Gait and force analysis of provoked pig gait on clean and fouled concrete surfaces

Wachenfelt, Hans von; Pinzke, Stefan; Nilsson, Christer

doi:10.1016/j.biosystemseng.2009.08.008

Cited by 17 publications

(14 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This could be explained by the use of clay, which had to be slightly wet to produce a good footprint and may have appeared slippery to the sows. Indeed, studies on the gait of pigs walking on different types of floor showed that pigs shortened their stride length and speed when they walked on a slippery surface (von Wachenfelt et al, 2009). Therefore, the use of a slippery surface in the present study may have prevented the discrimination of lame sows from non-lame ones.…”

Section: Discussionmentioning

confidence: 84%

“…It is studied using video recording where the subject's body is schematised with markers. Both of these methods have been used in pigs to evaluate gait and study the impact of floor friction level (von Wachenfelt et al, 2009), but they have never been used to quantify lameness in sows yet. Footprint analysis using high-resolution floor mat to record foot pressure has also been used to analyse gait in pigs, to compare different floor friction and identify which region of the claw is the most subject to stress (Carvalho et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of lameness in sows using gait, footprints, postural behaviour and foot lesion analysis

Gregoire

Bergeron

D’Allaire

et al. 2013

Animal

View full text Add to dashboard Cite

Lameness in sows has an economic impact on pig production and is a major welfare concern. The aim of the present project was to develop methods to evaluate and quantify lameness in breeding sows. Five methods to study lameness were compared between themselves and with visual gait scoring used as a reference: footprint analysis, kinematics, accelerometers, lying-tostanding transition and foot lesion observation. Fifty sows of various parities and stages of gestation were selected using visual gait scoring and distributed into three groups: lame (L), mildly lame (ML) and non-lame (NL). They were then tested using each method. Kinematics showed that L sows had a lower walking speed than NL sows (L: 0.83 6 0.04, NL: 0.96 6 0.03 m/s; P , 0.05), a shorter stride length than ML sows (L: 93.0 6 2.6, ML: 101.2 6 1.5 cm; P , 0.05) and a longer stance time than ML and NL sows (L: 0.83 6 0.03, ML: 0.70 6 0.03, NL: 0.69 6 0.02 s; P , 0.01). Accelerometer measurements revealed that L sows spent less time standing over a 24-h period (L: 6.3 6 1.3, ML: 13.7 6 2.4, NL: 14.5 6 2.4%; P , 0.01), lay down earlier after feeding (L: 33.4 6 4.6, ML: 41.7 6 3.1, NL: 48.6 6 2.9 min; P , 0.05) and tended to step more often during the hour following feeding (L: 10.1 6 2.0, ML: 6.1 6 0.5, NL: 5.4 6 0.4 step/min standing; P 5 0.06) than NL sows, with the ML sows having intermediate values. Visual observation of back posture showed that 64% of L sows had an arched back, compared with only 14% in NL sows (P 5 0.02). Finally, footprint analysis and observation of lying-to-standing transition and foot lesions were not successful in detecting significant differences between L, ML and NL sows. In conclusion, several quantitative variables obtained from kinematics and accelerometers proved to be successful in identifying reliable indicators of lameness in sows. Further work is needed to relate these indicators with causes of lameness and to develop methods that can be implemented on the farm.

show abstract

Section: Discussionmentioning

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Assessment of lameness in sows using gait, footprints, postural behaviour and foot lesion analysis

Gregoire

Bergeron

D’Allaire

et al. 2013

Animal

View full text Add to dashboard Cite

show abstract

“…This may be expected to be worse in on-farm situations where individual pig assessment is impeded within a pen with other pigs. Previous quantitative studies have investigated the instantaneous gait adjustment of pigs on slippery and nonslippery surfaces by means of gait analysis with force plates and 2D video kinematics (Thorup et al, 2008;von Wachenfelt et al, 2009). However, there appears to be no longitudinal study quantifying the gait and gait variability of pigs exposed to different commercial floor types for an extended part of their development.…”

Section: Introductionmentioning

confidence: 99%

Longitudinal gait development and variability of growing pigs reared on three different floor types

