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Improvement of Tomato Breeding Selection Capabilities using Vibrational Spectroscopy and Prediction Algorithms

Akpolat, Hacer
http://orcid.org/0000-0002-8335-9005
http://rave.ohiolink.edu/etdc/view?acc_num=osu1574812034661898

Abstract Details

2019, Doctor of Philosophy, Ohio State University, Food Science and Technology.
Tomatoes are one of the most consumed vegetables throughout the world delivering important nutrients as a widely available and cost-effective option. When 2010 Dietary guidelines were released with an effort to increase vegetable consumption, tomatoes were moved from “other vegetables” subgroup to the newly created “red-orange vegetables” subgroup as a nutritionally dense, widely available and affordable vegetable option for a healthy diet. Domestication and breeding for yield, size, disease resistance caused unexpected negative consequences, and the lack of aroma and taste has become a major complaint among consumers of modern tomato varieties. The overall objective of this research was to develop rapid and effective methods based on vibrational spectroscopy to improve tomato breeding selections in terms of improving tomato taste and flavor as well as color and nutritionally important components of tomatoes. In the first chapter, a background and literature review are given on tomatoes and breeding. A comprehensive review is given on vibrational spectroscopy and applications in food industry, and two independent experimental studies are presented. The first study focused on development of a rapid technique based on infrared spectroscopy to use in field applications in order to improve the selection of new tomato varieties with desired levels of chemical traits which are related to tomato flavor and aroma. In this part of the study, predictive regression algorithms were developed using portable FTIR devices with different sampling approaches to find the best application to utilize in breeding industry. Multiple quality traits were simultaneously determined by using a single drop of sample providing fast (<1 min) measurements and minimal sample preparation based on unique spectral fingerprints. The prediction models were then validated successfully with external set of samples. The second part of study investigated the identification of major tomato carotenoids non-destructively using Raman spectroscopy combined with linear and non-linear chemometrics techniques. Findings indicated that portable Raman spectroscopy can be applied successfully to profile and quantify the major tomato carotenoids in genetically-diverse tomatoes. Non-destructive evaluation of tomato carotenoids can be useful for tomato breeders as a simple and rapid tool for developing new varieties with different health benefits and colors varying from yellow to orange. As a conclusion, this research study overall demonstrated the value of portable vibrational spectroscopy techniques in determining the quality traits of tomatoes whether it is related to organoleptic or nutritional quality of fresh market tomatoes.
Luis Rodriguez-Saona, Dr (Advisor)
Christopher Simons, Dr (Committee Member)
Monica Giusti, Dr (Committee Member)
Rafael Jimenez-Flores, Dr (Committee Member)
Jeff Hattey, Dr (Other)
201 p.
Food Science
vibrational spectroscopy; infrared spectroscopy; Raman spectroscopy; portable sensors; tomato breeding; chemometrics

Recommended Citations

Citations

  • Akpolat, H. (2019). Improvement of Tomato Breeding Selection Capabilities using Vibrational Spectroscopy and Prediction Algorithms [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574812034661898

    APA Style (7th edition)

  • Akpolat, Hacer. Improvement of Tomato Breeding Selection Capabilities using Vibrational Spectroscopy and Prediction Algorithms. 2019. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1574812034661898.

    MLA Style (8th edition)

  • Akpolat, Hacer. "Improvement of Tomato Breeding Selection Capabilities using Vibrational Spectroscopy and Prediction Algorithms." Doctoral dissertation, Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574812034661898

    Chicago Manual of Style (17th edition)

osu1574812034661898
305
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This open access ETD is published by The Ohio State University and OhioLINK.