CN117726476B - Method for predicting effective performances of feed raw materials for black pigs and live pigs based on effective performances of feed raw materials of ternary pigs - Google Patents
Method for predicting effective performances of feed raw materials for black pigs and live pigs based on effective performances of feed raw materials of ternary pigs Download PDFInfo
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P60/00—Technologies relating to agriculture, livestock or agroalimentary industries
- Y02P60/80—Food processing, e.g. use of renewable energies or variable speed drives in handling, conveying or stacking
- Y02P60/87—Re-use of by-products of food processing for fodder production
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Abstract
The application discloses a method for predicting effective performances of feed raw materials for black pigs and live pigs based on effective performances of feed raw materials of ternary pigs, which comprises the following steps: s1, measuring and comparing effective energy and nutrient digestibility of feed raw materials of the ternary pigs, the black pigs and the live pigs; s2, establishing a dead pig and dead pig effective efficiency prediction model based on the effective efficiency of the ternary pig feed raw materials. The application pointedly evaluates the effectiveness of two conventional feed raw materials of corn and bean pulp and a Hainan province ground-source feed raw material on the dead pig and the dead pig, thereby being beneficial to realizing the accurate nutrition of the dead pig and avoiding the increase of the cultivation cost caused by the waste of the feed; based on the effective performances of the three-element pigs, an effective performances prediction equation of the dead pig and the dead pig is established, the transfer of the three-element pig feed raw material database to the dead pig and the dead pig raw material database is realized, and a good foundation is laid for the accurate nutrition and the efficient feeding of the dead pig and the dead pig.
Description
Technical Field
The invention belongs to the technical field of animal feed science, and particularly relates to a method for predicting effective performances of feed materials for black pigs and live pigs based on effective performances of feed materials for ternary pigs.
Background
The black pig and the pig are excellent pig germplasm resources in Hainan province, and have the advantages of good meat quality, coarse feeding resistance, strong stress resistance and the like. The growing speed of the pig is faster than that of the pig, and the pig accounts for a large proportion (13-15%) in the Hainan live pig market, however, the evaluation and research of feed raw materials of domestic local pig species represented by the pig is almost blank, and the experience of a feed raw material database or a farm for Duzhou ternary pigs (hereinafter referred to as ternary pigs) is still consulted in the actual cultivation process of the pig and the pig, so that the standardized cultivation of the pig and local pig species is severely restricted.
At present, the animal nutrition field is mainly used for evaluating the nutrition value of feed raw materials through a traditional digestive metabolism test. The method comprises the steps of preparing feed raw materials to be tested into feed, feeding the feed raw materials to animals in corresponding growth stages at regular time and quantity, measuring residual amounts of energy in feces and urine by collecting the feces and urine of the animals, calculating digestion and metabolism conditions of the feed raw material energy in the animal bodies, and further evaluating effective performance of the feed raw materials. In addition, with the development of computational science, related research at home and abroad is based on a large number of animal test data accumulated for a long time, and according to different feed raw materials, a mathematical model between chemical components and effective energy of the feed raw materials is established by utilizing a multiple regression (stepwise regression) algorithm through chemical components such as total energy (GE), crude Protein (CP), crude fat (EE), crude Ash (Ash), crude Fiber (CF), neutral washing fiber (NDF), acid washing fiber (ADF) and the like, so that the effective energy of different feed raw materials is predicted by chemical component content, and part of research also establishes a prediction equation of the effective energy of the feed raw materials of the sow produced by the ternary pig through the effective energy of the feed raw materials of the ternary pig, so that the feed effective energy prediction of the same pig species and different physiological stages is realized. At present, based on a large number of animal digestion and metabolism tests and corresponding prediction model results, a feed raw material nutritional value database of some livestock and poultry animals, such as a feed nutritional value database of a ternary pig, is gradually established in China. However, a database of nutritional values for feed materials for local pigs has not been established, as the evaluation of the effective performance of the corresponding feed materials on some local pigs is almost blank.
