OrangerV1, PascalFrancis, Corpus, bibRecord, 000233

Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy

Identifieur interne : 000233 ( PascalFrancis/Corpus ); précédent : 000232; suivant : 000234

Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy

Auteurs : YONGQIANG ZHENG ; SHAOLAN HE ; SHILAI YI ; ZHIQIN ZHOU ; SHASHA MAO ; XUYANG ZHAO ; LIE DENG

Source :

Scientia horticulturae [ 0304-4238 ] ; 2010.

RBID : Pascal:10-0341400

Descripteurs français

Pascal (Inist)
- Prédiction, Spectrométrie réflexion, Rayonnement visible, Rayonnement IR proche, Spectrométrie IR proche, Méthode non destructive, Fruit, Horticulture, Citrus sinensis.

English descriptors

KwdEn :
- Citrus sinensis, Fruit, Horticulture, Near infrared radiation, Near infrared spectrometry, Non destructive method, Prediction, Reflection spectrometry, Visible radiation.

Abstract

Oleocellosis is a major limiting factor for citrus exports. Therefore, it is important to classify fruit that is sensitive to oleocellosis before storing and shipping the produce. The purpose of this study was to determine the significant wavelengths that could be used to classify fruits susceptible to oleocellosis using "Trovita" sweet orange (Citrus sinensis L.). A spectrophotometer with a wavelength range of 325-1075 nm was used to measure the spectral reflectance data of fruit peels from different harvest times, and a relationship was established between non-destructive visible/near-infrared spectroscopy (VNIRS) measurements and the rates of oleocellosis (RO) and degree of oleocellosis (DO). The data set (absorbance [log 1/R]) was analyzed to build the best predictive model for these characteristics using partial least square (PLS) regression with several spectral pretreatments and multivariate calibration techniques. The RO and DO prediction models (r=0.9836 and 0.9880, respectively) and standard error of prediction (0.0079 and 0.0056 with a bias of -0.0015 and -0.0013, respectively) resulted in excellent predictive ability. The VNIRS technique had significantly greater accuracy for determining the sensitivity of "Trovita" sweet orange to oleocellosis. These results provide fundamental and practical knowledge for the development of a non-destructive, fast, and accurate technology for classifying fruit oleocellosis based on spectral reflectance.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

