CN112733084B - Method and device for measuring weight of six-month-old Hu sheep - Google Patents
Method and device for measuring weight of six-month-old Hu sheep Download PDFInfo
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Abstract
The disclosure relates to the technical field of livestock information processing, and particularly provides a method for measuring the weight of six-month-old Hu sheep, a model and a prediction method. Grouping according to the sibling number of the Hu sheep sample at birth to obtain the weaning weight data of the Hu sheep sample, obtaining the weight, body length, body height and chest circumference data of the Hu sheep sample of june age when the Hu sheep sample grows to june, and establishing several groups of body weight measurement models according to the corresponding relationship between the weight and the body length, the body height, the chest circumference and the weaning weight respectively according to the sibling number grouping result; obtaining the number of siblings of the Hu sheep to be detected at birth and weight data of the Hu sheep at weaning; and acquiring body size data of the six-month-old Hu sheep to be detected, determining a proper weight measurement model according to the number of siblings of the six-month-old Hu sheep to be detected at birth, and substituting the proper weight measurement model into the body size data and the weaning weight data of the six-month-old Hu sheep to be detected to obtain the weight measurement model. The method solves the problems that the binding four-hoof weighing method or the suspension weighing method of the six-month-old Hu sheep in the prior art is high in operation difficulty, long in operation time, large in weighing error and easy to damage the Hu sheep.
Description
Technical Field
The utility model relates to a poultry information processing technology field specifically provides a measurement and device of six months old hu sheep weight.
Background
The statements herein merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The Hu sheep is one of important livestock in Taihu plain, is a first-level protective local livestock and poultry variety in China, and has the excellent properties of precocity, four-season estrus, multiple lambs, good lactation performance, high temperature and high humidity resistance, coarse feeding and the like. As the economic level and the living quality of people continuously rise, the requirements on the mutton quality are continuously improved, and the Hu sheep with the characteristics of high quality and easy reproduction is favored by consumers and the breeding industry. Therefore, the large-scale Hu sheep farms appear in various places of China.
From the histological character change of the longissimus dorsi and the rule of muscle fat deposition in each early growth stage of the Hu sheep and the maximization of the culture input-output ratio, the optimal slaughter time of the Hu sheep is preferably 6 months old. In order to breed the Hu sheep improved variety with high growth performance and meat production performance, the Hu sheep breeding method needs to be developed, and the Hu sheep with excellent characteristics is selected to form a core group. Currently, hu sheep with high feed conversion rate and high meat production performance are bred as core group replacement sheep by measuring production performance measuring indexes such as weight scales of birth, weaning, 6-month-old and the like in a breeding farm. Therefore, the meat production performance of 6 months old is one of the key factors for developing Hu sheep breeding.
However, in the prior art, when Hu sheep core group breeding is carried out, the body weight and body size of 6 months of age are measured, or the eye muscle area is measured by ultrasonic measurement and a backfat instrument, or even the meat production performance of 6 months of age is obtained by directly sampling and slaughtering. As the body weight ruler and the 6-month-old meat production performance can not establish necessary connection, blind selection is often carried out by measuring indexes such as birth weight, weaning and 6-month-old body weight ruler during breeding, the body weight ruler comprises height, length, chest circumference, chest depth and the like, and the relevance between the body weight and each body ruler is not clear, so that great blind property is brought to the selection of backup sheep. In order to reduce the occurrence of blindness, the meat production performance is generally determined by weighing the slaughtered sheep and measuring the eye muscle area, and although the method is more accurate in selecting the meat production performance, the slaughtering is meaningless in selecting and protecting excellent breed sheep and has great loss to the breeding work. Although the mode of measuring the eye muscle area by using the ultrasonic wave or backfat instrument is more intuitive than the body weight and body size, the method has high requirements on personnel equipment and technology, and brings great workload for breeding. If the prediction of the meat production performance of 6 months old can be carried out according to the production data in the early stage, and the backup sheep which does not reach the standard in the breeding can be removed as soon as possible, the method has very important practical significance for the breeding of Hu sheep and the development of mutton sheep industry.
In conclusion, the inventor finds that the measurement of the body weight of the Hu sheep at the age of 6 months in the prior art has a plurality of defects and is not suitable for breeding sheep in a large-scale farm.
