CN103558296B - Animal source feed raw material identification method based on fatty acid detection - Google Patents
Animal source feed raw material identification method based on fatty acid detection Download PDFInfo
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Abstract
The invention provides an animal source feed raw material identification method based on fatty acid detection. The identification method comprises the following steps: 1) collecting and preparing different species of animal source feed samples with a known source; 2) detecting fatty acids; 3) determining detected and un-detected information basic data of the fatty acids; 4) establishing a discriminatory analysis model; 5) evaluating the discriminatory analysis model; 6) determining detected and un-detected information data of the fatty acids in the animal source feed samples to be detected, inputting the determined detected and un-detected information data of the fatty acids in the animal source feed samples to be detected in the model and performing species identification analysis. According to the identification method, fatty samples are extracted by using a conventional soxhlet method, so that fatty acid detection results of different species of animal source feeds can be obtained accurately; composition difference characteristics of the fatty acids in different species of animal source feeds are embodied intuitively and significantly; the stability of the identification model is effectively ensured; meanwhile, identification analysis results are displayed intuitively. Through using the identification method, the effective identification analysis of different species of animal source feeds can be realized, so that the analysis requirement of animal source feeds on feed quality and safety supervision can be satisfied.
Description
Technical field
The invention belongs to the discriminating field of animalsderived feedstuffs, particularly a kind of discriminatory analysis method of the different genera animal-based protein feed based on fatyy acids.
Background technology
In recent years, " rabid ox disease " event all brings enormous impact to European Union and even worldwide animal husbandry, public safety, feed industry and livestock products international trade, while serious threat animals and humans health, also result in huge economic loss.In order to cut off the route of transmission of rabid ox disease from source, make laws one after another in countries in the world, the use of regulation limitations or animalsderived feedstuffs such as forbidding meat meal tankage etc.But because protein feed resource is deficient, in addition the ordering about of interests, the behavior of the Misuse animalsderived feedstuffs such as the contraband of import, manufacturing and marketing the fake and violated interpolation remains incessant after repeated prohibition, and this is very disruptive market order not only, the interests of infringement consumer, also result in very large rabid ox disease hidden danger.
Meet feeding quality security control demand, guarantee effective enforcement of relevant laws and regulations, the reliable detection technique of science and method are important guarantees.And in order to the sustainable development of implementing feed industry better with recycle, whether be the inevitable development trend of animalsderived feedstuffs forbidding laws and regulations, this also proposes higher requirement to the authentication technique of different genera animalsderived feedstuffs if to be progressively refined between different genera mutually feeding.At present, microscopic analysis and polymerase chain reaction method is mainly for the animalsderived feedstuffs examination criteria method of official's arbitration in international coverage, although these two kinds of methods can carry out the discriminatory analysis of different genera animal derived materials, but all have some limitations, the species discrimination that single use is difficult to meet efficiently and accurately analyzes requirement.
Summary of the invention
For this area Problems existing, the object of this invention is to provide a kind of discriminatory analysis method of the different genera animalsderived feedstuffs raw material based on fatyy acids.
Animalsderived feedstuffs raw material of the present invention comprises the protein feeds such as terrestrial animal meat meal tankage, terrestrial animal digested tankage, terrestrial animal bone meal and fish meal.On Vehicles Collected from Market, animalsderived feedstuffs mostly is single kind animal and makes, and the present invention is also that the animalsderived feedstuffs made for multiple different single kind animal carries out discriminatory analysis.
The technical scheme realizing the object of the invention is:
Based on an animalsderived feedstuffs raw material discrimination method for fatyy acids, comprise the following steps:
1) the different genera animalsderived feedstuffs sample collection in known source and preparation;
2) common fatty acids of 2-24 carbon number measures;
3) determine that fatty acid detects and do not detect information base data;
4) detect according to the fatty acid determined in step 3) and do not detect information data, setting up different genera animalsderived feedstuffs discriminatory analysis model;
5) evaluation procedure 4) the discriminatory analysis model set up;
6) determine that in tested animal source feed sample, fatty acid detects and do not detect information data, input step 4) in the discriminatory analysis model set up carry out species discrimination analysis.
Wherein, described step 1) also comprises carries out Cyclone mill pulverizing to collected with the different genera animalsderived feedstuffs in the known source of preparation, then crosses 1.0mm sieve.
Preferably, in step 2) in, adopt soxhlet extraction to extract lipid samples, adopt common 37 kinds of fatty acid of gas chromatography determination 2-24 carbon number.
Wherein, the detecting and do not detect information data determination mode and be defined as " 1 " for be detected by certain fatty acid of fatty acid in described step 3), does not detect and is defined as " 0 ".
Wherein, in described step 4), adopt the Return Law and leaving-one method validation-cross, set up different genera animalsderived feedstuffs partial least squares discriminant analysis model.
Wherein, in described step 5), adopt discrimination Sensitivity and reject rate Specificity two indices to evaluate discrimination model, Sensitivity and Specificity is more close to 1, and discrimination model precision is higher.