A01	`01`	`1`		`@0 0304-4238`
A02	`01`			`@0 SHRTAH`
A03		`1`		`@0 Sci. hortic.`
A05				`@2 125`
A06				`@2 3`
A08	`01`	`1`	`ENG`	`@1 Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy`
A11	`01`	`1`		`@1 YONGQIANG ZHENG`
A11	`02`	`1`		`@1 SHAOLAN HE`
A11	`03`	`1`		`@1 SHILAI YI`
A11	`04`	`1`		`@1 ZHIQIN ZHOU`
A11	`05`	`1`		`@1 SHASHA MAO`
A11	`06`	`1`		`@1 XUYANG ZHAO`
A11	`07`	`1`		`@1 LIE DENG`
A14	`01`			`@1 National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences @2 Chongqing 400712 @3 CHN @Z 1 aut. @Z 2 aut. @Z 3 aut. @Z 7 aut.`
A14	`02`			`@1 College of Horticulture and Landscape Architecture, Southwest University @2 Chongqing 400718 @3 CHN @Z 1 aut. @Z 4 aut. @Z 5 aut. @Z 6 aut.`
A20				`@1 401-405`
A21				`@1 2010`
A23	`01`			`@0 ENG`
A43	`01`			`@1 INIST @2 16233 @5 354000181783440350`
A44				`@0 0000 @1 © 2010 INIST-CNRS. All rights reserved.`
A45				`@0 1/4 p.`
A47	`01`	`1`		`@0 10-0341400`
A60				`@1 P`
A61				`@0 A`
A64	`01`	`1`		`@0 Scientia horticulturae`
A66	`01`			`@0 NLD`
C01	`01`		`ENG`	@0 Oleocellosis is a major limiting factor for citrus exports. Therefore, it is important to classify fruit that is sensitive to oleocellosis before storing and shipping the produce. The purpose of this study was to determine the significant wavelengths that could be used to classify fruits susceptible to oleocellosis using "Trovita" sweet orange (Citrus sinensis L.). A spectrophotometer with a wavelength range of 325-1075 nm was used to measure the spectral reflectance data of fruit peels from different harvest times, and a relationship was established between non-destructive visible/near-infrared spectroscopy (VNIRS) measurements and the rates of oleocellosis (RO) and degree of oleocellosis (DO). The data set (absorbance [log 1/R]) was analyzed to build the best predictive model for these characteristics using partial least square (PLS) regression with several spectral pretreatments and multivariate calibration techniques. The RO and DO prediction models (r=0.9836 and 0.9880, respectively) and standard error of prediction (0.0079 and 0.0056 with a bias of -0.0015 and -0.0013, respectively) resulted in excellent predictive ability. The VNIRS technique had significantly greater accuracy for determining the sensitivity of "Trovita" sweet orange to oleocellosis. These results provide fundamental and practical knowledge for the development of a non-destructive, fast, and accurate technology for classifying fruit oleocellosis based on spectral reflectance.
C02	`01`	`X`		`@0 002A32`
C03	`01`	`X`	`FRE`	`@0 Prédiction @5 01`
C03	`01`	`X`	`ENG`	`@0 Prediction @5 01`
C03	`01`	`X`	`SPA`	`@0 Predicción @5 01`
C03	`02`	`X`	`FRE`	`@0 Spectrométrie réflexion @5 02`
C03	`02`	`X`	`ENG`	`@0 Reflection spectrometry @5 02`
C03	`02`	`X`	`SPA`	`@0 Espectrometría reflexión @5 02`
C03	`03`	`X`	`FRE`	`@0 Rayonnement visible @5 03`
C03	`03`	`X`	`ENG`	`@0 Visible radiation @5 03`
C03	`03`	`X`	`SPA`	`@0 Radiación visible @5 03`
C03	`04`	`X`	`FRE`	`@0 Rayonnement IR proche @5 04`
C03	`04`	`X`	`ENG`	`@0 Near infrared radiation @5 04`
C03	`04`	`X`	`SPA`	`@0 Radiación infrarroja cercana @5 04`
C03	`05`	`X`	`FRE`	`@0 Spectrométrie IR proche @5 05`
C03	`05`	`X`	`ENG`	`@0 Near infrared spectrometry @5 05`
C03	`05`	`X`	`SPA`	`@0 Espectrometría IR próximo @5 05`
C03	`06`	`X`	`FRE`	`@0 Méthode non destructive @5 06`
C03	`06`	`X`	`ENG`	`@0 Non destructive method @5 06`
C03	`06`	`X`	`SPA`	`@0 Método no destructivo @5 06`
C03	`07`	`X`	`FRE`	`@0 Fruit @5 07`
C03	`07`	`X`	`ENG`	`@0 Fruit @5 07`
C03	`07`	`X`	`SPA`	`@0 Fruto @5 07`
C03	`08`	`X`	`FRE`	`@0 Horticulture @5 08`
C03	`08`	`X`	`ENG`	`@0 Horticulture @5 08`
C03	`08`	`X`	`SPA`	`@0 Horticultura @5 08`
C03	`09`	`X`	`FRE`	`@0 Citrus sinensis @2 NS @5 10`
C03	`09`	`X`	`ENG`	`@0 Citrus sinensis @2 NS @5 10`
C03	`09`	`X`	`SPA`	`@0 Citrus sinensis @2 NS @5 10`
C07	`01`	`X`	`FRE`	`@0 Rutaceae @2 NS`
C07	`01`	`X`	`ENG`	`@0 Rutaceae @2 NS`
C07	`01`	`X`	`SPA`	`@0 Rutaceae @2 NS`
C07	`02`	`X`	`FRE`	`@0 Dicotyledones @2 NS`
C07	`02`	`X`	`ENG`	`@0 Dicotyledones @2 NS`
C07	`02`	`X`	`SPA`	`@0 Dicotyledones @2 NS`
C07	`03`	`X`	`FRE`	`@0 Angiospermae @2 NS`
C07	`03`	`X`	`ENG`	`@0 Angiospermae @2 NS`
C07	`03`	`X`	`SPA`	`@0 Angiospermae @2 NS`
C07	`04`	`X`	`FRE`	`@0 Spermatophyta @2 NS`
C07	`04`	`X`	`ENG`	`@0 Spermatophyta @2 NS`
C07	`04`	`X`	`SPA`	`@0 Spermatophyta @2 NS`
C07	`05`	`X`	`FRE`	`@0 Agrume @5 31`
C07	`05`	`X`	`ENG`	`@0 Citrus fruit @5 31`
C07	`05`	`X`	`SPA`	`@0 Agrios @5 31`
N21				`@1 221`
N44	`01`			`@1 OTO`
N82				`@1 OTO`

