Estimation of Oil Content and Fatty Acid Composition in Cottonseed Kernel Powder Using Near Infrared Reflectance Spectroscopy

Quampah, Alfred; Huang, Zhuangrong; Wu, Jian; Liu, Hai Ying; Li, Jin Rong; Zhu, Shuhua; Shi, Chun Hai

doi:10.1007/s11746-011-1945-2

Cited by 28 publications

(29 citation statements)

References 22 publications

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“…Spectral coverage was in the 1,100-2,500 nm wavelength band. Elfadl et al (2010) with safflower (R 2 = 0.90) and Quampah et al (2012) with cotton (R 2 = 0.99) were other authors who have reported interesting results working in the spectral band of wavelengths above 1,100 nm. Velasco et al (1999b), in similar work with seeds from the Brassicaceae germplasm, developed a model for the prediction of oil content having an R 2 equal to 0.97.…”

Section: Also Inmentioning

confidence: 94%

“…This assumes that the use of many LVs, more than nine, increases the error and lowers the predictive robustness of the VIS-NIR model. Quampah et al (2012), Liu et al (2009), Sivakesava and Irudayaraj (2002) and Swierenga et al (1999) consider that over-adjusted models can be avoided by selecting the optimal number of LVs using the minimum RMSECV, with a relatively high R 2 . .…”

Section: Effect Of Pre-treatment Of the Spectral Datamentioning

confidence: 99%

“…These results suggest the good predictive ability of the model. Quampah et al (2012), Moghimi et al (2010) and Liu et al (2009) consider that the best model presents high values for R 2 and low values for RMSEC and RMSEP. Table 3 are presented the statistical results of the external validation, which were consistent with the results seen for the calibration set, recording values for R 2 p of 0.7760 and RMSEP of 7.081.…”

Section: Effect Of Pre-treatment Of the Spectral Datamentioning

confidence: 99%

“…To assess the productive potential of different genotypes, qualitative and quantitative chemical analyses of the fruit of the macauba palm are required. However one of the difficulties faced by researchers is being able to access this information in the fruit due to the laborious and expensive processes of conventional methods of evaluation (QUAMPAH et al, 2012). For example, the evaluation of a single sample to determine the oil content using the standard method, Soxhlet, requires approximately 50 hours between prior preparation of the sample and the extraction itself, without taking into consideration that the solvent (n-hexane) used for extraction of the oil is toxic and polluting.…”

Section: Introductionmentioning

confidence: 99%

“…In several studies, the use of VIS-NIR spectrometry has been proposed in the development of models for the prediction of the oil content of various oilseeds: sunflower (PÉREZ-VICH et al, 1998), rapeseed (VELASCO et al, 1999a, Brassicaceae (VELASCO et al, 1999b), safflower (ELFADL et al, 2010;RUDOLPHI et al, 2012), Jatropha (VAKNIN et al, 2011) and cotton (QUAMPAH et al, 2012). However, to date there are no reports of its application on specific fruit fractions, such as palm mesocarp.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of oil content in the mesocarp of fruit from the macauba palm using spectrometry1

Matsimbe¹,

Motoike²,

Pinto³

et al. 2015

Rev. Ciênc. Agron.

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-In the present work a model was developed for the prediction of the oil content of the mesocarp of fruit from the macauba palm, using visible and near infrared spectrometry. Reference values were determined the by Soxhlet method. The model was calibrated using spectral data from the mesocarp of macauba fruit by partial least squares regression, considering nine latent variables. The results of the calibration series were consistent with those of the validation series, registering an The coefficient of determination between the reference method and the developed model, systematic error between the predicted values and the measured values and root mean square error, for calibration and validation with independent data, respectively, equal to 0.8223, -9.2-14 and 5.917 and 0.7760, 7.081 and -0.064. VIS-NIR spectroscopy is a viable tool in the evaluation of genotypes in breeding programs for the macauba palm.Key words: Acrocomia aculeata. Quantification of the oil. VIS-NIR model calibration. RESUMO -No presente trabalho, foi desenvolvido um modelo para a predição do teor de óleo do mesocarpo nos frutos de macaúba, usando a espectrometria do visível e infravermelho próximo. Os valores de referência foram determinados pelo método soxhlet. O modelo foi calibrado usando dados espectrais do mesocarpo dos frutos de macaúba pela regressão por mínimos quadrados parciais, considerando nove variáveis latentes. Os resultados da série da calibração foram consistentes com os da série da validação, registrando o coeficiente de determinação entre o método referencia e o modelo desenvolvido, erro sistemático entre os valores preditos e os valores mensurados e a raiz quadrada do erro médio quadrático entre o método referência e o modelo desenvolvido, de 0,8223, -9,2-14 e 5,917 e de 0,7760, -0,064 e 7,081, para a calibração e validação respectivamente. A espectrometria VIS-NIR é viável como ferramenta de avaliação de genótipos em programas do melhoramento de macaúba.Palavras-chave: Acrocomia aculeata. Quantificação do óleo. Calibração de modeloVIS-NIR.

