阅读说明：本技术 一种基于电子鼻与电子舌联合检测畜禽肉中淀粉的方法 (Method for detecting starch in livestock and poultry meat based on combination of electronic nose and electronic tongue ) 是由 王淑玲 孙京新 王宝维 李鹏 张希斌 黄明 徐幸莲 徐琳 于林宏 于 2018-06-13 设计创作，主要内容包括：本发明公开了一种基于电子鼻与电子舌联合检测畜禽肉中淀粉的方法。本发明优化了电子鼻与电子舌联合检测畜禽肉中淀粉的条件,操作简单、检测速度快,其灵敏度、可靠性和重复性都有很大的提高,填补了GB 5009.9-2016国标中的三种方法以及其他方法的不足,如所用试剂较多易造成环境污染,反应终点不易掌控和判断,所用时间过长,实验过程繁琐容易出现误差等,尤其适合应用于工厂生产线上已知配方的畜禽肉中淀粉含量是否稳定的检测与控制。(The invention discloses a method for detecting starch in livestock and poultry meat based on the combination of an electronic nose and an electronic tongue. The method optimizes the condition of detecting the starch in the livestock meat by combining the electronic nose and the electronic tongue, has simple operation, high detection speed and greatly improved sensitivity, reliability and repeatability, fills the defects of three methods in GB 5009.9-2016 national standard and other methods, such as more reagents used, environmental pollution, difficult control and judgment of reaction end points, overlong used time, complicated experimental process, easy error occurrence and the like, and is particularly suitable for detecting and controlling whether the starch content in the livestock meat with a known formula is stable on a factory production line.)

1. A method for detecting starch in livestock meat based on combination of an electronic nose and an electronic tongue is characterized by comprising the following steps:

(1) adding starch into minced livestock and poultry meat according to a series of proportions, respectively, uniformly mixing, wherein the total mass of each proportion is 10g, preparing a modeling sample, sequentially adding 0.01g of alpha-amylase (200000U/g), uniformly mixing, reacting at 60 ℃ for 15min, heating to 90 ℃, inactivating enzyme, and stopping enzymolysis; then adding 0.1 g-0.2 g of glycine, uniformly mixing, and carrying out Maillard reaction for 15min at the temperature of 95 ℃ to prepare a modeling sample after reaction;

(2) respectively transferring the modeling samples into a measuring bottle to be cooled to room temperature, contacting the electronic nose sensor with the air above the measuring bottle, and respectively generating corresponding sensor response values (SS)₁～SS₁₄) Adding KCl leaching solution into the modeling sample measuring bottle after reaction, leaching, filtering to obtain the modeling sample leaching solution after reaction, contacting the electronic tongue sensor with the leaching solution to respectively generate corresponding sensor response values (S)₁～S₆）；

(3) Respectively carrying out optimization processing on sensors of an electronic nose and an electronic tongue to obtain an optimal sensor combination, extracting response values of 60 s-80 s of the electronic nose sensor and response values of 100 s-120 s of the electronic tongue sensor, carrying out partial least square analysis through signal conversion processing, and finally outputting a starch doping proportion (%) formula by a computer as follows:

proportion (%) of starch incorporated =

106.728+0.064SS₃+0.029SS₉+0.047S₅+0.030S₂-0.058SS₁₀-0.019S₄

Wherein SS₃、SS₉And SS₁₀Respectively, the sensor response value of the electronic nose, S₂、S₄And S₅Respectively the sensor response values of the electronic tongue;

(4) taking 10g of ground livestock and poultry meat paste sample to be detected containing starch, adding 0.01g of alpha-amylase (200000U/g), mixing uniformly, reacting at 60 ℃ for 15min, heating to 90 ℃, inactivating enzyme, and stopping enzymolysis; adding 0.1 g-0.2 g of glycine, uniformly mixing, carrying out Maillard reaction for 15min at 95 ℃, transferring a sample to be detected after reaction into a measuring bottle, cooling to room temperature, contacting an electronic nose sensor with air above the measuring bottle to generate a sensor response value SS₁～SS₁₄Setting the detection condition of the electronic nose and modeling a sample after reaction, adding KCI leaching liquor into a measuring bottle, leaching for 30min, filtering to obtain the leaching liquor of the sample to be detected after reaction, contacting the electronic tongue sensor with the leaching liquor to generate a sensor response value S₁～S₆Setting the detection condition of the electronic tongue and modeling a sample after reaction;

(5) and (4) extracting the response values of 60 s-80 s of the electronic nose sensor as parameters, and the response values of 100 s-120 s of the electronic tongue sensor as parameters, substituting into the PLS model established in the step (3), and calculating the starch content in the livestock and poultry meat.

