Dimensions of the Modern Pig

2018 ◽  
Vol 61 (5) ◽  
pp. 1729-1739 ◽  
Author(s):  
Isabella C. F. S. Condotta ◽  
Tami M. Brown-Brandl ◽  
John P. Stinn ◽  
Gary A. Rohrer ◽  
Jeremiah D. Davis ◽  
...  
Keyword(s):  
Animal Husbandry ◽  
Finishing Pigs ◽  
Depth Sensor ◽  
Livestock Farming ◽  
Body Depth ◽  
Depth Images ◽  
Engineering Standards ◽  
Feed Form ◽  
Current Engineering ◽  
Physical Dimensions

Abstract. It is important to know the physical dimensions of livestock to properly design confined animal housing facilities as well as feeding and drinking equipment. An engineering standard for the dimensions of livestock and poultry published by ASABE reports swine dimensions that were originally published in 1968. Changes in animal husbandry practices for swine, such as improved and new genetic lines, nutrition and feed form, and improved facility and equipment design, make it necessary to validate or update these dimensions for modern animals. The objective of this study was to evaluate dimension data for the grow-finish stages of modern pigs. A total of 150 growing-finishing pigs were sampled at five approximate ages: 4, 8, 12, 16, and 20 weeks old (30 animals at each age). The animals equally represented three commercial sire lines (Landrace, Duroc, and Yorkshire), and equal numbers of barrows and gilts were sampled. Dorsal and lateral color digital and depth images were collected using a Kinect sensor as the pigs were held individually in a stanchion or scale, and the images were analyzed by manual and automated methods. Measured physical dimensions included height from top of back to the floor, length from nose to base of the tail, width at shoulders, jowl length, front leg height, body depth from top of back to lowest point of the belly, and others. It was determined that the conformation of modern pigs has changed from the dimensions reported in current engineering standards such that modern pigs tend to be wider (15.1%) and shorter in height (-10.2%) and length (-4.9% on average) between 4 and 20 weeks of age. These updated pig dimensions will enable engineers to better design modern swine equipment and facilities. Keywords: Depth sensor, Dimensions, Image analysis, Precision livestock farming, Swine.

Effect of feed form and heat processing on the growth performance of growing and finishing pigs

2021 ◽  
Vol 245 ◽  
pp. 104430
Author(s):  
Leopoldo M. Almeida ◽  
Lucas S. Bassi ◽  
Ronan O. Santos ◽  
Uislei A.D. Orlando ◽  
Alex Maiorka ◽  
...  
Keyword(s):  
Growth Performance ◽  
Heat Processing ◽  
Finishing Pigs ◽  
Feed Form

scholarly journals RFaNet: Receptive Field-Aware Network with Finger Attention for Fingerspelling Recognition Using a Depth Sensor

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2815
Author(s):  
Shih-Hung Yang ◽  
Yao-Mao Cheng ◽  
Jyun-We Huang ◽  
Yon-Ping Chen
Keyword(s):  
Receptive Field ◽  
American Sign Language ◽  
Multiple Scales ◽  
Receptive Fields ◽  
Depth Image ◽  
Small Scale ◽  
Feature Maps ◽  
Depth Sensor ◽  
Depth Images ◽  
Effective Transfer

Automatic fingerspelling recognition tackles the communication barrier between deaf and hearing individuals. However, the accuracy of fingerspelling recognition is reduced by high intra-class variability and low inter-class variability. In the existing methods, regular convolutional kernels, which have limited receptive fields (RFs) and often cannot detect subtle discriminative details, are applied to learn features. In this study, we propose a receptive field-aware network with finger attention (RFaNet) that highlights the finger regions and builds inter-finger relations. To highlight the discriminative details of these fingers, RFaNet reweights the low-level features of the hand depth image with those of the non-forearm image and improves finger localization, even when the wrist is occluded. RFaNet captures neighboring and inter-region dependencies between fingers in high-level features. An atrous convolution procedure enlarges the RFs at multiple scales and a non-local operation computes the interactions between multi-scale feature maps, thereby facilitating the building of inter-finger relations. Thus, the representation of a sign is invariant to viewpoint changes, which are primarily responsible for intra-class variability. On an American Sign Language fingerspelling dataset, RFaNet achieved 1.77% higher classification accuracy than state-of-the-art methods. RFaNet achieved effective transfer learning when the number of labeled depth images was insufficient. The fingerspelling representation of a depth image can be effectively transferred from large- to small-scale datasets via highlighting the finger regions and building inter-finger relations, thereby reducing the requirement for expensive fingerspelling annotations.