The classical animal nutrition method is used for determining the digestion energy and the metabolic energy of the pig feed raw material, but the method has the advantages of more personnel, long time and higher capital cost for carrying out related animal tests, and particularly, the test is carried out on pigs. If the nutritional value of different feed raw materials is assessed on the dead pigs and the dead pigs one by one according to the traditional animal test method, the huge workload is not estimated. Although a great deal of work related to the nutritional value assessment of pig feed raw materials is carried out at home at present, the work is mainly carried out around ternary pigs. The ternary pigs have different genetic backgrounds from the black pigs and the dead pigs, and have differences in digestion and growth. With the continuous and deep evaluation of the nutritional value of the feed raw materials of the ternary pigs at home and abroad, the effective energy and the predictive equation of various types of raw materials of the ternary pigs are accumulated. When the effective feed efficiency evaluation of the dead pigs and the dead pigs is carried out, if the difference rule of the ternary pigs and the dead pigs on the digestion and absorption of the nutrient substances can be explored, the correlation of the nutritional value of the ternary pigs and the feed raw materials of the dead pigs is clear, and a prediction equation of the effective feed efficiency of the dead pigs and the dead pigs is established based on the effective feed efficiency of the ternary pigs, the transfer of the nutritional value database of the ternary pig feed to the nutritional value database of the dead pigs and the dead pigs can be rapidly, conveniently and cheaply realized.
Disclosure of Invention
In order to solve the problems, the invention provides a method for predicting the effective performance of feed materials for black pigs and live pigs based on the effective performance of feed materials for ternary pigs.
The method for predicting the effective performances of the feed raw materials of the dead pigs and the dead pigs based on the effective performances of the feed raw materials of the ternary pigs comprises the following steps:
S1, measuring and comparing effective energy and nutrient digestibility of feed raw materials of the ternary pigs, the black pigs and the live pigs;
s2, establishing a dead pig and dead pig effective efficiency prediction model based on the effective efficiency of the ternary pig feed raw materials.
The determination and comparison of the effective energy and nutrient digestibility of the feed raw materials of the ternary pigs, the black pigs and the dead pigs in the step S1 comprises the following steps:
s101, determining the outline nutrients of the feed raw materials to be evaluated;
S102, preparing a test diet formula;
S103, feeding management and sample collection;
s104, index detection and effective energy calculation;
S105, determining the effective performance of feed raw materials of the ternary pigs, the black pigs and the dead pigs.
The feed raw materials to be evaluated in the step S101 comprise corn, soybean meal, sweet potato, cassava, shredded coconut, coconut meal, bran, cassava residue, palm meal and fruit residues.
The general nutrients in the step S101 include dry matter, moisture, organic matter, coarse ash, coarse fat, coarse protein, neutral washing fiber, acid washing fiber, and total energy.
The test diet formulas in the step S102 include ten kinds of diet including corn diet, corn-soybean meal diet, diet containing 38.8% sweet potato, diet containing 38.8% tapioca, diet containing 29.1% bran, diet containing 29.1% desiccated coconut, diet containing 29.1% coconut meal, diet containing 29.1% palm meal, diet containing 29.1% tapioca, and diet containing 29.1% pomace, respectively.
The determination of the effective performance of the feed raw material in the step S104 includes: testing total energy, moisture, crude ash, crude fat, crude protein, neutral washing fiber and acid washing fiber in diet, feed raw materials and manure samples; measurement of crude protein and total energy in urine samples.
The step S2 of establishing the effective efficiency prediction model of the dead pig and the dead pig based on the effective efficiency of the feed raw materials of the ternary pig comprises the following steps:
s201, correlation analysis: performing correlation analysis on the result measured in the step S1;
S202, establishing a prediction equation: and establishing a prediction equation according to the correlation analysis result.
As a result of the correlation analysis in the step S201, the digestion energy among the three pigs is extremely obviously and positively correlated with the metabolic energy value, the organic matter content is obviously correlated with the digestion energy metabolic energy of the dead pig, the crude fat content is obviously correlated with the digestion energy of the dead pig, the effective energy is positively correlated with the total energy, the organic matter, the crude fat and the crude protein, and the effective energy is negatively correlated with the crude ash, the neutral washing fiber and the acidic washing fiber.
