猪肉中挥发性盐基氮含量光谱检测模型的修正方法

目的 研究猪肉新鲜度指标挥发性盐基氮(TVB-N)含量检测模型修正方法, 以提高光谱校正模型对不同品种猪肉样品的适用性。方法 建立基于偏最小二乘回归(PLSR)的杜长大猪肉TVB-N模型, 采用光谱信号补正与模型更新两种方法对该模型进行修订, 比较修正后杜长大模型对恩施山猪样本的预测效果。结果 建立的杜长大猪肉样本模型预测决定系数R2p为0.884, 预测标准差RMSEP为1.792, 将此模型用于预测恩施山猪TVB-N值, R2p为0.552, RMSEP为4.733。修正后的杜长大猪肉样本模型预测恩施山猪TVB-N值时, R2p分别提高到0.964和0.943, RMSEP分别降低为1.329和1.885。结论 光谱信号补正和模型更新方法均能有效改善模型预测性能, 提高模型适应性。     

一种基于高光谱图像的熟牛肉TVB-N含量预测方法

传统肉制品新鲜度检测方法具有耗时费力、效率低、有损等缺陷,提出利用高光谱成像(HSI)技术预测熟牛肉新鲜度指标挥发性盐基氮(TVB-N)含量。首先通过HSI系统获取熟牛肉样本的高光谱数据,并进行黑白校正。进而采用移动平均平滑和多元散射校正对高光谱数据进行预处理。最后采用支持向量回归(SVR)方法分别建立基于全光谱特征、单一光谱特征、单一纹理特征、主成分分析(PCA)融合特征对TVB-N含量的预测模型。结果显示,使用PCA融合特征的SVR模型,对新鲜度的关键指标TVB-N含量的平均预测准确度(APA)可达到85.13%,表明高光谱成像技术与信息融合技术相结合能够提升模型准确度。     

近红外光谱技术快速检测小龙虾新鲜度

应用近红外光谱技术实现对小龙虾新鲜度的快速检测。利用化学计量学方法,通过对近红外品质分析仪采集的虾肉绞碎前后光谱（850～1 050 nm）调整不同预处理方法、偏最小二乘法和组合算法,建立一种基于总挥发性盐基氮（total volatile basic nitrogen,TVB-N）含量的小龙虾新鲜度定量预测模型。结果表明：采用标准正态变量变换与一阶导数结合的预处理方法模型预测效果最好,且绞碎后的虾肉光谱比绞碎前建模效果更好;为满足实际应用需要,对绞碎前的虾肉TVB-N含量预测模型进行分析,其交叉验证误差为3.123,交叉验证相关系数为0.947,用此模型对预测集24 个样品进行预测,预测值与实测值的交叉验证相关系数为0.951 4,在TVB-N含量超过20 mg/100 g（不新鲜）的检测准确率为100%。近红外光谱技术可应用于快速检测小龙虾新鲜度,所建模型具有较好的预测能力。     

鲫鱼新鲜度近红外定量预测模型的建立

为实现鲫鱼新鲜度的快速测定,本文基于近红外漫反射光谱定量分析技术和化学计量学方法,采集了144个鲫鱼鱼肉样品在1000~1799 nm范围内的光谱数据,测定了鲫鱼样品的p H、TVB-N含量、TBA含量和K值四种新鲜度指标;在确定近红外光谱数据最佳预处理方法和适宜波段的基础上,分别采用偏最小二乘法、主成分分析和BP人工神经网络技术、偏最小二乘法和BP人工神经网络技术建立了鲫鱼新鲜度定量预测模型。结果表明,鲫鱼样品四种指标数据范围均较大,可满足建模要求。以p H为鲜度指标时,采用偏最小二乘法和BP人工神经网络技术建立的模型最好,其定标相关系数为0.9945;以TVB-N、TBA和K值为鲜度指标时,采用偏最小二乘法建立的模型最好,其定标相关系数分别为0.9857、0.9985和0.9952。建立的四种鲜度指标定量模型均具有较好的预测能力。     

