Session 11 – BC Dairy System: Nutrition + Food Science

Objectives

After completing this lesson, you should be able to:

• Articulate the importance of and relationship between nutrition and food science in the BC Dairy System.

Required Readings and Resources

• Stoll-Kleemann, S., & O’Riordan, T. (2015). The Sustainability Challenges of Our Meat and Dairy Diets. Environment: Science and Policy for Sustainable Development, 57(3), 34. Access through the UBC Library.
• Carolan, M. (2012). Malnutrition: hidden and visible. Pp 66-86 in The Sociology of Food and Agriculture: London: Routledge. Available in Files section in Canvas.
• PODCAST: Mars, R. (January 12, 2016). Best Enjoyed By. 99% Invisible.Episode 195. http://99percentinvisible.org/episode/best-enjoyed-by/

For a long time, due to widespread income poverty in many low-income countries, many people were not able to economically access such luxuries as meat and dairy. As low-income countries have increased the proportion of the population in the so-called “middle-class” through the increasingly globalized economy, more and more people have the ability to afford meat and dairy. Research has suggested that the purchase of animal-source foods is positively correlated with household income.

In high-income countries like Canada, while food insecurity exists among marginalized populations (eg. rural communities, single-parent households, historically oppressed ethnic groups), the majority of consumers have economic access to meat and dairy so there is an immense market. As well, nutrition education is embedded in the public school system across the country and, most often, the Canada Food Guide is used to frame this education. For dairy consumption, the Canada Food Guide includes recommended daily intakes so as to get enough calcium for bone development and maintenance. When the Canada Food Guide is reviewed, dietitians and food scientists are joined at the table by stakeholders with interests in representing various food industries (https://www.canada.ca/en/health-canada/services/canada-food-guides/revision-process.html).

This short video follows the production of milk from farm to table in Canada from the perspective of the Dairy Farmers of Canada.

• NEWS ARTICLE: This recent article in the Globe and Mail stirs up some controversy about claims of calcium intake, human health, and the possible impacts of corporate funding on public knowledge.

• Carroll, A.E. 2014. Got Milk? Might Not Be Doing You Much Good. New York Times.
  

This article lays out the milk debate, claiming that there is not a lot of evidence that supports the widely-accepted belief that milk “does a body good”. It also presents recent studies that are beginning to refute this claim.

This short CBC piece discusses the history of the Canada Food Guidelines and follows a family who tries to follow the Canada Food Guide for a period of time.

• Ostry, A., Shannon, T., Dubois, L., & Nathoo, T. (2003). The interplay of public health and economics in the early development of nutrition policy in Canada. Critical Public Health, 13(2), 171–185.
  

Available through UBC library, this paper explores development of dairy policy in 1920s in Canada and argues that the switch in the 1920s from public health science’s vilification of cow’s milk to a position extolling its virtues cemented the alliance between the dairy industry and the federal government and shifted public attitudes towards milk. A key issue in today’s nutrition policy-making environment will be the role which science, scientists and scientific evidence plays in the nutrition policy-making arena.

With respect to food safety and minimizing waste, food scientists have made huge gains in the dairy industry. As described in the article by Ostry and colleagues (2003), before processing facilities existed that minimized the risk of food-borne diseases, fluid milk was not always considered a healthy beverage and had the potential to pose serious harm to consumers, especially infants. Likewise, as covered in the 99% Invisible podcast, we have much room for improvement in developing evidence-based policy that guides our "best-before" or expiry dates, and preventing food waste.

Tutorial Session

You will be conducting a sensory evaluation of milk products in today’s tutorial.

EVALUATION OF FLUID MILK PRODUCTS AND STATISTICAL ANALYSIS OF DATA

• Many thanks to LFS Faculty members Brent Skura, Alejandro Rojas, Art Bomke, and Eunice Li-Chan for contributing to the design of this activity.
  

The food we eat is part of a larger system than supermarkets, shelf-lives and kitchens; lessons that broaden knowledge and analyze all system components benefit the learner by creating an understanding of the complex relationships among the health of human populations, individuals and the environment. Our food systems envelop broad concepts such as cultural preferences and system analysis, and the best nutritionist/dietitian (and all students in food-related disciplines) has a profound awareness of the entire food system and how it relates to sustainability and human health.

This activity explores the processing, distribution, marketing, consumption and consumer preference of milk and milk alternative products. Students sample and rate a variety of different products on a scale of 1-9, from like extremely (1) to dislike extremely (9). The data generated is then used to demonstrate statistical measures of central tendency (mean, median and mode) as well as standard deviation. Students also become familiar with evaluating sensory properties and are introduced to the role of packaging and marketing of common food products. Discussions stemming from this activity touch upon a wide range of food industry topics such as marketing and consumer behaviour, nutritional value of milk and milk alternatives, and product packaging, waste generation and dairy industry sustainability.