Disclosure of Invention
Aiming at the problems of blindness, long breeding time consumption, high technical requirement, and even loss of breeding work of Hu sheep due to the sacrifice of breeding mode of superior breeding sheep in the breeding of six-month-old Hu sheep in the prior art. In addition, in the prior art, the prediction of the weight of the Hu sheep at the age of 6 months only adopts the weight ruler at the age of 6 months and the methods of measuring the eye muscle area and slaughtering, and can not meet the requirements of the mutton sheep breeding work.
In one or some embodiments of the present disclosure, a method for measuring the body weight of a six-month-old hu sheep is provided, which includes the following steps:
grouping the Hu sheep samples according to the number of siblings of the Hu sheep samples at birth;
acquiring the weaning weight of the Hu sheep sample;
when the Hu sheep sample grows to June, acquiring weight, body length, body height and chest circumference data of the Hu sheep sample at June age, performing linear fitting, and establishing a weight measurement model at June age;
obtaining the number of siblings of the Hu sheep to be detected at birth and weight data of the Hu sheep at weaning;
and acquiring body length, body height and chest circumference data of the six-month-old Hu sheep to be detected, determining a proper weight measurement model according to the number of siblings of the six-month-old Hu sheep at birth, and substituting the body length, body height, chest circumference and weaning weight data of the six-month-old Hu sheep to be detected to obtain the weight of the six-month-old Hu sheep to be detected.
In one or some embodiments of the present disclosure, a method for predicting the weight of a six-month-old hu sheep is provided, which includes the following steps:
acquiring the weight of the Hu sheep after weaning;
establishing a six-month-old weight prediction model based on the number of siblings according to the weight measurement model establishing method in the six-month-old Hu sheep weight measurement method, selecting a weight prediction model with high weaning weight influence factors from a plurality of groups of weight prediction models, and selecting a Hu sheep with low weaning weight to be eliminated for the Hu sheep to be detected adapting to the model.
In one or some embodiments of the disclosure, a device for measuring the weight of a six-month-old Hu sheep is provided, which comprises a processing unit and a weight estimation unit;
the processing unit comprises a data acquisition unit, a model construction unit and a body size data measurement unit;
the data acquisition unit is used for acquiring the weight, body height, body length, chest circumference, weaning weight and sibling number data of the Hu sheep sample;
the model building unit is used for grouping according to the number of the lake sheep sample siblings, and each group of model building several groups of weight measurement models according to the corresponding relation between the weight of the lake sheep sample and the height, length, chest circumference and weaning weight;
and the body size data measuring unit is used for acquiring the body height, body length, chest circumference, weaning weight and sibling number data of the six-month-old Hu sheep to be measured.
And the weight estimation unit is used for inputting the body size data into the corresponding weight prediction model according to the body size data of the six-month-old Hu sheep to be detected and the sibling number groups to obtain the weight of the six-month-old Hu sheep.
One or some of the above technical solutions have the following advantages or beneficial effects:
1) According to the method, different sibling numbers of the Hu sheep are grouped, a plurality of models are respectively established, different equations are established among different sibling numbers, parameters among each set of equations are different, different body size data are substituted according to different coefficients required by different equations during weight measurement, and the Hu sheep does not need to be bound for body size measurement, so that the measurement difficulty is low, the method is less in damage to the Hu sheep, and the practical applicability is strong.
2) According to the method, the Hu sheep with high weaning weight coefficient and low weaning weight are eliminated according to the fact that the relevant coefficients of the weaning weights of different models of the Hu sheep are different, the problem of feed waste of the Hu sheep with low meat production performance in the production period is solved to a great extent, and the income of a farm is greatly improved.
3) According to the method, a model for predicting the weight of the 6-month-old sheep is established by analyzing and researching a large number of Hu sheep breeding data and applying early-stage data of the Hu sheep, including 5 factors of the number of siblings, the weight of weaning, the body length and the body height during weaning and the chest circumference, and the method has great significance for breeding work of a core breeding field of mutton sheep and promotion of development of sheep breeders in China.
4) As Hu sheep have multiple fetuses and different sibling numbers have certain nutrition on the growth of the Hu sheep, in order to research the relationship between the sibling numbers and the meat production performance of the Hu sheep at the age of 6 months, improve the feeding conversion rate and further determine the influence of the sibling numbers on the breeding direction, the weight of the Hu sheep at the age of 6 months can be predicted for the sheep flock with the special sibling numbers, and the breeding farm can judge whether the Hu sheep can be eliminated in advance to ensure the maximum benefit,
drawings
The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate embodiments of the disclosure and, together with the description, serve to explain the disclosure and not to limit the disclosure.
