An Efficient Online Offline Data Collection Software Solution for Creating Reference Population to Established Genomic Selection Under Small Holders’ Dairy System in India

International Journal of Computer Science, Engineering and Information Technology (IJCSEIT),
Vol.13, No.4, August 2023
DOI : 10.5121/ijcseit.2023.13401 1
AN EFFICIENT ONLINE OFFLINE DATA
COLLECTION SOFTWARE SOLUTION FOR CREATING
REFERENCE POPULATION TO ESTABLISHED
GENOMIC SELECTION UNDER SMALL HOLDERS’
DAIRY SYSTEM IN INDIA
Y S Gaundare, S A Joshi, N K Punde, K G Bhave, T V Shirsath, V V Potdar, V
Dhanikachalam, S Jadhav, A S Joshi and M Swaminathan
Central Research Station, BAIF Development Research Foundation, Pune 411058, India
ABSTRACT
This article as part of an Enhanced Genetics Project assumes special significance in the light of emergence
of electronic mode of data collection system. Pen and paper method of data collection although very
familiar to field people, but is generates the errors and requires digitization and data cleaning. The
software solution surveying is easier mode of ensuring uniformity in data collection, reducing errors and
better storage and analysis of data. In this regard, this article gives a clearer picture of the digital tablet
based data collection system employed part of the Enhanced Genetics Project across 49 selected Data
Recorders (Data Enumerators) in Maharashtra, Uttar Pradesh, Jharkhand, Punjab, Odisha, Gujarat,
Andhra Pradesh, Rajasthan, and Bihar. The manual outlines the processes to be fulfilled by the digital
mobile based solution, the user interface involved and the software and hardware infrastructure to support
such a platform independent system. In this project we have enrolled the 33,293 dairy animals and
collecting there production, reproduction, body weight data, as well as, collecting the baseline & herd
management information of that farm. This system increase Data Accuracy GPS (Global Positioning
System) enabled data collection system for genomic evolution. This is very unique software solution
developed for to collect the structured phenotype data of the dairy animals in Indian conditions on real-
time basis. As well, show case the robust data collection system for the Genomic Selection for dairy
animal’s initiative. This sub-system also focused on the various activities and operations related to
molecular biological laboratory. In this software solution system the two major feedback systems for
actively participation of the farmers were participation certificate and Graphical Animal Ranking system
for the farmer and animal. The locational data collection with seamless interfacing with the user and the
data repository for Genetic Improvement Data collection system. Data capture system was quite successful
in gathering field phenotype data for Genetic Improvement Program in the complex dairy production
system like India.
KEYWORDS
Data Collection, Data Enumerators, GPS, Farmer Feedback.
1. INTRODUCTION
Department of Animal Husbandry & Dairying under Ministry of Fisheries, Animal Husbandry &
Dairying attributes critical importance to livestock. Also, the collection and availability of up-to-
date and accurate data related to livestock, as they are the important component of the rural
economy. For proper planning and formulation of any programme meant for achieving further
improvement in this field and its effective implementation and monitoring, data validation are

