Cluster analysis of citrus genotypes using near-infrared spectroscopy

Liao, Qiuhong; Huang, Yanbo; He, Shuang-Hui; Xie, Rui; Lu, Qiang; Yi, Shilai; Zheng, Yongqiang; Tian, Xi; Deng, Lie; Qian, Chun

doi:10.1080/10798587.2013.824719

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…Moreover, in actual manufacture and storage stages, it has been employed as the most important internal feature for grading and quality evaluation. Near-infrared (NIR) spectroscopy combined with chemometrics is a fast, accurate, non-destructive technique relatively easy to implement, moreover, NIR is well-established for internal quality analysis in food industries, in particular for the intact fruits such as apple (Lammertyn, Nicolaï, Ooms, De Smedt, & De Baerdemaeker, 1998;Mendoza, Lu, & Cen, 2012;Zhang, Xu, & Gu, 2014;Zhu et al, 2007), pear (Nicolaï et al, 2008;Li, Huang, Zhao, & Zhang, 2013), peach (Carlomagno, Capozzo, Attolico, & Distante, 2004;Golding, Satyan, Liebenberg, Walsh, & McGlasson, 2006), mango (Jha et al, 2012;Saranwong, Sornsrivichai, & Kawano, 2001;Subedi, Walsh, & Owens, 2007), citrus (Liao et al, 2013;Magwaza et al, 2012) and other fruits Nicolaï et al, 2007). Many researchers focused on developing NIR model using one or more varieties harvest during the year.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Informative Spectral Regions in FT-NIR Spectroscopy for Measuring the Soluble Solids Content of Apple

Wang

Cheng

Liu

et al. 2015

Intelligent Automation & Soft Computing

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A novel potential method, linear combination weight PLS (LCW-PLS) model, was suggested for improving the performance of routine PLS model based on selected informative regions. Moving window partial least squares (MWPLS), genetic algorithms interval partial least squares (GAiPLS) and synergy interval partial least squares (SiPLS) were used to optimize informative spectral regions from FT-NIR spectra. A total of 660 apples harvested at 2006, 2007 and 2008, were divided into calibration and prediction sets by Kennard-Stone method. The best calibration model was obtained by LCW-PLS method based on informative spectral regions of 4328-4787, 5323-5512, 5982-7135 and 7159-7463 cm 21 selected by MWPLS procedure, and corresponding weights of 0.004, 0.070, 0.066 and 0.860, respectively. The LCW-MWPLS model was applied to predict samples, the prediction results were with R P of 0.942, RMSEP of 0.649 %Brix and RPD P of 3.10. In addition, developed LCW-MWPLS model using random two years samples was used to predict one year samples excluded. The predictive results were with R P of 0.921-0.927, RMSEP of 0.714-0.795 %Brix and RPD P of 2.44-2.88. The LCW-MWPLS model giving a prediction error equal to 4% of fresh weight was sufficiently accurate to determine the SSC of apple non-destructively.

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Section: Introductionmentioning

confidence: 99%

Optimization of Informative Spectral Regions in FT-NIR Spectroscopy for Measuring the Soluble Solids Content of Apple

Wang

Cheng

Liu

et al. 2015

Intelligent Automation & Soft Computing

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“…However, characteristics such as sexual compatibility between citrus and related genera, the high frequency of bud mutations, the long history of cultivation and wide dispersion make it very rich in citrus germplasm. On the other hand, it is quite complicated, controversial and confusing in citrus germplasm identification, taxonomic and phylogenetic relationships Liao et al (2013). Studies on citrus germplasm identification, taxonomic and phylogenetic relationships were carried out.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Phylogenetic Relationships of Main Citrus Germplasms Based on Ftir Spectra of Petals

Li¹,

Yi²,

Zheng³

et al. 2015

Intelligent Automation & Soft Computing

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To develop a quick, accurate and reliable technique for studying phylogenetic relationship of Citrus, FTIR (Fourier transform infrared spectroscopy) technique was used. The petals spectra of eighteen varieties of citrus germplasms were investigated by FTIR. Pretreatment methods of raw spectra (2000-500 cm 21 ) were composed of baseline correction, normalize and first derivative (Savitzky-Golay). We used One-way ANOVA (analysis of variance) and Tukey's HSD (honestly significant difference) to extract effective wave bands, where the spectral absorbance values of different citrus germplasms were significantly different. The results showed that 2000 , 1831 cm 21 , 1763 , 1595 cm 21 , 1517 , 1090 cm 21 , 1035 , 1024 cm 21 , 950 , 935 cm 21 , 861 , 784 cm 21 , 744 , 721 cm 21 and 653 , 608 cm 21 were the effective wave bands. HCA (hierarchical cluster analysis) was adopted to classify citrus germplasms based on the above eight effective wave bands. It was found that eighteen citrus varieties were classified into six subgroups. The results of classification and citrus phylogenetic relationships between six subgroups were consistent of results from Morphology, Biochemistry, Cytology and Molecular Biology. The overall results demonstrated that fourier transform infrared spectroscopy technique with One-way ANOVA and Tukey's HSD and hierarchical cluster analysis model were promising for the rapid, accurate and reliable classification for citrus as well as studying citrus phylogenetic relationship.

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Study on the optimal algorithm prediction of corn leaf component information based on hyperspectral imaging

Wang

et al. 2016

Infrared Physics & Technology

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Cluster analysis of citrus genotypes using near-infrared spectroscopy

Cited by 4 publications

References 25 publications

Optimization of Informative Spectral Regions in FT-NIR Spectroscopy for Measuring the Soluble Solids Content of Apple

Optimization of Informative Spectral Regions in FT-NIR Spectroscopy for Measuring the Soluble Solids Content of Apple

Analysis of Phylogenetic Relationships of Main Citrus Germplasms Based on Ftir Spectra of Petals

Study on the optimal algorithm prediction of corn leaf component information based on hyperspectral imaging

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