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I created a survey tool in Google Forms that automatically generated the graphs. Doing word frequency counts in Excel is an advanced topic I do with my students.

It doesn't matter. The math works both ways.

In the Pearson Square method, you can balance whatever component from your analysis that you want. It is only meant to be a single variate approach, it's not multivariate, so it can't balance and optimize multiple analytes at the same time.

It sounds like the course or training that you are getting is using the ASTM method E1885 − 04. I'm presenting a simplified version of it. But let me jump in with a bit more rigor. From the ASTM method, here are your definitions: α (alpha) risk-probability of concluding that a perceptible difference exists when, in reality, one does not. (Also known as Type I Error or significance level.) β (beta) risk-probability of concluding that no perceptible difference exists when, in reality, one does. (Also known as Type II Error.) pc-probability of a correct response. pd (proportion of discriminators) -proportion of the population represented by the assessors that can distinguish between the two products.

When it comes to setting an α/β ratio, or a 1- β calculation, we often reflect how willing are we to have a mistake. If we're a multimillion dollar product, with high risk on failure, we want low α/β ratio. If we're testing something out such as a lab prototype or a early stage formulation, we can put up with a higher α/β ratio. Most common, we see a α set to 0.05 to keep it simple. There are calculator tools such as V Power that can be used for estimating α/β values and estimate the number of discriminators in the population.

From the ASTM method: "For α-risk: A statistically significant result at: 10 to 5 % (0.10 to 0.05) indicates “slight” evidence that a difference was apparent; 5 to 1 % (0.05 to 0.01) indicates “moderate” evidence that a difference was apparent; 1 to 0.1 % (0.01 to 0.001) indicates “strong” evidence that a difference was apparent; and Below 0.1 % (<0.001) indicates “very strong” evidence that a difference was apparent. For β-risk: The strength of the evidence that a difference was not apparent is assessed using the same criteria as above (substituting “was not apparent” for “was apparent”). For pd: the maximum allowable proportion of distinguishers, pd, falls into three ranges: pd < 25 % represent small values; 25 % < pd < 35 % represent medium sized values; and pd > 35 % represent large values."

It's really only highly specialized sensory groups that actually calculate confidence limits on Pd, rather most practitioners use the tables that are attached to official methods. I classify myself as an advanced practitioner for sensory rather than a specialist.

​@@amyproulx78 Thanks for the response. We recently conducted a Triangle Test. To calculate one-sided UCL/LCL values, I referred to Sensory Evaluation Techniques (Fifth Edition) by Meilgaard, Civille, and Carr. However, the values that I calculated didn't make sense to me. I looked at other resources, stumbled upon this video, and asked my query. I also referred to the ASTM method E1885 − 04 research paper and realized that the book's formula for calculating Pd's standard deviation (Sd) was wrong. They had forgotten to mention the factor of 1.5. Although the calculations in their example had this value, the formula didn't. When I used the correct formula, I got the right answers. Anyway, once again, thanks for your response as well. For the uninitiated, here's the full name of the research paper. Designation: E1885 − 04 (Reapproved 2011) - Standard Test Method for Sensory Analysis-Triangle Test

I am glad you found this useful.

Awesome! I am glad you passed! I'm a firm believer that teachers should teach for success, and not set traps for students to fail. That's why I have fun making this channel. I want every student to succeed whether you are in my program or somewhere else on a learning journey.

Don't get me wrong - I have an awesome Ag teacher. I just didn't understand the way he was explaining it. I did however watch a video from some university, and it was boring and useless to me. this vid was awesome. @@amyproulx78

Hi there, great question. So you would give each of your four coffee samples a random number to code it, so people know which sample they are analysing, while not introducing bias by calling the product by its proper name or brand. Then it is up to you to decide which attributes are important in your CATA analysis. There is a World Coffee Research Sensory Lexicon that can help you decide which terms are meaningful for your analysts. If your analysts are well trained, they can deal with more descriptors, while if they are from the general public and untrained, they usually can't deal with more than 10-12 descriptors without getting confused.

Here's the weblink to the World Coffee Research Sensory Lexicon worldcoffeeresearch.org/resources/sensory-lexicon

Thank you so much ma’am. Your response are truly highly appreciated ❤️ actually i was about to search you in facebook or instagram because i want to have a constant guidance regarding on my study 🤗 thank you maam thank you ❤️

Thank you for this! 🥹❤️

Thank you! I am creating a new series which I should be able to launch in a week or two.