2. The method according to claim 1, wherein the series of ratios in step (1) are 0.0%, 2.5%, 5.0%, 7.5%, 10.0%, 15.0% in this order.

3. The method of claim 1, wherein the electronic nose detection conditions in step (2) are as follows: carrier gas flow is 0.6L/min, sensor cleaning time is 120s, sample preparation time is 10s, and sampling time is 80 s.

4. The method of claim 1, wherein the electronic tongue detection conditions in step (2) are as follows: sample time 120s, sensor wash time 10 s.

5. The process according to claim 1, wherein the concentration of KCl leaching solution in the step (2) is 0.1 mol/L.

Technical Field

The invention belongs to the technical field of meat detection, relates to a method for detecting starch in livestock and poultry meat, and particularly relates to a method for detecting whether starch is mixed in the livestock and poultry meat or not and the content of the starch in the livestock and poultry meat based on the combination of an electronic nose and an electronic tongue.

Background

The livestock and poultry meat is an important part of dietary nutrition, has tender texture and rich nutrition, has the advantages of high protein, low fat, low calorie, low cholesterol and the like, and is popular with consumers. However, due to the special properties of livestock and poultry meat, protein is difficult to form a good network structure in the processing process, thereby affecting the elasticity and mouthfeel of the product. Relevant studies show that the tenderness and water retention of meat products can be improved by adding a proper amount of starch into the meat products (Dangli, Miao Hamming. research on the influence of modified starch on the quality of chicken paste [ J ]. food industry science and technology, 2005, 3(13): 72-75.), thereby improving the eating quality of the meat products and improving the yield (Kangzhuanli, Zhudong Yang, Zhao Zhi, Zhao Ming, Mahan army, Song Zhao Sheng Ming, influence of corn starch on the water retention and sensory quality of fried chicken blocks [ J ]. food and fermentation industry, 2017,43(06):198 and 202.). The addition of starch can also obviously improve the processing quality of meat products, reduce the addition amount of fat in meat product processing, and also obviously improve the sensory quality of meat products (Liuwenying, Linhailong, Huaxianing, Chengxua, Lijiapeng, Xue Xiaozhong, Gaoshan, Xiaoyu, Zhang Shuangliang. At present, some illegal merchants excessively add starch (generally not more than 15.0%) into meat, and some of the meat even contain transgenic ingredients, so that the quality of the meat is seriously influenced, and the meat is deceived for consumers.

At present, the existing methods for detecting starch in meat products at home and abroad mainly comprise acid hydrolysis, enzyme hydrolysis, iodometry, optical rotation and the like. The GB 5009.9-2016 national standard is adopted to measure the starch content in meat and meat products at the present stage of China. This standard first method (enzymatic hydrolysis) and second method (acid hydrolysis) are suitable for the determination of starch in food products (excluding meat products); the third method (iodometry) is suitable for the determination of starch in meat products. The reaction end point of the acid hydrolysis method is difficult to control and judge, and the experimental process is complicated and has errors; the enzyme hydrolysis method considers the gelatinization factor of starch, the measurement result has great relation with the size of starch grains and the type of samples, and the measurement is not accurate enough; the iodometry is a special method for measuring the starch content in the meat product, and the iodometry is long in time consumption and relatively complicated in sample treatment; the optical rotation method has large measurement error for starch samples of unknown sources, and the measurement result for the starch denatured by heat is unreliable.

At present, research on the aspect of detecting meat products by using an electronic nose and an electronic tongue has been reported, for example, the electronic nose is used for identifying meat types (jiahong feng, luyi, he jiang hong. the application of the electronic nose in identifying yak meat and beef pork [ J ]. agricultural engineering bulletin, 2011, 27(5): 358.), the electronic tongue is used for meat quality differentiation (royal jelly, xu Hai Lian, Rong. the research on meat quality differentiation based on the electronic tongue technology [ J ]. food science, 2012,33(21):100-, 2017,38(04):73-76+ 80.), the quality of beef detected by the electronic nose and the electronic tongue (Wangweijing, Zhangshan, Xipeng, Zhangshisheng, Sunbao, the quality of beef under stewing [ J ] detected by the electronic nose and the electronic tongue [ J ] food research and development, 2017,38(17): 124-. The application aims to innovate a new method for detecting starch in livestock and poultry meat.