FIG. 1 is a comparison graph of the weight of the Hu sheep weaned between different siblings in the example. In the figure, the lower case letters with different symbols indicate significant difference (P < 0.05), and the same letters indicate insignificant difference (P > 0.05).
FIG. 2 is a graph showing the comparison of body weights of six-month-old Hu sheep with different siblings in examples. In the figure, the lower case letters are marked differently to indicate that the difference is significant (P < 0.05), and the same letters indicate that the difference is not significant (P > 0.05).
FIG. 3 is a graph showing body length comparisons of six-month-old Hu sheep with different siblings in examples. In the figure, the lower case letters are marked differently to indicate that the difference is significant (P < 0.05), and the same letters indicate that the difference is not significant (P > 0.05).
FIG. 4 is a graph showing the body height of six-month-old Hu sheep at different siblings in the examples. In the figure, the lower case letters are marked differently to indicate that the difference is significant (P < 0.05), and the same letters indicate that the difference is not significant (P > 0.05).
Figure 5 is a comparison of chest circumferences of six month old Hu sheep with different siblings in the example. In the figure, the lower case letters are marked differently to indicate that the difference is significant (P < 0.05), and the same letters indicate that the difference is not significant (P > 0.05).
FIG. 6 is a fitted line graph of body weight versus body height at junior six months.
Fig. 7 is a fitted line graph of body weight at junior and weaning weight at junior.
FIG. 8 is a fitted line graph of body weight at june versus body length at june.
FIG. 9 is a fitted line graph of body weight at june and chest circumference at june.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the disclosure without making any creative effort, shall fall within the protection scope of the disclosure.
The method aims at solving the problems that the four-hoof binding weighing method or the hanging weighing method for the six-month-old Hu sheep in the prior art is high in operation difficulty, long in operation time, large in weighing error and easy to damage the Hu sheep. In addition, in the prior art, the weight prediction of the Hu sheep only adopts a visual method, and the reliability is very low.
The meaning of the disclosure "number of siblings" is: the number of the Hu sheep parent in the same fetus is large.
In one or some embodiments of the present disclosure, a method for measuring the body weight of a six-month-old hu sheep is provided, which includes the following steps:
grouping the Hu sheep samples according to the number of siblings of the Hu sheep samples at birth;
acquiring weaning weight data of the Hu sheep sample;
when the Hu sheep sample grows to June, acquiring weight, body length, body height and chest circumference data of the Hu sheep sample at June age, performing linear fitting, and establishing a weight measurement model at June age;
obtaining the number of siblings of the Hu sheep to be detected at birth and weight data of the Hu sheep at weaning;
and acquiring body length, body height and chest circumference data of the six-month-old Hu sheep to be detected, determining a proper weight measurement model according to the number of siblings of the six-month-old Hu sheep at birth, and substituting the body length, body height, chest circumference and weaning weight data of the six-month-old Hu sheep to be detected to obtain the weight of the six-month-old Hu sheep to be detected.
According to the method, different sibling numbers of the Hu sheep are grouped, a plurality of models are respectively established, different equations are established among different sibling numbers, parameters among each group of equations are different, different body size data are substituted according to different coefficients required by different equations during weight measurement, and the Hu sheep do not need to be bound during body size measurement, so that the measurement difficulty is low, the method is less in damage to the Hu sheep, and the practical applicability is strong.
Preferably, the weight measurement models are all multiple linear regression models. The method for establishing the multivariate linear regression model is simple, easy to adjust, easy to calculate and high in practicability.
Preferably, when the number of siblings of the Hu sheep sample is 1, only the weight, weaning weight and chest circumference data of the Hu sheep sample of six months old are obtained, and a weight measurement model of six months old is established according to the weight, weaning weight and chest circumference data;
correspondingly, the Hu sheep to be detected with the number of siblings of 1 is only substituted into the weaning weight and chest circumference data of the Hu sheep to be detected, and the weight of the Hu sheep to be detected with the number of siblings of 1 is obtained.
Preferably, when the number of siblings is 2, only obtaining the weight, height, weaning weight and length data of a sample of six-month-old Hu sheep, and establishing a weight measurement model according to the weight, weaning weight and chest circumference data;
correspondingly, the data of the height, the weaning weight and the length of the tested Hu sheep are only substituted into the data of the height, the weaning weight and the length of the tested Hu sheep with the sibling number of 2 to obtain the weight of the tested Hu sheep with the sibling number of 2.
Preferably, the number of siblings is 1, 2 and 3 or more.