Thanks - that's my aim with this channel, to make food science and technology topics easier to understand so you can do your job better, or get ahead in studies.

I am glad it was helpful! Good luck on your test tomorrow! And let me know more topics for videos, as I will be starting production again soon!

Hi Louise, check out the full video library playlist that I developed for formulation and labelling. Back in the day, we would look up each line in the USDA NAL Food Composition Database, enter each line into a spreadsheet for every component contribution, then multiply by the percent contribution within the formula. Now when I am doing formulation with an end target in mind, I use apps for tracking contributions to formulation from each ingredient as the app will scrape the USDA NAL database for my values and enter them direct. My preference is for ESHA, but this software is expensive and bulky for small businesses. Recipal is what I recommend for small operators as it is low cost and good functionality. I use these apps for iterative formulation work. Just last week, in one of my product innovation classes, I had my students reverse engineer Nutella using the Nutrition Facts Table and Ingredient Declaration in one of my food labs, and they kept entering the ingredients in ESHA until the NFT almost matched.

It would help if I attached the playlist! :) th-cam.com/play/PLE1C5IAdMbhL5uZnDV_3XpPTJj-8eJYqM.html

Thank you very much. I am very grateful for your reply.

I've worked with Aqualab, Rotronic, and Novasina water activity meters. All of these meters are quite small. Portable just implies that they are on battery versus plugged in. Make sure that there is a clear calibration methodology. Also ask, how often do you need to test water activity, and does it make sense for you to own a meter, versus sending samples to a local lab.

Hi Kenzie, in my class we refer to some different approaches of bootstrapping data analysis, knowing my undergrads have a limited statistics background. In the short term, I'm going to recommend checking out this guidance document from Kent State University. libguides.library.kent.edu/SPSS/Multiple-Response-Sets

Agreed, during COVID I had to rush production of video for my students. I am trying to re-record some of the videos that were lower quality.

Oh, this is a good question. So, if you are not seeing syneresis when the topping and base are two separate elements, but you are when the two are composed together, I am guessing there is one part of the dessert that has more sugar, or something that is modifying the moisture balance in the product, causing moisture to migrate to the other phase. We had a similar scenario in a student project, a plant based yogurt parfait with fruit layers. We sprayed the layer with a thin coating of coconut fat, and this stopped moisture from migrating, and reduced the colour bleeding and textural changes on holding the product. Alternatively, can you investigate using a combination of gelatin and freeze-thaw stable starch? Gelatin is notorious for fracturing on freezing, while a combination of gelatin and freeze-thaw stable starch may have better performance.

@@amyproulx78 Hi Amy, sorry for my late reply, final exams from Uni this week. Oh, that's awesome! How do spray coconut fat? Do you buy it in a spray can already? Do you think all the layers should have the same percentage of sugar to avoid the migration of the moisture? We did add freeze-thaw stable starch, which helped a lot, but we still can see a little bit. This product is for export so it needs to be very stable.

@@irisforgiarinipasini1753 I was away on duty travel, pardon my slow response. The layers should have similar water activity to reduce moisture migration. Not the same as moisture or sugar concentration. As for spraying coconut fat, you just need an aerosol nozzle on a heated holding container.

There won't be a single answer, rather it will be a continuum of answers. Rather, when I have people who are doing product development with nutrition targets, I recommend tracking formulation in a spreadsheet or in a NFT database such as ESHA Genesis, to gauge the formulation with the nutrition target in mind.

Here is an example: Lets say you have ingredients A, B, C with 40%, 35% and 10% of protein respectively. Your aim is a 20-lb mix with 25% protein. Do a Pearson square in which you compare one bigger than 25, other smaller than 25: --> 40(A) - 25 - 10(C), you get 15 for C, 15 for A, so they are in a 1:1 ratio (C:A)) Do another Pearson square in which you compare the other bigger than 25 with the same 15 --> 35(B) - 25 - 10(C), you get 10 for C, 15 for B, so they are in a 2:3 ratio (C:B)) Add the common ratios for C : 2+1 = 3 So the ratio between A:B:C is 1:3:3 Add those ratios : 1+3+3 = 7 Divide the total weight: 20 / 7 Multiply each ingredient ratio by 20 /7 For A: 20 /7 * 1 = 20 / 7 = 2 6/7 lb For B: 20 /7 * 3 = 60 / 7 = 8 4/7 lb For C: 20 /7 * 3 = 60 / 7 = 8 4/7 lb

Who me? I'm just a food science professor who likes science communications and democratizing skills development.