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Section: Also Inmentioning

confidence: 94%

Section: Effect Of Pre-treatment Of the Spectral Datamentioning

confidence: 99%

Section: Effect Of Pre-treatment Of the Spectral Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Prediction of oil content in the mesocarp of fruit from the macauba palm using spectrometry1

Matsimbe¹,

Motoike²,

Pinto³

et al. 2015

Rev. Ciênc. Agron.

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Estimation of Protein and Fatty Acid Composition in Shell‐Intact Cottonseed by Near Infrared Reflectance Spectroscopy

Wang

Xing

Liu

et al. 2019

J Americ Oil Chem Soc

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Rapid and accurate analysis of cottonseed protein content and the composition of fatty acids (especially, saturated fatty acids) is often required in cotton production and breeding programs. This study aimed to establish a set of effective estimation models for these parameters. Near infrared reflectance spectroscopy (NIRS) calibration equations using partial least‐squares regression for protein concentration, oil concentration, and five fatty acids of shell‐intact cottonseeds were established based on 90 varieties, and the prediction abilities of the calibration models were verified using 45 other varieties. The prediction abilities of the NIRS calibration equations were basically consistent with external validation results. Each equation was assessed based on the ratio of performance to deviation (RPDp). Protein content and seed total fatty acid (STA) content had high RPDp values (3.687 and 3.530, respectively), whereas cottonseed kernel total fatty acid (KTA) content, linoleic acid (18:2), stearic acid (18:0), myristic acid (14:0), and palmitic acid (16:0) exhibited relatively high RPDp (2.866, 2.836, 2.697, 2.676, and 2.506, respectively). The calibration model for oleic acid (18:1) had a low RPDp (1.945). The results indicated that NIRS can be used to rapidly determine contents of STA, KTA, protein, stearic acid (18:0), myristic acid (14:0), and palmitic acid (16:0) in shell‐intact cottonseed.

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Determination of the Fatty Acid Composition in Tree Peony Seeds Using Near‐Infrared Spectroscopy

Cui

Cheng

Peng

2016

J Americ Oil Chem Soc

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Tree peonies (Paeonia Sect Moutan DC) are an emerging oil crop because of their high oil and α‐linolenic acid (ALA) content. This research was to investigate the potential use of near infrared reflectance spectroscopy (NIRS) for estimating the major fatty acids contents, such as palmitic acid (C16:0), oleic acid (C18:1), linoleic acid (C18:2) and linolenic acid (C18:3) in tree peonies. A total of 115 small seed samples and 447 single seeds were selected to calibrate the predictive models. NIRS absorbance spectra were collected using a Fourier transform near infrared (FT‐NIR) spectrometer for the small seed samples, and acousto‐optic tunable filter‐near infrared (AOTF‐NIR) for the single seed samples. Statistical analysis was performed with partial least squares (PLS). For the husked samples, C18:3, C18:1 and C18:2 showed the highest correlation coefficient of validation (Rv; = 0.9756, 0.9467 and 0.8485, respectively) and the ratio of performance to deviation (RPD; = 3.58, 1.91 and 2.17, respectively); however, C16:0 did not reach expectations (Rv = 0.7783, RPD = 1.32). For intact samples, C18:3 showed the best prediction (Rv = 0.9096, RPD = 3.14), followed by C18:2 (Rv = 0.8479, RPD = 1.96). The results for C18:1 were poor (Rv = 0.7237, RPD = 1.70). For single seeds, only the results for C18:3 (R = 0.9150, RPD = 1.73) were good in the husked seed samples. It was concluded that NIRS can be used to rapidly assess the content of the major fatty acids in small samples.

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Estimation of Oil Content and Fatty Acid Composition in Cottonseed Kernel Powder Using Near Infrared Reflectance Spectroscopy

Cited by 28 publications

References 22 publications

Prediction of oil content in the mesocarp of fruit from the macauba palm using spectrometry1

Prediction of oil content in the mesocarp of fruit from the macauba palm using spectrometry1

Estimation of Protein and Fatty Acid Composition in Shell‐Intact Cottonseed by Near Infrared Reflectance Spectroscopy

Determination of the Fatty Acid Composition in Tree Peony Seeds Using Near‐Infrared Spectroscopy

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