基于特征融合的猪肉新鲜度高光谱图像检测

利用高光谱反射图像技术研究了猪肉新鲜度的无损检测。采集了180个猪肉样本在400~1 000 nm范围内的高光谱反射图像,提取了高光谱图像的光谱均值和熵两类特征;分别利用连续投影算法、主成分分析,以及连续投影算法结合主成分分析3种特征降维方法,提取了反映肉类新鲜度信息的重要特征变量;并建立了这些特征变量与挥发性盐基氮(TVB-N)的最小二乘支持向量机(LSSVM)预测模型;在此基础上提出了猪肉TVB-N含量的可视化检测方法。研究结果表明:相比于单一特征模型,利用光谱均值和熵融合特征的LSSVM模型可显著提高模型的准确度;连续投影算法结合主成分分析的特征降维方法,可显著降低模型的复杂度,提高模型准确度。利用光谱均值和熵两类特征,通过连续投影算法和主成分分析相结合的特征降维方法所建立的LSSVM预测模型,可取得最佳的预测准确度,其预测集的均方根误差RMSEP为1.96,相关系数(RP)为0.948,剩余预测偏差(RPD)为3.12,可满足实际检测需要。建立在此基础上的可视化方法,可直观显示肉类的腐败区域和程度。     

比色法测定原料肉新鲜度方法的建立

总挥发性盐基氮(TVB-N)值是国家标准中用于评价肉质鲜度的唯一理化指标。以对二甲氨基苯甲醛(PDAB)为显色剂,研究原料肉中TVB-N含量与吸光度的关系。结果表明,1mL的肉浸汁中加入1.8%(W/V)PDAB显色剂4.5mL,浓盐酸1.2mL,蒸馏水3.3mL,于80℃水浴中加热8min,在446nm处测定其吸光度,一定范围内吸光度与TVB-N的含量成线性关系,因此建立了比色法测定原料肉新鲜度的方法。利用PDAB比色法检测原料肉的新鲜度,具有较高的精确度和回收率,而且快速、稳定、操作简单,可作为国家标准中测定原料肉新鲜度的替代方法之一。     

基于近红外光谱的大黄鱼新鲜度评价模型

目的 探索定量评价大黄鱼新鲜度的方法。方法 在整鱼背部采集近红外光谱, 将原始光谱预处理后分别与挥发性盐基氮(TVB-N)、菌落总数建立偏最小二乘(PLS)模型、区间偏最小二乘(iPLS)模型、向后区间偏最小二乘(biPLS)模型和联合区间偏最小二乘(siPLS)模型。结果 biPLS模型的精度最高、预测性能最佳。TVB-N的biPLS模型的校正集和预测集相关系数分别为0.8371和0.7652; 菌落总数的biPLS模型的校正集和预测集相关系数分别为0.878和0.7009。结论 大黄鱼的近红外光谱信息与其TVB-N、菌落总数间都存在较高的相关性, 所建模型可以快速、无损地定量评价大黄鱼的新鲜度。     

高光谱成像技术定量可视化检测熟牛肉中挥发性盐基氮的含量

为了能够快速、准确的检测出熟牛肉在冷藏过程中的新鲜状况,尝试利用高光谱成像技术对熟牛肉中的挥发性盐基氮(TVB-N)含量进行定量可视化分析。采集400~1000 nm范围内样品高光谱图像,采用变量组合集群分析法(VCPA)提取出6个光谱特征波段变量,针对特征波段图像,利用Tamura算法共提取出18个纹理特征变量,基于RGB颜色模型,分别计算出R、G和B分量图中共9个颜色特征变量。利用粒子群优化最小二乘支持向量机(PSO-LS-SVM)算法分别建立了不同变量组合的TVB-N含量预测模型。经分析比较,基于光谱与颜色特征融合的PSO-LS-SVM模型展现出最优的预测能力,预测集决定系数(R2p)和均方根误差(RMSEP)分别为0.955和1.093。利用最优模型将TVB-N含量进行可视化表达。结果表明,融合高光谱图像中光谱与颜色特征并结合PSO-LS-SVM算法对熟牛肉中TVB-N含量进行准确的预测与可视化表达是可行的,该研究可为其它肉及肉制品新鲜度检测提供理论参考。     

