Advanced Search
EAAP Scientific Series
Arazi, A., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Pinski, N., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Schcolnik, T., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Aizinbud, E., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Katz, G., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Maltz, E., Institute of Agricultural Engineering, ARO, The Volcani Center, P.O. Box 6, Bet Dagan, 50250, Iceland
Two new sensors recently developed by S.A.E. Afikim, an on-line milk analyzer (Afilab™) and a behavior meter (Pedomer+™), provide new data at higher resolution than was previously possible. Applied research was performed to identify beneficial tools for dairy herd management from the new data that became available. A controlled large-scale field trial was carried out by the S.A.E. Afikim Applied Research Team in a commercial dairy herd of 800 milking cows in Israel from May/07 through July/07. Milk analyzer data (milk solids and SCC) were recorded three times daily for all the milking cows, and were compared to reference laboratory data. At the group and herd level, the analyzer can be used as a reliable detector of nutritional problems. Small differences in the daily calculated bulk tank fat and protein were found between the analyzer and the laboratory data (-0.05%-+0.28% and +0.01%-+0.05%, respectively). These results show that the analyzer is a useful tool to estimate payment returns to the dairies. Under milk formulas corrected for the Israeli economy, the difference between the results of the reference laboratory and the on-line analyzer was less than 1.1%. At the level of the individual cow, milk analyzer data can be used for several purposes. Real time on-line milk separation based on milk protein content can be performed on the farm. A difference of 5.2% in high quality (protein>3.2%) milk volume was found between the analyzer and laboratory data. This opens new options regarding individual feeding by using the milk components to formulate precise rations suited to the needs of individual cows. Other applications concerning detection of metabolic diseases and clinical and sub-clinical mastitis are currently under study with promising initial results involving multivariable models. These models include low fat and fat-to-protein ratio as indicators for metabolic disorders, and decreases in lactose for the detection of mastitis. Applied studies for uses of the behavioral meter were conducted by researchers from the Israeli Agricultural Research Organization-The Volcani Center. The results of these studies together with observations made on commercial farms revealed several useful applications derived from behavioral data (lying down time, lying down frequency and activity). At the group and herd level it was found useful for early detection of stressful events such as extreme climate and noise disturbance. It is also a promising tool for defining bedding conditions and to signal changes in farm routine. At the level of the individual cow, the data can be used to predict calving time, and will be examined for heat detection in tie stalls. The authors believe that the derived applications will improve management of commercial dairy herds. Further research will allow better understanding of complex behavior of dairy cows which will certainly reveal more applications for this new data.
Powered by ClearMash Solutions Ltd -
Volcani treasures
About
Terms of use
Innovations arising from applied research on a new on-line milk analyzer and a behavior meter
129
Arazi, A., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Pinski, N., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Schcolnik, T., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Aizinbud, E., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Katz, G., S.A.E Afimilk, Kibbutz Afikim 15148, Iceland
Maltz, E., Institute of Agricultural Engineering, ARO, The Volcani Center, P.O. Box 6, Bet Dagan, 50250, Iceland
Innovations arising from applied research on a new on-line milk analyzer and a behavior meter
Two new sensors recently developed by S.A.E. Afikim, an on-line milk analyzer (Afilab™) and a behavior meter (Pedomer+™), provide new data at higher resolution than was previously possible. Applied research was performed to identify beneficial tools for dairy herd management from the new data that became available. A controlled large-scale field trial was carried out by the S.A.E. Afikim Applied Research Team in a commercial dairy herd of 800 milking cows in Israel from May/07 through July/07. Milk analyzer data (milk solids and SCC) were recorded three times daily for all the milking cows, and were compared to reference laboratory data. At the group and herd level, the analyzer can be used as a reliable detector of nutritional problems. Small differences in the daily calculated bulk tank fat and protein were found between the analyzer and the laboratory data (-0.05%-+0.28% and +0.01%-+0.05%, respectively). These results show that the analyzer is a useful tool to estimate payment returns to the dairies. Under milk formulas corrected for the Israeli economy, the difference between the results of the reference laboratory and the on-line analyzer was less than 1.1%. At the level of the individual cow, milk analyzer data can be used for several purposes. Real time on-line milk separation based on milk protein content can be performed on the farm. A difference of 5.2% in high quality (protein>3.2%) milk volume was found between the analyzer and laboratory data. This opens new options regarding individual feeding by using the milk components to formulate precise rations suited to the needs of individual cows. Other applications concerning detection of metabolic diseases and clinical and sub-clinical mastitis are currently under study with promising initial results involving multivariable models. These models include low fat and fat-to-protein ratio as indicators for metabolic disorders, and decreases in lactose for the detection of mastitis. Applied studies for uses of the behavioral meter were conducted by researchers from the Israeli Agricultural Research Organization-The Volcani Center. The results of these studies together with observations made on commercial farms revealed several useful applications derived from behavioral data (lying down time, lying down frequency and activity). At the group and herd level it was found useful for early detection of stressful events such as extreme climate and noise disturbance. It is also a promising tool for defining bedding conditions and to signal changes in farm routine. At the level of the individual cow, the data can be used to predict calving time, and will be examined for heat detection in tie stalls. The authors believe that the derived applications will improve management of commercial dairy herds. Further research will allow better understanding of complex behavior of dairy cows which will certainly reveal more applications for this new data.
Scientific Publication
You may also be interested in