Preferably, when the number of siblings is 1, the weight measurement model is t =0.645d +0.350w-3.561;
when the sibling number is 2, the weight measurement model is t =0.359g +0.554d +0.083c-0.556;
when the number of siblings is more than or equal to 3, the weight measurement model is t =0.485w +0.112g-0.135c +0.476;
wherein t is the body weight of 6 months old, d is the weaning body weight, c is the body length, g is the body height and w is the chest circumference.
Preferably, the method further comprises the following steps, when the number data of the Hu sheep to be detected at birth cannot be acquired, the weight of the Hu sheep of six months of age is acquired by adopting the following steps:
acquiring data of the weight of a Hu sheep sample after weaning, acquiring data of the weight, the height and the chest circumference of a six-month Hu sheep sample,
when the Hu sheep sample grows to June, acquiring the weight, body length, body height and chest circumference data of the Hu sheep sample at the June age, performing linear fitting, and establishing a 6-month-old weight measurement model;
acquiring weight data of the Hu sheep to be detected during weaning;
and acquiring body height and chest circumference data of the six-month-old Hu sheep to be detected, and substituting the body height, chest circumference and weaning weight data of the six-month-old Hu sheep to be detected to obtain the weight of the six-month-old Hu sheep to be detected.
Preferably, when the data of the number of siblings of the Hu sheep to be detected at birth cannot be obtained, the weight measurement model is t =0.240w +0.246g +0.068d +1.242;
wherein t is the body weight of 6 months old, d is the weaning body weight, g is the body height, and w is the chest circumference.
In one or some embodiments of the present disclosure, a method for predicting the weight of a six-month-old hu sheep is provided, which includes the following steps:
obtaining the weight of the Hu sheep after weaning,
establishing a weight prediction model related to the number of siblings according to the weight measurement model establishing method in the method for measuring the weight of the six-month-old Hu sheep, selecting the weight prediction model with high weaning weight influence factors from a plurality of groups of weight prediction models, and selecting the Hu sheep with low weaning weight to be eliminated for the Hu sheep to be measured adapting to the model.
According to the method, the Hu sheep with high weaning weight influence factor but low weaning weight is eliminated according to the fact that the weaning weight influence factor of the Hu sheep is different among different models, the problem of feed waste of the Hu sheep with low meat production performance in the production period is solved to a great extent, and the income of a farm is greatly improved.
If the sibling number is 1, the weight measurement model is t =0.645d +0.350w-3.561, wherein the weaning weight influence factor is as high as 0.645, and if the weaning weight of a Hu sheep individual is low and the sibling number is 1, the weight of the Hu sheep individual at the age of six months is estimated to be light, the meat production performance is poor, the weight of the Hu sheep individual can be eliminated during weaning, and the waste of feed is avoided.
Similarly, if the number of siblings is 3, the weight measurement model is t =0.485w +0.112g-0.135c +0.476; if the number of siblings of a Hu sheep individual is 3, the weight of a weaned sheep has little influence on the weight of the sheep at the age of six months, so that the sheep with lower weaned weight can only gain weight by selecting a mode of enhancing the feeding management.
In one or some embodiments of the present disclosure, there is provided a device for measuring the weight of a six-month-old hu sheep, comprising a processing unit and a weight estimation unit;
the processing unit comprises a data acquisition unit, a model construction unit and a body size data measurement unit;
the data acquisition unit is used for acquiring the weight, body height, body length, chest circumference, weaning weight and sibling number data of the Hu sheep sample;
the model building unit is used for grouping according to the number of the lake sheep sample siblings, and each group of model building several groups of weight measurement models according to the corresponding relation between the weight of the lake sheep sample and the height, length, chest circumference and weaning weight;
a body size data measuring unit for acquiring the body height, body length, chest circumference, weaning weight and sibling number data of the six-month-old Hu sheep to be measured
And the weight estimation unit is used for inputting the body size data into the corresponding weight prediction model according to the body size data of the six-month-old Hu sheep to be detected and the sibling number groups to obtain the weight of the six-month-old Hu sheep.
Preferably, the device also comprises a de-sibling number unit, wherein the de-sibling number unit comprises a de-sibling number processing unit and a de-sibling number weight estimation unit,
the decellularization number data processing unit is used for acquiring the weight, height, length, chest circumference and weaning weight data of the Hu sheep sample; establishing several groups of weight measurement models according to the corresponding relation between the weight and the height, the length, the chest circumference and the weaning weight;
the desmosing weight estimation unit is used for inputting body size data into a corresponding weight prediction model according to the body size data of the six-month-old Hu sheep to be detected to obtain the weight of the six-month-old Hu sheep.