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required at every decision-making stage. Present scenario of livestock data in Indian scenario
data The Livestock Census is the main source of such data in the country. The livestock census is
conducted across the country periodically since 1919. The census usually covers all domesticated
animals and head counts of these animals are taken. The uniformity of data is really important of
data quality.Uniformatity of data quality removes the duplications of data and improves quality of
data. Using manual data entry with pen and paper in the software, Excel or any database is risk to
data reliability and manual errors. The present project phase is going to emphasis on not just
crossbred but also indigenous breed of cattle and buffalo as well. Apart from that we are going to
focus other important traits like fertility (Age at first calving, Service period, calving interval
etc.), other important production traits (milk components like fat, SNF), conformation traits,
disease incidence traits, heat tolerance traits etc. The emphasis will be given on female farmer
preferred traits like temperament trait as well. This way of genomic evaluation will allow
selection of farmer desire good type and associated traits associated with profitability and
sustainability of farmer.BAIF has a historical evolution of implementing several electronic data
capturing systems starting from heavy data loggers to mobile based platforms Potdar et al.,
(2017). Even before the Enhanced Genetics Project, data collection using windows phones, palm
mobiles was experimented. However, considering the unavailability of windows phones, palm
devices and emergence of smart phones, it was decided to go with Windows Tablets with
Windows based operating system of 8/10. In this stage, the system was like an interactive
assistant to various levels like Data Recorder, Supervisor, State Monitoring officer and HO-
Central Research Station. The BAIF organization is committed to improving the livelihoods of
the poor with deep-rooted focus on development research. With its implementation across several
states in India and a major change-maker in the lives of many, the monitoring and improvement
of different programmes of BAIF assumes significant importance. Enhanced Genetics Project for
genetic improvement based on genetic evaluation of smallholder dairy production system in India
(Al Kalaldeh et al. (2021). Every project requires a good monitoring programme, however, this
project, in particular, being concerned with the future prospect of up scaling and moreover related
to the core of BAIF’s focus, necessitates a better genetic analysis and genomic evaluation. This
demands that the raw data collected from the field is documented in the right format for future
accuracy of the analysis carried out. In this regard, a change from the traditional book-keeping
system to digital database management seems unquestionable.
2. METHODOLOGY
49 Data Recorders (Enumerators) were selected for this project in 42 districts of Maharashtra,
Uttar Pradesh, Jharkhand, Punjab, Odisha, Gujarat, Andhra Pradesh, Rajasthan and Bihar. On an
end-to-end basis the project was operational from November 2016 till August 2021.
In 2015-16 we have started to develop the data structure of this data collection system with help
of national & International Genetic Experts. We have listed the exhaustive data points and make
the list of all the data points. Then we have develop the online-offline mode software on windows
tablet platform for data collection, this software we have developed in Microsoft dot net and
Microsoft SQL server technologies.

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Figure 1: Software solution cycle
Above figure gives an Idea about the software solution methodology adopted for the design of
this data collection system.
Architecture of software solution designed in various layers of sub-architectures is as follows:
 At the base of the design is the process architecture, which encompasses design and
layout of all the business processes and activities that we plan to automate.
 On top of this is the solution architecture, which encompasses the design and layout of
information flow (structure of information, systemic check and constraints, business
logics etc.) and various modules and user interactions handling the information flow.
 On basis of process and Solution architecture the software architecture develop, which
encompasses the design of software modules and concrete implementation of solution
architecture on a specific technological platforms, (namely, Microsoft .Net 4.0/4.5,
Microsoft SQL Server 2008/2012, Windows 7/8/10 and Windows Server 2008/2012).
2.1. Back-End Infrastructure
This topic explains about the back-end infrastructure of Enhanced Genetics Project. The
architecture was designed taking into account the activities to be carried out, organisational
hierarchy, etc.
The architecture consists of the software and hardware portions. The software is concerned with
the development of different software modules and application interfaces. The hardware consists
of the infrastructure in which the software will be housed and their field deployment.
2.2. Software Architecture
Software architecture consists of four parts which form the different layers:
1. Primary – framework
2. Secondary – implementation components
3. Tertiary – database facilities
4. Quaternary – user interface
The primary core of the architecture is the framework which is the information structure model. It
will simulate all the data collection activities (like production, breeding, feeding and body
weight) and participating entities (like animals, sires, farming households).

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The framework/model is then implemented by a set of secondary software components, referred
as Implementation components, which incorporate the logics, validations and rules pertaining to
each and every research activity and participating entities.
Further these modules depend on the database management facilities which form the tertiary layer
in the software architecture. There are two sets of components, one developed for Windows
Tablets platform on Microsoft SQL Server and another for Windows Server platform on Cloud
Azure Microsoft SQL Server.
The tertiary and last set of software components are the user interfaces, also referred to as
consoles, both on Windows tablets and PC platform. These have all the necessary display forms
for all user reporting and other interactions.
Figure 2: Software Architecture with User interphases
The Performance Recorder’s software edition is deployed on Windows tablets with the Data
Recorders. This is the primary source of recorded information. The District Supervisor edition is
deployed on web-portal at District level. Information collected by the Data Recorders is
transferred and synchronized on Cloud servers through internet. The State unit is deployed on
web-portal at State level. Information collected by the Data Recorders is directly accessed by the
State Monitoring Officers. Additional reporting utilities, dashboards are developed for day to day
data monitoring & reporting. The Central Research Station-HO is deployed on web-portal at the
central office (CRS, Uruli Kanchan). Information collected by the all Data Recorders is available
on this web-portal. As well as, cloud servers data real-time synchronised with the in-premises
physical server for a data repository, research and data analysis was done.
2.3. Hardware Architecture
Initially, considering the processing power, internet connectivity issues, etc. an online-offline
hardware infrastructure was envisaged wherein data from Data Recorders tablet was
automatically get synchronised at Cloud servers further all the data from district level cross
checked with the district supervisors and at state level and eventually all the project data was
stored in the Cloud sever & it gets replicated on Central Research Station’s physical server.

