Water content detection of Camellia oleifera seeds based on temperature correction and visible/near infrared spectroscopy

Authors

WANG Zhi-qiang, College of Mechanical and Electrical Engineering, Central South University ofForestry and Technology, Changsha, Hunan 410004 , China
LI Da-peng, College of Mechanical and Electrical Engineering, Central South University ofForestry and Technology, Changsha, Hunan 410004 , China
LIU Qiang, College of Mechanical and Electrical Engineering, Central South University ofForestry and Technology, Changsha, Hunan 410004 , China
LIAO Shu-huai, College of Mechanical and Electrical Engineering, Central South University ofForestry and Technology, Changsha, Hunan 410004 , China
YI Zong-pei, College of Mechanical and Electrical Engineering, Central South University ofForestry and Technology, Changsha, Hunan 410004 , China

Abstract

Objective: In order to solve the problem that temperature change during drying can detect the moisture content of Camellia oleifera seeds by visible/near infrared spectroscopy, a temperature modified Camellia oleifera seed moisture content detection model was proposed. Methods: Drying experiments were carried out at different temperatures (50,60,70 ℃) to collect spectral data. By acquiring the spectral data collected at different temperatures, the reasons why the temperature affected the spectrum were analyzed. Then, by comparing the three spectral preprocessing methods, using the Competitive Adaptive Reweighting(CARS)and Partial Least Squares Regression (PLSR) were used to establish the benchmark PLSR model at 60 ℃. Finally, the slope/bias method was used to correct the predicted values of external samples at 50 ℃ and 70 ℃, which greatly improved the precision and accuracy. Results: The coefficients of determination before and after correction at the two temperatures were 0.729 and 0.848, 0.763 and 0.862, respectively. The relative analytical error RPD values were 1.921 and 2.565, 2.054 and 2.692, respectively. Conclusion: The modified model could effectively improve the prediction accuracy, achieve good prediction effect, overcome the influence of temperature, and provide a new method to eliminate the influence of temperature when detecting the oil Camellia oleifera seed moisture content by visible/near infrared spectroscopy in the drying field.

Publication Date

12-28-2022

First Page

127

Last Page

132

DOI

10.13652/j.spjx.1003.5788.2022.80274

Recommended Citation

Zhi-qiang, WANG; Da-peng, LI; Qiang, LIU; Shu-huai, LIAO; and Zong-pei, YI (2022) "Water content detection of Camellia oleifera seeds based on temperature correction and visible/near infrared spectroscopy," Food and Machinery: Vol. 38: Iss. 12, Article 21.
DOI: 10.13652/j.spjx.1003.5788.2022.80274
Available at: https://www.ifoodmm.cn/journal/vol38/iss12/21