Examples
This embodiment provides a process for establishing a one-dimensional and multiple-dimensional linear regression equation in the present disclosure, including the following steps:
1 materials and methods
1.1 sample Collection and processing
868 Hu sheep are taken as test groups in the research and are all from Hangzhou huge agriculture development limited company which is the national mutton sheep core breeding farm. Sibling number and weaning weight are from breeding records in a farm, and weight, height, length and chest circumference of 6 months old are measured one by one. Three groups were assigned based on the number of siblings at birth, namely TBS1 (1 siblings), TBS2 (2 siblings), TBS3 (3 and above), as detailed in table 1.
TABLE 1 sample information Table
Table 1 Information of samples
1.2 data processing
The obtained test data are analyzed by adopting SPSS22.0 software, the significance test is carried out by adopting one-factor variance analysis, the significance level is set to be alpha =0.05, the correlation between the weight of 6-month old and the weaning weight, the body length, the body height and the chest circumference is determined by adopting a linear regression model method, and the result is expressed by 'mean value plus or minus standard deviation'.
2.1 Effect of sibling number on weaning weight
In the Hu sheep population studied, the average value of the weaning weight of TBS1 group was 20.50 + -4.14Kg, the average value of the weaning weight of TBS2 group was 16.88 + -2.49Kg, the average value of the weaning weight of TBS3 group was 16.67 + -9.25 Kg, and we found that the standard deviation of TBS3 group was larger than that of the other two groups, the data showed higher dispersion and the individual weaning weight within the group differed greatly. TBS3 group weaned weights were significantly lower (P < 0.05) than TBS1 and TBS2 groups, with no significant difference between TBS1 and TBS2 groups, see figure 1.
2.2 Effect of sibling number on body weight at 6 months of age
The average weight of 6 months of age in TBS1 group is 38.69 + -7.28Kg, the average weight of 6 months of age in TBS2 group is 36.78 + -5.32Kg, and the average weight of 6 months of age in TBS3 group is 35.16 + -4.74 Kg. As the number of siblings increases, the weight of the Hu sheep at the age of six months is reduced. Among them, TBS1 group was significantly (P < 0.05) higher in body weight at 6 months than TBS2 and TBS3 groups, and TBS2 was significantly (P < 0.05) higher than TBS3 group, as shown in fig. 2.
2.3 Effect of sibling number on body Length
The average value of 6-month-old body length of the TBS1 group is 79.13 +/-14.77cm, the average value of 6-month-old body length of the TBS2 group is 73.16 +/-10.41cm, and the average value of 6-month-old body length of the TBS3 group is 70.51 +/-9.254 cm. As the number of siblings increases, the body length of the Hu sheep in six months of age is in a decreasing trend. TBS1 group had the greatest body length value at 6 months, TBS3 group had the smallest body length value at 6 months, and all three groups had significant differences (P < 0.05), as shown in fig. 3.
2.4 Effect of sibling number on body height
The average height of 6-month-old body is 65.92 + -12.28cm in TBS1 group, 61.08 + -8.55cm in TBS2 group, and 58 + -7.73 cm in TBS3 group. As the number of siblings increases, the height of six months old Hu sheep changes in a decreasing manner. TBS1 group had the highest 6-month age, next to TBS2, and the TBS3 group had the lowest, with all three groups having significant differences (P < 0.05), as shown in fig. 4.
2.5 Effect of sibling number on bust size
The mean value of the bust size at 6 months in the TBS1 group was 87.11. + -. 16.17cm, that at 6 months in the TBS2 group was 80.52. + -. 11.42cm, and that at 6 months in the TBS3 group was 77.55. + -. 10.10cm. As the number of siblings increases, the chest circumference of Hu sheep in six months of age shows a decreasing trend. Among them, TBS1 group had a 6-month chest size significantly (P < 0.05) higher than TBS2 and TBS3 groups, and TBS2 significantly (P < 0.05) higher than TBS3 group, as shown in fig. 5.
