Mahdi Khojastehkey; mohammad yeganehparast; majid kalantar; hassan sadeghipanah
Abstract
ABESTRACT This research was conducted to investigate the feasibility of estimating the weight of broiler chicks using machine vision technology. 600 Ross broiler chicks were reared under standard conditions for a 42-day period. At selected intervals (7 days), 60 birds from a total of 600 chicks were ...
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ABESTRACT This research was conducted to investigate the feasibility of estimating the weight of broiler chicks using machine vision technology. 600 Ross broiler chicks were reared under standard conditions for a 42-day period. At selected intervals (7 days), 60 birds from a total of 600 chicks were randomly selected and weighed individually using the appropriate scale. At the same times, digital images were captured individually and in groups 2, 3 and 4 of birds. The digital images were initially preprocessed and the necessary changes were made on the photos and required features were extracted from images by designing an appropriate algorithm, and these features were used to design the neural network to estimate the body weight of chicks. The correlation coefficient between the extracted features of digital images including the Major axis length, Minor axis length, Bonding box, Convex Area, Filled area, Perimeter and Area of the image with live weight of the chicks were 0/92, 0/93, 0/53, 0/99, 0/99, 0/94, and 0/99 respectively (p <0.01). A Multilayer perceptron neural network, which was trained with back propagation learning algorithm, containing 22 neurons in the input layer, 20 neurons in the mid layer and one neuron in the output layer presented the highest accuracy(99%) to estimate the weight of broiler chicks at different ages. The results of this study showed that there is a possibility of using image processing and artificial neural network as an appropriate and efficient tool to estimate the weight of broiler chicks during the breeding period.
Mahmood Sahraei; Hassan sadeghipanah; nader asadzadeh; Abazar ghanbari
Abstract
This experiment was carried out to investigate the Moghani ewe production performance improvement through reproductive management and nutrition methods during the non-breeding season in rangeland condition. For doing these projects, in one flock with 400 ewes, two groups were identified, that including ...
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This experiment was carried out to investigate the Moghani ewe production performance improvement through reproductive management and nutrition methods during the non-breeding season in rangeland condition. For doing these projects, in one flock with 400 ewes, two groups were identified, that including group 1(estrus synchronization+hormone therapy+supplementary feeding) and group 2 or control group (without estrus synchronization+ hormone therapy+supplementary feeding). Supplementary feeding duration in pre mating for 4 weeks and 1.5 month in late gestation with concentrate were done. During the project, production, reproductive traits and economical evaluation was carried out in each two groups. For quantities data analysis of T-test methods and for qualitative traits were used of frequency table and Chi-square. The results showed that, parturition rate, lamping rate, twining rate, born lamb crop (BLC) and weaned lamb crop (WLC) in experimental group was more than control group (p<0.05). In terms of fecundity, there was significant statistical difference between two methods, so that 104.21 vs. 48.64 percent in experimental group compared with control group were observed (p<0.05). In conclusion, in non-breeding season, in Moghani ewe using of estrus synchronization+hormone therapy+supplementary feeding, have the highest economic interest compared to the control group.
