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Navigating the Era of Neo-Heirloom Tomatoes (Solanum lycopersicum L.) : = Developing an Heirloom Market Type Classifier Using High-Throughput Phenomics and Machine Learning.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Navigating the Era of Neo-Heirloom Tomatoes (Solanum lycopersicum L.) :/
Reminder of title:	Developing an Heirloom Market Type Classifier Using High-Throughput Phenomics and Machine Learning.
Author:	Bryant, Giselle D'Aubin.
Description:	1 online resource (86 pages)
Notes:	Source: Masters Abstracts International, Volume: 84-04.
Contained By:	Masters Abstracts International84-04.
Subject:	Agriculture. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29324062click for full text (PQDT)
ISBN:	9798352935095

Navigating the Era of Neo-Heirloom Tomatoes (Solanum lycopersicum L.) : = Developing an Heirloom Market Type Classifier Using High-Throughput Phenomics and Machine Learning.
Bryant, Giselle D'Aubin.

Navigating the Era of Neo-Heirloom Tomatoes (Solanum lycopersicum L.) :Developing an Heirloom Market Type Classifier Using High-Throughput Phenomics and Machine Learning. - 1 online resource (86 pages)

Source: Masters Abstracts International, Volume: 84-04.

Thesis (M.S.)--University of Hawai'i at Manoa, 2022.

Includes bibliographical references

Although there are various informal definitions for heirloom tomatoes (Solanum lycopersicum L.), there is no official botanical classification or certification scheme. Novel hybrid cultivars advertised as 'heirloom-like' exemplify the term's application as a phenotypic descriptor, departing from the term's established conceptions. Two field trials were conducted in Hawai'i to screen cultivars representing traditional heirlooms, heirloom hybrids, and commercial cultivars to explore this concept. We observed significant differences in total and marketable yields (kg/plant) within and between three tomato market classes. Phenotypic traits related to fruit morphology, color, and physicochemical quality were used to develop a Multilayer Perceptron Neural Network (MLPNN) classifier to investigate whether the heirloom archetype could be defined. The model could distinguish between traditional heirlooms, heirloom hybrids, and commercial cultivars with an accuracy rate of 85%. Global and local agnostic tests identified traits for physicochemical quality, color, distal end shape, blockiness, and the latitudinal section as most influential for distinguishing the heirloom class. This study demonstrated that a wide range of phenotypic traits could be selected to target the heirloom ideotype; however, quality standards should be considered to preserve the integrity and value of the heirloom insignia.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798352935095Subjects--Topical Terms:

518588
Agriculture.
Subjects--Index Terms:

ClassificationIndex Terms--Genre/Form:

542853
Electronic books.

Navigating the Era of Neo-Heirloom Tomatoes (Solanum lycopersicum L.) : = Developing an Heirloom Market Type Classifier Using High-Throughput Phenomics and Machine Learning.
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502 $a Thesis (M.S.)--University of Hawai'i at Manoa, 2022.
504 $a Includes bibliographical references
520 $a Although there are various informal definitions for heirloom tomatoes (Solanum lycopersicum L.), there is no official botanical classification or certification scheme. Novel hybrid cultivars advertised as 'heirloom-like' exemplify the term's application as a phenotypic descriptor, departing from the term's established conceptions. Two field trials were conducted in Hawai'i to screen cultivars representing traditional heirlooms, heirloom hybrids, and commercial cultivars to explore this concept. We observed significant differences in total and marketable yields (kg/plant) within and between three tomato market classes. Phenotypic traits related to fruit morphology, color, and physicochemical quality were used to develop a Multilayer Perceptron Neural Network (MLPNN) classifier to investigate whether the heirloom archetype could be defined. The model could distinguish between traditional heirlooms, heirloom hybrids, and commercial cultivars with an accuracy rate of 85%. Global and local agnostic tests identified traits for physicochemical quality, color, distal end shape, blockiness, and the latitudinal section as most influential for distinguishing the heirloom class. This study demonstrated that a wide range of phenotypic traits could be selected to target the heirloom ideotype; however, quality standards should be considered to preserve the integrity and value of the heirloom insignia.
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