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Figure 3: Hardware Architecture of Software Solution
3. SCOPE OF THE SOFTWARE SOLUTION
Following are the sets of software modules and sub-modules that planned, designed, developed
and deployed during project period,
 Data management service: This software module designed, developed and implemented
as a database on Microsoft SQL Server 2008/2012 on Microsoft Azure Platform. Primary
responsibilities of this module will be storage of data, back-up and restoration etc.
 Solution service: This software module deployed on a Microsoft Azure Web App
Service. It will be background service software, hosting various sub-modules. These sub-
modules will be implementing the systemic checks, business constraints and business
logic as envisaged in the solution architecture.
 User-interface service: These tablet as well as web based software modules used by
end-users and supervisory staff to interact with the solution service. Software installed on
Windows Tablets at Data recorders level and web -applications for others.
 Security management console: This console used to configure and set the solution service
settings for security sub-system management
 Solution consoles
 Administration console: This console used to configure and manage settings for solution
sub-system modules.
 State Office Console: This console used by state office staff for day-to-day activities
related data monitoring & reporting.
 District Office Console: This console used by district level supervisor staff for day-to-day
activities related data monitoring & reporting.
 Data Recorder Console (Windows Tablet software): This console used by data entry
operators for day-to-day activities (as listed above) happening at the data recorder level.
This console running on an online-offline mode on Windows Tablet.
 Reporting Console: This console provided to other data consumers who are more
interested in reports and data for further analysis at various levels.

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4. FARMER FEEDBACK SYSTEM
Any field recording system is active if we give the feedback to the stakeholders, in this software
solution system we have developed the following feedback systems for actively participation of
the farmers.
4.1. The participation certificate for the farmer:
Digitally generated certificate is available at an online portal. As well as we are in process for the
physical printing at central level.
Figure 4: Farmer Feedback System: Farmer Participation Certificate
4.2. Graphical Animal Ranking system
This is also available on an online portal a state/district/data recorder level animal ranking system
on the milk yield rating, FAT/SNF/Protein rating. As well as, Milk recorders are able to show this
ranking to participated farmers.
Figure 5: Farmer Feedback System: Animal Ranking System

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4.3. Prerequisites of hardware and software
1. Software modules hosted as follows:
2. Data management service on MS SQL Server running on Microsoft Azure Platform.
3. Solution service on Internet Information Server running on Microsoft Azure Platform.
4. User interfaces for end-users on Window Tablets with Operating System Windows 8.1 &
10 and Windows/Linux PCs with Internet Explorer.
5. Dot Net Framework 4.8
6. SAP Crystal Reports for Visual Studio (SP30) runtime (32-bit & 64-bit)
4.4. Software solution Availability
Demo version of software is available on request on following link,
https://baifonline.org/EnhancedGenetics/Home/Downloads
5. RESULTS
As we know the Data is the new fuel for any organization in this digital world. An Organizations
have the difficulties in getting the field data from various location in structured manner. As well,
it is difficult to maintain the quality of incoming data. So to overcome this problem our software
solution is the good tool to adopt and replicate.
Following tables gives the idea of the volume of data we have collected through this mechanism
for various research purposes.
Table 1: State wise coverage
State
No.
of
Distr
icts
No. of
Cattle
Breeding
Centers
No. of
Villages
No. of
Data
Recorders
No. of
Farmers
/ herds
No. of
Animals
Registered
No. of Animals
under performance
recording
Andhra Pradesh 2 18 72 2 211 1,300 1,300
Bihar 4 12 152 4 2078 4,476 3,262
Gujarat 6 12 60 7 970 2,727 2,694
Jharkhand 4 42 267 6 1666 5,554 5,094
Maharashtra 3 21 90 5 1599 6,665 5,842
Odisha 4 10 127 4 1342 3,314 2,560
Punjab 4 12 161 6 1358 4,858 4,306
Rajasthan 2 2 25 2 538 1,158 1,025
Uttar Pradesh 13 26 396 13 3563 8,559 7,210
Total 42 155 1,350 49 13,325 38,611 33,293