3 unary linear regression
Firstly, according to the principle of least square method, a unary linear regression model is adopted to analyze the correlation coefficients of the weight of 6 months old and the weight, the body length, the body height and the chest circumference of weaning respectively. Goodness of fit (R)2) Is an important test index of a unary linear regression model, R2The maximum value is 1, and the closer the value is to 1, the better the fitting degree of the regression straight line to the observed value is, and the closer the value is to the actual production. The fitted straight line between the two parameters and the regression equation are analyzed by unary linear regression simulation, see fig. 6, fig. 7, fig. 8, fig. 9 and table 2 for details. From FIGS. 6 to 9, the body weight (t) at 6 months of age and the body weight at weaning (T)d) The body length (c), the body height (g) and the chest circumference (w) are in a linear positive correlation. It can be seen from table 2 that the body weight at 6 months of age has good goodness of fit with the regression equation of body length, body height and chest circumference, and the correlation degree is highly correlated; the fitness of the regression equation of the body weight of the six months old and the weaning body weight is low, and the correlation degree is weak correlation.
TABLE 2 regression equation
3 multiple linear regression
To further investigate the correlation of body weight at 6 months of age with weaning weight, body length, body height and chest circumference. Based on the sibling number, a stepwise regression method is applied to establish a multivariate linear regression equation with the weight (t) of 6 months old as a dependent variable and indexes of weaning weight (d), body length (c), body height (g) and chest circumference (w) as independent variables.
3.1 establishment of regression equation with sibling number of 1 fetus
Regression analysis is carried out on the parameters by adopting a multiple linear regression model, and a regression equation based on the number of siblings of 1 fetus, the weight of 6 months old, the weight of weaning and the chest circumference is as follows:
t＝0.645d+0.350w-3.561
the regression equation was subjected to goodness-of-fit test, significance F test, regression coefficient significance t test, and residual analysis to determine its reliability.
3.1.1 goodness of fit test
Model abstractc
a predicted variable: (constant), bust; b. the predicted variables are: (constant), bust, weaning weight; c. dependent variable: 6 month old heavy (KG)
The estimation standard error of the model 2 is smaller than that of the model 1; model 2 adjusted R2R with a value greater than model 12Value, illustrating the regression equationAnd the fitting goodness is higher.
3.1.2 significance F test
Analysis of variance
The regression equation reaches a significant level (P < 0.05) overall, ensuring the validity of the overall equation
3.1.3 significance t test
Coefficient of regression
The chest circumference and weaning weight regression coefficients reached a significant level overall (P < 0.05), and the regression coefficients were valid.
3.1.4 residual analysis
Residual analysis
Note: dependent variable, 6-month-old body weight
The conventional residual error of the body weight at the age of 6 months is independent and follows normal distribution, the average value is 0, and the variance is equal, so that the regression equation is reliable.
3.2 establishment of regression equation with sibling number of 2-child
Regression analysis is carried out on the parameters by adopting a multiple linear regression model, and based on a regression equation with the sibling number of 2 births and the weight of 6 months old and the weight, height and length of weaning are as follows:
t＝0.359g+0554d+0.083c-0.556
the regression equation is subjected to goodness-of-fit test, significance F test, regression coefficient significance t test and residual analysis to determine the reliability of the regression equation.
3.2.1 goodness of fit test
Model abstractd
a. Prediction variables: (constant), body height; b. prediction variables: (macroid), high body, heavy weaning (KG)
c. Prediction variables: (macroid), height, weaning weight, length; d. dependent variable: 6 month old heavy (KG)
The standard error of the model 3 is smaller than the standard error of the model 1 and the model 2; model 3 adjusted R2R with a value greater than that of model 1 and model 22Value, model 3R2And =0.913, the regression equation has higher goodness of fit.
3.2.2 significance F test
Analysis of variance
The regression equation overall reaches a significant level (P < 0.05), ensuring the validity of the overall equation.
3.2.3 significance t test
Regression coefficient
The body height, body length and weaning weight regression coefficients reached significant levels overall (P < 0.05), and the regression coefficients were valid.
3.2.4 residual analysis
Residual analysis
Note: dependent variable, 6-month-old body weight
The conventional residual error of the body weight at the age of 6 months is independent and follows normal distribution, the average value is 0, and the variance is equal, so that the regression equation is reliable.
3.3 establishment of regression equation with multiple births (≧ 3) of sibling number
Performing regression analysis on the parameters by adopting a multiple linear regression model, wherein the regression equation of the weight of 6 months, the weight of weaning and the chest circumference is as follows based on the number of siblings being multiple (not less than 3):
t＝0.485w+0.112g-0.135c+0.476
the regression equation was subjected to goodness-of-fit test, significance F test, regression coefficient significance t test, and residual analysis to determine its reliability.
