52 research outputs found

    Research on Leg Tags in Goat Breeding for Electronic Identification Purposes

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    This study is on the fall and readability of electronic leg tags, plastic ear tags and electronic ear tags used in 2 flocks of goats. Honamlı and Turkish Hair goat flocks were followed for 4 months and bred under different conditions. While the flock of Honamli goats went to pasture every day, the Turkish Hair goats remained indoors. It was found that the leg tags fell from 5 goats in the Honamli flock (96%), while none fell in the Turkish Hair flock. Plastic ear tags attached to goats were found to have fallen from 11 goats (92%) in the Honamli flock and 7 goats from Turkish Hair goat flock (90%). The readability of electronic leg tags, plastic ear tags and electronic ear tags used in goats for 4 months was determined as 100%. It is useful to carry out research on the use of electronic leg tags as an alternative option for goat breeding for identification purposes, with different trial groups formed on animals of different ages and different legs

    Research on leg tags in goat breeding for electronic identification purposes

    Get PDF
    This study is on the fall and readability of electronic leg tags, plastic ear tags and electronic ear tags used in 2 flocks of goats. Honamlı and Turkish Hair goat flocks were followed for 4 months and bred under different conditions. While the flock of Honamli goats went to pasture every day, the Turkish Hair goats remained indoors. It was found that the leg tags fell from 5 goats in the Honamli flock (96%), while none fell in the Turkish Hair flock. Plastic ear tags attached to goats were found to have fallen from 11 goats (92%) in the Honamli flock and 7 goats from Turkish Hair goat flock (90%). The readability of electronic leg tags, plastic ear tags and electronic ear tags used in goats for 4 months was determined as 100%. It is useful to carry out research on the use of electronic leg tags as an alternative option for goat breeding for identification purposes, with different trial groups formed on animals of different ages and different legs

    Review on agriculture and rural development : X. évf. (2021) 1-2. sz.

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    Comparison of different identification systems in Iberian ibex (Capra pyrenaica) for the control of wild populations and the traceability of game products

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    The efficiency of different visual and electronic identification systems was studied in 2 fenced populations of Iberian ibexes (Capra pyrenaica) in Tarragona and Granada (Spain), using a total of 58 individuals each of them identified simultaneously with visual ear tags or collars and other electronic devices. Electronic devices were injectable transponders of 2 sizes: small-sized (12-12.2 mm, n = 47), injected intramuscularly between the escapuli, and large-sized (32 mm), injected subcutaneously in the left armpit (n = 58) or intraperitoneally in the belly (n = 44), and ceramic rumen boluses (n = 30) administered orally and retained in the forestomaches. The study lasted 1.6 to 5 years according to devices. Except ear tags (<50%), all devices were highly retained (94 to 100%), although readability was variable and lower than retention rate (96 to 99%). Main losses were observed in large-sized transponders immediately after injection, while small-sized transponder were difficult to read because of migration. Rumen boluses showed the greatest retention rate (100%) and readability (98.6%), being applied safely in ibexes greater than 28 kg. Retention was predicted at the long term (10 yr) and using an interspecific logistic equation for ruminants (R2 = 0.96). Rumen boluses were also safe for predators, scavengers and game consumers and recommended for traceability purposes.Se ha estudiado la eficiencia de diferentes sistemas de identificación visual y electrónica en 2 poblaciones cautivas de cabra montés (Capra pyrenaica) en Tarragona y Granada (España), en un total de 58 individuos, cada uno de ellos identificados simultáneamente con crotales y collares visuales y otros dispositivos electrónicos. Los dispositivos electrónicos consistieron en transpondedores inyectables de dos tamaños: pequeños (12-12.2 mm, n = 47), inyectados intramuscularmente entre las escápulas, y grandes (32 mm), inyectados subcutáneamente en la axila izquierda (n = 58) o intraperitonealmente en el abdomen (n = 44), y bolos ruminales cerámicos (n = 30) administrados oralmente y retenidos en los preestómagos. El estudio duró de 1.6 a 5 años según los dispositivos. Excepto los crotales auriculares (<50%), todos los dispositivos presentaron elevadas tasas de retención (94 a 100%), aunque la capacidad de lectura fue variable e inferior a la retención (96 a 99%). La mayoría de las pérdidas se observaron en los transpondedores grandes inmediatamente después de la inyección, mientras que los pequeños fueron difíciles de leer a causa de la migración. Los bolos ruminales mostraron la mayor tasa de retención (100%) y legibilidad (98.6%), con una aplicación segura en cabras mayores de 28 kg. La retención de los bolos fue capaz de ser predicha a largo plazo (10 años) y mediante una ecuación logística interespecífica para rumiantes (R2 = 0.96). Los bolos ruminales fueron seguros para depredadores y carroñeros, así como también para los consumidores de carne de caza, por lo que se recomienda su uso para trazabilidad

