Mapping the Density and Distribution of Indigenous Cattle Population Using Geographic Information System (GIS) Tools
B. Gopalakrishnan
Department of Environmental Sciences, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India and ICAR - National Institute of Abiotic Stress Management, Baramati, Maharashtra, India.
M. P. Sugumaran *
Department of Environmental Sciences, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
Balaji Kannan
Agricultural Engineering College and Research Institute, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
M. Thirunavukkarasu
Department of Veterinary and Animal Sciences, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
V. Davamani
Department of Environmental Sciences, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India.
*Author to whom correspondence should be addressed.
Abstract
Aim:The current research aims to map the density and distribution of indigenous cattle population using GIS technique.
Study Design: Survey research - Cross-sectional.
Place and Duration of Study: Thondamuthur Block, Coimbatore District, Tamil Nadu State, India. September 2018 to January 2019.
Methodology: A house to house survey was conducted and the locations of farms and households with the indigenous cattle population were geocoded using a handheld Global Positioning System (GPS) device. The points generated were used to create density and distribution maps using QGIS 3.4 software and the information collected from the survey.
Results: The study revealed that a total of 21 indigenous breeds were found in the study area out of which 15 breeds were under the descript category and 6 breeds under the non-descript category. In the adult category, the Kangayam breed (descript) was found to be dominant compared to other breeds, occupying 25% of the total indigenous cattle population followed by the non-descript Kongu cattle (19%). Breeds like Hallikar, Kankrej, Umblachery, Tharparkar, and Sahiwal (all descript) occupied 7%, 5%, 4%, 2%, and 2% of the total indigenous cattle population, respectively. The results were similar in the calves category (including heifers) as well, with the Kangayam breed dominating the category with 8% of the total population, followed by the Kongu cattle (7%), Kankrej (2%), Hallikar (1%), Umblachery (1%), Sahiwal (1%), and Gir (1%). The distribution was found to be more concentrated towards the settlements and lower in the individual farms outside the settlements. The reverse scenario was observed with regard to density. Both the density and distribution were found to be least along the village boundaries adjoining the hilly areas.
Conclusion: Spatial distribution and density related information can be effectively utilized in cattle management, policy-making and decision support systems.
Aim:The current research aims to map the density and distribution of indigenous cattle population using GIS technique.
Study Design: Survey research - Cross-sectional.
Place and Duration of Study: Thondamuthur Block, Coimbatore District, Tamil Nadu State, India. September 2018 to January 2019.
Methodology: A house to house survey was conducted and the locations of farms and households with the indigenous cattle population were geocoded using a handheld Global Positioning System (GPS) device. The points generated were used to create density and distribution maps using QGIS 3.4 software and the information collected from the survey.
Results: The study revealed that a total of 21 indigenous breeds were found in the study area out of which 15 breeds were under the descript category and 6 breeds under the non-descript category. In the adult category, the Kangayam breed (descript) was found to be dominant compared to other breeds, occupying 25% of the total indigenous cattle population followed by the non-descript Kongu cattle (19%). Breeds like Hallikar, Kankrej, Umblachery, Tharparkar, and Sahiwal (all descript) occupied 7%, 5%, 4%, 2%, and 2% of the total indigenous cattle population, respectively. The results were similar in the calves category (including heifers) as well, with the Kangayam breed dominating the category with 8% of the total population, followed by the Kongu cattle (7%), Kankrej (2%), Hallikar (1%), Umblachery (1%), Sahiwal (1%), and Gir (1%). The distribution was found to be more concentrated towards the settlements and lower in the individual farms outside the settlements. The reverse scenario was observed with regard to density. Both the density and distribution were found to be least along the village boundaries adjoining the hilly areas.
Conclusion: Spatial distribution and density related information can be effectively utilized in cattle management, policy-making and decision support systems.
Keywords: Cattle management, decision support system, GPS and GIS, spatial distribution, survey.