دانلود مقاله ISI انگلیسی شماره 127118
ترجمه فارسی عنوان مقاله

طراحی و ارزیابی سیستم تست ترجیح نور برای مرغ تخمگذار

عنوان انگلیسی
Design and evaluation of a lighting preference test system for laying hens
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
127118 2018 8 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Computers and Electronics in Agriculture, Volume 147, April 2018, Pages 118-125

ترجمه کلمات کلیدی
مرغ تخمگذار، ترجیح نورپردازی، سیستم تست، تجزیه و تحلیل تصویر، روش ارزش گذاری،
کلمات کلیدی انگلیسی
Laying hens; Lighting preference; Test system; Image analysis; Weighting method;
پیش نمایش مقاله
پیش نمایش مقاله  طراحی و ارزیابی سیستم تست ترجیح نور برای مرغ تخمگذار

چکیده انگلیسی

Understanding the lighting needs of laying hens provides crucial implications on animal welfare regulations and production stewardship in commercial egg farms. A lighting preference test system (LPTS) that is used to explore hen’s lighting preference was recently designed and developed by our research team. The objectives of this study were to (1) describe the design of the LPTS, and (2) validate two algorithms that automatically determine the number of hens in individual compartments of the LPTS, and identify the reasons of false recognitions by the two algorithms. The LPTS consisted of five light-proof compartments connected in tandem. Each compartment can be operated at a desired lighting environment (e.g. lighting type, color, and intensity). Hens can move freely through passing doors between two adjacent compartments. Two loadcells and a camera were installed in each compartment to continuously monitor, respectively, the hen weight and record hen activities. Two algorithms, by image analysis (using video data) and by weight (using loadcell data), were developed to determine the real-time hen numbers in each compartment; and the accuracy of the two algorithms was determined by comparing their results to visual observation. Eight hens were kept in the LPTS and used for the algorithm validation. The validation results show that the accuracy of image analysis algorithm was 71.23%, which was much lower than that of weight algorithm (99.70%). False recognition of hen numbers by the image analysis algorithm stemmed from a variety of hen activities (e.g. feeding, wing flapping, preening, etc.) that may cause significant changing in the representing areas (or number of pixels) of animals in the images. The weight method/algorithm, on the other hand, offered a simple and accurate way to determine animal occupancy in the LPTS compartments. The newly developed LPTS and algorithms could be useful tools to investigate the preference responses and time budget of hens at different lighting conditions.