CN101361677A - Estimation method of lean meat percentage of live pig - Google Patents
Estimation method of lean meat percentage of live pig Download PDFInfo
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- CN101361677A CN101361677A CNA200810200154XA CN200810200154A CN101361677A CN 101361677 A CN101361677 A CN 101361677A CN A200810200154X A CNA200810200154X A CN A200810200154XA CN 200810200154 A CN200810200154 A CN 200810200154A CN 101361677 A CN101361677 A CN 101361677A
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- 235000020997 lean meat Nutrition 0.000 title claims abstract description 55
- 238000000034 method Methods 0.000 title claims abstract description 23
- 210000003205 muscle Anatomy 0.000 claims abstract description 27
- 241000282887 Suidae Species 0.000 claims abstract description 26
- 230000037396 body weight Effects 0.000 claims description 5
- 238000003307 slaughter Methods 0.000 abstract description 8
- 238000001514 detection method Methods 0.000 abstract description 4
- 210000002784 stomach Anatomy 0.000 abstract 1
- 238000002604 ultrasonography Methods 0.000 abstract 1
- 238000005259 measurement Methods 0.000 description 11
- 210000000988 bone and bone Anatomy 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 230000002596 correlated effect Effects 0.000 description 2
- 210000003734 kidney Anatomy 0.000 description 2
- 235000015277 pork Nutrition 0.000 description 2
- 230000003187 abdominal effect Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000008014 freezing Effects 0.000 description 1
- 238000007710 freezing Methods 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 238000001727 in vivo Methods 0.000 description 1
- 238000007427 paired t-test Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 210000000689 upper leg Anatomy 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
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Abstract
The invention discloses a method of estimating the lean meat percentage of a live pig and relates to the field of detection technique, which aims at solving the problems of detection technique for lean meat percentage of the live pig. The method of estimating the lean meat percentage of the live pig comprises steps as follows: 1) measuring the weight of the pig with empty stomach, and determining the sizes of back fat and eye muscles of the live pig by a B-typed ultrasound scanner; 2) substituting the weight, thickness of the back fat and size of the eye muscles into a regression equation of estimating the lean meat percentage of the live pig as follows: y is equal to 67.264 plus ax1 plus bx2 plus cx3; wherein, y refers to the estimated lean meat percentage, x1 the weight, x2 the thickness of the back fat and x3 the size of eye muscles; a represents a number between -0.067 and -0.059, b represents a number between -2.206 and -2.038, and c represents a number between 0.195 and 0.215; then finally gaining an estimated lean meat percentage of the detected pig. The method of estimating the lean meat percentage of the live pig has the advantages of high accuracy and measuring speed, and can determine the lean meat percentage of live pigs, without bringing any loss caused by the slaughtering.
Description
Technical Field
The invention relates to a detection technology, in particular to a detection technology of an estimation method for estimating lean meat percentage by using pig living back fat thickness and eye muscle area.
Background
To meet the market and consumer demand, there is a trend to produce commercial pork pigs of high quality lean type, and for this reason, the lean performance of the pigs needs to be continuously improved to improve the quality of the commercial pork pigs, and the measurement of the carcass lean rate of the pigs is the basis of the above work. The lean meat percentage of the prior pig is obtained by slaughter measurement, namely, the pig is slaughtered, the left carcass is taken and weighed, then the lard and the kidney are removed, and the lean meat, fat, skin and bone are stripped. The ratio of lean meat weight to the total weight of lean meat, fat, skin and bone is carcass lean meat percentage. The method is time-consuming and labor-consuming, has certain errors, cannot carry out large-scale measurement, causes slaughtering loss, cannot regenerate as a breed even if the performance of a pig is excellent, and only can use the measurement result as a performance reference of a sibling or an amphiphilic parent.
The correlation research shows that the backfat thickness is negatively correlated with the pig lean meat percentage table type, the eye muscle area is positively correlated with the pig lean meat percentage table type, and the heritability of the two is high, so that the method can be used for estimating the pig lean meat percentage. With the increasing maturity of real-time ultrasonic measurement technology, the measurement of the backfat thickness and the eye muscle area of the living pig becomes possible, but at present, no estimation method for estimating the lean meat percentage by using the backfat thickness and the eye muscle area of the living pig exists.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide the method for estimating the lean meat percentage of the live pig, which has the advantages of good accuracy, high measuring speed, capability of measuring the live pig and no slaughter loss.
In order to solve the technical problem, the invention provides an estimation method of lean meat percentage of a live pig, which is characterized by comprising the following steps:
1) measuring the weight of the pig after fasting, and measuring the backfat thickness and the eye muscle area of the live pig by using a B-type ultrasonic scanner;
3) substituting the data of the weight, the backfat thickness and the eye muscle area into the following regression equation for calculating the lean meat percentage of the live pig:
wherein,estimating lean meat percentage; x is the number of1: body weight; x is the number of2: backfat thickness; x is the number of3: eye muscle area a: -0.067 to-0.059; b: -2.206 to-2.038; c: 0.195 to 0.215;
and finally obtaining the estimated lean meat percentage of the detected pig.