Sensitivity=PA/（PA+ND） （1）
Specificity=NA/（PD+NA） （2）
In formula: PA is for differentiating positive number, and ND is for differentiating false negative sample number, and NA is for differentiating negative sample number, and PD is for differentiating false positive sample number.
Preferably, when described discrimination Sensitivity and reject rate Specificity is 0.85-1.0, described discriminatory analysis model is effective.
Wherein, in step 6), adopt soxhlet extraction to extract tested animal source feed lipid samples, common 37 kinds of fatty acid of a gas chromatography determination 2-24 carbon number, and be defined as " 1 " by fatty acid is detected, do not detect and be defined as " 0 " and determine detecting and not detecting information data, input step 4 of variety classes fatty acid in tested animal source feed sample) in the discriminatory analysis model set up carry out species discrimination analysis.
Excellent results of the present invention is:
1) the present invention adopts conventional soxhlet extraction to carry out lipid samples extraction, adopts gas chromatography classical way to carry out common 37 kinds of fatty acid determination of 2-24 carbon number, can the fatyy acids result of conventional Obtaining Accurate different genera animalsderived feedstuffs.
2) the present invention is defined as " 1 " by being detected by certain fatty acid, do not detect the mode being defined as " 0 ", determine detecting and not detecting information base data of fatty acid, intuitively also significantly can embody the composition difference characteristic of fatty acid in different genera animalsderived feedstuffs.
3) the present invention utilizes the Return Law and leaving-one method validation-cross to set up different genera animalsderived feedstuffs partial least squares discriminant analysis model, and evaluated by discrimination Sensitivity and reject rate Specificity two indices, while effectively ensureing discrimination model stability and the discriminatory analysis ability of display model directly perceived.
4) discrimination method provided by the invention, effective discriminatory analysis of different genera animalsderived feedstuffs can be realized, thus meet the analysis requirement of feeding quality security control for animalsderived feedstuffs species discrimination, can ensure while efficient strick precaution " rabid ox disease ", effectively implement the sustainable development of feed industry and recycle.
Accompanying drawing explanation
Fig. 1 is the different genera animalsderived feedstuffs principal component analysis (PCA) figure based on fatyy acids in the embodiment of the present invention.
Embodiment
Following examples for illustration of the present invention, but are not used for limiting the scope of the invention.
Below in conjunction with drawings and Examples, the present invention is described in detail.
The present invention includes following steps:
1) collect the different genera animalsderived feedstuffs sample with preparation reliable sources, pulverize 1.0mm sieve with Cyclone mill.
2), after adopting soxhlet extraction to extract above-mentioned sample lipid samples, common 37 kinds of fatty acid of gas chromatography determination 2-24 carbon number are adopted.
3) certain fatty acid is detected be defined as " 1 ", do not detect and be defined as " 0 ", determine detecting and not detecting information base data of variety classes fatty acid;
4) detect according to determined fatty acid and do not detect information data, adopting the Return Law and leaving-one method validation-cross, set up different genera animalsderived feedstuffs partial least squares discriminant analysis model.
5) adopt discrimination Sensitivity and reject rate Specificity two indices to evaluate discrimination model, wherein Sensitivity and Specificity is more close to 1, and discrimination model precision is higher.
Sensitivity=PA/（PA+ND） （1）
Specificity=NA/（PD+NA） （2）
In formula: PA is for differentiating positive number, and ND is for differentiating false negative sample number, and NA is for differentiating negative sample number, and PD is for differentiating false positive sample number.
6) after same procedure adopts soxhlet extraction to extract tested animal source feed lipid samples, common 37 kinds of fatty acid of a gas chromatography determination 2-24 carbon number, and be defined as " 1 " by certain fatty acid is detected, do not detect and be defined as " 0 " and determine detecting and not detecting information data, input step 4 of variety classes fatty acid in tested animal source feed sample) in the discriminatory analysis model set up carry out species discrimination analysis.
Enumerate a specific embodiment below, apply the present invention to discriminatory analysis five different generas (pig source, Ji Yuan, Niu Yuan, Yang Yuan and the source of fish) animalsderived feedstuffs sample.
Embodiment 1
1) sample collection and preparation is studied
Research sample is the animalsderived feedstuffs of 51 parts of known animal species, comprise and collect product from home and overseas protein feed enterprise and self-control sample two parts through relevant quality testing department, sample covers terrestrial animal digested tankage, bone meal, meat meal tankage, feather meal and fish meal etc., wherein 10, pig source sample, 8, chicken source sample, 9, ox source sample, 11, sheep source sample and 13, source of fish sample).
All research samples adopt Cyclone mill to pulverize, and then cross 1.0mm sieve.
2) sample determination of fatty acid
Soxhlet extraction is adopted to utilize full-automatic Milko-Tester (SoxtecTM2050, FOSS company of Denmark) extract above-mentioned research sample lipid samples, then gas chromatograph (GC-2014C is adopted, SHIMADZU company of Japan) measure common 37 kinds of fatty acid of 2-24 carbon number, wherein fatty acid methyl ester hybrid standard product (47885-U) are purchased from Sigma-Aldrich company.
