AI/ML block includes a model trainer which may be configured to train the AI model and the ML model. Further the trained model, may be configured to generate results for the input data processed by the AI model. A tuner, may be configured to evaluate the results of the output. Further the tuner based on the feedback received on the results by evaluation is configured to optimize the training model.

[0031] In yet another embodiment, the system of the present invention employs a digital twin model capable of receiving data from each subsystem of each independently located devices including subsystem level components, enabling predictive analysis of maintenance, operations, and to facilitate updates to various system models, units, subsystems, components, devices, applications inter alia. Additionally, the system is capable of accessing data such as antibiotic sensitivity of locations nearby the site of sample collection, based on which treatment plans, prescriptions, may be suggested and/or administered to said testing site and information regarding the same may not only be communicated to the site/ through the user device but also to surrounding sites to ensure a complete approach of treatment and preventive measures has been implemented. Further, the system of the present invention also enables true value entries of SCC measured with a reference method for the image processing system to “self-learn” and progressively modify with each test performed. Wherein the system employs a self-learning model enabling the system to be progressively modified with each test performed and a collective model wherein the processed data in the form of reports, test or simply modified data is updated to all locally present devices connected to the central system.

A person of ordinary skill in the art will readily ascertain that the aforementioned embodiments are set out to explain the present invention, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. The embodiments are presented herein for purposes of clarity and disclosure, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments. ,CLAIMS:We Claim:
Claim 1. A device to quantitatively determine the total somatic cell count, said device comprising:
a.at least one impregnated filter layer (105);
b.an absorptive layer (106,107), to collect the filtrate; and
c.an outer casing (104,108) having a counter reference (101) and a QR code (103) for correcting any errors in the process of determining the total somatic cell count; wherein the impregnated filter layer(105) is capable of forming a colored compound with the enzyme present in somatic cells, the color intensity of which is directly proportionate to the quantity of somatic cells calculated for a corrective reading of the results in consideration of counter reference (101).

Claim 2. The device as claimed in Claim 1 wherein the impregnated filter layer (105), is preferably What man grade 2 filter; the absorptive layer (106,107) is preferably made of glass fibre being ~0.08mm thick x3; and the outer casing (104,108) having a counter reference being QR code, a color mat, or both wherein the Color mat is capable of countering for camera imaging errors.

Claim 3. The device as claimed in Claim 1 wherein the counter reference being a QR code (103) disclosing calibration details preferably a calibration curve required for a corrective reading of the results to negate any erroneous results and batch code.

Claim 4. The device as claimed in Claim 1 wherein the impregnated filter layer (105) is preferably impregnated with Taloxin, a dye substrate immobilized to react with the ester from the Somatic Cells to form a coloured compound, the colour intensity of which is directly proportionate to the quantity of total somatic cells.

Claim 5. A system to accurately determine the Total Somatic Cell count by employing an LED reader, said system comprising:
a.at least a device as claimed in claim 1 being housed into or onto the LED reader located within a portable device having
i.at least a sensor;
ii.at least two LEDs;
iii.a display screen;
to quantifiably detect somatic cell count in the sample tested on the device as claimed in claim 1, or
b.being imaged or scanned by at least a mobile device having a mobile application enabling the mobile device to quantifiably detect somatic cell count in the sample tested on the device as claimed in claim 1,
wherein each component of the system is inter connected by means of a wireless communication.

Claim 6. The system as claimed in Claim 5, wherein the sensor may be a color sensor or a CCD sensor and wherein the LED reader or the mobile application has a calibration system which is updated periodically or in real time, from the backend server (203).

Claim 7. The system as claimed in Claim 5, said system comprising:
A.at least a portable device (201a) or a mobile device (201b) having a camera capable of imaging and scanning the device as claimed in claim 1 locally present and connected by wireless connection (202) with a central sub-system (203);
B.at least an application preferably a mobile application to enable controlling the camera of said mobile device for imaging, scanning or both purposes, or an application to control the colour sensor in the portable device and thereafter processing said captured data, wherein the mobile devise is selected from a mobile phone, tablet, laptop, smart watch, or such alternate device; and
C.a central sub-system (203) where the data captured by the portable device or the mobile device is processed, stored, referenced and otherwise used by the system.

Claim 8. The system as claimed in Claims 5 and 7, wherein the central system employs an algorithm, a controller, a processor (204), sub-systems (203), a user application preferably being a mobile or web application onboarded onto one or more user device (201a,201b), a server being physical (203a) or cloud based(203b) and an AI/ML block, each communicating vide wireless connection (202) and wherein the processor configured to an inbuilt correction model is configured to an AI/ML model containing a training model such that the AI/ML model is provided with preset training data which is updated by the training model, said AI/ML model attempts to map various corrective algorithms onto the type of sample and infers to confirm if the data fits the trained AI model so as to improve accuracy with each test performed.

Claim 9. The system as claimed in Claims 5 and 8 wherein the AI/ML block has a model trainer configured to train the AI and ML models to generate results for the input data received from and processed by the AI model such that a tuner is configured to evaluate the results of the output, wherein the tuner is configured to optimize the training model based on the feedback received by evaluation.

Claim 10. The system as claimed in Claims 5 and 8 wherein the AI/ML block includes a task executor wherein an input dataset may be provided to or received by a task executor configured to forward the input dataset to the trained model which is configured to implement the AI model trained by model trainer.

Claim 11. The system as claimed in Claims 5 and 8 employs a digital twin model capable of receiving data from each subsystem of each independently located devices including subsystem level components, enabling predictive analysis of maintenance, operations, and to facilitate updates to various system models, units, subsystems, components, devices, applications.

Claim 12. The system as claimed in Claims 5 and 8 employs a model capable of accessing data being antibiotic sensitivity of locations around the geographical location of sample collection in the form of reports, based on said reports treatment plans, prescriptions, or both are suggested to the user through the user device and to other devices connected to the central sub-system.

Claim 13. The system as claimed in Claims 5 and 8 employs a self-learning model wherein the system is progressively modified with each test performed and a collective model wherein the processed data in the form of reports, test or simply modified data is updated to all locally present devices connected to the central system.

Claim 14. A method of operating the system as claimed in claim 5 comprising at least the following steps:
i.collecting a sample of milk and dropping it onto the impregnated filter layer of the device as claimed in claim 1;
ii.adding to the above, running buffer, preferably TRIS at pH 10 to assist with developing the complex faster;
iii.Upon complex formation and obtaining a color change to blue, subjecting the device to be analyzed by the present system in the following manner:
a.Subjecting the device as claimed in Claim 1 to an LED reader or a camera of a mobile device;
b.determining the intensity of the blue color to quantify the total somatic cell count by means of a system as claimed in claim 5;
c.Sending the data including readings along with sample parameters including location and type of milk sample, to the sub-system (203).
d. Receiving said data by AI/ML model which attempts to map various corrective algorithms onto the type of sample and infers to confirm if the data fits the trained AI model so as to improve accuracy with each test performed
e.Receiving said data by the processor and recalculating said result by considering the errors relating to camera imaging by means of a color mat located on the device as claimed in claim 1;
f.employing by a calibration system present in the mobile application or LED reader, a calibration curve as disclosed by the QR code present in the device of the present invention to further eliminate errors;
g.processing said results and displaying the same to the user interface while storing a copy of the test data within the database of the system.