Format Inist (serveur)

NO :	PASCAL 10-0341400 INIST
ET :	Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy
AU :	YONGQIANG ZHENG; SHAOLAN HE; SHILAI YI; ZHIQIN ZHOU; SHASHA MAO; XUYANG ZHAO; LIE DENG
AF :	National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences/Chongqing 400712/Chine (1 aut., 2 aut., 3 aut., 7 aut.); College of Horticulture and Landscape Architecture, Southwest University/Chongqing 400718/Chine (1 aut., 4 aut., 5 aut., 6 aut.)
DT :	Publication en série; Niveau analytique
SO :	Scientia horticulturae; ISSN 0304-4238; Coden SHRTAH; Pays-Bas; Da. 2010; Vol. 125; No. 3; Pp. 401-405; Bibl. 1/4 p.
LA :	Anglais
EA :	Oleocellosis is a major limiting factor for citrus exports. Therefore, it is important to classify fruit that is sensitive to oleocellosis before storing and shipping the produce. The purpose of this study was to determine the significant wavelengths that could be used to classify fruits susceptible to oleocellosis using "Trovita" sweet orange (Citrus sinensis L.). A spectrophotometer with a wavelength range of 325-1075 nm was used to measure the spectral reflectance data of fruit peels from different harvest times, and a relationship was established between non-destructive visible/near-infrared spectroscopy (VNIRS) measurements and the rates of oleocellosis (RO) and degree of oleocellosis (DO). The data set (absorbance [log 1/R]) was analyzed to build the best predictive model for these characteristics using partial least square (PLS) regression with several spectral pretreatments and multivariate calibration techniques. The RO and DO prediction models (r=0.9836 and 0.9880, respectively) and standard error of prediction (0.0079 and 0.0056 with a bias of -0.0015 and -0.0013, respectively) resulted in excellent predictive ability. The VNIRS technique had significantly greater accuracy for determining the sensitivity of "Trovita" sweet orange to oleocellosis. These results provide fundamental and practical knowledge for the development of a non-destructive, fast, and accurate technology for classifying fruit oleocellosis based on spectral reflectance.
CC :	002A32
FD :	Prédiction; Spectrométrie réflexion; Rayonnement visible; Rayonnement IR proche; Spectrométrie IR proche; Méthode non destructive; Fruit; Horticulture; Citrus sinensis
FG :	Rutaceae; Dicotyledones; Angiospermae; Spermatophyta; Agrume
ED :	Prediction; Reflection spectrometry; Visible radiation; Near infrared radiation; Near infrared spectrometry; Non destructive method; Fruit; Horticulture; Citrus sinensis
EG :	Rutaceae; Dicotyledones; Angiospermae; Spermatophyta; Citrus fruit
SD :	Predicción; Espectrometría reflexión; Radiación visible; Radiación infrarroja cercana; Espectrometría IR próximo; Método no destructivo; Fruto; Horticultura; Citrus sinensis
LO :	INIST-16233.354000181783440350
ID :	10-0341400