电子鼻技术对猪肉挥发性盐基氮的预测研究

为预测不同肥瘦配比猪肉的新鲜度,对4℃恒温贮藏条件下的新鲜猪肉进行挥发性盐基总氮(Total Volatile Basic Nitrogen,TVB-N)检测和营养成分检测,同时利用电子鼻技术检测挥发性气味的信息。以传感器阵列特征值为自变量建立蛋白质、脂肪的回归预测模型,分别对不同肥瘦配比的猪肉样本建立不分类和分类2种TVB-N神经网络预测模型。结果表明:先分类再建立神经网络模型预测的效果更优,将样本进行二分类建立2个模型后,模型训练组的相关系数达0.994、0.985(p<0.01),预测组的相关系数达到0.984、0.979(p<0.01);模型的绝对误差小而且分布区间集中,训练组和预测组各有86%、62.6%的样本的绝对误差在0~1之间;训练组中没有绝对误差大于2.5的样本,预测组中仅有8.5%的样本绝对误差大于2.5。电子鼻传感器特征信号与TVB-N数据具有很强的相关性,电子鼻可以快速预测出不同肥瘦配比猪肉在贮藏期间TVB-N含量的变化,进而无损的评价猪肉的新鲜度。     

高光谱成像技术对羊肉新鲜度的无损检测

为探究高光谱成像技术对羊肉新鲜度无损检测的可行性,通过高光谱成像系统获取羊肉样本935～2 539 nm的高光谱图像,测定羊肉挥发性盐基氮(total volatile basic nitrogen,TVB-N)含量并划分样本新鲜度类别。借助连续投影法(successive projection algorithm,SPA)优选的12个特征波长建立基于反向人工神经网络(back-propagation artificial neural network,BPANN)和分类回归决策树(classification and regression trees,CART)算法的羊肉新鲜度判别模型。结果表明,BPANN模型对校正集和预测集的平均分类准确率为100%和83. 33%,对3个新鲜度类别样本的识别率分别为88. 89%、75%和85. 71%;CART模型对校正集和预测集的平均分类准确率为100%和91. 67%,对3个新鲜度类别样本的识别率分别为88. 89%、87. 50%和100%。CART模型的平均分类准确率和对3个类别样本的识别率均高于BPANN模型,表明高光谱成像技术结合C...     

Difference in tenderness and pH decline between water buffalo meat and beef during postmortem aging

The objective of this research was to determine the difference in tenderness and some characteristics of water buffalo meat and beef during postmortem aging. Five female crossbred water-buffalo (Philippine Carabao×Bulgarian Murrah) and five female crossbred cattle (Brahman×Philippine Native), were finished on the same diet for 6 months and slaughtered at 30 months of age. The muscle pH was measured at 40min, 3h, 7h, 24h, and 48h postmortem. Longissimus thoracis (LT) and semimembranosus (SM) muscles were excised at 2d postmortem, and shear force was measured at 2, 4, 7, and 14d postmortem. Glycogen and lactate concentrations were determined from 0, 2, and 4d LT samples, and myosin heavy chain type of buffalo and cattle LT was determined by ELISA methods. Myofibrillar protein degradation was also observed by SDS-PAGE and Western blotting of fast-type troponin T. Results showed that the buffalo meat had significantly lower shear force values compared to beef for LT and SM muscles, which was supported by a difference in troponin T degradation. Postmortem pH decline of buffalo meat was significantly slower than that of beef, which was confirmed by lactic acid concentrations, but was not explained by glycogen content. In addition, there was no significant difference in the ratio of slow to fast type muscle fibers in buffalo and cattle, indicating that myosin heavy chain type was not responsible for the difference in pH decline and tenderness between the buffalo meat and beef. This study demonstrated that the tenderness of water buffalo meat was superior to that of Brahman beef, which may have been due to the difference in pH decline and the subsequent effect on muscle protease activity.     

Differentiation of cattle species in beef by PCR-RFLP of mitochondrial and satellite DNA

Methods currently used for the identification of the species origin of meat or tissue samples have not been validated for other bovine species than taurine cattle or water buffalo. These methods also do not discriminate between the different bovine species that are used as source of beef. Here, we describe two complementary methods for detection and differentiation of bovine species, which are based on mutations in mitochondrial DNA and centromeric satellite DNA, respectively. The analysis of satellite DNA is especially relevant for the identification of animals that are of hybrid origin.     

