語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Use of near-infrared spectroscopy fo...
~
Cheewapramong, Panjama.
FindBook
Google Book
Amazon
博客來
Use of near-infrared spectroscopy for qualitative and quantitative analyses of grains and cereal products.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Use of near-infrared spectroscopy for qualitative and quantitative analyses of grains and cereal products./
作者:
Cheewapramong, Panjama.
面頁冊數:
168 p.
附註:
Adviser: Randy L. Wehling.
Contained By:
Dissertation Abstracts International68-12B.
標題:
Agriculture, Food Science and Technology. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3293917
ISBN:
9780549383482
Use of near-infrared spectroscopy for qualitative and quantitative analyses of grains and cereal products.
Cheewapramong, Panjama.
Use of near-infrared spectroscopy for qualitative and quantitative analyses of grains and cereal products.
- 168 p.
Adviser: Randy L. Wehling.
Thesis (Ph.D.)--The University of Nebraska - Lincoln, 2007.
The purpose of the first part of the study was to develop a simplified near-infrared reflectance (NIR) spectroscopy method for detecting insect larvae in individual wheat kernels. Discriminant analysis, based on Mahalanobis distances calculated from log 1/R data at only four discrete wavelengths, yielded better results for classification of sound and insect infested wheat kernels than principal component analysis (PCA) using the spectral region from 1100 to 1900 nm. This simplified technique was then used to detect 3- and 4-week-old larvae of granary and maize weevils in wheat kernels. A model developed from a calibration set containing sound kernels and kernels infested with 3- week-old larvae was applied to a validation set containing sound kernels, sound air-dried kernels, kernels containing 3-week-old larvae of granary and maize weevils, kernels containing 4-week-old larvae of granary and maize weevils, and infested air-dried kernels containing dead larvae of both species. Correct classification rates of 92, 98, 77, 73, 95, 98, 96, and 94%, respectively, were achieved. Additionally, 99% of sound kernels from ten different wheat varieties were correctly classified into their respective classes. First and second derivative spectral treatments did not improve classification results for 3-week-old infested kernels.
ISBN: 9780549383482Subjects--Topical Terms:
1017813
Agriculture, Food Science and Technology.
Use of near-infrared spectroscopy for qualitative and quantitative analyses of grains and cereal products.
LDR
:03345nam 2200277 a 45
001
938967
005
20110512
008
110512s2007 eng d
020
$a
9780549383482
035
$a
(UMI)AAI3293917
035
$a
AAI3293917
040
$a
UMI
$c
UMI
100
1
$a
Cheewapramong, Panjama.
$3
1262944
245
1 0
$a
Use of near-infrared spectroscopy for qualitative and quantitative analyses of grains and cereal products.
300
$a
168 p.
500
$a
Adviser: Randy L. Wehling.
500
$a
Source: Dissertation Abstracts International, Volume: 68-12, Section: B, page: 7723.
502
$a
Thesis (Ph.D.)--The University of Nebraska - Lincoln, 2007.
520
$a
The purpose of the first part of the study was to develop a simplified near-infrared reflectance (NIR) spectroscopy method for detecting insect larvae in individual wheat kernels. Discriminant analysis, based on Mahalanobis distances calculated from log 1/R data at only four discrete wavelengths, yielded better results for classification of sound and insect infested wheat kernels than principal component analysis (PCA) using the spectral region from 1100 to 1900 nm. This simplified technique was then used to detect 3- and 4-week-old larvae of granary and maize weevils in wheat kernels. A model developed from a calibration set containing sound kernels and kernels infested with 3- week-old larvae was applied to a validation set containing sound kernels, sound air-dried kernels, kernels containing 3-week-old larvae of granary and maize weevils, kernels containing 4-week-old larvae of granary and maize weevils, and infested air-dried kernels containing dead larvae of both species. Correct classification rates of 92, 98, 77, 73, 95, 98, 96, and 94%, respectively, were achieved. Additionally, 99% of sound kernels from ten different wheat varieties were correctly classified into their respective classes. First and second derivative spectral treatments did not improve classification results for 3-week-old infested kernels.
520
$a
NIR spectroscopy was also used to predict the degree of cook in products produced by HTST extrusion of corn meal. Corn meal was cooked with a Wenger TX-57 twin screw extruder using screw speeds ranging from 250 to 350 rpm, and moisture contents ranging from 13-20%, providing a wide range of pressures and shear conditions in the extruder barrel. Extruded samples were analyzed using reference methods that measure different aspects of cooking, including water absorption index (WAI), water solubility index (WSI), viscosity profile as measured with a Rapid Viscoanalyzer (RVA), hardness and fracturability as measured by Texture Profile Analysis. Calibrations for each parameter were developed using multiple linear regression (MLR) and partial least squares (PLS) regression. Correlations with r-value>0.95 were achieved between the NIR and laboratory values. Relative predictive determinant (RPD) values ranged from 5.3 to 6.3 for the various parameters (except for hardness, and trough viscosity) indicating that the NIR measurements should be useful in quality control applications.
590
$a
School code: 0138.
650
4
$a
Agriculture, Food Science and Technology.
$3
1017813
690
$a
0359
710
2 0
$a
The University of Nebraska - Lincoln.
$b
Food Science & Technology.
$3
1262945
773
0
$t
Dissertation Abstracts International
$g
68-12B.
790
$a
0138
790
1 0
$a
Wehling, Randy L.,
$e
advisor
791
$a
Ph.D.
792
$a
2007
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3293917
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9109155
電子資源
11.線上閱覽_V
電子書
EB W9109155
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入