Further, the pigs determined in the step 1) are pigs after 12 hours of fasting.
Further, the regression equation in the step 2) The parameters of (2): a is-0.063; b is-2.122; c is 0.205.
The method for estimating the lean meat percentage of the live pigs has the beneficial effects that:
in order to verify the actual effect of comparing the method for estimating the lean meat percentage of live weight, backfat thickness and eye muscle area of the pig with the prior art, 10 100kg of live pig bodies are randomly selected to weigh the weight, measure the backfat thickness and the eye muscle area of the live pig bodies, the lean meat percentage of the live pig bodies is estimated and measured by using the formula of the invention, the measured pig bodies are slaughtered to obtain the lean meat percentage of the live pig bodies, and the difference between the lean meat percentage and the measured pig bodies is compared to verify the accuracy and precision of the method disclosed by the invention, which is detailed in the following table.
Comparison of lean meat percentage measurements for Table pigs
| Numbering | Body weight (kg) | Backfat thickness (cm) | Eye muscle area (cm)2) | Method estimation value (%) | Slaughter measurement value (%) |
| 1 | 98 | 1.92 | 35.73 | 64.34 | 64.76 |
| 2 | 98 | 1.77 | 40.12 | 65.56 | 65 |
| 3 | 100 | 1.8 | 36.87 | 64.7 | 66.5 |
| 4 | 104 | 1.39 | 40.65 | 66.1 | 67.53 |
| 5 | 99 | 1.48 | 42.16 | 66.53 | 65.95 |
| 6 | 102 | 1.2 | 46.67 | 67.86 | 67.06 |
| 7 | 103 | 1.01 | 38.85 | 66.6 | 66.3 |
| 8 | 96 | 0.95 | 37.83 | 66.96 | 68.53 |
| 9 | 100 | 1.05 | 48.09 | 68.59 | 70.37 |
| 10 | 95.6 | 0.99 | 39.61 | 67.26 | 66.86 |
| Mean value | 99.56 | 1.356 | 40.658 | 66.45 | 66.9 |
The results of paired t-test analysis show that the pig lean meat percentage estimated by the method is compared with the actual lean meat percentage of the pig determined by slaughter, and the difference is not significant, namely | -1.263| < t0.05(9) | -2.262. The method for estimating the lean meat percentage of the pigs has the advantages of good accuracy, high determination speed, capability of determining the live pigs, no slaughtering loss and the like, can be applied to batch rapid determination of the lean meat performance of the pigs, and can timely find and utilize excellent pigs.
Detailed Description
The following examples are further detailed, but the present invention is not limited thereto, and all similar methods and similar variations using the present invention shall fall within the scope of the present invention.
The embodiment of the invention provides an estimation method of lean meat percentage of a live pig, which is characterized by comprising the following steps:
1) determination of the weight x of the pigs weighed 12 hours after fasting1Measuring the back fat thickness x of the live pig by using a B-type ultrasonic scanner2And eye muscle area x3；
4) The body weight x1Backfat thickness x2And eye muscle area x3The data were substituted into the following regression equation for estimation of lean meat percentage of live pigs:
wherein,
estimating lean meat percentage; x is the number of1: body weight; x is the number of2: backfat thickness; x is the number of3: area of eye muscle
a: -0.067 to-0.059, median-0.063; b: -2.206 to-2.038, intermediate-2.122; c: 0.195 to 0.215, median 0.205;
finally obtaining the estimated lean meat percentage of the pig
The embodiment of the invention comprises the following steps: the weight of the pig (100kg) was measured after fasting for 12 hours at about 100kg, and the backfat thickness (1.8cm) and the eye muscle area (36.87 cm) were measured in vivo using a B-mode ultrasonic scanner2) And will beBody weight (100kg), backfat thickness (1.8cm) and eye muscle area (36.87 cm)2) Substituting the data into the regression equation (intermediate value) to obtain the estimated lean meat percentage of the pig <math> <mrow> <mo>×</mo> <mn>100</mn> <mo>+</mo> <mrow> <mo>(</mo> <mo>-</mo> <mn>2.122</mn> <mo>)</mo> </mrow> <mo>×</mo> <mn>1.8</mn> <mo>+</mo> <mn>0.205</mn> <mo>×</mo> <mn>36.87</mn> <mo>≈</mo> <mn>64.7</mn> <mo>,</mo> </mrow></math>
The lean meat percentage is 64.7.