Links to Exploration step

Pascal:10-0341400

Le document en format XML

<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy</title>
<author><name sortKey="Yongqiang Zheng" sort="Yongqiang Zheng" uniqKey="Yongqiang Zheng" last="Yongqiang Zheng">YONGQIANG ZHENG</name>
<affiliation><inist:fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</inist:fA14>
</affiliation>
<affiliation><inist:fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Shaolan He" sort="Shaolan He" uniqKey="Shaolan He" last="Shaolan He">SHAOLAN HE</name>
<affiliation><inist:fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Shilai Yi" sort="Shilai Yi" uniqKey="Shilai Yi" last="Shilai Yi">SHILAI YI</name>
<affiliation><inist:fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Zhiqin Zhou" sort="Zhiqin Zhou" uniqKey="Zhiqin Zhou" last="Zhiqin Zhou">ZHIQIN ZHOU</name>
<affiliation><inist:fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Shasha Mao" sort="Shasha Mao" uniqKey="Shasha Mao" last="Shasha Mao">SHASHA MAO</name>
<affiliation><inist:fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Xuyang Zhao" sort="Xuyang Zhao" uniqKey="Xuyang Zhao" last="Xuyang Zhao">XUYANG ZHAO</name>
<affiliation><inist:fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Lie Deng" sort="Lie Deng" uniqKey="Lie Deng" last="Lie Deng">LIE DENG</name>
<affiliation><inist:fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">INIST</idno>
<idno type="inist">10-0341400</idno>
<date when="2010">2010</date>
<idno type="stanalyst">PASCAL 10-0341400 INIST</idno>
<idno type="RBID">Pascal:10-0341400</idno>
<idno type="wicri:Area/PascalFrancis/Corpus">000233</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy</title>
<author><name sortKey="Yongqiang Zheng" sort="Yongqiang Zheng" uniqKey="Yongqiang Zheng" last="Yongqiang Zheng">YONGQIANG ZHENG</name>
<affiliation><inist:fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</inist:fA14>
</affiliation>
<affiliation><inist:fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Shaolan He" sort="Shaolan He" uniqKey="Shaolan He" last="Shaolan He">SHAOLAN HE</name>
<affiliation><inist:fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Shilai Yi" sort="Shilai Yi" uniqKey="Shilai Yi" last="Shilai Yi">SHILAI YI</name>
<affiliation><inist:fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Zhiqin Zhou" sort="Zhiqin Zhou" uniqKey="Zhiqin Zhou" last="Zhiqin Zhou">ZHIQIN ZHOU</name>
<affiliation><inist:fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Shasha Mao" sort="Shasha Mao" uniqKey="Shasha Mao" last="Shasha Mao">SHASHA MAO</name>
<affiliation><inist:fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Xuyang Zhao" sort="Xuyang Zhao" uniqKey="Xuyang Zhao" last="Xuyang Zhao">XUYANG ZHAO</name>
<affiliation><inist:fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
<author><name sortKey="Lie Deng" sort="Lie Deng" uniqKey="Lie Deng" last="Lie Deng">LIE DENG</name>
<affiliation><inist:fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</inist:fA14>
</affiliation>
</author>
</analytic>
<series><title level="j" type="main">Scientia horticulturae</title>
<title level="j" type="abbreviated">Sci. hortic.</title>
<idno type="ISSN">0304-4238</idno>
<imprint><date when="2010">2010</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt><title level="j" type="main">Scientia horticulturae</title>
<title level="j" type="abbreviated">Sci. hortic.</title>
<idno type="ISSN">0304-4238</idno>
</seriesStmt>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Citrus sinensis</term>
<term>Fruit</term>
<term>Horticulture</term>
<term>Near infrared radiation</term>
<term>Near infrared spectrometry</term>
<term>Non destructive method</term>
<term>Prediction</term>
<term>Reflection spectrometry</term>
<term>Visible radiation</term>
</keywords>
<keywords scheme="Pascal" xml:lang="fr"><term>Prédiction</term>
<term>Spectrométrie réflexion</term>
<term>Rayonnement visible</term>
<term>Rayonnement IR proche</term>
<term>Spectrométrie IR proche</term>
<term>Méthode non destructive</term>
<term>Fruit</term>
<term>Horticulture</term>
<term>Citrus sinensis</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en">Oleocellosis is a major limiting factor for citrus exports. Therefore, it is important to classify fruit that is sensitive to oleocellosis before storing and shipping the produce. The purpose of this study was to determine the significant wavelengths that could be used to classify fruits susceptible to oleocellosis using "Trovita" sweet orange (Citrus sinensis L.). A spectrophotometer with a wavelength range of 325-1075 nm was used to measure the spectral reflectance data of fruit peels from different harvest times, and a relationship was established between non-destructive visible/near-infrared spectroscopy (VNIRS) measurements and the rates of oleocellosis (RO) and degree of oleocellosis (DO). The data set (absorbance [log 1/R]) was analyzed to build the best predictive model for these characteristics using partial least square (PLS) regression with several spectral pretreatments and multivariate calibration techniques. The RO and DO prediction models (r=0.9836 and 0.9880, respectively) and standard error of prediction (0.0079 and 0.0056 with a bias of -0.0015 and -0.0013, respectively) resulted in excellent predictive ability. The VNIRS technique had significantly greater accuracy for determining the sensitivity of "Trovita" sweet orange to oleocellosis. These results provide fundamental and practical knowledge for the development of a non-destructive, fast, and accurate technology for classifying fruit oleocellosis based on spectral reflectance.</div>
