Letters In Animal Biology

Farm animal welfare as a key element of sustainable food production

Muhammad Adil Sardar, Muhammad Irtaza Ali Khan, Muhammad Salman, Imran Ullah — Mon, 04 Sep 2023 00:00:00 +0000

This comprehensive review article explores the critical relationship between farm animal welfare and sustainable food production, addressing the growing awareness of the ethical, environmental, and economic implications of animal treatment in agriculture. Prioritizing farm animal welfare is not only a moral imperative but also a key element in achieving a truly sustainable and resilient food system. The study examines the challenges and opportunities associated with enhancing animal welfare practices and their profound impact on sustainability. It analyzes potential benefits and barriers for farmers, consumers, and society at large in adopting more ethical and humane food production practices. By addressing these issues, the article aims to foster a more sustainable food production system that promotes animal welfare, environmental conservation, and social responsibility. Emphasizing the importance of ethical treatment, the review discusses improved animal health and productivity, the environmental impact, consumer perspectives, and successful case studies that highlight the transformative potential of embracing farm animal welfare in shaping a compassionate, resilient, and sustainable food industry.

The role of veterinary research in human health promotion in South Asia

Vishnu Prasad Santhosh Pillai, Sneha Aji Reji — Fri, 29 Sep 2023 00:00:00 +0000

Veterinary science research has a leading role in promoting human health, in a One Health approach. In this review the public health challenges in the South Asian region were analyzed and the role of the veterinary sector in addressing them were highlighted. Livestock and livestock products research is integral to achieving food security and beating malnutrition. The veterinary public health domain encompassing zoonoses research, food safety, environmental health, and antimicrobial resistance research, is worthy of attention as it integrates animal and human health. Biomedical research is an exciting field that utilizes veterinary expertise to understand human diseases. Food security and safety, antimicrobial resistance, environmental pollution and climate change, and insufficient funds were described as major challenges faced by South Asian countries. Impressive prospects of veterinary science research to address these challenges were highlighted. Increasing awareness, better allocation of funds and One Health approach were enumerated as some recommendations to overcome the challenges. From a One Health perspective, veterinary science research has a notable role in addressing major public health issues in South Asian countries. Increased surveillance and optimized research could promote better public health and support economic growth in the South Asian region.

Comparison of Fluorescence Polarization Assay with Rose Bengal Plate Agglutination test and Competitive Enzyme-Linked Immunosorbent assay for bovine brucellosis in Tanzania

Godwin Minga, Proscovia Kagaruki, Grace Banda, Zacharia Makondo, Henry Magwisha — Wed, 20 Sep 2023 00:00:00 +0000

Brucella are Gram-negative, facultative, intracellular bacterial species with B. abortus, B. melitensis, and B. suis carrying the smooth-lipopolysaccharide antigen. Accurate diagnostic results of brucellosis are needed for its control and eradication, however, they are primarily based on the serological testing of brucellosis in animals. The Rose Bengal Plate Agglutination Test (RBPT) and competitive Enzyme-Linked Immunosorbent Assay (c-ELISA) are the most commonly used tests for making such diagnosis. The use of Fluorescence Polarization Assay (FPA) in Tanzania is still in nascent stage. The purpose of this study was to compare RBPT, c- ELISA, and FPA in the diagnosis of bovine brucellosis. A total of 75 serum samples from cattle that were infected with Brucella in Kagera region were obtained. The FPA showed 90% (68 samples) prevalence, RBPT revealed 93% (70 samples) prevalence, and c-ELISA revealed 81% (61 samples) prevalence of brucellosis in the farm. The RBPT test has shown an inability to distinguish antibodies from cross-reacting organisms compared to the FPA test, while the c- ELISA was unable to pick a positive sample compared to the FPA test. FPA is very quick (5 min per sample), does not require specialized staff, and may be performed under field conditions. Therefore, FPA has a potential to overcome limitations in the detection of bovine brucellosis and can be used as a confirmatory test.

Entrepreneurship potential of chicken nuggets and meat balls in Puducherry

Mon, 04 Sep 2023 00:00:00 +0000

Poultry industry is one of the important segments of livestock sector in India. The growth rate of poultry production in India is showing an upward trend as per the latest 20th livestock census of India. In this study manufacturing of meat products was undertaken over a period of four months in Department of Livestock Product Technology, Rajiv Gandhi Institute of Veterinary Education and Research (RIVER), Puducherry. During this project, chicken nuggets were manufactured and marketed in and around Puducherry region. The net profit of project was around 55.4 percentage. The data obtained in the current study may be useful as a reference for future scientific chicken nuggets production as potential entrepreneurship opportunity.

A comparative study of ensemble machine learning algorithms for brucellosis disease prediction

Tue, 03 Oct 2023 00:00:00 +0000

Brucellosis, caused by Brucella spp., is a global public health concern, particularly in underdeveloped regions. Cattle, predominantly infected with B. abortus, encounter reproductive challenges, reduced productivity, and fertility issues. Effective control measures, including serological tests like iELISA (indirect Enzyme-linked Immunosorbent Assay) are vital. This research harnesses machine learning techniques, encompassing AdaBoostM1, Vote, Bagging, and LogitBoost, to forecast Brucella infection in cattle, utilizing comprehensive data sourced from Qazvin, Iran. Detailed model descriptions are provided, highlighting AdaBoostM1 as the optimal choice, boasting a robust 75% correlation, low RMSE (Route Mean Square Error), MAE (Mean Absolute Error), and a commendable Kappa Statistics score of 0.4965. Ensemble machine learning demonstrates significant potential in Brucellosis prediction, adept at handling intricate datasets, and enhancing predictive accuracy. AdaBoostM1 stands out as the preferred model, offering valuable insights for Brucellosis prediction and contributing to the enhancement of disease control strategies.