Economic Advantages of Individual Animal Identification in Fattening Pigs

Thölke, Henrich; Wolf, Petra

doi:10.3390/agriculture12020126

Cited by 4 publications

(3 citation statements)

References 22 publications

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“…A number of researchers are of the opinion that an older slaughter age of pigs results in decreased daily gains and increased feed consumption per 1 kg of gain [Latorre et al 2003, Virgili et al 2003, Tyra 2012, Borah et al 2016, Bocian et al 2017, Thölke and Wolf 2022. In the case of non-castrated animals, attention should also be paid to the quality of the obtained slaughter material.…”

Section: Discussionmentioning

confidence: 99%

Growth rate and carcass quality of hybrid fatteners depending on the age of slaughter

Jankowiak,

Cebulska,

Novotni-Dankó

et al. 2023

Acta Sci. Pol. Zootech.

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The aim of the study was to evaluate the effect of age on the fattening performance qualities and carcasses slaughter value. The assessment covered 99 crossbred pigs (Danish Landrace × Yorkshire × Duroc). The animals were subdivided into two groups with different slaughter age (159 and 169 days). The assessment covered fattening and post-slaughter characteristics. It has been proven that, at slaughter, younger crossbred pigs showed a higher growth rate than older pigs (P < 0.01). In addition, the former were fattened for a shorter period and consumed less feed across the entire fattening period as well as per 1 kg of gain. Carcasses of pigs older at slaughter were characterised by greater warm carcass weight and height of the loin muscle relative to group I carcasses (P < 0.01). Slaughter value of fatteners from both groups studied was very high, as each of the carcasses under assessment was classified under the most valuable categories S, E, and U.

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Section: Discussionmentioning

confidence: 99%

Growth rate and carcass quality of hybrid fatteners depending on the age of slaughter

Jankowiak,

Cebulska,

Novotni-Dankó

et al. 2023

Acta Sci. Pol. Zootech.

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“…Animal Behavior Monitoring [94], [67], [41], [101], [19], [53], [42], [33], [96], [92], [63], [7], [84], [32], [93], [64], [102], [86], [44], [105], [104], [6], [80], [75], [30], [82], [108], [109], [31], [34] Livestock Management [51], [57], [89], [90], [103], [69], [52], [95], [91], [73], [35], [38], [21], [48], [37], [61], [107], [39], [8], [106], [76], …”

Section: Types Of Problems Publication Referencementioning

confidence: 99%

RFID Technology for Animal Tracking: A Survey

Pereira,

Araújo,

Silva

et al. 2023

IEEE J. Radio Freq. Identif.

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The application of animal tracking holds significant importance across diverse economic domains, encompassing sectors including livestock husbandry, agricultural practices, and the conservation of wildlife populations. It aims to track and understand animal behavior, movement patterns, and health status. The predominant use of RFID technology is observed within the domains of logistics, localization, and the tracking of goods. Notably, the application of this technology in the field of animal tracking has experienced a significant surge in popularity in recent years. This paper conducts a systematic literature review focused on understanding how RFID technology is being applied in the field of animal tracking. We have conducted a stateof-the-art research regarding animal tracking solutions in the scientific literature and patents. We have analyzed these solutions targeting which animals are being tracked, which problems are addressed, operating frequency, and whether other technologies are combined with RFID for animal tracking purposes. Among the categories of problems addressed, livestock management emerged as the main area, followed by animal tracking and traceability. Mammals, especially cattle, are the most common type of animal monitored. Considering RFID technology, passive UHF tags appeared more often. Moreover, many works also employed cameras and GPS together with RFID. Finally, this work can significantly contribute to this field by systematically presenting a state-of-the-art application of RFID for animal tracking.

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“…The individual identification of different animals is a prerequisite for obtaining accurate body condition data of different individuals, which can enable precise control such as disease monitoring, precise feeding, and personalized management [2], and also help to improve animal welfare [3]. Individual identification is also the first step to achieve traceability technology in the animal product supply chain [4], and can provide a more accurate reference for animal insurance [5].…”

Section: Introductionmentioning

confidence: 99%

Individual Pig Identification Using Back Surface Point Clouds in 3D Vision

Zhou

Xie

2023

Sensors

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The individual identification of pigs is the basis for precision livestock farming (PLF), which can provide prerequisites for personalized feeding, disease monitoring, growth condition monitoring and behavior identification. Pig face recognition has the problem that pig face samples are difficult to collect and images are easily affected by the environment and body dirt. Due to this problem, we proposed a method for individual pig identification using three-dimension (3D) point clouds of the pig’s back surface. Firstly, a point cloud segmentation model based on the PointNet++ algorithm is established to segment the pig’s back point clouds from the complex background and use it as the input for individual recognition. Then, an individual pig recognition model based on the improved PointNet++LGG algorithm was constructed by increasing the adaptive global sampling radius, deepening the network structure and increasing the number of features to extract higher-dimensional features for accurate recognition of different individuals with similar body sizes. In total, 10,574 3D point cloud images of ten pigs were collected to construct the dataset. The experimental results showed that the accuracy of the individual pig identification model based on the PointNet++LGG algorithm reached 95.26%, which was 2.18%, 16.76% and 17.19% higher compared with the PointNet model, PointNet++SSG model and MSG model, respectively. Individual pig identification based on 3D point clouds of the back surface is effective. This approach is easy to integrate with functions such as body condition assessment and behavior recognition, and is conducive to the development of precision livestock farming.

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Economic Advantages of Individual Animal Identification in Fattening Pigs

Cited by 4 publications

References 22 publications

Growth rate and carcass quality of hybrid fatteners depending on the age of slaughter

Growth rate and carcass quality of hybrid fatteners depending on the age of slaughter

RFID Technology for Animal Tracking: A Survey

Individual Pig Identification Using Back Surface Point Clouds in 3D Vision

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