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Application of a Multiple Linear Regression Model in Predicting Abdominal Fat Mass of Broilers or Breeding Low-fat Broilers

A multiple linear regression and abdominal fat technology, applied in the field of poultry genetics and breeding, can solve the problems of insignificant correlation, etc., and achieve the effects of reducing the difficulty of blood collection, reducing seed selection errors, and preventing hemolysis

Active Publication Date: 2021-04-27
NORTHEAST AGRICULTURAL UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, studies have shown that plasma VLDL concentrations are only significantly associated with abdominal fat traits in the fed state and not in the fasted state

Method used

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  • Application of a Multiple Linear Regression Model in Predicting Abdominal Fat Mass of Broilers or Breeding Low-fat Broilers
  • Application of a Multiple Linear Regression Model in Predicting Abdominal Fat Mass of Broilers or Breeding Low-fat Broilers
  • Application of a Multiple Linear Regression Model in Predicting Abdominal Fat Mass of Broilers or Breeding Low-fat Broilers

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0022] 1. Experimental materials

[0023] 1. Experimental Animals and Determination of Traits

[0024] The 18th generation roosters of broiler high-fat and low-fat two-way selection line selected by Northeast Agricultural University were used as the experimental group. At the age of 46 days and 48 days, after the broilers had eaten, blood was collected from the subwing vein, and the blood sample was placed in a 1.5ml centrifuge tube (EDTA-Na2 was used as an anticoagulant) and centrifuged at 3000r / min for 15min to obtain plasma. Put it into an EP tube and store it in a -20°C refrigerator for later use. At the age of 7 weeks, the live weight was measured before slaughtering, and the abdominal fat weight was measured after slaughtering, and the percentage of abdominal fat was calculated by dividing by the live weight at 7 weeks old.

[0025] 2. Drugs and enzymes

[0026] Triglyceride detection kit; total cholesterol detection kit; high-density lipoprotein cholesterol detection...

Embodiment 2

[0043] Example 2 Comparison of Chicken Plasma Biochemical Indexes Between High and Low Fat Two-way Selection Line Broilers

[0044] The 18th generation broiler chickens of high-fat and low-fat two-way selection line selected by Northeast Agricultural University were used as experimental materials to compare and analyze the abdominal fat traits of high-fat and low-fat broiler chickens. The results showed that the abdominal fat weight and abdominal fat rate of high-fat broilers were significantly higher than those of low-fat broilers (Table 1, P<0.01).

[0045] Table 1 Comparison of abdominal fat traits between high and low-fat broilers

[0046]

[0047] Note: ** P<0.01.

[0048]The 18th generation broiler chickens of high-fat and low-fat two-way selection line selected by Northeast Agricultural University were used as experimental materials to compare and analyze the plasma biochemical indicators between high-fat and low-fat broiler chickens. The results showed that the p...

Embodiment 3

[0053] Example 3 Phenotypic correlation between plasma biochemical indicators and abdominal fat traits

[0054] Phenotypic correlation analysis was carried out between the plasma biochemical indexes and abdominal fat traits in Example 2, and the results showed that plasma triglycerides, total bile acids, total proteins, globulins, γ-glutamyl transpeptidase, uric acid, creatinine and The level of VLDL had a very significant positive phenotype correlation with abdominal fat traits (P0.05).

[0055] Table 3 Phenotypic correlation between plasma biochemical indicators and abdominal fat traits

[0056]

[0057]

[0058] Note: * P** P<0.01; HDL-C high-density lipoprotein cholesterol; LDL-C low-density lipoprotein cholesterol; VLDL very low-density lipoprotein.

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Abstract

The invention discloses the application of a multiple linear regression model in predicting the abdominal fat mass of broilers or breeding low-fat broilers, and belongs to the technical field of poultry genetics and breeding. The multiple linear regression model provided by the present invention is a multiple linear regression model constructed from the white globular ratio, VLDL, triglyceride, globulin, total bile acid and uric acid levels in blood plasma when the chicken is full. The plasma biochemical indicators in this model have significant differences between low-fat broiler chickens and high-fat broiler chickens, and are significantly correlated with abdominal fat traits. This model eliminates the indicators that do not contribute significantly in the model and can be used for broiler abdominal fat mass prediction and selection of low-fat broiler lines. In addition, the invention also provides the application and construction method of the multiple linear regression model.

Description

technical field [0001] The invention relates to a multiple linear regression model for assisting in predicting low-fat broilers and its application, and belongs to the technical field of poultry genetics and breeding. Background technique [0002] Since the end of the last century, broiler breeders have made significant progress in the selection of broiler body weight. However, the excessive growth rate of broilers is accompanied by excessive body fat (especially abdominal fat) deposition and other phenomena. Fat, a by-product of chicken production, has very little commercial value, and high fat deposits can reduce feed conversion efficiency. Therefore, reducing fat deposition in broilers and cultivating low-fat broilers has always been one of the main tasks of broiler breeders. The traditional breeding method is mainly to measure the abdominal fat mass after slaughter, and carry out full-sib or half-sib breeding, which wastes resources and takes a long time. Therefore, w...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/02
CPCG06Q10/04G06Q50/02
Inventor 李辉张慧董佳强
Owner NORTHEAST AGRICULTURAL UNIVERSITY