Development of a volatile amine sensor for the monitoring of fish spoilage

A sensor with potential for the development of a “chemical barcode” for real-time monitoring of fish freshness is described. This on-package sensor contains a pH sensitive dye, bromocresol green, that responds through visible colour change to basic volatile spoilage compounds, such as trimethylamine (TMA), ammonia (NH₃) and dimethylamine (DMA) collectively known as Total Volatile Basic Nitrogen (TVB-N). The sensor characteristics were studied as well as its response with standard ammonia gas. Trials on cod and under-utilised species have verified that the sensor response correlates with bacterial growth patterns in fish samples thus enabling the “real-time” monitoring of spoilage in various fish species. The sensor response can be interrogated with a simple, inexpensive reflectance colorimeter that we have developed based on two light emitting diodes (LEDs) and a photodetector.     

Effect of multi-frequency ultrasound assisted thawing on the quality of large yellow croaker (Larimichthys crocea)

The effects of mono-, dual- and tri-frequency ultrasound-assisted thawing (UAT) on the physicochemical quality, water-holding capacity, moisture migration and distribution and myofibrillary structure of frozen large yellow croaker (Larimichthys crocea) were detected. The results indicated that multifrequency UAT treatment significantly increased the thawing rate, maintained the stability of myofibrils and reduced the lipid oxidation. The multifrequency UAT samples had better water-holding capacity (higher water-holding capacity values, lower thawing loss and cooking loss) and physicochemical quality (higher hardness, springiness, resilience, chewiness and lower total volatile basic nitrogen (TVB-N) values, thiobarbituric acid reactive substances (TBARS) values), higher immobilized water content, and lower free water content. Therefore, the results provide a further understanding of the quality stability of frozen large yellow croaker treated by the multifrequency UAT.     

羊肉挥发性盐基氮的高光谱图像快速检测研究

挥发性盐基氮(TVB-N)通常被作为评价羊肉新鲜度的理化参考指标。为了揭示高光谱图像技术(HSI)快速检测羊肉新鲜度的可行性,采集了71个新鲜度具有代表性的羊肉样品的漫反射高光谱图像(400～1 000 nm),并利用半微量定氮法测定了其挥发性盐基氮(TVB-N)的化学值。选择感兴趣区域(ROIs)提取样品的代表性光谱,采用含量梯度法划分校正集和预测集,比较不同的光谱预处理方法,比较逐步多元线性回归(SMLR)、偏最小二乘(PLSR)和主成分分析(PCR)建模方法,建立并验证了TVB-N的校正模型。结果表明,利用多元散射校正(MSC)、一阶导数、Savitzky-Golay(S-G)平滑及中心化处理结合的预处理方法,PLSR和PCR模型都可以实现对羊肉TVB-N的定量检测。对于建立的PLSR模型,采用的预处理方法为MSC、15点2次S-G平滑、1阶导数和中心化相结合的方法,选择的潜变量因子数为11,获得的校正集的相关系数(R)和校正均方根误差(RMSEC)分别为0.92和3.00 mg·(100 g)-1,预测集的相关系数(r)、预测均方根误差(RMSEP)和相对分析误差(RPD)分别为0.92,3.46 mg·(100 g)-1和2.35。研究表明,高光谱图像技术可用于准确快速地检测分析羊肉中新鲜度关键指标TVB-N的含量。该研究为采用高光谱图像技术进一步分析羊肉新鲜度其他指标、改善TVB-N的建模效果及在实际生产中应用该技术提供了基础。     

近红外光谱法快速检测猪肉中挥发性盐基氮的含量

为了实现快速无损地检测猪肉新鲜度的目的,应用近红外光谱法测定猪肉新鲜度重要指标一挥发性盐基氮(TVB-N)的含量.猪肉原始光谱经标准偏差归一化方法(SNV)预处理后,用联合区间偏最小二乘法(siPLS)建立猪肉预处理后光谱和TVB-N含量的校正模型并与经典偏最小二乘法(PLS)模型、间隔偏最小二乘法(iPLS)模型作比较.试验结果表明,利用联合区间偏最小二乘法所建的预测模型最佳,其校正集相关系数(Rc)和交瓦验证均方根误差(fRv)分别为0.8332和3.75,预测集的相关系数(Rp)和预测均方根误差(fRP)分别为0.8238和4.17.研究结果表明利用近红外光谱和联合区间偏最小二乘法可以快速地测定猪肉中挥发性盐基氮的含量.     