That's a great topic. I took a little break from videos, and look forward to making new content this spring.

I am glad you find it useful! Please let me know more topics for videos. I took a break as I was on some different projects during the fall and winter, but look forward to making new videos soon.

Thanks for your kind words. I made the video to help my undergraduate students, and felt it could help other students and teachers as well.

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Food quality is a huge topic. What specific information do you want to learn? I will be making more videos soon.

@@amyproulx78 kind of introduction like😊. Highly appreciated

If you have selected appropriate pathogen or spoilage organisms of interest, and then chosen appropriate D, Z and T reference values, then used the calculator correctly, then yes, you refer to the log reduction of the process. In many cases, governments make log reduction of process targets as part of regulatory performance standards. For example in Canada, canned low acid foods have a requirement for at least 12 log reduction of Clostridium botulinum using T ref 121C, Z of 10C and D value of 0.25. Some meat products require a minimum 5 log reduction of E. coli, while others require a minimum 6.5 or 7.0 log reduction of Salmonella.

Maybe you really like hermetically sealed jars? Maybe you are a food scientist, or should become one? I take video requests, if there is something you would like to learn about food processing industries.

Thank you! Your kind words mean a lot. I started this series for my undergrad students, and then when they graduated they asked for the videos to share with their coworkers. I'll start new videos in January! Let me know topics you are interested in.

@@amyproulx78 Looking forward to seeing new videos on the channel. I am doing my master's in food science in New Zealand and I always come to your TH-cam channel to understand better about the topics as my professor does not explain them as great as you do! I would love to learn more about starches in food applications. I am working as a product developer in a frozen dessert company and we are always having problems with syneresis. Lately, we have been having problems with the shrinkage of meringue and marshmallows after freezing them. I don't know if is related to the starches I am adding to it to control the syneresis or if it is related to any protein reaction occurring due to the drop in temperature. I also would love to know more about vegan, gluten-free, and keto product development. The products we can use to create similar textures as close as possible to normal in cakes, mousses, creams, etc. Tips on scaling up recipes as well I would love to see. Thank you very much for sharing all this great content here. Kind Regards.

@@irisforgiarinipasini1753 I sent you a message in Linkedin so we can discuss more.

Great question. I prepare these videos for my undergraduates, but found that many want to refer back to them when they graduate. I'm glad you are finding them helpful for you. I will be making a whole new series this January. As for food-NHP interface products, inevitably it is up to your Health Canada regulators to make a final disposition on the product. The guidance document for deciding is here: www.canada.ca/en/health-canada/services/drugs-health-products/natural-non-prescription/legislation-guidelines/guidance-documents/classification-products-at-food-natural-health-product-interface.html

The statement that stands out from the Health Canada document is as follows - In deciding whether a product in food format is an NHP or a food, the following criteria will be taken into account: Product composition; Product representation; Product format; and Public perception and history of use. So thinking of this product, how is it being represented in advertising and marketing? What are the other SKUs within your company portfolio and how are they being represented? What is the branding differentiation between food products in your company portfolio versus NHP products in the company portfolio? What is the meaningfulness of the dosing within the product? In general, confectionery inspired products that try to fit as NHPs tend to end up as foods when assessed by HC. A lot of this food-NHP interface conflict comes from abuse of the food industry of NHP loopholes prior to tightening of the legislation in 2016. The reference I just shared has a section in 2.1 describing the interface challenges of confectionery type products. Feel free to connect with me on Linkedin to discuss further.

@@amyproulx78 I love that you’re creating content for your undergraduates to refer back to and looking forward to your new series in January! And appreciate you responding to my question - thanks for confirming my assumption :)

I have lots of videos on lipid structure-function chemistry, as well as on nutrition labelling. Do check out the play lists and search for some of the lipid content.

This video was designed for students in Culinary studies at Niagara College. You would have to contact ITS with your student account to ensure you are registered on CFWI Splashtop.

@@amyproulx78 ok