Stavrakakis

Guy

Warlow

et al. 2014

Animal

View full text Add to dashboard Cite

Biomechanical investigation into locomotor pathology in commercial pigs is lacking despite this being a major concern for the industry. Different floor types are used in modern, intensive pig production systems at different stages of the pigs' production cycle. The general perception holds that slatted and/or hard solid concrete surfaces are inferior to soft straw-covered floors regarding healthy musculoskeletal development. Previous studies have compared pigs housed on different floor types using clinical, subjective assessment of leg weakness and lameness. However, reliability studies generally report a low repeatability of clinical lameness scoring. The objective of this study was to quantitatively assess the long-term effect of pen floors, reflected in the biomechanical gait characteristics and associated welfare of the pigs. A cohort of 24 pigs housed on one of three different floor types was followed from 37 to 90 kg average liveweight, with gait analysis (motion capture) starting at 63 kg. The three floor types were fully slatted concrete, partly slatted concrete and deep straw-bedded surfaces, all located within the same building. Pigs underwent five repeated camera-based motion captures, 7 to 10 days apart, during which 3D coordinate data of reflective skin markers attached to leg anatomical landmarks were collected. Pigs walked on the same solid concrete walkway during captures. One-way ANOVA and repeated measures ANOVA were used to analyse the gait data. Results revealed changes over time in the spatiotemporal gait pattern which were similar in magnitude and direction for the pigs from different floor types. Significant increases in elbow joint flexion with age were observed in all pigs (P ⩽ 0.050; +6°). There were few differences between floor groups, except for the step-to-stride ratio in the hind legs being more irregular in pigs housed on partly slatted floors (P = 0.012; 3.6 times higher s.d.) compared with those on 5 to 10 cm straw-bedding in all pen areas. As the level of clinical problems was generally low in this cohort, it may be that floors elicit problems only when there is a primary predisposing factor increasing weakness in susceptible tissues.

show abstract

“…Selection of proper sampling time intervals for accurate AI measurement of certain animal species should consider the velocities of both continuous movements (e.g., walking and running) and discrete movements (e.g., pecking, touching, smelling, dashing, etc.). A sampling time interval of 0.03 s has been used for cows [ 19 , 21 ], 0.04 s for pigs [ 20 , 22 ], and 0.2 s and 0.3 s for poultry [ 10 , 12 , 23 ].…”

Section: Discussionmentioning

confidence: 99%

Accuracy of Broiler Activity Index as Affected by Sampling Time Interval

Yang

Zhao

Tabler

2020

Animals

View full text Add to dashboard Cite

Different time intervals between consecutive images have been used to determine broiler activity index (AI). However, the accuracy of broiler AI as affected by sampling time interval remains to be explored. The objective of this study was to investigate the effect of the sampling time interval (0.04, 0.2, 1, 10, 60, and 300 s) on the accuracy of broiler AI at different bird ages (1–7 weeks), locations (feeder, drinker, and open areas) and times of day (06:00–07:00 h, 12:00–13:00 h, and 18:00–19:00 h). A ceiling-mounted camera was used to capture top-view videos for broiler AI calculations. The results show that the sampling time interval of 0.04 s yielded the highest broiler AI because more bird motion details were captured at this short time interval. The broiler AIs at longer time intervals were 1–99% of that determined at the 0.04-s interval. The broiler AI at 0.2-s interval showed an acceptable accuracy with 80% less computational resources. Broiler AI decreased as birds aged but increased after week 4 at the drinker area. Broiler AI was the highest at the open area for weeks 1–4 and at the feeder and drinker areas for weeks 5–7. It is concluded that the accuracy of broiler AI was significantly affected by sampling time intervals. Broiler AI in commercial housing showed both temporal and spatial variations.

show abstract

Gait and force analysis of provoked pig gait on clean and fouled concrete surfaces

Cited by 17 publications

References 32 publications

Assessment of lameness in sows using gait, footprints, postural behaviour and foot lesion analysis

Assessment of lameness in sows using gait, footprints, postural behaviour and foot lesion analysis

Longitudinal gait development and variability of growing pigs reared on three different floor types

Accuracy of Broiler Activity Index as Affected by Sampling Time Interval

Contact Info

Product

Resources

About