Applied Research on Near-infrared for On-line Rapid Determination of Tea Moisture Content

CHEN Shousong; ZHENG Gongyu; JIN Xinyi; HAO Zhilong; YE Qiuping; LAI Zhilong

doi:10.13305/j.cnki.jts.2014.04.004

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Journal of Tea Science ›› 2014, Vol. 34 ›› Issue (4) : 337-343. DOI: 10.13305/j.cnki.jts.2014.04.004

Applied Research on Near-infrared for On-line Rapid Determination of Tea Moisture Content

CHEN Shousong^1,2, ZHENG Gongyu¹, JIN Xinyi^1,2,*, HAO Zhilong^1,2, YE Qiuping¹, LAI Zhilong¹

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Abstract

Research on an implement method to determinate tea moisture content with rapid non-destructive and on-line technology. Comparing to national standard method, it was proved that the effect of those factors including the dynamic and static state of conveyor belt, spread thickness, measuring height, tea grade on the accuracy of tea moisture content accuracy. The results showed that there were significant differences between CK and different spread thickness and grade, no obvious difference in the treatment of dynamic or static state and measure height. The optimal parameters are that tea conveyor belt speed is 0.8 m·s^-1, conveyor belt should be fully covered by tea samples, and should avoid from the external light irradiate tea samples, spread thickness is (20±5) mm, measure height is (250±50) mm. Different grade of tea set at different measuring channels can be more accurate in measured results.

Key words

influence factors / moisture content / near-infrared / on-line / tea

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CHEN Shousong, ZHENG Gongyu, JIN Xinyi, HAO Zhilong, YE Qiuping, LAI Zhilong. Applied Research on Near-infrared for On-line Rapid Determination of Tea Moisture Content[J]. Journal of Tea Science. 2014, 34(4): 337-343 https://doi.org/10.13305/j.cnki.jts.2014.04.004

References

[1] 周健, 成浩, 王丽鸳. 近红外技术在茶叶上的研究进展[J]. 茶叶科学, 2008, 28(4): 294-300.
[2] 胡茶根, 赵红霞, 边文亮. 近红外技术在茶叶快速无损检测方面的研究与应用[J]. 食品科学, 2007, 28(10): 638-643.
[3] 金心怡, 陈济斌, 吉克温. 茶叶加工工程[M]. 北京: 中国农业出版社, 2003: 183-187.
[4] 周亦斌, 王俊. 新技术在茶叶品质评价中应用的现状及趋势[J]. 茶叶科学, 2004, 24(2): 82-85.
[5] 陈寿松, 占杨, 郑功宇, 等. 茶叶含水率常用测定方法及比较分析[J]. 中国茶叶加工, 2013(3): 33-36.
[6] 中华人民共和国国家质量监督检验检疫总局. GB/T 8403—2002 茶水分测定[S]. 北京: 中国标准出版社, 2002.
[7] 陈全胜, 赵杰文, 蔡健荣. 基于近红外光谱和机器视觉的多信息融合技术评判茶叶品质[J]. 农业工程学报, 2008, 24(3): 5-10.
[8] 丁海樱, 金叶, 刘雪松, 等. 中药粉末混合过程近红外在线检测研究[J]. 中国药学杂志, 2013, 48(14): 1151-1156.
[9] 刘洁, 李小昱, 李培武, 等. 基于近红外光谱的板栗水分检测方法[J]. 农业工程学报, 2010, 26(2): 338-341.
[10] 周小芬, 叶阳, 陈芃, 等. 近红外光谱技术在茶叶品质评价中的研究与应用[J]. 食品工业科技, 2012, 33(5): 413-417.
[11] Holger Grohganz, Delphine Gildemyn, Erik Skibsted, et al. Towards a robust water content determination of freeze-dried samples by near-infrared spectroscopy[J]. Anal Chim Acta, 2010, 676(1/2): 34-40.
[12] 牛智有, 林新. 茶叶定性和定量近红外光谱分析方法研究[J]. 光谱学与光谱分析, 2009, 29(9): 2417-2420.
[13] 王玉霞, 徐荣荣, 任广鑫, 等. 绿茶茶汤中主要品质成分近红外定量分析模型的建立[J]. 茶叶科学, 2011, 31(4): 355-361.
[14] 陈美丽, 张俊, 龚淑英, 等. 茉莉花茶主要品质成分定量近红外光谱分析模型的建立[J]. 茶叶科学, 2013, 33(1): 21-26.
[15] 李晓丽, 何勇, 裘正军, 等. 一种基于可见近红外光谱快速鉴别茶叶品种的新方法[J]. 光谱学与光谱分析, 2007, 27(2): 279-282.
[16] Daiki Ono, Takeshi Bamba, Yuichi Oku, et al. Application of Fourier transform near-infrared spectroscopy to optimization of green tea steaming process conditions[J]. Journal of Bioscience and Bioengineering, 2011, 112(3): 247-251.
[17] 何茂栋. 在线水分检测系统在混匀配料中的应用[J]. 自动化技术与应用, 2011, 30(4): 101-103,110.
[18] Lourdes Salguero-Chaparro, Vincent Baeten, Juan A, et al. Near infrared spectroscopy (NIRS) for on-line determination of quality parameters in intact olives[J]. Food Chemistry, 2013, 139(1/4): 1121-1126.
[19] 孙通. 梨可溶性固形物和酸度的可见/近红外光谱静态和在线检测研究[D]. 杭州: 浙江大学, 2011.
[20] 孙旭东, 郝勇, 刘燕德. 苹果可溶性固形物近红外光谱在线检测影响因素研究[J]. 中国农机化学报, 2013, 34(1): 86-90.
[21] 金华丽, 卞科. 近红外光谱法检测小麦粉中的水分含量[J]. 中国粮油学报, 2010, 25(8): 109-112.