著者

Xiwen Yang Ping Jiang Yahui Luo Yixin Shi

出版者

Japan Oil Chemists' Society

雑誌

Journal of Oleo Science (ISSN:13458957)

巻号頁・発行日

vol.72, no.1, pp.69-77, 2023 (Released:2023-01-07)

参考文献数

22

被引用文献数

1

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As a unique traditional vegetable oil in China, camellia seed oil has very high edible value. Camellia seed kernel is mainly composed of fatty acids, which not only determines the oil yield of camellia seed, but also exert an important impact on the storage performance of camellia seed. In order to quickly and accurately determine the fatty acid content of camellia seed, this paper took camellia seed as the research object, used hyperspectral technology to determine the fatty acid content of camellia seed, and establishes a spectral model. 8 pretreatment methods, such as Savitzky-Golay smoothing, normalization, baseline correction, multivariate scattering correction, standard normal variable transformation, detrending algorithm, first derivative and second derivative, were adopted in this paper. The spectral prediction model of fatty acid content in camellia seed was established by combining 4 modeling methods: principal components regression (PCR), partial least square regression (PLSR), back propagation neural network (BP), radial basis function neural network (RBF). The optimal prediction model was selected by comparing the coefficient of determination (R2) and root mean square error (RMSE) of various models. The results showed that the spectral sensitive bands with high correlation coefficients (r) were 410-420 nm, 450-460 nm, 490-510 nm, 545-580 nm, 845-870 nm and 905-925 nm, respectively. The r obtained by MSC pretreatment of spectral data was the largest. The data obtained by 8 different pretreatment methods combined with RBF neural network model was the best, in which the average value of coefficient of determination (RC2) in the calibration set was 0.8654, and the root mean square error of calibration (RMSEC) was 0.0777; the average value of coefficient of determination (RP2) and root mean square error of prediction (RMSEP) in the prediction set model were 0.8437 and 0.0827, respectively. It could be seen that the best accuracy could be achieved by MSC pretreatment combined with RBF neural network modeling. This paper can provide reference for rapid nondestructive detection of fatty acid content in camellia seed by hyperspectral technology.

著者

Xiwen Yang Ping Jiang Yahui Luo Yixin Shi

出版者

Japan Oil Chemists' Society

雑誌

Journal of Oleo Science (ISSN:13458957)

巻号頁・発行日

pp.ess22139, (Released:2022-12-12)

被引用文献数

1

---

As a unique traditional vegetable oil in China, camellia seed oil has very high edible value. Camellia seed kernel is mainly composed of fatty acids, which not only determines the oil yield of camellia seed, but also exert an important impact on the storage performance of camellia seed. In order to quickly and accurately determine the fatty acid content of camellia seed, this paper took camellia seed as the research object, used hyperspectral technology to determine the fatty acid content of camellia seed, and establishes a spectral model. 8 pretreatment methods, such as Savitzky-Golay smoothing, normalization, baseline correction, multivariate scattering correction, standard normal variable transformation, detrending algorithm, first derivative and second derivative, were adopted in this paper. The spectral prediction model of fatty acid content in camellia seed was established by combining 4 modeling methods: principal components regression (PCR), partial least square regression (PLSR), back propagation neural network (BP), radial basis function neural network (RBF). The optimal prediction model was selected by comparing the coefficient of determination (R2) and root mean square error (RMSE) of various models. The results showed that the spectral sensitive bands with high correlation coefficients (r) were 410-420 nm, 450-460 nm, 490-510 nm, 545-580 nm, 845-870 nm and 905-925 nm, respectively. The r obtained by MSC pretreatment of spectral data was the largest. The data obtained by 8 different pretreatment methods combined with RBF neural network model was the best, in which the average value of coefficient of determination (RC2) in the calibration set was 0.8654, and the root mean square error of calibration (RMSEC) was 0.0777; the average value of coefficient of determination (R2P) and root mean square error of prediction (RMSEP) in the prediction set model were 0.8437 and 0.0827, respectively. It could be seen that the best accuracy could be achieved by MSC pretreatment combined with RBF neural network modeling. This paper can provide reference for rapid nondestructive detection of fatty acid content in camellia seed by hyperspectral technology.

著者

Qiang LIU Bo JIANG Li-Ping JIANG Ying WU Xiao-Guang WANG Feng-Ling ZHAO Bao-Hua FU Turai ISTVAN Enhai JIANG

出版者

Journal of Radiation Research Editorial Committee

雑誌

Journal of Radiation Research (ISSN:04493060)

巻号頁・発行日

vol.49, no.1, pp.63-69, 2008 (Released:2008-02-01)

参考文献数

12

被引用文献数

47

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On 26 April 1999, three persons were accidentally exposed by high dose 60Co irradiation. They suffered from severe (one case) or moderate (two cases) hemopoietic form of acute radiation sickness (ARS). As part of the comprehensive treatment, strict reverse isolation and granulocyte-macrophage colony-stimulating factor (GM-CSF) therapy were applied. All the patients recovered after an appropriate treatment for 83 days. In our experience, the correct diagnosis and effective treatment at an early stage proved to be helpful to the patients in pulling out from the critical stage of acute radiation sickness. To avoid menstruation by the female patient just in the critical stage, we modified her menstruation cycle by testosterone. In our view, GM-CSF should be given as early as possible with enough dosage for promoting early hematological reconstruction. The experience obtained from the medical management of these patients is valuable for the treatment of such patients in the future.

著者

Xiaochuan LIU Yuwei YANG Ping JIANG Xiaohui LI Yanliang GE Yang CAO Zhihui ZHAO Xibi FANG Xianzhong YU

出版者

JAPANESE SOCIETY OF VETERINARY SCIENCE

雑誌

Journal of Veterinary Medical Science (ISSN:09167250)

巻号頁・発行日

vol.80, no.8, pp.1329-1336, 2018 (Released:2018-08-30)

参考文献数

20

被引用文献数

3

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QSOX1 (quiescin-sulfhydryl oxidase 1) is involved in various processes, including apoptosis and the development of breast diseases. Here, we investigated the effect of QSOX1 on the meat quality of Simmental cattle by analyzing the correlation between QSOX1 single nucleotide polymorphisms (SNPs), I2 204 C>T and I2 378 C>T, and certain meat quality traits. The effects of QSOX1 on triglyceride synthesis and cell apoptosis were further validated by gene silencing or overexpression in bovine fetal fibroblasts and mammary epithelial cells. The results showed that I2 204 C>T and I2 378 C>T had significant correlations with loin thickness, hind hoof weight, fat coverage, liver weight, heart weight, marbling and back fat thickness (P<0.05). QSOX1 overexpression also increased triglyceride production and suppressed apoptosis. In summary, QSOX1 is an important factor for meat quality, lipid metabolism, and cell apoptosis, indicating that QSOX1 could be used as a biomarker to assist in breeding cattle with superior meat.