Awareness and adoption of farm biosecurity practices in commercial dairy, pig and poultry farms of Uttar Pradesh (India).

India's livestock sector has been facing significant losses due to episodes of disease outbreaks since time immemorial. Hence, biosecurity measures are very important to maintain and improve animal health along with prevention of disease outbreak. Keeping these facts into consideration, the study was proposed with an objective to assess the existing biosecurity practices adopted by the commercial dairy, pig and poultry farms. The current study was undertaken in the state of Uttar Pradesh as it is the leading state in milk and meat production. A total of 120 farmers were selected randomly including 40 each practicing commercial dairy, pig and poultry farming. An ex-post facto research methodology was used with face-to-face interview and observation to collect data. The biosecurity practices were assessed under seven dimensions such as, location and design of farm, restricted access, isolation and quarantine, cleaning and disinfection, management of feed and water, disposal of carcass, manure and waste, and health management. Results elicited that about 50% of the farmers had medium level of adoption who adopted 18-34 practices out of 51 practices. The average overall adoption score was 34.17 out of 51 (67%) which makes an overall adoption gap of 33%. Maximum adoption gap was seen in case of restricted access (43%) whereas minimum gap in adoption was seen in case of management of feed and water (27%). Pig and poultry farmers showed significantly higher biosecurity measures than dairy farmers (p < 0.05). The more significant contributors to the adoption of biosecurity measures were the level of knowledge of the farmers (p < 0.01). Other factors such as education, income, herd/flock size, Information and Communication Technology utilization, number of trainings also had a significant contribution (p < 0.05) in actual implementation of biosecurity. Hence, better understanding of these measures among the farmers must be ensured by hands on training along with proper demonstration of various procedures involved in maintaining farm biosecurity is need of the hour.

Predicting opinion using deep learning: From burning to sustainable management of organic waste in Indian State of Punjab.

In winter season, the burning of crop residues for ease of sowing the next crop, along with industrial emissions and vehicular pollution leads to settling of a thick layer of smog in northern part of India. Therefore, to understand the opinion of farmers regarding sustainable management of organic waste, the present study was conducted in Ludhiana district of Indian state of Punjab. An ex post facto research design was used and a total of 800 dairy farmers having significant crop area were selected randomly for the study, grouped equally as small and large dairy farmers. Results revealed that majority of farmers had a highly favourable opinion regarding organic waste management due to the fact that they were aware of the ill-effects of undesirable practices like crop residue burning. Further, to predict the farmers' opinion and the effect of independent variables on farmers' opinion, a multi-layer perceptron feed-forward deep neural network was developed with mean squared error of 0.036 and 0.137 for validation and training data sets respectively, marking a novel approach of analysing farmers' behaviour. The neural network highlighted that with increase in the magnitude of input variables, namely, education, experience in dairying, information source utilisation, knowledge regarding organic waste management, etc., the farmers' opinion regarding sustainable waste management increases. The study concluded with the impression that cognitive processes like education, information and knowledge play a significant role in forming the opinion of the farmers. Therefore, efforts focusing on enhancing cognition should be made for sustainable management of organic waste.