Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/68182
Title: Penentuan suhu kritis atas pada sapi perah dara fries holland berdasarkan respon fisiologis dengan manajemen pakan melalui simulasi Artificial Neural Network
Upper critical temperature of Fries Holland heifers based on physiological responseses for feeding management using Artificial Neural Network simulation.
Authors: Purwanto, Bagus Priyo
Manalu, Wasmen
Permana, Idat Galih
Suherman, Dadang
Issue Date: 2013
Publisher: IPB (Bogor Agricultural University)
Abstract: The management strategy was carried out by predicting the heifer critical temperature determination based on physiological response on feeding management trough ANN simulation. The purpose of this research was to determined the critical temperature for FH heifer based on physiological response with on different feeding time which was fed concentrate that contains different TDN. The objective of the present study is to evaluate physiological responses of dairy heifer to feeding time when fed concentrate differences in TDN content. Six dairy heifers were randomly allocated to 1 of 6 treatments: two feeding times (5 am/6 pm or 8 am/4 pm) of concentrate with 70 % or 75 % of concentrate unsupplemented or supplemented with 3.5 % coconut oil, in each of 6 periods of 14 d each in 6 x 6 Latin square design. The environmental conditions (air temperature, relatitive humidity, temperature humidity index, radiation, and wind velocity) and animals responses (rectal temperature, skin temperature, body temperature, heart rate, respiration rate, feed consumption, feed comsumption rate, chewing rate, and average daily gain) were then measured. The environmental condition were measured daily at 1 h intervals from 5 am to 8 pm. The animals responses were measured at the 4th, 8th, 12th, 14th, day of each periode at 1 h intervals from 5 am to 8pm, Tukey’s test and LSD were used for statististical analysis among treatments. The heifer critical temperature determination with physiological response indicator on feeding management was simulated by using Artificial Neural Networks (ANN) analysis. Artificial Neural Network (ANN) simulation for industrial engineering is used to define critical temperature of Fries Holland (FH) heifer based on physiological responses on models to predict rectal temperature, skin temperature, heart rate and respiratory rate, using ambient temperature and humidity inputs. The research was conducted using six dairy cattle in Bogor and Jakarta. The heifers were fed 6 am and 3 pm daily. The environmental condition (Ta, Rh, THI, and Va) and physiological responses (rectal temperature, skin temperature, heart rate, and respiration rate) were then measured for 14 days in two months at 1 h intervals started from 5 am to 8 pm. By using this ANN simulation. The critical temperature for FH heifer were defined, from rectal temperature at Ta 26 0C and Rh 86 % at Bogor, and at Ta 26 0C and Rh 88 % at Jakarta, from skin temperature at Ta 31 0C and Rh 86 % at Bogor, and at Ta 32.5 0C and Rh 88 % at Jakarta, from heart rate at Ta 24.5 0C and Rh 78 % at Bogor, and at Ta 23.5 0C and Rh 88 % in Jakarta, from respiratory rate at Ta 22.5 0C and Rh 78 % at Bogor, and Ta 23.5 0C and Rh 78 % at Jakarta. The result of this research was physiological response was lower in FH heifers which was fed at 05.00 am and 06.00 pm compared to the heifers which was fed at 08.00 am and 04.00 pm. The critical temperature on FH heifer was increased on heifers which was fed at 05.00 am and 06.00 pm compared to the heifers which was fed at 08.00 am and 04.00 pm, and also with the feeding of TDN 75 % concentrate that contains 3.5 % coconut oil compared with the feeding of TDN 75% concentrate. The rectal temperature and respiration frequency of FH heifers was more sensitive exposed to stress which was caused by temperature and humidity changes compared to skin temperature and heart rate, both on the heifers which was fed at 05.00 am and 06.00 pm and at 08.00 and 04.00 pm with the feeding of TDN concentrate 70 %, 75 %, and 75 % that contains 3.5 % coconut oil. The physiological responses were significantly lower on cattle which fed at 5 am and 6 pm than 8 am and 4 pm also for cattle which fed concentrate contained 3.5 % coconut oil than not containing that with the same TDN (75 %). Chewing velocity was higher on cattle fed concentrate containing 3.5 % coconut oil than without coconut oil. Average daily gain were higher on cattle fed 5 am and 6 pm than 8 am and 4 pm or fed with concentrate containing 3.5 % coconut oil than without coconut oil. The conclusion of this research can predict the critical temperature determination for FH heifers with different feeding time management and also different TDN feeding. The heat stress of dairy heifer could be reduced with managemen feeding time and feeding with easily digestible nutrient.
URI: http://repository.ipb.ac.id/handle/123456789/68182
Appears in Collections:DT - Animal Science

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