手机数字图像与甘薯β-胡萝卜素含量间相关性
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摘要
该研究旨在探讨手机数字图像信息与甘薯β-胡萝卜素含量间的关系。采用智能手机采集甘薯块根切片的图像,对图像的RGB信息与甘薯β-胡萝卜素含量间的关系进行了研究,并建立了预测模型。研究发现,甘薯β-胡萝卜素含量与甘薯切片图像的绿值(G)间呈极强的负相关,与蓝值(B)呈中等强度负相关,红值(R)与β-胡萝卜素含量之间无相关性。采用对数函数对G值与β-胡萝卜素含量间的关系进行拟合,模型的拟合确定系数(R~2)达到0. 947,模型的预测相关系数(r_p)、预测均方误差(RMSEP)和标准偏差比(SDR)分别为0. 983、0. 819和5. 269。结果表明,手机数字图像可以反映甘薯β-胡萝卜素含量间的差异,使用图像的颜色值信息可以较为精确地估计甘薯β-胡萝卜素含量,为甘薯品质快速检测提供了新的思路。
The aim of this study was to explore the relationship between mobile phone digital images and β-carotene content in sweet potato. A smart phone was used to collect the image of sweet potato slices. Moreover,the relationship between the RGB information of the images and the content of β-carotene in sweet potato was studied,and predict models were calibrated. The results showed that the content of β-carotene in sweet potato had a strong negative correlation with green(G) value,and a moderate negative correlation with blue(B) value. There was no correlation betweenβ-carotene content and red(R) value of sweet potato slice images. The logarithmic function was used to fit the relationship between G value and β-carotene content. The coefficient of determination(R~2) of the model reached 0. 947,the predicted correlation coefficients(r_p),root mean square error of prediction(RMSEP) and standard deviation ratio(SDR) of the model were 0. 983,0. 819 and 5. 269,respectively. Overall,digital images of mobile phone can reflect the differences of β-carotene content in sweet potato,and the RGB information of digital image can accurately estimate the β-carotene content of sweet potato,which provides a new idea for rapid detection of sweet potato quality.
The aim of this study was to explore the relationship between mobile phone digital images and β-carotene content in sweet potato. A smart phone was used to collect the image of sweet potato slices. Moreover,the relationship between the RGB information of the images and the content of β-carotene in sweet potato was studied,and predict models were calibrated. The results showed that the content of β-carotene in sweet potato had a strong negative correlation with green(G) value,and a moderate negative correlation with blue(B) value. There was no correlation betweenβ-carotene content and red(R) value of sweet potato slice images. The logarithmic function was used to fit the relationship between G value and β-carotene content. The coefficient of determination(R~2) of the model reached 0. 947,the predicted correlation coefficients(r_p),root mean square error of prediction(RMSEP) and standard deviation ratio(SDR) of the model were 0. 983,0. 819 and 5. 269,respectively. Overall,digital images of mobile phone can reflect the differences of β-carotene content in sweet potato,and the RGB information of digital image can accurately estimate the β-carotene content of sweet potato,which provides a new idea for rapid detection of sweet potato quality.
引文
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[2]朱旭霞,刘莉莎,何素兰,等.保健甘薯的功能及产品开发研究[J].中国食物与营养,2014,20(11):34-36.
[3]邹波,曾丹,吴继军,等.不同品种紫肉甘薯抗氧化能力及花色苷成分分析[J].食品科学,2018,39(2):38-44.
[4]吴玲艳,申燕飞,赵晓飞,等.不同汽蒸工艺对甘薯薯块口感和抗氧化能力的影响[J].食品科学,2016,37(9):66-70.
[5]周郑坤,郑元林.甘薯营养价值与保健功能的再认识[J].江苏师范大学学报(自然科学版),2016,34(4):16-19.
[6]SUN Y,MI W,WU L. Effects of foliar Fe and Zn fertilizers on storage root Fe,Zn,and beta-carotene content of sweet potato(Ipomoea batatas L.)[J]. Journal of Plant Nutrition,2019,42(1):16-26.
[7]DHUIQUE-MAYER C,SERVENT A,MESSAN C,et al.Bioaccessibility of biofortified sweet potato carotenoids in baby food:Impact of manufacturing Process[J]. Frontiers in Nutrition,2018,5:98.
[8]惠伯棣,许岱,宫平,等.水溶性有机试剂萃取杜氏藻中的β-胡萝卜素[J].食品科学,2015,36(10):179-184.
