Updated: Oct 14, 2018
Quinoa, an incredibly nutritious grain crop native to South America that cultivated for its edible seeds, has been domesticated for thousands of years. It is considered a quintessential superfood, due to the fact that it contains complete protein with all 9 essential amino acids unlike other whole grains, is high in vitamins and fiber and low in fat, starch and gluten. It is also very versatile in terms of its culinary usage and can be used in a wide variety of recipes, and can replace traditional high-starch grains such as rice.
As consumers are becoming more and more health conscious in many parts of the world, the demand for quinoa has skyrocketed worldwide. Not all quinoas are created equal though, as there are different kinds with different colors, most commonly white, red and black. The taste, texture, flavors of these different colored quinoa are all different, and the price of each color of quinoa is different too. To achieve a certain taste or texture, food companies have created blends of various colored quinoas, often called “tricolor quinoa.” Tricolor quinoa has become a very popular product among consumers. However, how can food companies ensure that their final product of blend of tricolor quinoa is of a consistent quality? It might be hard to imagine that in 2018, a lot of this still comes down to human visual inspection, which is susceptible to error. This creates an issue because the nutrition label on food product packages typically specify a particular blend ratio of individual quinoa varieties included in a particular tricolor quinoa product, but often times companies can’t really know for sure that their final packaged products actually match the precise blend specifications in the nutrition label, which creates problems for food companies from the standpoint of consistency, regulatory compliance, and perhaps most importantly, consumer satisfaction.
To solve this problem, it is necessary to take guess work out of the equation and replace error-prone human inspection with accurate and consistent measurement, in order to know exactly what is in your tricolor quinoa blend and achieve consistent quality for the food product. Vibe has developed an application specifically for this purpose: Vibe’s tricolor quinoa phenotyping solution provides an innovative method of ensuring that tricolor quinoa blends are of the consistent high quality designed and promised by food companies to their customers.
So how do does Vibe’s tricolor quinoa phenotyping solution help food companies get the exact blend and high quality product that will set food companies apart from their competitors? Our QM3 analyzer and tricolor quinoa application can measure:
· Absolute color characterization in Lab and RGB scales
· Grains counting
· Grain grouping by color and size
· Broken grains detection (%)
· 1,000 grains weight
· Grain and sample level dimensions and statistics:
- Length to Width ratio
· Color recognition:
- Normal range
- Abnormal colors
· Results stored in Excel and SCV files for traceability and further analysis
Some additional information on this application include:
· Sample weight- up to 12 grams (~3,000 grains)
· 40 seconds analysis time
· 25 micron measurement accuracy
· 240 X 170 mm (9.5” X 6.7”) Inspection area
· Advanced algorithm for high density sample
· 1,500 color pixels per grain
· High resolution industrial grade camera
· No minimum sample size
Vibe’s QM3 application for tricolor quinoa phenotyping is a powerful tool for food companies that care about their product quality to want ensure a consistent and high quality product for their consumers. It also makes sense from the company’s operational and financial perspective – different colored and quality quinoa have different prices, and in order to fully control your cost it helps to know exactly what’s in your product, and make adjustments accordingly when the result is different from the product design. Knowledge is power, and to get to the next level of control over your product quality, accurate measurement is a critical step. With the statistics and information provided by our system, it’s so much easier to improve product quality and consistency.