ABSTRACT
The management of livestock in extensive production systems may be challenging, especially in large areas. Using Unmanned Aerial Vehicles (UAVs) to collect images from the area of interest is quickly becoming a viable alternative, but suitable algorithms for extraction of relevant information from the images are still rare. This article proposes a method for counting cattle which combines a deep learning model for rough animal location, color space manipulation to increase contrast between animals and background, mathematical morphology to isolate the animals and infer the number of individuals in clustered groups, and image matching to take into account image overlap. Using Nelore and Canchim breeds as a case study, the proposed approach yields accuracies over 90% under a wide variety of conditions and backgrounds.
Subject(s)
Aircraft , Neural Networks, Computer , Animals , Cattle , Image Processing, Computer-AssistedABSTRACT
Knowledge of thermoregulatory responses in taurine cattle contribute to identification of animals most adapted to heat and productive when raised under Brazilian climate. The objectives were to verify the morphological and physiological responses related to adaptation to heat of taurine breeds raised under in Brazilian meteorological conditions in different seasons of the year and day periods, and to detect differences within and between breeds to know breed is most adapted. Measurements were made of 74 young bulls (nâ¯=â¯31 Angus; nâ¯=â¯43 Simmental) for the morphological traits: hair length (HL), number of hairs (NH), and coat thickness (CT); and for the physiological traits: respiratory rate (RR) and hair coat surface temperature (ST). The temperature-humidity index (THI) was calculated. The data were subjected to analyses of variance, cluster analysis, and principal component analysis (PCA). The THI (<74) indicates thermal comfort. In the winter, the HL and CT higher than in the spring season (Pâ¯<â¯0.0001) in both breeds. Angus exhibited higher HL and CT (Pâ¯<â¯0.0001). Within each breed, the animals differed from one another for HL (Pâ¯<â¯0.0005). In the spring, CT was similar between the breeds, differing only in the winter season. Angus had higher values (Pâ¯<â¯0.0005) of RR and lower values (Pâ¯<â¯0.0001) of ST. Both breeds had higher (Pâ¯<â¯0.0001) RR and ST in the afternoon. PCA showed that NH and HL better explained variation in adaptation. In general, the breeds have similar morphological responses in the hottest months, but have different physiological responses; Simmental proves to be more physiologically resistant. The afternoon was more stressful than the morning, even though the animals were in a thermal comfort zone. Measuring traits related to hair coat is sufficient for effective evaluation of adaptation, and the season affects the morphological and physiological traits of taurine cattle raised.
Subject(s)
Body Temperature Regulation , Cattle/physiology , Thermotolerance , Animal Fur , Animals , Brazil , Cattle/genetics , Hot Temperature , Male , Respiratory Rate , Tropical ClimateABSTRACT
The term allergy has been misinterpreted, although this condition may affect more than half of the population in some countries. This study aimed to evaluate how health professionals living in the city of Sao Paulo, Brazil, understand the term allergy. Two questions were asked to participants: 1) What is an allergy? and 2) Have you ever developed or seen anyone developing allergies? To what? Data were obtained by interviewing more than 1,000 volunteers. After exclusion criteria were applied, 886 answers were analyzed, 606 from health professionals and 280 from individuals from other fields. The texts were submitted to lexical analysis and word cloud generation. As an additional control, a lexical analysis of a reference text defining the term allergy was used. Results revealed that this method yielded good knowledge of how allergy is understood and that health professionals failed to define the term with accuracy.
O termo alergia tem sido mal interpretado, embora a doença possa acometer até metade da população em alguns países. Este trabalho objetivou avaliar a compreensão desse termo por profissionais da área da saúde que residem na cidade de São Paulo. Duas questões foram feitas aos participantes: (1) O que é alergia? e (2) Você já desenvolveu ou já viu alguém desenvolvendo uma alergia? Contra o quê? Os dados foram obtidos após entrevistas com mais de 1.000 voluntários. Após a aplicação dos critérios de exclusão, 886 respostas foram consideradas, sendo 606 de profissionais atuantes na área da saúde e 280 de profissionais de outras áreas. Os textos foram submetidos a análise lexical e geração de nuvem de palavras. Como controle adicional, foi utilizada a análise lexical de um texto de referência que define o termo alergia. Os resultados mostraram que a metodologia de análise gerou um bom conhecimento sobre a compreensão do termo alergia e que os profissionais não conseguiram descrever o significado desse termo com precisão.