Disclosure of Invention

The invention aims to provide a method for detecting the content of starch doped in livestock meat based on the combination of an electronic nose and an electronic tongue, so as to overcome the problems existing at present.

The method for detecting the content of the starch doped in the livestock and poultry meat comprises the following steps:

(1) adding starch into minced livestock and poultry meat according to a series of proportions, respectively, uniformly mixing, wherein the total mass of each proportion is 10g, preparing a modeling sample, sequentially adding 0.01g of alpha-amylase (200000U/g), uniformly mixing, reacting at 60 ℃ for 15min, heating to 90 ℃, inactivating enzyme, and stopping enzymolysis; then adding 0.1 g-0.2 g of glycine, uniformly mixing, and carrying out Maillard reaction for 15min at the temperature of 95 ℃ to prepare a modeling sample after reaction;

the series of proportions are 0.0%, 2.5%, 5.0%, 7.5%, 10.0% and 15.0% in sequence.

(2) Respectively transferring the modeling samples into a measuring bottle to be cooled to room temperature, contacting the electronic nose sensor with the air above the measuring bottle, and respectively generating corresponding sensor response values (SS)₁～SS₁₄). The electronic nose detection conditions were set as follows: carrier gas flow is 0.6L/min, sensor cleaning time is 120s, sample introduction time is 10s, and sampling time is 80 s; adding KCl leaching solution into the reacted modeling sample measuring bottle, leaching, filtering to obtain reacted modeling sample leaching solution, contacting the electronic tongue sensor with the leaching solution to respectively generate corresponding sensor response values (S)₁～S₆). The electronic tongue detection conditions were set as follows: sampling time 120s, and sensor cleaning time 10 s;

the concentration of the KCl leaching liquor is 0.1 mol/L.

(3) And respectively carrying out optimization processing on the sensors of the electronic nose and the electronic tongue to obtain the optimal sensor combination. Extracting the response values of 60 s-80 s of the electronic nose sensor and the response values of 100 s-120 s of the electronic tongue sensor, performing partial least squares analysis through signal conversion processing, and finally outputting a starch doping proportion (%) formula by a computer as follows:

proportion (%) of starch incorporated = 106.728+0.064SS₃+0.029SS₉+0.047S₅+0.030S₂-0.058SS₁₀-0.019S₄

Wherein SS₃、SS₉And SS₁₀Respectively, the sensor response value of the electronic nose, S₂、S₄And S₅Respectively, the sensor response values of the electronic tongue.

(4) Taking minced livestock and poultry meat paste containing starch to be testedAdding 0.01g of alpha-amylase (200000U/g) into 10g of a sample, uniformly mixing, reacting at 60 ℃ for 15min, heating to 90 ℃, inactivating enzyme, and stopping enzymolysis; adding 0.1 g-0.2 g glycine, mixing, Maillard reacting at 95 deg.C for 15min, transferring the reacted sample to the measuring bottle, cooling to room temperature, contacting the electronic nose sensor with the air above the measuring bottle to generate sensor response value (SS)₁～SS₁₄) Setting the detection condition of the electronic nose and modeling a sample after reaction; adding KCl leaching solution into the measuring bottle, leaching for 30min, filtering to obtain reacted sample leaching solution, contacting the electronic tongue sensor with the leaching solution to generate sensor response value (S)₁～S₆) And setting the electronic tongue detection conditions and modeling samples after reaction.

(5) And extracting the response value of 60 s-80 s of the electronic nose sensor as a parameter, and the response value of 100 s-120 s of the electronic tongue sensor as a parameter, substituting the parameters into the established PLS model, and calculating the starch content in the livestock meat. The relative error of the content of the starch measured by the method is about 0.09 percent and is obviously lower than that of the prior method.