三重real-time PCR同步检测黄牛、水牛和牦牛成分

为准确快速地鉴定黄牛、水牛和牦牛的成分,研发具有这3 种牛特异性的引物和探针,并建立单重、双重和三重实时聚合酶链式反应（real-time polymerase chain reaction,real-time PCR）方法,同步检测上述3 种牛的成分。单重real-time PCR检测时,3 种牛的检测灵敏度均为0.025 ng/μL;双重real-time PCR检测时,两两组合的引物探针含量比例为1∶1时,黄牛的检测灵敏度降低至0.1 ng/μL,而水牛和牦牛仍为0.025 ng/μL;对三重real-time PCR检测体系进行优化,当黄牛、水牛和牦牛3 组引物探针的含量比例为3∶3∶2时,检测灵敏度最佳,黄牛和水牛的检测灵敏度可达到0.1 ng/μL,而牦牛的灵敏度仍可达到0.025 ng/μL。但上述双重和三重real-time PCR检测的灵敏度,是建立在3 种牛的含量比例为1∶1∶1的情况下,若3 种牛的比例差异较大,特别是黄牛和牦牛的含量比例差异较大时,如比例为9∶1时,含量低的成分会存在漏检。因此,在对整块肉的样品进行检测时,可采用三重real-time PCR的方法同步检测3 种牛的成分;若样品可能为上述3 种肉的为混合物,如肉糜、肉松等,则建议采用单重real-time PCR检测。     

搅拌型芒果果粒水牛酸乳制作工艺及其优化途径的研究

以具有广西特色的芒果和水牛奶为原料,先进行单因素实验,再利用Box-Behnken中心组合设计,将组合赋权评价方法和响应面分析法结合运用,优化搅拌型芒果果粒水牛酸乳制作工艺。结果表明:搅拌型酸乳的色泽、风味、质构的组合权重分别为0.311,0.373,0.336。其最优制作工艺条件是:砂糖质量分数为8%,果粒添加量10%,复配稳定剂添加量0.09%。依照优化工艺进行验证,采用组合赋权法评价样品,制品质量总分为1.21,误差较小,可见所建立的数学模型能较准确地反映搅拌型芒果果粒酸乳的工艺条件。     

Study of Fourier transform near infrared (FT‐NIR) spectra of ghee (anhydrous milk fat)

Ghee is chemically highly complex in nature. The authentication and characterisation of edible fats and oils by routine chemical methods are highly laborious and time‐consuming. Fourier transform near infrared (FT‐NIR) spectroscopy has emerged as the predominant analytical tool in the study of edible fats/oils. In order to assign absorption bands in the infrared (IR) spectrum, spectra of cow and buffalo ghee samples were acquired in the NIR region (10 000–4000 cm^?1). In the FT‐NIR spectrum, a total of nine peaks were obtained for cow and buffalo ghee, with almost equal intensity of absorption. The intensity of absorbance was higher for cow ghee compared to buffalo ghee.     

Use of duplex polymerase chain reaction (duplex-PCR) technique to identify bovine and water buffalo milk used in making mozzarella cheese

Molecular biology techniques have been used for species identification in food of animal origin in relatively recent years. A polymerase chain reaction (PCR) based method, the multiplex PCR, was recently applied to species identification in meat and meat products. It allows co-amplification of separate regions of a single gene or specific fragments, each typical of a different animal species in a single PCR reaction, using different pairs of primers in the same reaction mix. In the present paper, the duplex-PCR technique is proposed to identify bovine and water buffalo DNA in a single PCR assay in milk and mozzarella cheese (a typical Italian cheese, originally made from pure water buffalo milk). Because of its lower cost, undeclared bovine milk is added to water buffalo milk for making different kinds of mozzarella cheese. The results of this experiment indicate the applicability of this method, which showed an absolute specificity for the two species and a high sensitivity even down to low DNA concentrations (1 pg). In bovine and water buffalo mixtures of both milk and mozzarella cheese, the minimum concentration tested was 1% of bovine in water buffalo milk and water buffalo in bovine milk. The importance of the somatic cell content in raw milk is also discussed with special reference to the evaluation of mixtures (milk or cheese) of the two species.     

