東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Food process control based on sensor...

Kupongsak, Sasikan.

Linked to FindBook

Google Book

Amazon

博客來

Food process control based on sensory evaluations.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Food process control based on sensory evaluations./
Author:	Kupongsak, Sasikan.
Description:	141 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-12, Section: B, page: 5854.
Contained By:	Dissertation Abstracts International64-12B.
Subject:	Agriculture, Food Science and Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3115564
ISBN:	0496630510

Food process control based on sensory evaluations.
Kupongsak, Sasikan.

Food process control based on sensory evaluations. - 141 p.

Source: Dissertation Abstracts International, Volume: 64-12, Section: B, page: 5854.

Thesis (Ph.D.)--University of Missouri - Columbia, 2003.

Sensory evaluations are often the ultimate measure of quality for many food products but food process controls rely on instrumental measurements. Effective techniques are needed to map desired sensory quality targets into instrumental process set points. In this research, fuzzy set and neural network techniques were used to determine food process set points that would produce products of certain desirable sensory quality. Fuzzy sets were applied to represent the intrinsic fuzzy characteristics of sensory responses without unverifiable assumptions, and neural networks were used to model the relationship between process and sensory variables. Rice cake production was used as a model process. Product sensory attributes were evaluated by a trained panel. Multi-judge responses were formulated as fuzzy membership vectors, which in turn were formed into fuzzy membership matrices of multiple sensory attributes. Multi-input multi-output (MIMO) neural networks were successfully used to determine process control set points for the manipulatable and instrumentally measurable variables. Experimental validation showed that the process set points led to products with desired sensory attributes.

ISBN: 0496630510Subjects--Topical Terms:

1017813
Agriculture, Food Science and Technology.

Food process control based on sensory evaluations.
LDR:02040nmm 2200265 4500 001 1836805
005 20050315121047.5
008 130614s2003 eng d
020 $a 0496630510
035 $a (UnM)AAI3115564
035 $a AAI3115564
040 $a UnM $c UnM
100 1 $a Kupongsak, Sasikan. $3 1925270
245 1 0 $a Food process control based on sensory evaluations.
300 $a 141 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-12, Section: B, page: 5854.
500 $a Supervisor: Jinglu Tan.
502 $a Thesis (Ph.D.)--University of Missouri - Columbia, 2003.
520 $a Sensory evaluations are often the ultimate measure of quality for many food products but food process controls rely on instrumental measurements. Effective techniques are needed to map desired sensory quality targets into instrumental process set points. In this research, fuzzy set and neural network techniques were used to determine food process set points that would produce products of certain desirable sensory quality. Fuzzy sets were applied to represent the intrinsic fuzzy characteristics of sensory responses without unverifiable assumptions, and neural networks were used to model the relationship between process and sensory variables. Rice cake production was used as a model process. Product sensory attributes were evaluated by a trained panel. Multi-judge responses were formulated as fuzzy membership vectors, which in turn were formed into fuzzy membership matrices of multiple sensory attributes. Multi-input multi-output (MIMO) neural networks were successfully used to determine process control set points for the manipulatable and instrumentally measurable variables. Experimental validation showed that the process set points led to products with desired sensory attributes.
590 $a School code: 0133.
650 4 $a Agriculture, Food Science and Technology. $3 1017813
690 $a 0359
710 2 0 $a University of Missouri - Columbia. $3 1017522
773 0 $t Dissertation Abstracts International $g 64-12B.
790 1 0 $a Tan, Jinglu, $e advisor
790 $a 0133
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3115564