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Items: 1 to 20 of 34

1.
2.

Modelling and Validation of Computer Vision Techniques to Assess Heart Rate, Eye Temperature, Ear-Base Temperature and Respiration Rate in Cattle.

Jorquera-Chavez M, Fuentes S, Dunshea FR, Warner RD, Poblete T, Jongman EC.

Animals (Basel). 2019 Dec 6;9(12). pii: E1089. doi: 10.3390/ani9121089.

3.

Bubbles, Foam Formation, Stability and Consumer Perception of Carbonated Drinks: A Review of Current, New and Emerging Technologies for Rapid Assessment and Control.

Viejo CG, Torrico DD, Dunshea FR, Fuentes S.

Foods. 2019 Nov 20;8(12). pii: E596. doi: 10.3390/foods8120596. Review.

4.

Chocolate Quality Assessment Based on Chemical Fingerprinting Using Near Infra-red and Machine Learning Modeling.

Gunaratne TM, Gonzalez Viejo C, Gunaratne NM, Torrico DD, Dunshea FR, Fuentes S.

Foods. 2019 Sep 20;8(10). pii: E426. doi: 10.3390/foods8100426.

5.

Spatial Variability of Aroma Profiles of Cocoa Trees Obtained through Computer Vision and Machine Learning Modelling: A Cover Photography and High Spatial Remote Sensing Application.

Fuentes S, Chacon G, Torrico DD, Zarate A, Gonzalez Viejo C.

Sensors (Basel). 2019 Jul 11;19(14). pii: E3054. doi: 10.3390/s19143054.

6.

Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach.

Fuentes S, Tongson EJ, De Bei R, Gonzalez Viejo C, Ristic R, Tyerman S, Wilkinson K.

Sensors (Basel). 2019 Jul 30;19(15). pii: E3335. doi: 10.3390/s19153335.

7.

D-Tagatose as a Sucrose Substitute and Its Effect on the Physico-Chemical Properties and Acceptability of Strawberry-Flavored Yogurt.

Torrico DD, Tam J, Fuentes S, Gonzalez Viejo C, Dunshea FR.

Foods. 2019 Jul 12;8(7). pii: E256. doi: 10.3390/foods8070256.

8.

Consumer Acceptability, Eye Fixation, and Physiological Responses: A Study of Novel and Familiar Chocolate Packaging Designs Using Eye-Tracking Devices.

Gunaratne NM, Fuentes S, Gunaratne TM, Torrico DD, Ashman H, Francis C, Gonzalez Viejo C, Dunshea FR.

Foods. 2019 Jul 12;8(7). pii: E253. doi: 10.3390/foods8070253.

9.

Physiological Responses to Basic Tastes for Sensory Evaluation of Chocolate Using Biometric Techniques.

Gunaratne TM, Fuentes S, Gunaratne NM, Torrico DD, Gonzalez Viejo C, Dunshea FR.

Foods. 2019 Jul 5;8(7). pii: E243. doi: 10.3390/foods8070243.

10.

Effects of packaging design on sensory liking and willingness to purchase: A study using novel chocolate packaging.

Gunaratne NM, Fuentes S, Gunaratne TM, Torrico DD, Francis C, Ashman H, Gonzalez Viejo C, Dunshea FR.

Heliyon. 2019 Jun 6;5(6):e01696. doi: 10.1016/j.heliyon.2019.e01696. eCollection 2019 Jun.

11.

Chemical characterization of aromas in beer and their effect on consumers liking.

Gonzalez Viejo C, Fuentes S, Torrico DD, Godbole A, Dunshea FR.

Food Chem. 2019 Sep 30;293:479-485. doi: 10.1016/j.foodchem.2019.04.114. Epub 2019 Apr 29.

PMID:
31151637
12.

Computer vision and remote sensing to assess physiological responses of cattle to pre-slaughter stress, and its impact on beef quality: A review.

Jorquera-Chavez M, Fuentes S, Dunshea FR, Jongman EC, Warner RD.

Meat Sci. 2019 Oct;156:11-22. doi: 10.1016/j.meatsci.2019.05.007. Epub 2019 May 7. Review.

PMID:
31121361
13.

Development of emotion lexicons to describe chocolate using the Check-All-That-Apply (CATA) methodology across Asian and Western groups.

Gunaratne TM, Gonzalez Viejo C, Fuentes S, Torrico DD, Gunaratne NM, Ashman H, Dunshea FR.

Food Res Int. 2019 Jan;115:526-534. doi: 10.1016/j.foodres.2018.10.001. Epub 2018 Oct 2. Review.

PMID:
30599974
14.

Cross-cultural effects of food product familiarity on sensory acceptability and non-invasive physiological responses of consumers.

Torrico DD, Fuentes S, Gonzalez Viejo C, Ashman H, Dunshea FR.

Food Res Int. 2019 Jan;115:439-450. doi: 10.1016/j.foodres.2018.10.054. Epub 2018 Oct 22. Review.

PMID:
30599962
15.

Development of a Biosensory Computer Application to Assess Physiological and Emotional Responses from Sensory Panelists.

Fuentes S, Gonzalez Viejo C, Torrico DD, Dunshea FR.

Sensors (Basel). 2018 Sep 5;18(9). pii: E2958. doi: 10.3390/s18092958.

16.

Effects of Three Irrigation Strategies on Gas Exchange Relationships, Plant Water Status, Yield Components and Water Productivity on Grafted Carménère Grapevines.

Zúñiga M, Ortega-Farías S, Fuentes S, Riveros-Burgos C, Poblete-Echeverría C.

Front Plant Sci. 2018 Jul 12;9:992. doi: 10.3389/fpls.2018.00992. eCollection 2018.

17.

Novel techniques to understand consumer responses towards food products: A review with a focus on meat.

Torrico DD, Hutchings SC, Ha M, Bittner EP, Fuentes S, Warner RD, Dunshea FR.

Meat Sci. 2018 Oct;144:30-42. doi: 10.1016/j.meatsci.2018.06.006. Epub 2018 Jun 8. Review.

PMID:
30008336
18.

Non-Contact Heart Rate and Blood Pressure Estimations from Video Analysis and Machine Learning Modelling Applied to Food Sensory Responses: A Case Study for Chocolate.

Gonzalez Viejo C, Fuentes S, Torrico DD, Dunshea FR.

Sensors (Basel). 2018 Jun 3;18(6). pii: E1802. doi: 10.3390/s18061802.

19.

Assessment of Beer Quality Based on a Robotic Pourer, Computer Vision, and Machine Learning Algorithms Using Commercial Beers.

Gonzalez Viejo C, Fuentes S, Torrico DD, Howell K, Dunshea FR.

J Food Sci. 2018 May;83(5):1381-1388. doi: 10.1111/1750-3841.14114. Epub 2018 Mar 30.

PMID:
29603223
20.

The use of infrared thermal imaging as a non-destructive screening tool for identifying drought-tolerant lentil genotypes.

Biju S, Fuentes S, Gupta D.

Plant Physiol Biochem. 2018 Jun;127:11-24. doi: 10.1016/j.plaphy.2018.03.005. Epub 2018 Mar 8.

PMID:
29544209

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