Molecular detection of meat animal species targeting MT 12S rRNA gene

The efficacy of PCR-RFLP analysis of mt 12S rRNA gene in identification of animal species from meat samples of known and unknown origin and adulterated meat samples was evaluated. In PCR, all the samples generated an amplicon of 456 bp. Restriction enzyme digestion of the PCR product with AluI, HhaI, BspTI and ApoI revealed characteristic RFLP patterns. Of the samples of unknown origin few were identified as cattle, few as buffalo and some were admixtures of two, suggesting adulteration. The RFLP pattern of one did not match any of species included in the study, which on sequencing was confirmed as camel meat. Application of this technique on adulterated meat samples could detect both animal species in proportion of 50:50 and 75:25 (except in case of goat+cattle). The technique however could not detect any of the two species when proportion of mixture was 90:10 (except in case of cattle+buffalo).     

DETECTION OF COW MILK IN BUFFALO "MOZZARELLA" BY POLYMERASE CHAIN REACTION (PCR) ASSAY

The authors used a polymerase chain reaction (PCR) assay on buffalo mozzarella, a typical Italian dairy product, from the Apulia markets to evaluate the presence of cow milk and verification of the mozzarella label. The results obtained from 30 mozzarella samples demonstrated the presence of the cow genome in 22/30 samples, highlighting contamination as probable fraudulent adding of cow's milk or use of the same equipments in both working cycles.     

Marker discovery and associations with β-carotene content in Indian dairy cattle and buffalo breeds

Vitamin A is essential for human health, but current intake levels in many developing countries such as India are too low due to malnutrition. According to the World Health Organization, an estimated 250 million preschool children are vitamin A deficient globally. This number excludes pregnant women and nursing mothers, who are particularly vulnerable. Efforts to improve access to vitamin A are key because supplementation can reduce mortality rates in young children in developing countries by around 23%. Three key genes, BCMO1, BCO2, and SCARB1, have been shown to be associated with the amount of β-carotene (BC) in milk. Whole-genome sequencing reads from the coordinates of these 3 genes in 202 non-Indian cattle (141 Bos taurus, 61 Bos indicus) and 35 non-Indian buffalo (Bubalus bubalis) animals from several breeds were collected from data repositories. The number of SNP detected in the coding regions of these 3 genes ranged from 16 to 26 in the 3 species, with 5 overlapping SNP between B. taurus and B. indicus. All these SNP together with 2 SNP in the upstream part of the gene but already present in dbSNP (https://www.ncbi.nlm.nih.gov/projects/SNP/) were used to build a custom Sequenom array. Blood for DNA and milk samples for BC were obtained from 2,291 Indian cows of 5 different breeds (Gir, Holstein cross, Jersey Cross, Tharparkar, and Sahiwal) and 2,242 Indian buffaloes (Jafarabadi, Murrah, Pandharpuri, and Surti breeds). The DNA was extracted and genotyped with the Sequenom array. For each individual breed and the combined breeds, SNP with an association that had a P-value <0.3 in the first round of linear analysis were included in a second step of regression analyses to determine allele substitution effects to increase the content of BC in milk. Additionally, an F-test for all SNP within gene was performed with the objective of determining if overall the gene had a significant effect on the content of BC in milk. The analyses were repeated using a Bayesian approach to compare and validate the previous frequentist results. Multiple significant SNP were found using both methodologies with allele substitution effects ranging from 6.21 (3.13) to 9.10 (5.43) µg of BC per 100 mL of milk. Total gene effects exceeded the mean BC value for all breeds with both analysis approaches. The custom panel designed for genes related to BC production demonstrated applicability in genotyping of cattle and buffalo in India and may be used for cattle or buffalo from other developing countries. Moreover, the recommendation of selection for significant specific alleles of some gene markers provides a route to effectively increase the BC content in milk in the Indian cattle and buffalo populations.