scholarly journals Fluid milk consumption and demand response to advertising for non-alcoholic beverages

2002 ◽  
Vol 11 (1) ◽  
pp. 13-24
Author(s):  
K. RICKERTSEN ◽  
G.V GUSTAVSEN
Keyword(s):  
Demand Response ◽  
Alcoholic Beverages ◽  
Demand System ◽  
Milk Consumption ◽  
Stage Model ◽  
Generic Advertising ◽  
Second Stage ◽  
Whole Milk ◽  
Beverage Group ◽  
Fluid Milk

Norwegian fluid milk consumption has declined steadily over the last twenty years, despite the dairy industry spending increasing amounts of money on advertising. Using a two-stage model, we investigate whether advertising has increased the demand for milk. No effect of advertising on the demand for non-alcoholic beverages is found in the first stage. In the second stage, an almost ideal demand system including advertising expenditures on competing beverages is estimated. The effects of generic advertising within the beverage group are positive and significant for whole milk and negative and significant for lower fat milk. The own-advertising elasticity for the combined fluid milk group is 0.0008. This highly inelastic elasticity suggests that increased advertising will not be profitable for the producers. Several cross-advertising effects are statistically significant, emphasizing the usefulness of a demand system approach.

Development and Validation of a Dynamic Growth Model for Listeria monocytogenes in Fluid Whole Milk

1999 ◽  
Vol 62 (2) ◽  
pp. 170-176 ◽  
Author(s):  
S. H. ALAVI ◽  
V. M. PURI ◽  
S. J. KNABEL ◽  
R. H. MOHTAR ◽  
R. C. WHITING
Keyword(s):  
Experimental Data ◽  
Listeria Monocytogenes ◽  
Growth Model ◽  
Extreme Values ◽  
Exponential Growth Phase ◽  
Lag Phase ◽  
Maximum Relative Error ◽  
Whole Milk ◽  
Dynamic Growth ◽  
Fluid Milk

Listeria monocytogenes, a psychrotrophic microorganism, has been the cause of several food-borne illness outbreaks, including those traced back to pasteurized fluid milk and milk products. This microorganism is especially important because it can grow at storage temperatures recommended for milk (≤7°C). Growth of L. monocytogenes in fluid milk depends to a large extent on the varying temperatures it is exposed to in the postpasteurization phase, i.e., during in-plant storage, transportation, and storage at retail stores. Growth data for L. monocytogenes in sterilized whole milk were collected at 4, 6, 8, 10, 15, 20, 25, 30, and 35°C. Specific growth rate and maximum population density were calculated at each temperature using these data. The data for growth rates versus temperature were fitted to the Zwietering square root model. This equation was used to develop a dynamic growth model (i.e., the Baranyi dynamic growth model or BDGM) for L. monocytogenes based on a system of equations which had an intrinsic parameter for simulating the lag phase. Results from validation of the BDGM for a rapidly fluctuating temperature profile showed that although the exponential growth phase of the culture under dynamic temperature conditions was modeled accurately, the lag phase duration was overestimated. For an α0 (initial physiological state parameter) value of 0.137, which corresponded to the mean temperature of 15°C, the population densities were under-predicted, although the experimental data fell within the narrow band calculated for extreme values of α0. The maximum relative error between the experimental data and the curve based on an average α0 value was 10.42%, and the root mean square error was 0.28 log CFU/ml.

scholarly journals Fluid milk consumption patterns in the United States, 2003–2004

2007 ◽  
Vol 21 (5) ◽  
Author(s):  
Randy LaComb ◽  
Nancy Raper ◽  
Cecilia W. Enns ◽  
Joseph Goldman ◽  
Alanna J. Moshfegh
Keyword(s):  
United States ◽  
The United States ◽  
Consumption Patterns ◽  
Milk Consumption ◽  
Fluid Milk

A note on the effects of frequency and method of feeding milk substitute on the performance of Friesian and Ayrshire calves

1973 ◽  
Vol 17 (3) ◽  
pp. 333-336 ◽  
Author(s):  
P. J. Broadbent
Keyword(s):  
Food Intake ◽  
Cold Water ◽  
Live Weight ◽  
Drinking Behaviour ◽  
Milk Consumption ◽  
Blood Temperature ◽  
Whole Milk ◽  
Milk Substitute ◽  
Liquid Milk ◽  
Ad Libitum

SUMMARY1. Forty British Friesian and 33 Ayrshire male calves were reared on one of three treatments differing in frequency and method of feedingwhole milk and milk substitute.2. The calves were introduced to their treatments on arrival. The Ayrshire calves were offered whole milk for 24 days as two feeds of up to 1·42 litres warm milk each (2W), or one feed of up to 2·84 litres warm milk (1W) daily, or cold milk ad libitum (AC). Thereafter they received milk substitute on one of the following regimes which were applied to the Friesian calves from arrival. The regimes were 454 g milk-substitute powder reconstituted at the rate of 158 g per litre warm water (approximately blood temperature) given in two feeds of 227 g per day (2W) or one feed of 454 g per day (1W), and milk-substitute powder reconstituted with cold water at the rate of 100 g per litre offered ad libitum (AC).3. Calves on treatment AC had higher live-weight gains and consumed more whole milk, milk substitute and less concentrates than those on other treatments. These differences were significant. There were differences in drinking behaviour on treatment AC between Friesian and Ayrshire calves which may have been due to differences in age at the start of the experiment. Solid food intake was affected by both level and pattern of liquid milk consumption. The practical and financial implications of treatment AC are discussed.