scholarly journals REPRODUCING QUALITIES OF RAMS OF THE MOLDOVAN TYPE KARAKUL BREED

2020 ◽  
Vol 59 ◽  
pp. 92-96
Author(s):  
D. Rotari
Keyword(s):  
Sperm Count ◽  
Sperm Concentration ◽  
Animal Husbandry ◽  
Sperm Production ◽  
Livestock Farming ◽  
High Quality ◽  
Average Percentage ◽  
Reproductive Ability ◽  
First Time

Issues related to the reproduction of animals have been and remain one of the most complex and relevant problems of biology and are constantly finding a direct and effective way out into livestock farming practice. The rational use of breeding sheep as producers is limited by the lack of standard, objective methods and methods for the timely assessment of their reproductive ability. The article presents the results of evaluating the sperm production of rams-producers. For the first time, the freshly obtained sperm of rams of Moldavian type producers of the Karakul breed was evaluated using the macroscopic method - ejaculate volume, color and smell, as well as the microscopic method - motility, sperm concentration in the ejaculate, total sperm count in the ejaculate sperm movements (VAP; VSL and VCL) as well as the percentage of abnormal forms of sperm. The experiments were carried out on sheep producers grown on a pedigree farm of the experimental farm of the Moldavian Scientific and Practical Institute of Biotechnology in Animal Husbandry and Veterinary Medicine. As a result of the studies, it was found that the ejaculate volume on average was 0.99 ± 0.04 ml, motility was 0.95 ± 0.02 and sperm concentration 1.51 ± 0.14 billion/ml. The percentage of pathological forms in sperm averaged 13.72 ± 0.61, an indicator that characterizes the high quality of sperm. The average quality indicator of ejaculates obtained from ram-producers of the Moldavian type of the Karakul breed corresponds to physiological standards for the Karakul breed. The average percentage of pathological forms of sperm found in ejaculates indicates that the rams were in good conditions of feeding and keeping. According to research, we can say that the Moldovan type of Karakul rams can be successfully used to obtain high quality ejaculates suitable for freezing sperm at 196°C.

scholarly journals Formulation of chicken egg marketing strategy

2019 ◽  
Vol 6 (5) ◽  
pp. 285-302
Author(s):  
I Nyoman Padma Widyantara ◽  
I Gde Putu Sukaatmadja
Keyword(s):  
Data Analysis ◽  
Marketing Strategy ◽  
Swot Analysis ◽  
Animal Husbandry ◽  
Research Data ◽  
Livestock Farming ◽  
Analysis Techniques ◽  
Corn Prices ◽  
Older Farmers ◽  
Layer Farm

The laying chicken farming sector is an important sector because from this sector some animal protein needs for humans are met. The success of a layer farm is largely determined by marketing. Judging from the footsteps of livestock farming, it appears that older farmers have experienced several problems in animal husbandry, such as the 1997 monetary crisis, the outbreak of bird flu in late 2003, the fluctuation of corn prices in 2015. These conditions, many businesses closed farms. Even though there have been several problems with livestock, it turns out that some farms can still survive today, so it is necessary to conduct research on how to formulate an egg marketing strategy? This study took place in Karangasem Regency, Bali Province. Research data obtained from questionnaires and observations. Data analysis uses SWOT analysis techniques (strength, weakness, opportunity, and threat).

scholarly journals Worth of Artificial Intelligence in the Epoch of Modern Livestock Farming: A Review

2021 ◽  
Author(s):  
Bhavna Aharwal ◽  
Biswajit Roy ◽  
Somesh Meshram ◽  
Aayush Yadav
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Body Condition Score ◽  
Compliance Rate ◽  
Animal Husbandry ◽  
Dairy Farms ◽  
Individual Performance ◽  
Animal Origin ◽  
Livestock Farming ◽  
Measuring Device