3.3.1 goodness of fit test
Model abstract d
a. Prediction variables: (constant), bust; b. prediction variables: constant, chest circumference, height
c. Prediction variables: (constant), bust, height, length; d. dependent variable: 6 month old heavy (KG)
The estimation standard errors of the model 3 are smaller than those of the model 1 and the model 2; model 3 adjusted R2R with a value greater than that of model 1 and model 22Value, model 3R2And =0.903, which shows that the regression equation has higher goodness of fit.
3.3.2 significance F test
Analysis of variance
The regression equation overall reaches a significant level (P < 0.05), ensuring the validity of the overall equation.
3.3.3 significance t test
Regression coefficient
The body height, body length and chest circumference regression coefficients reach significant levels overall (P < 0.05), and the regression coefficients are valid.
3.3.4 residual analysis
Residual analysis
Note: dependent variable, 6-month-old body weight
The conventional residual errors of the 6-month-old body weight are independent, obey normal distribution, the average value is 0, and the variance is equal, so that the regression equation is the establishment of the credible parameter regression equation of the 3.4 Hu sheep population
Performing regression analysis on the parameters by adopting a multivariate linear regression model based on population, wherein the regression equation of the weight of the 6-month old, the weight of the weaning, the height of the body and the chest circumference is as follows:
t＝0.240w+0.246g+0.068d+1.242
the regression equation was subjected to goodness-of-fit test, significance F test, regression coefficient significance t test, and residual analysis to determine its reliability.
3.4.1 goodness of fit test
Model abstractd
a. Prediction variables: (constant), bust; b. prediction variables: constant, chest circumference, height
c. Prediction variables: (constant), chest circumference, height, weaning weight
d. Dependent variable: 6 month old heavy (KG)
The standard error of the model 3 is smaller than the standard error of the model 1 and the model 2; model 3 adjusted R2Value greater thanR of model 1 and model 22Value, model 3R2And =0.838, which shows that the regression equation has higher goodness of fit.
3.4.2 significance F-test
Analysis of variance
The regression equation reaches a significant level overall (P < 0.05), ensuring the validity of the overall equation
3.4.3 significance t test
Coefficient of regression
The regression coefficients reached a significant level overall (P < 0.05) and were valid.
3.4.4 residual analysis
Residual analysis
Note: dependent variable, 6-month-old body weight
The conventional residual error of the body weight at the age of 6 months is independent and follows normal distribution, the average value is 0, and the variance is equal, so that the regression equation is reliable.
The disclosure is intended to cover by the appended claims all such modifications as fall within the true spirit and scope of the disclosure.
Claims (9)
1. A method for measuring the body weight of a six-month-old Hu sheep is characterized by comprising the following steps of:
according to the number of siblings of the Hu sheep sample at birth, the Hu sheep sample is grouped,
acquiring the weaning weight data of the Hu sheep sample,
when the Hu sheep sample grows to June, acquiring the weight, body length, body height and chest circumference data of the Hu sheep sample at June age, performing linear fitting, establishing a weight measurement model at June age, specifically,
when the sibling number is 1, the weight measurement model is t =0.645d +0.350w-3.561;
when the number of siblings is 2, the weight measurement model is t =0.359g +0.554d +0.083c-0.556;
when the sibling number is more than or equal to 3, the weight measurement model is t =0.485w +0.112g-0.135c +0.476;
wherein t is the body weight of 6 months old, d is the weaning body weight, c is the body length, g is the body height and w is the chest circumference;
obtaining the sibling number of the Hu sheep to be detected at birth and the weight data of the Hu sheep at weaning;
and acquiring body length, body height and chest circumference data of the six-month-old Hu sheep to be detected, determining a proper weight measurement model according to the number of siblings of the six-month-old Hu sheep at birth, and substituting the body length, body height, chest circumference and weaning weight data of the six-month-old Hu sheep to be detected to obtain the weight of the six-month-old Hu sheep to be detected.
2. The method for measuring the weight of a six-month-old Hu sheep according to claim 1, wherein the weight measurement models are all linear regression models.
3. The method for measuring the weight of the six-month-old Hu sheep as claimed in claim 1, wherein when the number of siblings of the Hu sheep sample is 1, only the weight, weaning weight and chest circumference data of the six-month-old Hu sheep sample are obtained, and a weight prediction model is established according to the weight, weaning weight and chest circumference data;
correspondingly, the Hu sheep to be detected with the number of siblings of 1 is only substituted into the weaning weight and chest circumference data of the Hu sheep to be detected, and the weight of the Hu sheep to be detected with the number of siblings of 1 is obtained.