References

[1] 孟桂元,韩杰铖,詹兴国,等.我国油茶产业分析与发展对策[J].中国油脂,2021,46(7):104-108,113.MENG G Y,HAN J C,ZHAN X G,et al.Analysis and development countermeasures of Camellia oleifera industry in China[J].China Oils,2021,46(7):104-108,113.
[2] 郁李.油茶产业亟需高质量发展[J].农经,2019(12):52-55.YU L.Camellia olei fera industry urgently needs high-quality development[J].Agricultural Economics,2019(12):52-55.
[3] 陈永忠,邓绍宏,陈隆升,等.油茶产业发展新论[J].南京林业大学学报(自然科学版),2020,44(1):1-10.CHEN Y Z,DENG S H,CHEN L S,et al.New theory on the development of Camellia oil industry[J].Journal of Nanjing Forestry University(Natural Science Edition),2020,44(1):1-10.
[4] 周显青,赵希雷,张玉荣,等.谷物水分检测技术现状与展望[J].粮食加工,2015,40(4):29-34.ZHOU X Q,ZHAO X L,ZHANG Y R,et al.Present situation and prospect of grain moisture detection technology[J].Grain Processing,2015,40(4):29-34.
[5] 罗凡,费学谦,李康雄,等.预处理条件对油茶籽液压榨油效率和品质的影响研究[J].中国粮油学报,2016,31(4):94-99.LUO F,FEI X Q,LI K X,et al.The effect of different pretreatments on the efficiency and quality of camellia oil before hydraulic pressing[J].Journal of the Chinese Cereals and Oils Association,2016,31(4):94-99.
[6] 赵海瑞,滕兆丽,杨浩勇,等.油茶果干燥特性及烘干脱蒲技术[J].农业工程,2021,11(10):61-67.ZHAO H R,TENG Z L,YANG H Y,et al.Drying characteristics and drying technology of camellia oleifera[J].Agricultural Engineering,2021,11(10):61-67.
[7] 周宏平,胡逸磊,姜洪喆,等.基于高光谱成像的油茶籽含油率检测方法[J].农业机械学报,2021,52(5):308-315.ZHOU H P,HU Y L,JIANG H Z,et al.Detection method for oil content of camellia oleifera seeds based on hyperspectral imaging[J].Transactions of the Chinese Society for Agricultural Machinery,2021,52(5):308-315.
[8] 彭彦昆,杨清华,王文秀.基于近红外光谱的猪肉水分在线检测与分级[J].农业机械学报,2018,49(3):347-353.PENG Y K,YANG Q H,WANG W X.Online detection and classification of pork moisture based on near-infrared spectroscopy[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(3):347-353.
[9] 郭文川,朱德宽,张乾,等.基于近红外光谱的掺伪油茶籽油检测[J].农业机械学报,2020,51(9):350-357.GUO W C,ZHU D K,ZHANG Q,et al.Detection of adulterated camellia oil based on near-infrared spectroscopy[J].Transactions of the Chinese Society for Agricultural Machinery,2020,51(9):350-357.
[10] MELFSEN A,HOLSTERMANN M,HAEUSSERMANN A,et al.Accuracy and application of milk fatty acid estimation with diffuse reflectance near-infrared spectroscopy[J].Journal of Dairy Research,2018,85(2):212-221.
[11] ELSOHABY I,WINDEYER M C,HAINES D M,et al.Application of transmission infrared spectroscopy and partial least squares regression to predict immunoglobulin G concentration in dairy and beef cow colostrum[J].Journal of Animal Science,2018,96(2):771-782.
[12] JIANG H Y,XIE L J,PENG Y S,et al.Study on the influence of temperature on near infrared spectra[J].Spectroscopy and Spectral Analysis,2008,28(7):1 510-1 513.
[13] MAEDA H,OZAKI Y,TANAKA M,et al.Near infrared spectroscopy and chemometrics studies of temperature-dependent spectral variations of water:Relationship between spectral changes and hydrogen bonds[J].Journal of Near Infrared Spectroscopy,1995,3(4):191-201.
[14] 马帅帅,于慧春,殷勇,等.黄瓜水分和硬度高光谱特征波长选择与预测模型构建[J].食品与机械,2021,37(2):145-151.MA S S,YU H C,YIN Y,et al.Selection of hyperspectral characteristic wavelength and construction of prediction model for cucumber hardness and moisture[J].Food & Machinery,2021,37(2):145-151.
[15] 廉孟茹,张淑娟,任锐,等.基于高光谱技术的鲜食水果玉米含水率无损检测[J].食品与机械,2021,37(9):127-132.LIAN M R,ZHANG S J,REN R,et al.Nondestructive detection of moisture content in fresh fruit corn based on hyperspectral technology[J].Food & Machinery,2021,37(9):127-132.
[16] 第五鹏瑶,卞希慧,王姿方,等.光谱预处理方法选择研究[J].光谱学与光谱分析,2019,39(9):2 800-2 806.DIWU P Y,BIAN X H,WANG Z F,et al.Research on the selection of spectral preprocessing methods[J].Spectroscopy and Spectral Analysis,2019,39(9):2 800-2 806.
[17] 郭阳,郭俊先,史勇,等.CARS-SVM预测哈密瓜可溶性固形物含量[J].食品与机械,2021,37(6):81-85.GUO Y,GUO J X,SHI Y,et al.Prediction of soluble solids in Hami melon by CARS-SVM[J].Food & Machinery,2021,37(6):81-85.
[18] 张立欣,杨翠芳,陈杰,等.基于变量优选的苹果糖分含量近红外光谱检测[J].食品与机械,2021,37(10):112-118.ZHANG L X,YANG C F,CHEN J,et al.Detection of sugar content in apple by near infrared spectroscope based on variable optimization[J].Food & Machinery,2021,37(10):112-118.
[19] 吕都,唐健波,姜太玲,等.基于近红外光谱技术快速检测稻谷水分含量[J].食品与机械,2022,38(2):51-56,63.LU D,TANG J B,JIANG T L,et al.Research on rapid prediction model of rice moisture content based on near infrared spectroscope[J].Food & Machinery,2022,38(2):51-56,63.
[20] 王加华,戚淑叶,汤智辉,等.便携式近红外光谱仪的苹果糖度模型温度修正[J].光谱学与光谱分析,2012,32(5):1 431-1 434.WANG J H,QI S Y,TANG Z H,et al.Temperature compensation for portable Vis/NIR spectrometer measurement of apple fruit soluble solids contents[J].Spectroscopy and Spectral Analysis,2012,32(5):1 431-1 434.
[21] ZHANG Y,GUO W.Moisture content detection of maize seed based on visible/near-infrared and near-infrared hyperspectral imaging technology[J].International Journal of Food Science & Technology,2020,55(2):631-640.
[22] REN Y,LIN X,LEI T,et al.Recent developments in vibrational spectral analyses for dynamically assessing and monitoring food dehydration processes[J].Critical Reviews in Food Science and Nutrition,2022,62(16):4 267-4 293.
[23] 陆锡昆,罗亚辉,蒋,等.基于高光谱的油茶籽含水量检测方法[J].浙江农业学报,2020,32(7):1 302-1 310.LU X K,LUO Y H,JIANG P,et al.Detection of water content in camellia seeds based on hyperspectrum[J].Acta Agriculturae Zhejiangensis,2020,32(7):1 302-1 310.