</front>
</TEI>
<inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0304-4238</s0>
</fA01>
<fA02 i1="01"><s0>SHRTAH</s0>
</fA02>
<fA03 i2="1"><s0>Sci. hortic.</s0>
</fA03>
<fA05><s2>125</s2>
</fA05>
<fA06><s2>3</s2>
</fA06>
<fA08 i1="01" i2="1" l="ENG"><s1>Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy</s1>
</fA08>
<fA11 i1="01" i2="1"><s1>YONGQIANG ZHENG</s1>
</fA11>
<fA11 i1="02" i2="1"><s1>SHAOLAN HE</s1>
</fA11>
<fA11 i1="03" i2="1"><s1>SHILAI YI</s1>
</fA11>
<fA11 i1="04" i2="1"><s1>ZHIQIN ZHOU</s1>
</fA11>
<fA11 i1="05" i2="1"><s1>SHASHA MAO</s1>
</fA11>
<fA11 i1="06" i2="1"><s1>XUYANG ZHAO</s1>
</fA11>
<fA11 i1="07" i2="1"><s1>LIE DENG</s1>
</fA11>
<fA14 i1="01"><s1>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences</s1>
<s2>Chongqing 400712</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>2 aut.</sZ>
<sZ>3 aut.</sZ>
<sZ>7 aut.</sZ>
</fA14>
<fA14 i1="02"><s1>College of Horticulture and Landscape Architecture, Southwest University</s1>
<s2>Chongqing 400718</s2>
<s3>CHN</s3>
<sZ>1 aut.</sZ>
<sZ>4 aut.</sZ>
<sZ>5 aut.</sZ>
<sZ>6 aut.</sZ>
</fA14>
<fA20><s1>401-405</s1>
</fA20>
<fA21><s1>2010</s1>
</fA21>
<fA23 i1="01"><s0>ENG</s0>
</fA23>
<fA43 i1="01"><s1>INIST</s1>
<s2>16233</s2>
<s5>354000181783440350</s5>
</fA43>
<fA44><s0>0000</s0>
<s1>© 2010 INIST-CNRS. All rights reserved.</s1>
</fA44>
<fA45><s0>1/4 p.</s0>
</fA45>
<fA47 i1="01" i2="1"><s0>10-0341400</s0>
</fA47>
<fA60><s1>P</s1>
</fA60>
<fA61><s0>A</s0>
</fA61>
<fA64 i1="01" i2="1"><s0>Scientia horticulturae</s0>
</fA64>
<fA66 i1="01"><s0>NLD</s0>
</fA66>
<fC01 i1="01" l="ENG"><s0>Oleocellosis is a major limiting factor for citrus exports. Therefore, it is important to classify fruit that is sensitive to oleocellosis before storing and shipping the produce. The purpose of this study was to determine the significant wavelengths that could be used to classify fruits susceptible to oleocellosis using "Trovita" sweet orange (Citrus sinensis L.). A spectrophotometer with a wavelength range of 325-1075 nm was used to measure the spectral reflectance data of fruit peels from different harvest times, and a relationship was established between non-destructive visible/near-infrared spectroscopy (VNIRS) measurements and the rates of oleocellosis (RO) and degree of oleocellosis (DO). The data set (absorbance [log 1/R]) was analyzed to build the best predictive model for these characteristics using partial least square (PLS) regression with several spectral pretreatments and multivariate calibration techniques. The RO and DO prediction models (r=0.9836 and 0.9880, respectively) and standard error of prediction (0.0079 and 0.0056 with a bias of -0.0015 and -0.0013, respectively) resulted in excellent predictive ability. The VNIRS technique had significantly greater accuracy for determining the sensitivity of "Trovita" sweet orange to oleocellosis. These results provide fundamental and practical knowledge for the development of a non-destructive, fast, and accurate technology for classifying fruit oleocellosis based on spectral reflectance.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>002A32</s0>
</fC02>
<fC03 i1="01" i2="X" l="FRE"><s0>Prédiction</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Prediction</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Predicción</s0>
<s5>01</s5>
</fC03>
<fC03 i1="02" i2="X" l="FRE"><s0>Spectrométrie réflexion</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="ENG"><s0>Reflection spectrometry</s0>
<s5>02</s5>
</fC03>
<fC03 i1="02" i2="X" l="SPA"><s0>Espectrometría reflexión</s0>
<s5>02</s5>
</fC03>
<fC03 i1="03" i2="X" l="FRE"><s0>Rayonnement visible</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="ENG"><s0>Visible radiation</s0>
<s5>03</s5>
</fC03>
<fC03 i1="03" i2="X" l="SPA"><s0>Radiación visible</s0>
<s5>03</s5>
</fC03>
<fC03 i1="04" i2="X" l="FRE"><s0>Rayonnement IR proche</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="ENG"><s0>Near infrared radiation</s0>
<s5>04</s5>
</fC03>
<fC03 i1="04" i2="X" l="SPA"><s0>Radiación infrarroja cercana</s0>
<s5>04</s5>
</fC03>
<fC03 i1="05" i2="X" l="FRE"><s0>Spectrométrie IR proche</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="X" l="ENG"><s0>Near infrared spectrometry</s0>
<s5>05</s5>
</fC03>
<fC03 i1="05" i2="X" l="SPA"><s0>Espectrometría IR próximo</s0>
<s5>05</s5>
</fC03>
<fC03 i1="06" i2="X" l="FRE"><s0>Méthode non destructive</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="X" l="ENG"><s0>Non destructive method</s0>