Artificial intelligence (AI) is a human intelligence in machine encountered daily and impacts our lives. It is expected that the use of such technology in the livestock industry will automate the livestock processes and easy to manage. Biometric identification plays a key role in artificial intelligence which shows the individual identity, helps in the process of insurance and claim leakages, continue monitoring of farm animal is essential can be done with new technologies. Infra red temperature measurement camera is the newly added technology with sensor system in (AI). It is a temperature measuring device in the form of electromagnetic waves and the infrared radiation intensity. AI system consists of agent, sensor, actuators and effectors which are connected to cloud. It helps in the detection of estrus, animal diseases, body condition score and various physiological parameters using video surveillance data collection method. Artificial neural network is a branch of artificial intelligence (AI) which is based on a collection of connected units or nodes called artificial neurons and stored in a central database system. Sustainable economic future of dairy farms and to achieve 100% compliance rate. Modern dairy farms uses robotic system to deliver vaccines, machine milking and measurement of feed as per individual performance of the animal. AI analyzes the animal origin food quality traceability method from farm to fork. AI helps in the complete mechanized animal husbandry right from the birth of animal to production and food product. The future of AI in animal sector is not predictable, but advantages and daily increasing demand of AI over other sector will ensure future in animal sector as well.

scholarly journals On-farm welfare monitoring system for goats based on Internet of Things and machine learning

2020 ◽  
Vol 16 (7) ◽  
pp. 155014772094403
Author(s):  
Yuan Rao ◽  
Min Jiang ◽  
Wen Wang ◽  
Wu Zhang ◽  
Ruchuan Wang
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Animal Husbandry ◽  
Environmental Data ◽  
Software Systems ◽  
Data Detection ◽  
Livestock Farming ◽  
On Farm

Intensive animal husbandry is becoming more and more popular with the adoption of modern livestock farming technologies. In such circumstances, it is required that the welfare of animals be continuously monitored in a real-time way. To this end, this study describes one on-farm welfare monitoring system for goats, with a combination of Internet of Things and machine learning. First, the system was designed for uninterruptedly monitoring goat growth in a multifaceted and multilevel manner, by means of collecting on-farm videos and representative environmental data. Second, the monitoring hardware and software systems were presented in detail, aiming at supporting remote operation and maintenance, and convenience for further development. Third, several key approaches were put forward, including goat behavior analysis, anomaly data detection, and processing based on machine learning. Through practical deployment in the real situation, it was demonstrated that the developed system performed well and had good potential for offering real-time monitoring service for goats’ welfare, with the help of accurate environmental data and analysis of goat behavior.

scholarly journals ALT pedometer – a new sensor-aided measurement system for improvement in oestrus detection

2012 ◽  
Vol 52 (No. 1) ◽  
pp. 1-10 ◽  
Author(s):  
U. Brehme ◽  
U. Stollberg ◽  
R. Holz ◽  
T. Schleusener
Keyword(s):  
Animal Husbandry ◽  
Time Interval ◽  
Livestock Farming ◽  
Time Intervals ◽  
Measuring Systems ◽  
Non Invasive ◽  
Oestrus Cycle ◽  
Animal Data ◽  
New Type ◽  
Continuous Measuring

Without sensor-aided animal data measuring systems far fewer oestrus cycles are recognized because cycle length, oestrus duration and oestrus intensity have developed negatively at high animal performance rates. This development makes it eminently clear that observation of the mating season in the dairy cattle sector is even more important than assumed so far if the financial losses due to insufficient herd fertility are not to become a business problem. Electronic identification and measuring systems represent key technologies for progressive automation in animal husbandry in modern, future-oriented livestock farming. Suitable objective measuring systems are needed in animals husbandry to quickly and safely recognize animal illness, normal oestrus cycle, silent heat or suffering from stress. Pedometer and transponder from different companies play an important role for measuring from animals data and statements in animals health and oestrus monitoring. Modern sensors (sensors, bio sensors), increasingly non-invasive measuring and transfer methods make crucial improvements in the potential for measuring animal data. A new type of pedometer, called ALT pedometer, for three measurement parameters (activity, lying time, temperature), a real time watch and a change measuring time interval was developed. With this system it is possible to select different time intervals between 1 and 60 min for continuous measuring. The results for oestrus detection are excellent. The high correspondence between the measuring parameters activity and lying time allow a statement to be made early and safely on animal illnesses and the time of the oestrus cycle.

scholarly journals Relationship Between Sheep Farmer’s Characteristics with the Animal and Environmental Health Management Practices in Batur Village, Banjarnegara, Indonesia

