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ICAR-National Research Centre on Pig

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1 ICAR-National Research Centre on Pig
Image based systems for identification of individuals, breeds and diseases of pigs and goats N.H.Mohan ICAR-National Research Centre on Pig Guwahati, Assam

2 Team partners Lead Institute (LIN1): Kalyani Govt. Engineering College, Kalyani, Nadia, WB Participating Institute (PIN 1a): Indian Institute of Technology, Guwahati, Assam (PIN1b): ICAR Research Complex for NEH Region, Umiam, Meghalaya Agri Institutes Lead Institute (LIN2): National Research Centre on Pig, Rani, Guwahati, Assam (PIN2a): ICAR Research Complex for NEH Region, Tripura Centre, Tripura (PIN2b): Assam University (Central University),Silchar, Assam (PIN2c): Uttar Banga Krishi Viswavidyalaya, Cooch Behar, West Bengal

3 What has been achieved so far?
Some of the methods for identification of animals presently available are Traditional methods Electronic Identification Devices Tattoo Ear Notching Ear Tagging Micro-chipping Biometric Identifiers Retinal scan Muzzle patterns Iris patterns Facial recognition Ear vessel patterns DNA based methods

4 Major beneficiaries of the project
1. Small farmers will benefit from low cost identification for claim on insured animals in the event of its death and getting microfinance benefits and health management support. 2. Large scale pig farms will benefit from specific identification of individual animals and maintain as well as plan animal management, pedigree records, breeding plan etc. as well as claim on insured animals in the event of its death. 3. Animal insurance-The proposed methods of animal identification in the project such as retinal scans are considered more reliable than electronic identification because they cannot be falsified and hence will be of immense use for animal identification for insurance purposes. 4. Veterinarians and other health care management personnel will benefit from specific identification system for treatment and management especially when the number of animals are large as well as in vetero-legal cases.

5 Major beneficiaries of the project
5. Researchers will benefit from the system for precise planning, execution of experiments and interpretation of results. 6. Meat industry- One of the key benefactors of the animal identification system will be meat industry as it will facilitate individual animal identification for ensuring meat traceability, which is a key concern from export and disease transmission, including that of zoonotic diseases. 7. Zoo and biodiversity authorities who are intimately associated with identification of individual animals for the purpose of maintenance of biodiversity and conservation of endangered germplasm. 8. State Animal Husbandry and Veterinary Departments and Department of AH, dairying and fisheries, Govt. of India.

6 Objectives of the project
Identification of trait(s) suitable for unique identification of individual animals Image and DNA based classification of animals into clusters Image based behavioral indications and symptoms of epidemiologically important diseases

7 Task allocation among partners
Overall coordination of the project-ICAR-NRC on Pig and KGEC, Kalyani Coordination with mentors- KGEC, Kalyani IT component –KGEC, Kalyani and IITG will develop IT based image analysis system for individual/breed and disease identification and disease diganosis Sample collection- All agri based institutes Image based analysis of individuality/breed grouping- ICAR-NRC on Pig and KGEC, Kalyani DNA based studies- Assam University Disease confirmation-ICAR RC for NEH region, Meghalaya

8 Work allocation among team partners
Institute Work allocation/ responsibilities KGEC Development of algorithms to identify individuals and breeds based on retinal images Template database and its maintenance IIT-G Development of algorithms to identify individuals and breeds based on iris images. Behavioural pattern typing from video ICAR-NRCP Image data collection on traits, video on behavioural changes due to diseases in pigs Overall coordination of project ICAR NEH-B Image data collection on traits, video on behavioural changes due to diseases in pigs and goats ICAR NEH-T UBKV AU, Silchar Molecular biology works related to DNA based individual identification Lead Institute (LIN1): Participating Institute (PIN 1a): Indian Institute of Technology, Guwahati, Assam (PIN1b): ICAR Research Complex for NEH Region, Umiam, Meghalaya

9 Institutions involved in the Objectives
Technical plan with task allocation among partners Objectives Activities Institutions involved in the Objectives Identification of trait(s) suitable for unique identification of individual animals To identify and image which alone or in combination, unique to individual animals (all agri institutes) To capture images of unique traits using minimal optical facilities (agri and IT institutes) Transmission, storage and use of unique identification data (all IT institutes) NRC on Pig, Guwahati and KGEC, West Bengal IIT-G, ICAR RC for NEH Region, Meghalaya ICAR RC for NEH Region, Tripura UBKV, WB Assam University