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Table 2: State wise & Breed Wise total Animals Registered
State
Buffalo Cow Grand
Total
N. D. Indigenous Total HF X Indigenous JR X N. D. Total
Andhra Pradesh 211 211 - 1,089 - 1,089 1,300
Bihar 405 602 1,007 2,387 181 278 623 3,469 4,476
Gujarat 151 1,907 2,058 49 607 7 6 669 2,727
Jharkhand 117 221 338 3,404 229 1,298 285 5,216 5,554
Maharashtra 186 1004 1,190 4,595 132 621 127 5,475 6,665
Odisha 23 8 31 184 447 2,345 307 3,283 3,314
Punjab 447 1,423 1,870 1,893 532 353 210 2,988 4,858
Rajasthan 11 11 202 881 64 - 1,147 1,158
Uttar Pradesh 1,448 2,088 3,536 3,106 489 605 823 5,023 8,559
Total 2,777 7,475 10,252 15,820 4,587 5,571 2,381 28,359 38,611
Table 3: State wise & Breed Wise total Animals under phenotype performance recording
State
Buffalo Cow Grand
Total
N. D. Indigenous Total HF X Indigenous JR X N. D. Total
Andhra Pradesh 205 205 44 1,025 26 - 1,095 1,300
Bihar 276 423 699 1,789 111 197 466 2,563 3,262
Gujarat 138 1,914 2,052 48 584 5 4 642 2,694
Jharkhand 97 215 312 3,262 205 1,127 188 4,782 5,094
Maharashtra 158 904 1,062 4,024 101 552 103 4,780 5,842
Odisha 9 5 14 167 336 1,797 246 2,546 2,560
Punjab 410 1,293 1,703 1,705 449 307 142 2,603 4,306
Rajasthan 9 9 202 761 53 - 1,016 1,025
Uttar Pradesh 1,183 1,699 2,882 2,742 410 510 666 4,328 7,210
Total 2,271 6,667 8,938 13,983 3,982 4,574 1,816 24,355 33,293

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Table 4: State wise data recorded on various parameters
State
No.
of
test
day
milk
records
No.
of
test
day
milk
quality
records
No.
of
Body
Measurement
records
No.
of
feeding
records
No.
of
breeding
records
No.
of
animals
body
type
trait
records
No.
of
Bio-logical
Sample
records
No.
of
Animals
Genotyped
Andhra Pradesh 11,591 11,976 3,739 9,922 131 - 170 -
Bihar 47,590 30,540 10,166 26,538 1,535 48 2,288 1,002
Gujarat 35,551 24,902 8,861 25,076 6 22 2,044 44
Jharkhand 152,248 41,952 27,581 57,895 2,317 1,404 2,413 1,955
Maharashtra 94,080 10,611 24,838 41,415 7,141 1,862 2,623 985
Odisha 16,030 12,667 17,576 21,778 135 - 671 184
Punjab 100,820 31,870 5,056 7,711 291 - 2,844 1,266
Rajasthan 6,196 3,253 481 628 - - - -
Uttar Pradesh 126,613 73,010 32,649 73,311 1,151 1,953 3,570 1,546
Total 590,709 240,781 130,947 264,274 12,707 5,289 16,630 6,982
6. DISCUSSION
6.1. Need of Software Solution
The software solution needs to help in data management involved in the services of Data
Recorders. It is like an interactive assistant which notes daily appointments and pending tasks.
The various activities involved in a software solutions are explained in the following sections.
The exhaustive data point list with category is as follows,
6.2. One time data
1. Locality data: State, District, Recorder, CDC, Village.
2. Farmer data: Farmer details, Farmer baseline with land, major crops, economic status,
animal holding and income-asset data etc.
3. Herd Management data: Animal housing, Feeding practices, Animal treatment, Animal
sale-purchase and general herd details like, replacement source, milking etc.
4. Animal enrolment: Tag number, Species, Breed, Age, Dam & Sire, Lactation and last
calving information.
5. Biological sample collection data: Date and sample reference number.
6. Animal body type trait data: we are collecting the 27 body type trait data.
6.3. Transactional Individual animal wise data
We have fixed the frequency for following repeatedly data collection,
a. Milk yield data: Morning and evening with or without sucking.
b. Milk component data: FAT, Protein, SNF etc.
c. Mastitis instances.

