Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varieties
The variation of fruit among batches influences the performance of the portable near infrared spectroscopy (NIRS) instrument and then determines the success or failure for practical application in fruit industry. Model development and update methods were investigated for determining soluble solids c...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Nutrition |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnut.2022.976178/full |
| _version_ | 1828355997765206016 |
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| author | Xudong Sun Xudong Sun Di Deng Jiacheng Liu Shaoran Feng |
| author_facet | Xudong Sun Xudong Sun Di Deng Jiacheng Liu Shaoran Feng |
| author_sort | Xudong Sun |
| collection | DOAJ |
| description | The variation of fruit among batches influences the performance of the portable near infrared spectroscopy (NIRS) instrument and then determines the success or failure for practical application in fruit industry. Model development and update methods were investigated for determining soluble solids contents (SSC) and titrable acidity (TA) of navel orange. The pretreatment and variable selection methods were explored for building partial least square regression (PLSR) models. The best models, developed by the combination of second derivative (2D) and variable sorting for normalization (VSN), could predict SSC but not TA. The root mean square error of prediction (RMSEP), coefficient of determination for prediction (Rp2) and ratio of prediction to deviation (RPD) for SSC were 0.66 °Brix, 0.66 and 1.73. Model maintain methods of model update (MU) and slope and bias correction (SBC) achieved the best results in predicting SSC for two external validation sets with Rp2, RMSEP and RPD of 0.54, 0.83 °Brix, 1.60 and 0.52, 0.83 °Brix, 1.65, respectively. The results suggested model development and update with MU and SBC could improve the robustness of the portable NIRS instrument in predicting SSC of navel orange. |
| first_indexed | 2024-04-14T02:52:56Z |
| format | Article |
| id | doaj.art-dbcc470a28eb4966b3ff5bd8cca47eff |
| institution | Directory Open Access Journal |
| issn | 2296-861X |
| language | English |
| last_indexed | 2024-04-14T02:52:56Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Nutrition |
| spelling | doaj.art-dbcc470a28eb4966b3ff5bd8cca47eff2022-12-22T02:16:15ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2022-08-01910.3389/fnut.2022.976178976178Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varietiesXudong Sun0Xudong Sun1Di Deng2Jiacheng Liu3Shaoran Feng4School of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang, ChinaMinistry of Education, Key Laboratory of Conveyance Equipment (East China Jiaotong University), Nanchang, ChinaSchool of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang, ChinaCultivation Laboratory, Ganzhou Citrus Research Institute, Ganzhou, ChinaBeijing Sunlight Yishida Technology Co., Ltd., Beijing, ChinaThe variation of fruit among batches influences the performance of the portable near infrared spectroscopy (NIRS) instrument and then determines the success or failure for practical application in fruit industry. Model development and update methods were investigated for determining soluble solids contents (SSC) and titrable acidity (TA) of navel orange. The pretreatment and variable selection methods were explored for building partial least square regression (PLSR) models. The best models, developed by the combination of second derivative (2D) and variable sorting for normalization (VSN), could predict SSC but not TA. The root mean square error of prediction (RMSEP), coefficient of determination for prediction (Rp2) and ratio of prediction to deviation (RPD) for SSC were 0.66 °Brix, 0.66 and 1.73. Model maintain methods of model update (MU) and slope and bias correction (SBC) achieved the best results in predicting SSC for two external validation sets with Rp2, RMSEP and RPD of 0.54, 0.83 °Brix, 1.60 and 0.52, 0.83 °Brix, 1.65, respectively. The results suggested model development and update with MU and SBC could improve the robustness of the portable NIRS instrument in predicting SSC of navel orange.https://www.frontiersin.org/articles/10.3389/fnut.2022.976178/fullnavel orangeSSCTAnear infrared spectroscopybatchportable instrument |
| spellingShingle | Xudong Sun Xudong Sun Di Deng Jiacheng Liu Shaoran Feng Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varieties Frontiers in Nutrition navel orange SSC TA near infrared spectroscopy batch portable instrument |
| title | Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varieties |
| title_full | Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varieties |
| title_fullStr | Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varieties |
| title_full_unstemmed | Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varieties |
| title_short | Model development and update of portable NIRS instrument for assessment of internal quality attributes of two navel orange varieties |
| title_sort | model development and update of portable nirs instrument for assessment of internal quality attributes of two navel orange varieties |
| topic | navel orange SSC TA near infrared spectroscopy batch portable instrument |
| url | https://www.frontiersin.org/articles/10.3389/fnut.2022.976178/full |
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