    Current Situation and Future Prospects of the US Goat Industry

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    Abstract The current demand for goat meat in the US outstrips domestic supply. There is great potential for industry growth in the meat and dairy sectors. Whereas fiber prices have improved, loss of animals and market resources, labor costs for shearing, and lack of animal genetic resources prevent growth in the short term. As producers age, there is opportunity for new producers to enter the marketplace. Significant challenges exist, like access to local markets and abattoirs, dewormer resistant parasites, and feed costs. Establishing goat feedlots can increase meat supply and industry commercialization. Technologies used for cattle will be expanded for use in goats with interconnected sensors collecting health and production data. The field of genetic improvement will change from current production testing to identifying superior animals at an early age using DNA analysis. A quality assurance program is needed to address animal welfare issues and promote the consumption of domestic products to consumers. Keywords: Meat Goat Industry, Dairy Goat Industry, Goat Industry, Goat Industry Statu

    18th Wellmann International Scientific Conference : book of abstracts

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    Up from the Ground: Blogging the Farm and Farming the Blog

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    Up from the Ground: Blogging the Farm and Farming the Blog was written in the form of blog posts from May 2009 until March 2010. The blog chronicled successes and failures in the transition from city life to organic agriculture, as well as explored the nature of the blog form. The thesis reads in reverse chronological order, as a blog would. It was and remains an experiment in form, voice and technique

    SVMAUD: Using textual information to predict the audience level of written works using support vector machines

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    Information retrieval systems should seek to match resources with the reading ability of the individual user; similarly, an author must choose vocabulary and sentence structures appropriate for his or her audience. Traditional readability formulas, including the popular Flesch-Kincaid Reading Age and the Dale-Chall Reading Ease Score, rely on numerical representations of text characteristics, including syllable counts and sentence lengths, to suggest audience level of resources. However, the author’s chosen vocabulary, sentence structure, and even the page formatting can alter the predicted audience level by several levels, especially in the case of digital library resources. For these reasons, the performance of readability formulas when predicting the audience level of digital library resources is very low. Rather than relying on these inputs, machine learning methods, including cosine, Naïve Bayes, and Support Vector Machines (SVM), can suggest the grade level of an essay based on the vocabulary chosen by the author. The audience level prediction and essay grading problems share the same inputs, expert-labeled documents, and outputs, a numerical score representing quality or audience level. After a human expert labels a representative sample of resources with audience level, the proposed SVM-based audience level prediction program, SVMAUD, constructs a vocabulary for each audience level; then, the text in an unlabeled resource is compared with this predefined vocabulary to suggest the most appropriate audience level. Two readability formulas and four machine learning programs are evaluated with respect to predicting human-expert entered audience levels based on the text contained in an unlabeled resource. In a collection containing 10,238 expert-labeled HTML-based digital library resources, the Flesch-Kincaid Reading Age and the Dale-Chall Reading Ease Score predict the specific audience level with F-measures of 0.10 and 0.05, respectively. Conversely, cosine, Naïve Bayes, the Collins-Thompson and Callan model, and SVMAUD improve these F-measures to 0.57, 0.61, 0.68, and 0.78, respectively. When a term’s weight is adjusted based on the HTML tag in which it occurs, the specific audience level prediction performance of cosine, Naïve Bayes, the Collins-Thompson and Callan method, and SVMAUD improves to 0.68, 0.70, 0.75, and 0.84, respectively. When title, keyword, and abstract metadata is used for training, cosine, Naïve Bayes, the Collins-Thompson and Callan model, and SVMAUD specific audience level prediction F-measures are found to be 0.61, 0.68, 0.75, and 0.86, respectively. When cosine, Naïve Bayes, the Collins-Thompson and Callan method, and SVMAUD are trained and tested using resources from a single subject category, the specific audience level prediction F- measure performance improves to 0.63, 0.70, 0.77, and 0.87, respectively. SVMAUD experiences the highest audience level prediction performance among all methods under evaluation in this study. After SVMAUD is properly trained, it can be used to predict the audience level of any written work
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