Optimization of Fish Quality by Evaluation of Total Volatile Basic Nitrogen (TVB-N) and Texture Profile Analysis (TPA) by Near-Infrared (NIR) Hyperspectral Imaging

Hyperspectral images contain both spectral and spatial image information and were investigated to characterize the freshness of fish. However, most studies of this application have focused on spectral signals rather than image features. The goal of this work was to investigate the ability of spectral and image textural variables for predicting the chemical and physical qualities of fish, respectively, and to optimize the variables for the specific quality determination. The chemical (total volatile basic nitrogen, TVB-N) and physical (texture profile analysis, TPA) properties were investigated. Partial least square (PLS) was applied to develop fish quality prediction models with the spectral and textural variables from the hyperspectral images. The results showed that the TVB-N content of fish fillets was accurately predicted using the spectra. Meanwhile, the TPA parameters were determined through the image textural features with high accuracy, which indicated image textural features were highly related with the TPA parameters. Moreover, spectral and textural features were also extracted from fish eyes and gills and were further used to predict the intact fish quality, taking advantage of the freshness sensitivity of the eyes and gills. The results illustrate that spectra from fish eyes and gills are a potential tool to predict the TVB-N content and TPA parameters for intact fish.     

应用高光谱图像检测鱼肉挥发性盐基总氮含量研究

鱼类产品的新鲜程度研究一直是重要的课题,其中挥发性盐基总氮（TVB-N）是一项重要指标,该指标已列入我国食品卫生标准, 一般在低温条件下, 鱼类挥发性盐基氮的量达到30 mg/100 g时,即认为是肉质变质的标志。传统的物理检测方法不能够实现定量检测,化学检测法则耗时长,且需要专业人员进行破坏式检测。为了克服传统光谱检测技术无法检测分析外部空间属性的缺点,该实验采用波长范围在900～1 700 nm高光谱成像结合化学计量法实现了三文鱼的TVB-N含量检测。首先对从市场买的新鲜三文鱼按照背面和反面（腹部）进行分割处理,背面和反面（腹部）再10等分,每条三文鱼制作成20个样本,一共100个样本,其中75个样本用于校正集,25个样本用于预测集。然后用高光谱成像系统采集三文鱼鱼样本的光谱数据,再通过蒸馏法测定三文鱼TVB-N的含量,并建立其理化值样本,然后分别采用最小二乘支持向量机（LS-SVM）和偏最小二乘（PLS）模型对100个样本光谱全波长数据进行三文鱼TVB-N建模分析。LS-SVM模型和PLS模型预测决定系数(R2)分别为0.918和0.907,预测均方根误差(RMSEP)分别为2.312%和2.751%。为了进一步提高运算效率和优化模型,对全谱数据利用连续投影算法（SPA）提取到8个特征波长（956,1 013,1 152,1 210,1 286,1 301,1 397和1 464 nm）,基于8个特征波长分别建立SPA-LS-SVM和SPA-PLS模型,模型预测决定系数(R2)分别为0.903和0.901,RMSEP分别为2.761%和2.801%,SPA-LS-SVM模型的结果优于SPA-PLS。最后SPA-LS-SVM模型因其可靠性和有效性而被选择为最适合TVB-N预测模型,基于图像处理编程技术将高光谱图像中的每个像素转换成相应的TVB-N值并以不同颜色表示,实现了三文鱼肉TVB-N含量的可视化,可以很形象的表达三文鱼的TVB-N的含量分布情况。实验说明,可利用高光谱成像技术预测三文鱼的TVB-N含量预测,这为水产品的自动加工和分类奠定了基础,渔业可以从高光谱技术中获益。