Effects of Specific Essential Oil Compounds on, Feed Intake, Milk Production, and Ruminal Environment in Dairy Cows during Heat Exposure

The objective of this study was to determine effect of dietary essential oil (EO) compounds, which contained cinnamaldehyde, eugenol, peppermint, coriander, cumin, lemongrass, and an organic carrier on feed intake, milk composition, and rumen fermentation of dairy cows during heat exposure. Thirty-two Holstein cows (days in milk= 60 ± 5) were assigned to one of two treatment groups: a Control and EO fed. The experiment lasted 28 days. Dry matter intake (DMI) was measured daily while and milk production was measured weekly. Our result showed that DMI and milk yield was decreased (P < 0.01) in control cows relative to EO cows. Furthermore, supplementation with EO was associated with a decrease in the molar proportion of propionate (P < 0.05) and increase (P < 0.05) in acetate to propionate ratio. In conclusion, EO supplementations in diets can be useful nutritional modification to alleviate for the decrease DMI and milk production during heat exposure in lactating dairy cows.

Solving a New Mixed-Model Assembly LineSequencing Problem in a MTO Environment

In the last decades to supply the various and different demands of clients, a lot of manufacturers trend to use the mixedmodel assembly line (MMAL) in their production lines, since this policy make possible to assemble various and different models of the equivalent goods on the same line with the MTO approach. In this article, we determine the sequence of (MMAL) line, with applying the kitting approach and planning of rest time for general workers to reduce the wastages, increase the workers effectiveness and apply the sector of lean production approach. This Multi-objective sequencing problem solved in small size with GAMS22.2 and PSO meta heuristic in 10 test problems and compare their results together and conclude that their results are very similar together, next we determine the important factors in computing the cost, which improving them cost reduced. Since this problem, is NPhard in large size, we use the particle swarm optimization (PSO) meta-heuristic for solving it. In large size we define some test problems to survey it-s performance and determine the important factors in calculating the cost, that by change or improved them production in minimum cost will be possible.