The generation process of the optimal regression equation for estimating the lean meat percentage by utilizing the live weight, the backfat thickness and the eye muscle area of the pig is as follows:
51 pigs are selected in a pig farm, wherein about 21 pigs are selected, 11 pigs are selected from Duroc pigs and 19 pigs are selected from Changbai pigs. According to the genetic evaluation of the pigs and the requirement of marketing of the commercial pigs at present, the real-time ultrasonic determination is carried out when the pigs to be determined grow to about 100 kg;
measuring the weight of the pig before measurement, wherein the weight is empty in 12 hours before measurement;
thirdly, after the pig is fixed, scanning the upper part of the back of the pig and the 10 th to 11 th ribs by using a probe of a B-type ultrasonic scanner, wherein the scanning position is 4-6cm away from the central line of the back. Freezing the scanned image when the optimal back image is displayed on the ultrasonic screen, and respectively reading the backfat thickness and the eye muscle area of the living pig;
and fourthly, slaughtering the pig to be tested, weighing the carcass on the left side, removing the leaf fat and the kidney, and stripping the lean meat, the fat, the skin and the bones. When stripping, the fat between muscles is not removed as lean meat, and the skin muscles (including abdominal and thigh skin muscles) are not removed as fat; calculating the ratio of the lean meat weight to the total weight of lean meat, fat, skin and bone to obtain the lean meat percentage of the carcass of the pig;
and fifthly, configuring a multiple regression equation by taking the measured weight, the living body backfat thickness and the eye muscle area of the 51-head pig as independent variables and the lean meat percentage as dependent variables, simultaneously calculating the residual error between the measured lean meat percentage and the estimated lean meat percentage, and removing the measurement data with larger error to obtain the final lean meat percentage calculation formula.
Claims (3)
1. The method for estimating the lean meat percentage of the live pigs is characterized by comprising the following steps:
1) measuring the weight of the pig after fasting, and measuring the backfat and eye muscle area of the live pig by using a B-type ultrasonic scanner;
2) substituting the data of the weight, the backfat thickness and the eye muscle area into the following regression equation for estimating the lean meat percentage of the live pig:
wherein,
: estimating lean meat percentage; x is the number of1: body weight; x is the number of2: backfat thickness; x is the number of3: eye muscle area a: -0.067 to-0.059; b: -2.206 to-2.038; c: 0.195 to 0.215;
and finally obtaining the estimated lean meat percentage of the detected pig.
2. The method of claim 1, wherein the pig is determined to have fasted for 12 hours in step 1).
3. The method of claim 1, wherein the regression equation in step 2) is a regression equation The parameters of (2): a is-0.063; b is-2.122; c is 0.205.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104101692A (en) * | 2014-07-04 | 2014-10-15 | 中国农业科学院农产品加工研究所 | Identification method for pork of black pigs and landraces |
| CN104950091A (en) * | 2015-06-16 | 2015-09-30 | 黄涛 | Method for quickly determining intramuscular fat content of fattening duroc landrace big white |
| CN105011964A (en) * | 2015-06-03 | 2015-11-04 | 徐州市凯信电子设备有限公司 | Multi-functional handheld ultrasonic system for livestock and automatic backfat and eye muscle measuring method |
| CN105284662A (en) * | 2015-12-10 | 2016-02-03 | 河南省农业科学院畜牧兽医研究所 | Living body measuring method of high-grade beef weight in cattle |
| CN111990331A (en) * | 2020-08-05 | 2020-11-27 | 南京农业大学 | Living body breeding method for pork streaky pork |
-
2008
- 2008-09-19 CN CNA200810200154XA patent/CN101361677A/en active Pending
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104101692A (en) * | 2014-07-04 | 2014-10-15 | 中国农业科学院农产品加工研究所 | Identification method for pork of black pigs and landraces |
| CN104101692B (en) * | 2014-07-04 | 2016-06-01 | 中国农业科学院农产品加工研究所 | The discrimination method of a kind of aardvark and landrace meat |
| CN105011964A (en) * | 2015-06-03 | 2015-11-04 | 徐州市凯信电子设备有限公司 | Multi-functional handheld ultrasonic system for livestock and automatic backfat and eye muscle measuring method |
| CN104950091A (en) * | 2015-06-16 | 2015-09-30 | 黄涛 | Method for quickly determining intramuscular fat content of fattening duroc landrace big white |
| CN105284662A (en) * | 2015-12-10 | 2016-02-03 | 河南省农业科学院畜牧兽医研究所 | Living body measuring method of high-grade beef weight in cattle |
| CN111990331A (en) * | 2020-08-05 | 2020-11-27 | 南京农业大学 | Living body breeding method for pork streaky pork |
| CN111990331B (en) * | 2020-08-05 | 2022-06-10 | 南京农业大学 | Living body breeding method for pork streaky pork |
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