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Aurora Saulo (TPSS) and her co-authors applied the app BimiLeap to the emerging science of Mind Genomics to study which messages on food labels with geographical indications are perceived by respondents as truthful or misleading. They recently published the results in the journal Advances in Nutrition and Food Science, indicating that respondents considered it truthful when the name or brand or vignette of the product is consistent with the manufacturer’s location as declared on the package. A clustering program identified two mindsets, both of which agreed on the need for truthful and honest food labels with geographical indications.
HNFAS grad student Sanjeev Wasti received the Certificate of Excellence for the best research and presentation in the Nutrition and Metabolism section at the 2019 Poultry Science Association meeting in Montreal, Canada. Sanjeev is working towards his master’s degree in Animal Sciences under the mentorship of Birendra Mishra (left).
Kyle Caires (HNFAS) recently presented an important breakthrough stemming from his reproductive physiology research at the XXIII Brazilian Congress of Animal Reproduction held in Gramado, RS, Brazil. This project involved research trials using classic and contemporary techniques in embryology to improve embryo production in Wagyu cows.
A potentially historic collaborative project between CTAHR and the College of Engineering hit a triumphant milestone when the Box Farm project won 1st place in the Francis Rhodes Montgomery Design Competition. Kent Kobayashi (TPSS) advised the team of Mechanical Engineering and Biology students in creating a fully automated, robotically controlled hydroponic growing system that could be used to provide fresh produce for astronauts on lunar and Mars missions.
Travis Idol and Adel Youkhana (both NREM) recently published a helpful paper detailing an easy and accurate protocol for estimating coffee yield in Hawai‘i. “A Rapid Visual Estimation of Fruits per Lateral to Predict Coffee Yield in Hawaii,” published in Agroforestry Systems Journal, allows farmers to predict the amount of their crop, a crucial task and an ongoing challenge, with less cost, time and labor.