10 Institutions involved in the Objectives
Technical plan with task allocation among partners(cond.) Objectives Activities Institutions involved in the Objectives LINs PINs Image and DNA based classification of animals into breed level clusters 01. Identification of the minimum set of morphometric trait(s) necessary and sufficient for classification into breeds. (agri and IT institutes) 02.Validation of image based breed identification through molecular marker (Assam University) 03.Breed classification based on image analysis (NRC on Pig, ICAR RC for NEH region) NRC on Pig, Guwahati and KGEC, West Bengal IIT-G, ICAR RC for NEH Region, Meghalaya ICAR RC for NEH Region, Tripura UBKV, WB Assam University

11 Institutions involved in the Objectives
Technical plan with task allocation among partners(cond.) Objectives Activities Institutions involved in the Objectives LINs PINs To develop system for capturing behavioral indications of epidemiologically important diseases 1: (a) Acquisition and transmission of images of clinical symptoms of CSF and PCV in Pigs and, PPR and goat-pox in goats with mobile phones at the earliest feasible point of disease onset (all agri institutes except NRCP will work on goat and pig; NRC on Pig-pig diseases only) 1(b) Acquisition and transmission of images of clinical symptoms of CSF and PCV in Pigs and, PPR and goat-pox in goats with mobile phones at the best feasible point of disease onset. (agri and IT institutes) 02: Associating specific behavioral changes with onset of CSF and PCV in pigs and, PPR and goat-pox in goats. (agri institutes) NRCPig KGEC IIT-G, ICAR RC for NEH Region (Barapani and Tripura) UBKV, Assam University

12 Project milestones/deliverables
Time Milestone/deliverables 6 m At least one unique trait for identification of individual animal (pig and goat) Prototype software for processing of image traits 1st Yr List of unique morphometric traits in pigs and goats for individual identification Identification of clinical signs for tentative confirmation of specific diseases Prototype software for processing of video images for disease identification 2nd year Grouping of individual animal morphological data to breed level clustering Identification of minimum features of images/ mobile phones for capturing of images of unique trait(s) features/patterns.

13 ICAR-NRC on Pig Capture of iris images, Muzzle images
Collection of blood samples and processing for DNA based identification

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16 Major deliverables Deliverables
Complete system for data capture and analysis for unique traits for identification of individual animals- Software Database on different breeds of pigs/goats in NE region with their unique traits DNA based marker for identification of individual animals Identification of individual animals and classification with breeds Low cost imaging devices for animal & disease identification system Skilled human manpower Research based curricula

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18 Goat- Horizontal rectangular pupils Pig- circular pupils

19 Thanks

20 Activities First year List of unique morphometric traits in pigs and goats for individual identification Algorithms for processing of images of unique traits Protocols for image capture (retina, iris, muzzle, venation etc Data from different breeds of goats and pigs with candidate trait(s) like nose, vein distribution in pinna of ear and tail (goat), snout and inside and outside of ear (pig) Identification of clinical signs for tentative confirmation of specific diseases Standardization of protocols for DNA marker development

21 Activities Second year
Data from different breeds and observations on changes in trait(s) with respect to to age/sex Setting up minimum features of images/ mobile phones for capturing of images for all the traits (light intensity, distance from object, angle, resolution) to identify the unique trait(s) features/patterns. Disease identification system through image analysis for important diseases of pigs and goats Data on distribution of traits with respect to variation in DNA/breed/individual

22 Outreach plan Objective Activity Plan to disseminate the knowledge gained in the project among scientists and students and stakeholders (e.g. through seminars and workshops, and modification in curricular, publications) 1. Organizing seminars and workshops for the scientists, students, NGO’s personals etc 2. Presentations in national and international meetings 3. Publication in peer reviewed journals  4. Introduction of one course module on “Application of IT in agriculture” in UG and PG course curricular for IT as well as agriculture/ veterinary students 5. Sensitizing/ awareness programme and hands on training on use of the outcomes of the project for the stakeholders

23 Outreach plan Development of links with stakeholders
Objective Activity Development of links with stakeholders Government departments, insurance companies etc. Arrangement of interface meetings for linking various stakeholders

24 Individual identification and breed clustering
Service delivery Insurance Better management Biodiversity conservation Policy making Individual identification and breed clustering


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