<s5>06</s5>
</fC03>
<fC03 i1="06" i2="X" l="SPA"><s0>Método no destructivo</s0>
<s5>06</s5>
</fC03>
<fC03 i1="07" i2="X" l="FRE"><s0>Fruit</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="X" l="ENG"><s0>Fruit</s0>
<s5>07</s5>
</fC03>
<fC03 i1="07" i2="X" l="SPA"><s0>Fruto</s0>
<s5>07</s5>
</fC03>
<fC03 i1="08" i2="X" l="FRE"><s0>Horticulture</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="X" l="ENG"><s0>Horticulture</s0>
<s5>08</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Horticultura</s0>
<s5>08</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Citrus sinensis</s0>
<s2>NS</s2>
<s5>10</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Citrus sinensis</s0>
<s2>NS</s2>
<s5>10</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Citrus sinensis</s0>
<s2>NS</s2>
<s5>10</s5>
</fC03>
<fC07 i1="01" i2="X" l="FRE"><s0>Rutaceae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="01" i2="X" l="ENG"><s0>Rutaceae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="01" i2="X" l="SPA"><s0>Rutaceae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="FRE"><s0>Dicotyledones</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="ENG"><s0>Dicotyledones</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="02" i2="X" l="SPA"><s0>Dicotyledones</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="FRE"><s0>Angiospermae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="ENG"><s0>Angiospermae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="03" i2="X" l="SPA"><s0>Angiospermae</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="FRE"><s0>Spermatophyta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="ENG"><s0>Spermatophyta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="04" i2="X" l="SPA"><s0>Spermatophyta</s0>
<s2>NS</s2>
</fC07>
<fC07 i1="05" i2="X" l="FRE"><s0>Agrume</s0>
<s5>31</s5>
</fC07>
<fC07 i1="05" i2="X" l="ENG"><s0>Citrus fruit</s0>
<s5>31</s5>
</fC07>
<fC07 i1="05" i2="X" l="SPA"><s0>Agrios</s0>
<s5>31</s5>
</fC07>
<fN21><s1>221</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
<server><NO>PASCAL 10-0341400 INIST</NO>
<ET>Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy</ET>
<AU>YONGQIANG ZHENG; SHAOLAN HE; SHILAI YI; ZHIQIN ZHOU; SHASHA MAO; XUYANG ZHAO; LIE DENG</AU>
<AF>National Engineering Research Center for Citrus Technology, Citrus Research Institute, Southwest University-Chinese Academy of Agricultural Sciences/Chongqing 400712/Chine (1 aut., 2 aut., 3 aut., 7 aut.); College of Horticulture and Landscape Architecture, Southwest University/Chongqing 400718/Chine (1 aut., 4 aut., 5 aut., 6 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Scientia horticulturae; ISSN 0304-4238; Coden SHRTAH; Pays-Bas; Da. 2010; Vol. 125; No. 3; Pp. 401-405; Bibl. 1/4 p.</SO>
<LA>Anglais</LA>
<EA>Oleocellosis is a major limiting factor for citrus exports. Therefore, it is important to classify fruit that is sensitive to oleocellosis before storing and shipping the produce. The purpose of this study was to determine the significant wavelengths that could be used to classify fruits susceptible to oleocellosis using "Trovita" sweet orange (Citrus sinensis L.). A spectrophotometer with a wavelength range of 325-1075 nm was used to measure the spectral reflectance data of fruit peels from different harvest times, and a relationship was established between non-destructive visible/near-infrared spectroscopy (VNIRS) measurements and the rates of oleocellosis (RO) and degree of oleocellosis (DO). The data set (absorbance [log 1/R]) was analyzed to build the best predictive model for these characteristics using partial least square (PLS) regression with several spectral pretreatments and multivariate calibration techniques. The RO and DO prediction models (r=0.9836 and 0.9880, respectively) and standard error of prediction (0.0079 and 0.0056 with a bias of -0.0015 and -0.0013, respectively) resulted in excellent predictive ability. The VNIRS technique had significantly greater accuracy for determining the sensitivity of "Trovita" sweet orange to oleocellosis. These results provide fundamental and practical knowledge for the development of a non-destructive, fast, and accurate technology for classifying fruit oleocellosis based on spectral reflectance.</EA>
<CC>002A32</CC>
<FD>Prédiction; Spectrométrie réflexion; Rayonnement visible; Rayonnement IR proche; Spectrométrie IR proche; Méthode non destructive; Fruit; Horticulture; Citrus sinensis</FD>
<FG>Rutaceae; Dicotyledones; Angiospermae; Spermatophyta; Agrume</FG>
<ED>Prediction; Reflection spectrometry; Visible radiation; Near infrared radiation; Near infrared spectrometry; Non destructive method; Fruit; Horticulture; Citrus sinensis</ED>
<EG>Rutaceae; Dicotyledones; Angiospermae; Spermatophyta; Citrus fruit</EG>
<SD>Predicción; Espectrometría reflexión; Radiación visible; Radiación infrarroja cercana; Espectrometría IR próximo; Método no destructivo; Fruto; Horticultura; Citrus sinensis</SD>
<LO>INIST-16233.354000181783440350</LO>
<ID>10-0341400</ID>
</server>
</inist>
</record>

