C. Karthikeyan, S.R. Shri Rangasami, S. A. Kumar, R. Ajaykumar, K. Harishankar, M. Thirunavukkarasu, R. Karthika
{"title":"Digital Revolution in Livestock Farming: Empowering Indian Farmers with TNAU Cattle Expert System and User Feedback Insights","authors":"C. Karthikeyan, S.R. Shri Rangasami, S. A. Kumar, R. Ajaykumar, K. Harishankar, M. Thirunavukkarasu, R. Karthika","doi":"10.18805/ijar.b-5383","DOIUrl":null,"url":null,"abstract":"Background: Cattle husbandry in India is a cornerstone of the agricultural sector, supporting the livelihoods of millions of farmers. However, the industry grapples with challenges such as disease outbreaks, low productivity and limited access to veterinary services. The TNAU Cattle Expert System Application represents a digital innovation aimed at addressing these challenges by providing farmers with real-time guidance on various aspects of cattle management. Methods: The study was meticulously conducted in Tamil Nadu over the years of both 2022 and 2023. Feedback was systematically collected from 523 users of the TNAU Cattle Expert System Application. Text analysis tools were employed to categorize sentiments as positive, negative or neutral using Azure machine learing sotware in MS Excel. Log Regression was carried out to identify the variance of feedback sentiments followed by cluster analysis through jamovi further classified feedback into distinct groups, revealing patterns in user engagement. Result: Positive feedback praised the application’s detailed information on cattle protection and disease precautions, particularly for FMD, BRD, Mastitis, Johne’s disease, Brucellosis, Clostridia diseases and BVD. “Delicate” users (38.54%) gave appreciative feedback, “Arbitrator” users (26.04%) offered diverse opinions, “Eloquent” users (18.75%) expressed positive sentiments, while “Criticizer” (12.50%) and “Harsh stringer” users (4.17%) provided critical insights.\n","PeriodicalId":507727,"journal":{"name":"Indian Journal of Animal Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Animal Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18805/ijar.b-5383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Cattle husbandry in India is a cornerstone of the agricultural sector, supporting the livelihoods of millions of farmers. However, the industry grapples with challenges such as disease outbreaks, low productivity and limited access to veterinary services. The TNAU Cattle Expert System Application represents a digital innovation aimed at addressing these challenges by providing farmers with real-time guidance on various aspects of cattle management. Methods: The study was meticulously conducted in Tamil Nadu over the years of both 2022 and 2023. Feedback was systematically collected from 523 users of the TNAU Cattle Expert System Application. Text analysis tools were employed to categorize sentiments as positive, negative or neutral using Azure machine learing sotware in MS Excel. Log Regression was carried out to identify the variance of feedback sentiments followed by cluster analysis through jamovi further classified feedback into distinct groups, revealing patterns in user engagement. Result: Positive feedback praised the application’s detailed information on cattle protection and disease precautions, particularly for FMD, BRD, Mastitis, Johne’s disease, Brucellosis, Clostridia diseases and BVD. “Delicate” users (38.54%) gave appreciative feedback, “Arbitrator” users (26.04%) offered diverse opinions, “Eloquent” users (18.75%) expressed positive sentiments, while “Criticizer” (12.50%) and “Harsh stringer” users (4.17%) provided critical insights.