3) fatty acid detects and does not detect information base data and determine
Certain fatty acid is detected and is labeled as " 1 ", do not detect and be labeled as " 0 ", determine detecting and not detecting information base data of variety classes fatty acid, the statistics of all sources sample is in table 1, and between different genera sample, the fatty acid composition of indifference is unlisted in this table.
Table 1
4) discriminatory analysis model Establishment and evaluation
Adopt Matlab software (R2010b, Mathworks company of the U.S.), first in his-and-hers watches 1, experimental data carries out principal component analysis (PCA) (PCA).Fig. 1 detects and the different genera animalsderived feedstuffs principal component analysis (PCA) figure not detecting information data based on fatty acid.Legend shows: first three major component accounts for 25.31%, 13.75% and 11.60% of total variation respectively, study pig in sample, chicken, ox, sheep and fish five kinds sample be in five groups be separated from each other respectively, there is good degree of separation.
Detect according to above-mentioned determined fatty acid and do not detect information data, adopt the Return Law and leaving-one method validation-cross, set up different genera animalsderived feedstuffs partial least squares discriminant analysis (PLS-DA) model, discrimination Sensitivity and the reject rate Specificity of model the results are shown in Table 2:
Table 2
Result shows, the experiment sample discrimination Sensitivity of five Species origins and reject rate Specificity is all close to 1, especially the discrimination Sensitivity of pig source, Yang Yuan and source of fish sample and reject rate Specificity is 1.00, shows higher discriminatory analysis model accuracy.
5) discriminatory analysis modelling verification
Select experiment sample (pig, chicken, ox, Yang Heyu that 10 to be measured, every kind 2 samples, be labeled as respectively pig source 1, pig source 2, chicken source 1, chicken source 2 ... .), verify set up discriminatory analysis model, the fatty acid of checking sample detects and does not detect information base data in table 3:
Table 3
The result shows, the species discrimination analysis result of 10 samples is all correct, and discrimination Sensitivity and the reject rate Specificity of pig, chicken, ox, sheep and fish five kind samples are 1.00.
Above embodiment is only be described the preferred embodiment of the present invention; not scope of the present invention is limited; under not departing from the present invention and designing the prerequisite of spirit; the various modification that the common engineering technical personnel in this area make technical scheme of the present invention and improvement, all should fall in protection domain that claims of the present invention determine.
Claims (4)
1., based on an animalsderived feedstuffs raw material discrimination method for fatyy acids, comprise the following steps:
1) the different genera animalsderived feedstuffs sample collection in known source and preparation;
2) common fatty acids of 2-24 carbon number measures; Wherein, adopt soxhlet extraction to extract lipid samples, then adopt common 37 kinds of fatty acid of gas chromatography determination 2-24 carbon number;
3) determine that fatty acid detects and do not detect information base data;
4) according to step 3) in the fatty acid determined detect and do not detect information data, set up different genera animalsderived feedstuffs discriminatory analysis model; Wherein the detecting and do not detect information data determination mode and be defined as " 1 " for be detected by this kind of fatty acid of fatty acid, does not detect and is defined as " 0 ";
5) evaluation procedure 4) the discriminatory analysis model set up, discrimination Sensitivity and reject rate Specificity two indices is adopted to evaluate discriminatory analysis model, Sensitivity and Specificity is more close to 1, and described discriminatory analysis model accuracy is higher;
Described discrimination Sensitivity and reject rate Specificity computing method as follows:
Sensitivity＝PA/(PA+ND) (1)
Specificity＝NA/(PD+NA) (2)
In formula: PA is for differentiating positive number, and ND is for differentiating false negative sample number, and NA is for differentiating negative sample number, and PD is for differentiating false positive sample number;
6) lipid samples of tested animal source feed sample is extracted with soxhlet extraction, with common 37 kinds of fatty acid of a gas chromatography determination 2-24 carbon number, fatty acid is detected and is defined as " 1 ", do not detect and be defined as " 0 ", determine detecting and do not detect information data, input step 4 of variety classes fatty acid in tested animal source feed sample) in the discriminatory analysis model set up carry out the discriminatory analysis of different genera animalsderived feedstuffs raw material.
2. discrimination method according to claim 1, its feature spy is, described step 1) in, the different genera animalsderived feedstuffs also comprised collecting with the known source of preparation carries out Cyclone mill pulverizing, then crosses the step of 1.0mm sieve.
3. discrimination method according to claim 1, its feature spy is, described step 4) in, adopt fatty acid described in the Return Law and leaving-one method validation-cross detect and do not detect information data, set up different genera animalsderived feedstuffs partial least squares discriminant analysis model.
4. discrimination method according to claim 1, its feature spy is, when described discrimination Sensitivity and reject rate Specificity is 0.85-1.0, described discriminatory analysis model is effective.
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