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d. Breeding & Follow-ups: AI/Natural service, PD and Calving follow-up.
e. Body measurement: Length, Girth, Height and body weight.
f. Vaccination & Immunization instances
g. Feed and Fodder data: Green, Dry, Mineral and concentrate etc.
h. Disease instances and approximate cost for treatment & days to recover.
i. Animal disposal: Sold, Died or left out from the project due various reasons.
Simultaneously we have harmonised the state team and recruited the Enumerators (Data
Recorders). As well as we have developed the various SOPs for the selection of farmer, herd and
animal and circulated to state teams.
After successful development of this windows based software we have tested the software
thoroughly. In August 2016 we arranged the 3-4 days training of State coordinators, Monitoring
officers, Supervisors and the Data Recorders about the Genetic component project information,
need and objectives. As well as we had trained them how to operate the software. Initially we
have started this component in 6 states and subsequently we added more states and recorders as
our scope changes. For daily monitoring purpose we have developed the web-portal
www.baifonline.org with role management and created the various login credentials according to
the role of the person.
Figure 6: Interface of Software Solution
6.4. Achievements
1. The data capture and management system under Enhanced Genetics Project is a proof-of-
concept for multi locational data collection with seamless interfacing with the user and
the data repository for Genetic Improvement Data collection system.
2. Despite involving implementation of multiple validation checks and logics the data
capture system was quite successful in gathering field phenotype data for Genetic
Improvement Program in the complex dairy production system like India.
3. The data capture and management is the right MIS tool for better monitoring and
evaluation through fast and effective feedback and timely corrections.
4. The data analysed subsequently has provided much needed inputs for scientific and
management research.
5. The data capture system will provide an opportunity to superimpose newer field based
scientific and operations research plans.

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6. In view of the versatility of the system, it has proved to be a standard and would be worth
applying in other similar programmes in the country.
6.5. Challenges
1. There is a definite reluctance of Data Recorders/Supervisory staff to switch over new
technology because it may be quite unfamiliar. This may lead to improper handling of
device, internet, etc.
2. The software is being in English causes difficulties to some Data recorders who are not
fully conversant. Hence there could be misinterpretation of some parameters and spelling
errors. But those minimized after conducting the multiple revive trainings with them.
3. When a lot of details have to be recorded the Data Recorders may be impatient and may
not enter the precise data.
6.6. Recommendations and Future Scope
1. Considering the massive usage of smart phones especially with the younger generation, it
would be desirable to opt for electronic system of data capture although a complete shift
may be gradual due various reasons.
2. Taking into account the familiarity and availability of Internet Connectivity and Smart
Phones, it would be desirable to make next generation apps on the Web based platform.
So we are in process of upgrading this software solution on platform independent
Progressive Web App.
3. Geo-tagging and audio/video recording features could be included to ensure validity of
the data.
4. Provision for noting comments/unstructured data could be made.
5. Newer versions in development as the software evolve and regular review trainings and
follow up for Data Recorders.
6. Trainings for smooth English input and exercises to reduce spelling errors.
7. CONCLUSIONS
This is very unique software solution developed for to collect the structured phenotype data of the
dairy animals in Indian conditions on real-time basis. As well, show case the robust data
collection system for the Genomic Selection for dairy animal’s initiative to the funding agencies,
Government of India and amongst the stake holders of the projects is successfully achieved. Our
future work will primarily focus on expansion of this software solution amongst the country wide
phenotype performance recording of the dairy animals with the various technology upgrades &
validation. As well, we will develop the platform independent and more user friendly software
solution in future.
ACKNOWLEDGEMENTS
We acknowledged the President of BAIF, Vice President and colleagues.
We also acknowledged the extensive contributions of field level Data recorders, District level
supervisory staff, and State level monitoring officer’s, for tireless works in BAIF’s Enhanced
Genetics Project.