Pour manipuler ce document sous Unix (Dilib)

EXPLOR_STEP=$WICRI_ROOT/Wicri/Bois/explor/OrangerV1/Data/PascalFrancis/Corpus

HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000233 | SxmlIndent | more

HfdSelect -h $EXPLOR_AREA/Data/PascalFrancis/Corpus/biblio.hfd -nk 000233 | SxmlIndent | more

Pour mettre un lien sur cette page dans le réseau Wicri

{{Explor lien
   |wiki=    Wicri/Bois
   |area=    OrangerV1
   |flux=    PascalFrancis
   |étape=   Corpus
   |type=    RBID
   |clé=     Pascal:10-0341400
   |texte=   Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy
}}

This area was generated with Dilib version V0.6.25.
Data generation: Sat Dec 3 17:11:04 2016. Site generation: Wed Mar 6 18:18:32 2024

	Serveur d'exploration sur l'oranger
	Attention, ce site est en cours de développement ! Attention, site généré par des moyens informatiques à partir de corpus bruts. Les informations ne sont donc pas validées.

Serveur d'exploration sur l'oranger

Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy

Predicting oleocellosis sensitivity in citrus using VNIR reflectance spectroscopy

Source :

Descripteurs français

English descriptors

Abstract

Notice en format standard (ISO 2709)

Format Inist (serveur)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri