کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6458762 1421113 2017 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Online detection and localisation of piglet crushing using vocalisation analysis and context data
ترجمه فارسی عنوان
تشخیص آنلاین و محلی سازی خرد کردن دانه خردل با استفاده از تجزیه و تحلیل آوازی و داده های زمینه
کلمات کلیدی
تجزیه و تحلیل آوازی آنلاین، تشخیص خرد کردن بوته، جلوگیری از خرد شدن فعال دامداری دقیق،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Fatal piglet crushing by the mother sow is a pervasive economic and animal welfare issue in piglet production. To keep the mother sow in a farrowing cage is the established countermeasure. This facility is a compromise that results in an impairment of the sows' welfare to the benefit of her piglets and the farmer. A natural behaviour pattern which is demonstrated by most but not all sows is to free the trapped piglet by a posture change. Promoting this behaviour through aversive stimulations is an alternative approach to reduce piglet mortality. This approach requires an identification and localisation of ongoing piglet trapping in real-time. The present study investigates the online analysis of piglet vocalisation for this purpose. The results show, that trapping related stress articulations are outnumbered by other stress related articulations by a factor of 1:140 in a farrowing compartment with only 4 sows. Theoretical calculations for larger compartments indicate that this ratio becomes even worse due to an increasing influence of vocalisation from neighbouring pens. However, the specificity could be increased to more than 95% and precision to approximately 30% while maintaining a sensitivity of approximately 70% by retrospectively applying context based event filters. This specificity would be sufficient to limit the average number of erroneous trapping detections to one detection per sow within 3 days without a substantial loss of sensitivity. Effective parameters for filtering were the age of the piglets and the sows' body posture history. Calculations with hypothetical spatial event filters showed that this classification performance could be maintained even in much larger farrowing compartments. Combined with an aversive stimulation principle that can be applied to a whole region, this detection technology could be useful to reduce piglet mortality in loose farrowing applications. An already known and effective stimulation principle of this type is floor vibration. Such an active piglet rescue system would allow limiting the impairment of welfare to only those sows that actually crush piglets and to the time when piglets are being crushed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 135, 1 April 2017, Pages 108-114
نویسندگان
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