scholarly journals Strategies for Datacenters Participating in Demand Response by Two-Stage Decisions

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yuling Li ◽  
Xiaoying Wang ◽  
Peicong Luo
Keyword(s):  
Smart Grid ◽  
Demand Response ◽  
Smart Grids ◽  
Peak Load ◽  
Two Stage ◽  
The Sustainable Development ◽  
Second Stage ◽  
Potential Demand ◽  
Electricity Costs ◽  
Demand Response Programs

Modern smart grids have proposed a series of demand response (DR) programs and encourage users to participate in them with the purpose of maintaining reliability and efficiency so as to respond to the sustainable development of demand-side management. As a large load of the smart grid, a datacenter could be regarded as a potential demand response participant. Encouraging datacenters to participate in demand response programs can help the grid to achieve better load balancing effect, while the datacenter can also reduce its own power consumption so as to save electricity costs. In this paper, we designed a demand response participation strategy based on two-stage decisions to reduce the total cost of the datacenter while considering the DR requirements of the grid. The first stage determines whether to participate in demand response by predicting real-time electricity prices of the power grid and incentive information will be sent to encourage users to participate in the program to help shave the peak load. In the second stage, the datacenter interacts with its users by allowing users to submit bid information by reverse auction. Then, the datacenter selects the tasks of the winning users to postpone processing them with awards. Experimental results show that the proposed strategy could help the datacenter to reduce its cost and effectively meet the demand response requirements of the smart grid at the same time.

The Limulus Amoebocyte Lysate Assay and the Direct Epifluorescent Filter Technique as Estimators of Potential Shelf-life of Pasteurized Fluid Milk

1990 ◽  
Vol 53 (2) ◽  
pp. 151-153 ◽  
Author(s):  
ROBERT D. BYRNE ◽  
J. RUSSELL BISHOP
Keyword(s):  
Shelf Life ◽  
Benzalkonium Chloride ◽  
Detection Techniques ◽  
Filter Technique ◽  
Psychrotrophic Bacteria ◽  
Limulus Amoebocyte Lysate ◽  
Whole Milk ◽  
Before And After ◽  
Direct Epifluorescent Filter Technique ◽  
Fluid Milk

The Limulus Amoebocyte Lysate Assay, Direct Epifluorescent Filter Technique and modified Psychrotrophic Bacteria Count were used to indicate potential shelf-life of pasteurized fluid milk. Commercial whole milk samples, stored at 7°C, were analyzed for bacterial and biochemical parameters, as well as for potential shelf-life by daily sensory evaluation. Each sample was evaluated before and after the following preliminary incubations: milk alone, milk with benzalkonium chloride, milk and broth, and milk and broth with benzalkonium chloride. The Limulus Amoebocyte Lysate Assay, Direct Epifluorescent Filter Technique, and modified Psychrotrophic Bacteria Count in conjunction with the preliminary incubations, produced relatively high correlations to shelf-life (−0.78, −0.85, and −0.86 respectively). Thus, these bacterial detection techniques could be used as rapid methods of shelf-life estimation.

scholarly journals A Fast Learning Method for Accurate and Robust Lane Detection Using Two-Stage Feature Extraction with YOLO v3

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4308 ◽  
Author(s):  
Xiang Zhang ◽  
Wei Yang ◽  
Xiaolin Tang ◽  
Jie Liu
Keyword(s):  
Learning Algorithm ◽  
Structural Parameters ◽  
Feature Learning ◽  
Automatic Generation ◽  
Detection Algorithm ◽  
Lane Detection ◽  
Stage Model ◽  
Two Stage ◽  
Label Data ◽  
Second Stage

To improve the accuracy of lane detection in complex scenarios, an adaptive lane feature learning algorithm which can automatically learn the features of a lane in various scenarios is proposed. First, a two-stage learning network based on the YOLO v3 (You Only Look Once, v3) is constructed. The structural parameters of the YOLO v3 algorithm are modified to make it more suitable for lane detection. To improve the training efficiency, a method for automatic generation of the lane label images in a simple scenario, which provides label data for the training of the first-stage network, is proposed. Then, an adaptive edge detection algorithm based on the Canny operator is used to relocate the lane detected by the first-stage model. Furthermore, the unrecognized lanes are shielded to avoid interference in subsequent model training. Then, the images processed by the above method are used as label data for the training of the second-stage model. The experiment was carried out on the KITTI and Caltech datasets, and the results showed that the accuracy and speed of the second-stage model reached a high level.

scholarly journals The Use of Discrete Variables to Estimate Price and Income Elasticities for Products with Seasonal Consumption Patterns

1971 ◽  
Vol 3 (1) ◽  
pp. 109-113
Author(s):  
David L. Trammell ◽  
Verner G. Hurt
Keyword(s):  
Seasonal Variations ◽  
Agricultural Products ◽  
Consumption Patterns ◽  
Milk Consumption ◽  
Discrete Variables ◽  
Income Elasticities ◽  
Daily Average ◽  
Price And Income Elasticities ◽  
Per Capita ◽  
Fluid Milk

The consumption of a number of agricultural products varies from one season of the year to another. For some products, seasonal variations in consumption correspond to variations in production. For others, such as fluid milk, consumption and production patterns tend to vary inversely, Downen [2] reported significant seasonal variations in daily average sales of fluid milk with the highest sales occurring in the fall and winter months and the lowest in the spring and summer months. Other studies [1,5] have also reported seasonal variations in per capita sales of fluid milk. Conversely, production of fluid milk naturally tends to peak in the spring and summer months and reach its lowest point in the fall and winter.

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