The invention provides a method for detecting the content of starch in livestock meat based on the combination of an electronic nose and an electronic tongue. The method is simple to operate, high in detection speed, and greatly improved in sensitivity, reliability and repeatability, overcomes the defects of three methods in GB 5009.9-2016 national standard and other methods, and is especially suitable for detection and control of whether the starch content in livestock and poultry meat with a known formula is stable in a factory production line, such as more reagents are used, environmental pollution is easily caused, the reaction end point is not easy to control and judge, the used time is too long, the experimental process is complicated, errors are easily caused, and the like.

Detailed Description

The applicant has developed the present invention by improving the pretreatment process of the sample to be tested and the parameters of the test in order to create a new method for testing starch in livestock and poultry meat.

The method for detecting the starch in the chicken based on the combination of the electronic nose and the electronic tongue comprises the following steps:

(1) adding starch into minced livestock and poultry meat according to a series of proportions, respectively, uniformly mixing, wherein the total mass of each proportion is 10g, preparing a modeling sample, sequentially adding 0.01g of alpha-amylase (200000U/g), uniformly mixing, reacting at 60 ℃ for 15min, heating to 90 ℃, inactivating enzyme, and stopping enzymolysis; then adding 0.1 g-0.2 g of glycine, uniformly mixing, and carrying out Maillard reaction for 15min at the temperature of 95 ℃ to prepare a modeling sample after reaction;

the series of proportions are 0.0%, 2.5%, 5.0%, 7.5%, 10.0% and 15.0% in sequence.

(2) Respectively transferring the modeling samples into a measuring bottle to be cooled to room temperature, contacting the electronic nose sensor with the air above the measuring bottle, and respectively generating corresponding sensor response values (SS)₁～SS₁₄). The electronic nose detection conditions were set as follows: carrier gas flow is 0.6L/min, sensor cleaning time is 120s, sample introduction time is 10s, and sampling time is 80 s; adding KCl leaching solution into the reacted modeling sample measuring bottle, leaching, filtering to obtain reacted modeling sample leaching solution, contacting the electronic tongue sensor with the leaching solution to respectively generate corresponding sensor response values (S)₁～S₆). The electronic tongue detection conditions were set as follows: sampling time 120s, and sensor cleaning time 10 s;

the concentration of the KCl leaching liquor is 0.1 mol/L.

(3) And respectively carrying out optimization processing on the sensors of the electronic nose and the electronic tongue to obtain the optimal sensor combination. Extracting the response values of 60 s-80 s of the electronic nose sensor and the response values of 100 s-120 s of the electronic tongue sensor, performing partial least squares analysis through signal conversion processing, and finally outputting a starch doping proportion (%) formula by a computer as follows:

proportion (%) of starch incorporated = 106.728+0.064SS₃+0.029SS₉+0.047S₅+0.030S₂-0.058SS₁₀-0.019S₄

Wherein SS₃、SS₉And SS₁₀Respectively, the sensor response value of the electronic nose, S₂、S₄And S₅Respectively, the sensor response values of the electronic tongue.

(4) Taking minced starch containingAdding 10g of powdery livestock and poultry meat paste sample to be detected into 0.01g of alpha-amylase (200000U/g), uniformly mixing, reacting at 60 ℃ for 15min, heating to 90 ℃, inactivating enzyme and stopping enzymolysis reaction; adding 0.1 g-0.2 g glycine, mixing, Maillard reacting at 95 deg.C for 15min, transferring the reacted sample to the measuring bottle, cooling to room temperature, contacting the electronic nose sensor with the air above the measuring bottle to generate sensor response value (SS)₁～SS₁₄) Setting the detection condition of the electronic nose and modeling a sample after reaction; adding KCl leaching solution into the measuring bottle, leaching for 30min, filtering to obtain reacted sample leaching solution, contacting the electronic tongue sensor with the leaching solution to generate sensor response value (S)₁～S₆) And setting the electronic tongue detection conditions and modeling samples after reaction.

(5) And extracting the response value of 60 s-80 s of the electronic nose sensor as a parameter, and the response value of 100 s-120 s of the electronic tongue sensor as a parameter, substituting the parameters into the established PLS model, and calculating the starch content in the livestock meat. The relative error of the content of the starch measured by the method is about 0.09 percent and is obviously lower than that of the prior method.

The present invention will be described in detail with reference to specific examples.