[9]郑群雄,杜美霞,徐小强,等.高效液相色谱法测定15种蔬菜中的β-胡萝卜素[J].食品科学,2012,33(14):238-241.
[10]刘锐,杨瑞琴,常冠群.图像比色法测定有色溶液[J].理化检验-化学分册,2014,50(11):1 348-1 350.
[11]NETO J H S,PORTO I S A,SCHNEIDER M P,et al.Speciation analysis based on digital image colorimetry:Iron(Ⅱ/Ⅲ)in white wine[J]. Talanta,2019,194:86-89.
[12]MASAWAT P, HARFIELD A, NAMWONG A. An i Phone-based digital image colorimeter for detecting tetracycline in milk[J]. Food Chemistry,2015,184:23-29.
[13]DE SOUSA FERNANDES D D,ROMEO F,KREPPER G,et al. Quantification and identification of adulteration in the fat content of chicken hamburgers using digital images and chemometric tools[J]. LWT-Food Science and Technology,2019,100:20-27.
[14]THONGPRAJUKAEW K,CHOODUM A,SA-E B,et al.Smart phone:A popular device supports amylase activity assay in fisheries research[J]. Food Chemistry,2014,163:87-91.
[15]LEE K,BAEK S,KIM D,et al. A freshness indicator for monitoring chicken-breast spoilage using a Tyvek R sheet and RGB color analysis[J]. Food Packaging and Shelf Life,2019,19:40-46.
[16]JIA M Y,WU Q S,LI H,et al. The calibration of cellphone camera-based colorimetric sensor array and its application in the determination of glucose in urine[J]. Biosensors&Bioelectronics,2015,74:1 029-1 037.
[17]KOSTELNIK A, CEGAN A, POHANKA M. Color change of phenol red by integrated dmart phone camera as a tool for the determination of neurotoxic compounds[J].Sensors,2016,16(9):1 212.
[18]ONCESCU V,MANCUSO M,ERICKSON D. Cholesterol testing on a smartphone[J]. Lab on a Chip,2014,14(4):759-763.
[19]WONGNIRAMAIKUL W,LIMSAKUL W,CHOODUM A. A biodegradable colorimetric film for rapid low-cost field determination of formaldehyde contamination by digital image colorimetry[J]. Food Chemistry,2018,249:154-161.
[20]CHOODUM A,SRIPROM W,WONGNIRAMAIKUL W.Portable and selective colorimetric film and digital image colorimetry for detection of iron[J]. Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy,2019,208:40-47.
[21]SUMRIDDETCHKAJORN S,CHAITAVON K,INTARAVANNE Y. Mobile device-based self-referencing colorimeter for monitoring chlorine concentration in water[J].Sensors and Actuators B:Chemical,2013,182:592-597.
[22]LOPEZ-RUIZ N,CURTO V F,ERENAS M M,et al.Smartphone-based simultaneous p H and nitrite colorimetric determination for paper microfluidic devices[J]. Analytical Chemistry,2014,86(19):9 554-9 562.
[23]SEKINE Y,KATORI R,TSUDA Y,et al. Colorimetric monitoring of formaldehyde in indoor environment using built-in camera on mobile phone[J]. Environmental Technology,2016,37(13):1 647-1 655.
[24]WEI Q,NAGI R,SADEGHI K,et al. Detection and spatial mapping of mercury contamination in water samples using a smart-phone[J]. ACS Nano,2014,8(2):1 121-1 129.
[25]GUO J,WONG J X H,CUI C,et al. A smartphonereadable barcode assay for the detection and quantitation of pesticide residues[J]. Analyst,2015,140(16):5 518-5 525.
[26]沈升法,吴列洪,李兵,等.基于图像RGB特征值的甘薯色素与肉色关系初步探讨[J].植物遗传资源学报,2015,16(4):888-894.
[27]BISWAS A K,SAHOO J,CHATLI M K. A simple UVVis spectrophotometric method for determination ofβ-carotene content in raw carrot,sweet potato and supplemented chicken meat nuggets[J]. LWT-Food Science and Technology,2011,44(8):1 809-1 813.
[28]CHEN J,ZHU S,ZHAO G. Rapid determination of total protein and wet gluten in commercial wheat flour using si SVR-NIR[J]. Food Chemistry,2017,221:1 939-1 946.
[29]张立明,王庆美,王荫墀.甘薯的主要营养成分和保健作用[J].杂粮作物,2003,23(3):162-166.