2021 ◽  
Vol 33 ◽  
pp. 04010
Author(s):  
Alek Ibrahim ◽  
Deny Setyo Wibowo ◽  
I Gede Suparta Budisatria ◽  
Rini Widayanti ◽  
Wayan Tunas Artama
Keyword(s):  
Environmental Health ◽  
Significant Relationship ◽  
Informal Education ◽  
Management Practices ◽  
Health Management ◽  
Management Practice ◽  
Animal Health ◽  
Animal Husbandry ◽  
Livestock Farming ◽  
Low Level

The success of animal husbandry is supported by good animal and environmental health management practices. This study examined the correlation between the sheep farmer’s characteristics and the animal and environmental health management practices. The data collected by direct interviews with 48 respondents in Batur Village, Banjarnegara. Indonesia. The aspects of animal (exercise, grooming, wool shearing, supplement feeding, and water drinking) and environmental (sheepfold sanitation, waste processing, and waste removal) health management practices were divided into three categories, namely low, medium, and high levels. The results showed that 83.3% of respondents were in the low-level following by medium (14.6%) and high (2.1%) levels of animal health management. Furthermore, on the environmental health management shows, 27.1% of respondents were in the low level, 60.4% in the medium level, and 12.5% in the high level. There was a significant relationship between farmers’ characteristics (informal education, livestock farming experience, and the number of sheep) and animal health management practice. A significant relationship was also shown between formal education, livestock purpose, livestock experience, and number of sheep by farmers toward environmental health management practice. It may conclude that the low and medium levels of animal and environmental health management practices were dominant in Batur Village.

scholarly journals Towards Facial Expression Recognition for On-Farm Welfare Assessment in Pigs

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 847
Author(s):  
Mark F. Hansen ◽  
Emma M. Baxter ◽  
Kenneth M. D. Rutherford ◽  
Agnieszka Futro ◽  
Melvyn L. Smith ◽  
...  
Keyword(s):  
Animal Welfare ◽  
Animal Husbandry ◽  
Welfare States ◽  
Automated System ◽  
Expression Recognition ◽  
Livestock Farming ◽  
Precision Livestock Farming ◽  
Innovative Work ◽  
Leave One Out ◽  
On Farm

Animal welfare is not only an ethically important consideration in good animal husbandry but can also have a significant effect on an animal’s productivity. The aim of this paper was to show that a reduction in animal welfare, in the form of increased stress, can be identified in pigs from frontal images of the animals. We trained a convolutional neural network (CNN) using a leave-one-out design and showed that it is able to discriminate between stressed and unstressed pigs with an accuracy of >90% in unseen animals. Grad-CAM was used to identify the animal regions used, and these supported those used in manual assessments such as the Pig Grimace Scale. This innovative work paves the way for further work examining both positive and negative welfare states with the aim of developing an automated system that can be used in precision livestock farming to improve animal welfare.

scholarly journals Pork production and consumption issues from the perspective of the religion and the World's growing population

2020 ◽  
Vol 14 (1-2) ◽  
pp. 121-128
Author(s):  
Viktoria Vida ◽  
István Szűcs
Keyword(s):  
Dietary Habits ◽  
Animal Health ◽  
Animal Husbandry ◽  
Meat Production ◽  
Pork Meat ◽  
Livestock Farming ◽  
Production And Consumption ◽  
The World ◽  
Growing Population ◽  
Pork Consumption

In this article we would like to present the production and consumption issues of pork meat in the world. We intend to examine the production and consumption of pork meat from the point of view of the population. The growing population of the world requires an increasing amount of food, especially animal source of protein, ie meat. We want to examine how the world can supply the growing population with food, including (pork) meat. The growing population generates ever-increasing consumption from year to year, and may not be able to satisfy it, adequately supplying the population with food, especially (pork) meat. Livestock farming, especially extensive animal husbandry, will be less able to produce sufficient quantities of meat for the growing needs. During the analysis of food (meat) data we would like to present the difference between each continent on both the production and the consumption side. Examining the pork consumption, it should be mentioned the differences in the cultural habits, because the pork meat is the most affected in religious restrictions, regulations. The religious affiliation/identity is basically determined by the food and consumer habits, too. Due to the differences in dietary habits and religious culture, we think that the consumption of pork can be highly variable in the world and from country to country as well. In general, we would like to answer questions about how the world (pork) meat production is going, is the meat consumed in the countries where it is produced (export – import issues), what are the factors that influence (pork) meat consumption (culture and religion impact on pork consumption, animal health issues), and is there enough (pork) meat for the world's growing population. JEL code: P46, Q18, Q56

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