4. The method for measuring the weight of a six-month-old Hu sheep as claimed in claim 1, wherein when the number of siblings is 2, only the weight, height, weaning weight and length data of the six-month-old Hu sheep sample are obtained, and a weight prediction model is established according to the weight, weaning weight and chest circumference data;
correspondingly, the six-month-old Hu sheep to be detected with the sibling number of 2 is only substituted into the data of the height, the weaning weight and the length of the body of the Hu sheep to be detected, and the weight of the six-month-old Hu sheep to be detected with the sibling number of 2 is obtained.
5. The method for measuring the body weight of a six-month-old Hu sheep according to claim 1, wherein the number of siblings is 1, 2, and 3 or more.
6. The method for measuring the weight of the six-month-old Hu sheep as claimed in claim 1, further comprising the following steps, when the number of siblings of the Hu sheep to be measured at birth cannot be obtained, of obtaining the weight of the six-month-old Hu sheep:
acquiring data of the weight of a Hu sheep sample after weaning, acquiring data of the weight, the height and the chest circumference of a six-month Hu sheep sample,
when the Hu sheep sample grows to june, establishing a weight measurement model according to the corresponding relation between the weight and the height, the chest circumference and the weaning weight;
acquiring weight data of the Hu sheep to be detected during weaning;
acquiring body height and chest circumference data of the six-month-old Hu sheep to be detected, and substituting the body height, chest circumference and weaning weight data of the six-month-old Hu sheep to be detected to obtain the weight of the six-month-old Hu sheep to be detected;
when the data of the number of the Hu sheep siblings at birth to be detected cannot be obtained, the weight measurement model is
t＝0.240w+0.246g+0.068d+1.242；
Wherein t is the body weight of 6 months old, d is the weaning body weight, g is the body height, and w is the chest circumference.
7. The method for predicting the weight of the six-month-old Hu sheep is characterized by comprising the following steps of:
obtaining the weight of the Hu sheep after weaning,
the method for establishing a weight measurement model according to any one of claims 1 to 6, wherein the method comprises the steps of establishing a weight prediction model about the number of siblings, selecting a weight prediction model with high weaning weight influence factors from a plurality of groups of weight prediction models, and selecting a Hu sheep with low weaning weight for model-adapted Hu sheep to be tested to eliminate.
8. The device for measuring the weight of the six-month-old Hu sheep is characterized by comprising a processing unit and a weight estimation unit;
the processing unit comprises a data acquisition unit, a model construction unit and a body size data measurement unit;
the data acquisition unit is used for acquiring the weight, body height, body length, chest circumference, weaning weight and sibling number data of the Hu sheep sample;
the model construction unit is used for grouping according to the number of the lake sheep sample siblings, each group respectively establishes a plurality of groups of weight measurement models according to the corresponding relation between the weight of the lake sheep sample and the height, the length, the chest circumference and the weaning weight, concretely,
when the number of siblings is 1, the weight measurement model is t =0.645d +0.350w-3.561;
when the number of siblings is 2, the weight measurement model is t =0.359g +0.554d +0.083c-0.556;
when the number of siblings is more than or equal to 3, the weight measurement model is t =0.485w +0.112g-0.135c +0.476;
wherein t is the body weight of 6 months old, d is the weaning body weight, c is the body length, g is the body height and w is the chest circumference;
the body size data measuring unit is used for acquiring the body height, body length, chest circumference, weaning weight and sibling number data of the six-month-old Hu sheep to be measured;
and the weight estimation unit is used for inputting the body size data into the corresponding weight prediction model according to the body size data of the six-month-old Hu sheep to be detected and the sibling number groups to obtain the weight of the six-month-old Hu sheep.
9. The device for measuring the weight of a six-month-old Hu sheep as claimed in claim 8, further comprising a demogoing-number unit, the demogoing-number unit comprising a demogoing-number processing unit and a demogoing-number weight estimation unit,
the decellularization number data processing unit is used for acquiring the weight, height, length, chest circumference and weaning weight data of the Hu sheep sample; establishing several groups of weight measurement models according to the corresponding relationship between the weight and the height, the length, the chest circumference and the weaning weight;
the desmosing weight estimation unit is used for inputting body size data into a corresponding weight prediction model according to the body size data of the six-month-old Hu sheep to be detected to obtain the weight of the six-month-old Hu sheep.
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