多酚氧化酶(polyphenol oxidase,PPO)是引起甘薯酶促褐变的主要原因,常用的PPO活力检测方法操作繁琐,建立一种简便快捷的检测方法意义重大。实验采用手机拍摄甘薯切片的褐变视频,提取视频图像RGB变化数据,建立了PPO活力预测模型。研究发现,0~30 s图像R值的变化量(ΔR)与PPO活力呈极强的正相关(相关系数0.946),G值与B值的变化量(ΔG和ΔB)与PPO活力呈中等强度正相关(相关系数分别为0.799和0.620)。采用多元线性回归模型对ΔR、ΔG、ΔB与PPO活力间的关系进行拟合,所得模型的拟合确定系数(R2)达到0.903,模型的预测相关系数(rp)、预测均方误差和标准偏差比分别为0.956,2.079和3.459。结果表明,采用视频与数字图像比色快速检测甘薯多酚氧化酶活力是可行的。
Polyphenol oxidase (PPO) is the main cause of enzymatic browning of sweet potato. The commonly used method for detecting PPO activity is complicated, so it is of great significance to establish a simple and fast method for the detection of PPO activity. In the present study, the browning process of sweet potato slices were videotaped by a cell phone, and the changes of RGB values in these videos were extracted. The PPO activity prediction model was also be established. The results showed that the change of R value (ΔR) from 0 to 30 s was highly positive correlated with PPO activity (correlation coefficient was 0.946), and the change of G and B value (ΔG and ΔB) was moderately positive correlated with PPO activity (correlation coefficient was 0.799 and 0.620, respectively). Multivariate linear regression model was used to fit the relationship between ΔR, ΔG, ΔB and PPO activity. The coefficient of determination (R2) of the model reached 0.903, the predicted correlation coefficients (rp), root mean square error of prediction (RMSEP) and standard deviation ratio (SDR) of the model were 0.956, 2.079 and 3.459, respectively. The results indicated that the methodology developed here is feasible to predict PPO activity of sweet potato by video and digital image colorimetry.
[1] 刘水英, 李新生, 江海, 等. 彩色甘薯不同品种中基本物质及功能成分分析[J]. 江苏农业科学, 2015,43(1):303-305.
[2] 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;87.
[3] 郁志芳, 夏志华, 陆兆新. 鲜切甘薯酶促褐变机理的研究[J]. 食品科学, 2005,26(5):54-59.
[4] PIZZOCARO F, TORREGGIANI D, GILARDI G. Inhibition of apple polyphenol oxidase (PPO) by ascorbic, citric acid and sodium chloride[J]. Journal of Food Processing and Preservation, 1993,17(1):21-30.
[5] 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.
[6] JIA M, WU Q, 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.
[7] KOSTELNIK A, CEGAN A, POHANKA M. Color change of phenol red by integrated smart phone camera as a tool for the determination of neurotoxic compounds[J]. Sensors, 2016,16(9):1-10.
[8] ONCESCU V, MANCUSO M, ERICKSON D. Cholesterol testing on a smartphone[J]. Lab on A Chip, 2014,14(4):759-763.
[9] 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.
[10] 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.
[11] 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.
[12] LOPEZ-RUIZ N, CURTO V F, ERENAS M M, et al. Smartphone-Based simultaneous pH and nitrite colorimetric determination for paper microfluidic devices[J]. Analytical Chemistry, 2014,86(19):9 554-9 562.
[13] 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.
[14] 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.
[15] GUO J, WONG J X H, CUI C, et al. A smartphone-readable barcode assay for the detection and quantitation of pesticide residues[J]. Analyst, 2015,140(16):5 518-5 525.
[16] SANTOS NETO J H, 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.
[17] MASAWAT P, HARFIELD A, NAMWONG A. An iPhone-based digital image colorimeter for detecting tetracycline in milk[J]. Food Chemistry, 2015,184:23-29.
[18] MAHATO K, CHANDRA P. Paper-based miniaturized immunosensor for naked eye ALP detection based on digital image colorimetry integrated with smartphone[J]. Biosensors and Bioelectronics, 2019,128:9-16.
[19] SINGKHONRAT J, SRIPRAI A, HIRUNWATTHANAKASEM S, et al. Digital image colorimetric analysis for evaluating lipid oxidation in oils and its emulsion[J]. Food Chemistry, 2019,286:703-709.
[20] 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.
[21] 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.
[22] AZEEM S M A, MADBOULY M D, EL-SHAHAT M F. Determination of nitrite in processed meat using digital image method and powdered reagent[J]. Journal of Food Composition and Analysis, 2019,81:28-36.
[23] 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.
[24] LEE K, BAEK S, KIM D, et al. A freshness indicator for monitoring chicken-breast spoilage using a Tyvek® sheet and RGB color analysis[J]. Food Packaging and Shelf Life, 2019,19:40-46.
[25] 沈升法, 吴列洪, 李兵. 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.
[26] 王礼群, 刘硕, 杨春贤, 等. 鲜切甘薯不同部位褐变机理差异[J]. 食品科学, 2018,39(1):285-290.
[27] CHEN J, ZHU S, ZHAO G. Rapid determination of total protein and wet gluten in commercial wheat flour using siSVR-NIR[J]. Food Chemistry, 2017,221:1 939-1 946.
[28] CHOODUM A, KANATHARANA P, WONGNIRAMAIKUL W, et al. A sol–gel colorimetric sensor for methamphetamine detection[J]. Sensors and Actuators B: Chemical, 2015,215:553-560.