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REFERENCES
[1]. Genomic evaluation of milk yield in a smallholder crossbred dairy production system in India:
Mohammad Al Kalaldeh1* , Marimuthu Swaminathan2, Yuvraj Gaundare2, Sachin Joshi2, Hassan
Aliloo1, Eva M. Strucken1, Vincent Ducrocq3 and John P. Gibson1. December2021, Genetics
Selection Evolution 53(1),10.1186/s12711-021-00667-6.
[2]. BAIF Experience in Field Data Collection: Vinod V Potdar*, Bhave K, Gaundare YS, Khadse JR and
Pande AB Department of Genetics, BAIF Development and Research Foundation, India.
August 2017, 10.36876/ijas.1004
AUTHORS
Yuvraj S S Gaundare More than 17 years of operational and functional experience
in the software development, deployment, data analysis and data monitoring.
Proficient in R, C#, SQL programming languages. Strong experience in basic and
statistical analysis of gathered data. Currently working with “BAIF Development
Research Foundation” Central Research Station, UruliKanchan, Pune, as a Thematic
Program executive since 2010. Completed the Post-Graduation MBA in the
Information Systems and Graduation Degree in Bachelor of Engineering in Computer
Science. Around 17 research articles published to date.
Dr. Sachin Joshi is a post graduate in Veterinary Medicine and working as Chief
Thematic Programme Executive at BAIF Development Research Foundation. Since
2014, he is working in the capacity of Coordinator in implementing the piloting of
sorted semen under varied production environment in India and understanding the
success rates (conception rates and calf sex ratio) and adoption of sorted semen
among the small holder dairy farms in India. He has 23 years of working experience
in the area of livestock research and development. In addition, he has notable
experience of managing a large organized commercial dairy farm for the captive quality milk production.
He is the author and co-author of over 45 research publications in various journal.
Nikhil Punde, Post graduate in computer science at University of Pune and currently
working as a Information Technology Specialist for BAIF in Pune. I work on Data
Management and Analytics.
K. B. Bhave, PhD in Animal Genetics and Breeding, working as a Thematic Program
Executive in BAIF Development Research Foundation.
Tejashree Shirsath, Post graduate in computer science at University of Pune and
currently working as a Information Technology Specialist for BAIF in Pune. I work on
Data analysis Management and Server Administration. Around 16 research articles
published to date.

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Dr.Vinod Vijay Potdar completed his Masters in Animal Genetics & Breeding
(M.V.Sc.) from Maharashtra Animal and Fishery Science University, Nagpur in year
2003.Presently he is working at Animal Genetics and Breeding Department, Central
Research Station of BAIF Development Research Foundation at Urulikanchan, Pune,
and Maharashtra.. He is the author and co-author of more than 30 research articles in
national and international journals.
Dr.Santoshkumar JADHAV, Last 8 years working in the area of genomics. Working
as a thematic program executive in BAIF Development Research Foundation.
Dr.Velu Dhanikachlam,PHD in Biotechnology Last 8 years working in the area of
Biotechnology. Working as a thematic program executive in BAIF Development
Research Foundation. He is the author and co-author of over 16 research publications in
various journal.
Dr. A S JOSHI, M.V.Sc. in Animal Genetics and Breeding, currently working as
Senior research Officer in BAIF, Development Research Foundation
Dr. M Swaminathan, A Veterinarian with specialization in animal breeding and animal
production systems, having more than 25 years of experience in livestock-based
smallholder agriculture and agribusiness development program management and dairy
farm operations in several countries, worked in strategizing and implementation of the
climate-resilient livestock production, animal health technologies and marketing
strategies for the uplift of rural livestock farmers in developing countries.

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