Learning Objectives/Outcomes

Upon completion of this learning module, students will be able to:

• Describe the influence of social, cultural and economic factors on diet and consumption trends
• Discuss the role of milk and milk alternatives as a component of the human diet
• Recognize the sensory properties of various fluid milk products and milk alternatives
• Analyze sensory scores for fluid milk products and milk alternatives using statistics
• Evaluate packaging containers for fluid milk and milk alternative products and their impacts on food safety and the environment

Instructions for Sensory Evaluation

In your tutorial section, you will be presented with 12 coded samples of milk and milk alternatives. Please do not attempt to determine what the products are until everyone in the classroom has had an opportunity to sample the products. All products to be tested were purchased from a retail market. We encourage everyone to sample all products but understand if you do not wish to do so for religious reasons, or if you are allergic to cow’s milk, milk from other mammalian species, soybeans, almonds, oats, flax, rosemary or rice.

Each group should obtain the following (please assign 1 person from your group to collect the materials):

• 12 small plastic sample cups per individual in the group (if 5 group members, then 60 cups in total)
• 1 cup per individual to expectorate samples should you wish to not swallow the samples
• 1 package of unsalted crackers

From each coded product, place about 15 ml into one of the plastic cups. Fifteen ml will fill the cup about 1/3 full. It is recommended that individuals in your group try each milk product at the same time. One group member should bring one of the samples of milk to the group and fill each group members cup 1/3 full, be sure to record the number on your data input sheet. Taste the sample and record your rating on the data entry survey. Repeat for each of the 1 samples. It does not matter what order you taste in.

Prior to starting sensory evaluation and in between samples, you should eat an unsalted cracker and rinse your mouth with water (no other drink – only water). This will clear your palate. If you do not want to consume the milk products you can spit into an empty cup and discard after the exercise. Follow the directions on the sensory evaluation survey in order to determine a sensory score for each product. Please do not make comments about products as this may influence your colleague’s decisions.

Please ensure you clean up all of your cups and any spills prior to leaving your tutorial session.

Data Entry

You will enter your ratings in the following survey.

https://ubc.ca1.qualtrics.com/jfe/form/SV_b11umOclIsS1GQZ

We will discuss the results in our next Lecture Session. Here is more information on the statistical measures we will be using to analyze the class' preferences.

Measures of Central Tendency Several measures of central tendency can be calculated from sensory data as a means of reducing large amounts of data into measures that are easier to handle and report (eg. mean, median and mode). The mean, median and mode are values used to express a calculated estimate of the true value of the parameter (eg. Sensory score) that is being determined from a set of observations. Other calculations (eg. Standard deviation) can be conducted to provide an indication of the dispersion of the observations collected.

Mean (Average): The mean is a measure of where the center of the distribution of values in the data set lies. Calculate the mean for each coded sample by taking the sum of the score for the sample given by each panelist of the group and dividing that number by the number of panelists (eg.10).

The mean is strongly influenced by extreme values in the data set.

Median: is another way of expressing the middle range of a data set. There are an equal number of observations lower than the median and higher than the median. To calculate the median, rank the numbers in the set of observations a sample in numerical order from lowest to highest. If the number of scores is odd (eg. 5 scores), the middle value is taken as the median. If the number of scores is even (eg. 10 scores), the median is the average of the central pair of numbers. The median is less sensitive than the mean to the presence of extreme values in the data set.

Mode: The mode is defined as the most frequent score in a set of observations.

Range: The range is used to describe the dispersion of a data set. The value of the minimum and maximum values in a set of data also can be used to provide an assessment of dispersion.

Frequency distributions of sets of observations Data that is normally distributed will have a uniform distribution of values about the mean and the mean, median and mode will have the same value. Sometimes, data in a set of observations will not fall into a normal distribution but will be skewed either positively or negatively. A distribution of observations is said to be skewed to the left (negatively skewed distribution) because the slope of the frequency curve slopes to the left. A distribution of observations is to be skewed to the right (positively skewed distribution) because the frequency curve slopes to the right. You can plot a frequency distribution curve for one of the products tested by plotting the number of responses for each possible score (eg. # of panelists choosing a score of 1 (like extremely) ……. # of panelists choosing a score of 9 (dislike extremely) and plotting those numbers (on the y axis) as a function of the sensory score (1 to 9) on the x-axis of the graph ( histogram). The mean, median and mode in skewed frequency distributions will have different values while those values will be the same in a set of observations that are normally distributed.