The prediction equation established in the step S202 is:
DE( Black pig )＝0.916ME Ternary pig +0.159GE-0.387,R2＝0.995
ME( Black pig )＝0.945ME Ternary pig +0.11NDF+0.279,R2＝0.997
DE( Pig-mounted pig )＝0.932DE Ternary pig +0.136GE-0.967,R2＝0.989
ME( Pig-mounted pig )＝0.871DE Ternary pig -1.39Ash+1.828,R2＝0.989
Wherein DE is digestive energy, ME is metabolic energy, GE is total energy, NDF is neutral washing fiber, ash is coarse Ash, R 2 is a determining coefficient, P is a P value, and P is less than 0.01.
The beneficial effects of the invention are as follows:
1. The method has the advantages that basic data of nutritional values of the raw materials of the feed for the dead pigs and the dead pigs are perfected, the effective performance of the raw materials of the corn and the bean pulp of the conventional feed and the raw materials of the Hainan province ground source feed on the dead pigs and the dead pigs are pertinently evaluated, scientific and reliable reference basis is provided for the preparation of the feed for the dead pigs and the dead pigs, the precise nutrition of the dead pigs and the dead pigs is facilitated, the increase of the cultivation cost caused by the waste of the feed is avoided, and the cost reduction and the synergy of the dead pigs and the dead pigs are promoted.
2. Determining the digestibility difference rules of the ternary pigs and the black pigs on different nutrients, and determining the conversion coefficient of the effective raw material between the ternary pigs and the black pigs and between the ternary pigs and the black pigs; establishing a prediction model of digestion energy and metabolism energy of the dead pig and the dead pig based on the ternary pig effective energy database and the raw material key chemical components by using a stepwise regression algorithm, and facilitating the transfer of the ternary pig feed raw material database to the dead pig and the dead pig raw material database; lays a good foundation for the accurate nutrition and efficient feeding of the dead pigs and the dead pigs, and has important significance for finally realizing the accurate nutrition and efficient feeding of the dead pigs and promoting the establishment of a local pig feed raw material nutrition database in China.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The embodiments described below by referring to the drawings are illustrative and intended to explain the present invention and should not be construed as limiting the invention.
The method for predicting the effective performances of the feed raw materials of the dead pigs and the dead pigs based on the effective performances of the feed raw materials of the ternary pigs comprises the following steps:
s1, measuring and comparing effective energy and nutrient digestibility of feed raw materials of ternary pigs, black pigs and dead pigs
S101, determination of approximate nutrients of feed raw materials to be evaluated
The invention determines the parameters of general nutrients such as dry matters, moisture, organic matters, crude ash, crude fat, crude protein, neutral washing fiber, acid washing fiber, total energy and the like of corn, bean pulp, sweet potato, cassava, shredded coconut, coconut pulp, bran, tapioca, palm pulp and fruit residues (see table 1), and prepares a test diet formula with corresponding proportion according to the chemical composition of feed raw materials.
Table 1 chemical composition of the raw materials (%), feeding basis
S102, preparing a test diet formula
The invention selects 10 healthy and castrated three-way boars, dead black boars and dead boars with 90 days of age, and the initial weight is 29.31+/-2.94 kg, 31.60+/-4.41 kg and 23.36+/-4.88 kg respectively. The test was set to 310 x 6 incomplete latin square tests, for a total of 10 different diet treatments, each diet treatment was designed with three pigs, a dead pig and a dead pig each in duplicate 6, 1 pig each in duplicate. The 10 test feeds were corn feed, corn-soybean meal feed (basal feed), feed containing 38.8% sweet potato, feed containing 38.8% tapioca, feed containing 29.1% bran, feed containing 29.1% coconut meal, feed containing 29.1% palm meal, feed containing 29.1% tapioca and feed containing 29.1% fruit residues, respectively, and the nutritional compositions of the 10 feeds were each dosed with reference to the recommended amounts in pig nutritional requirements (2020). The feeding test was performed in 6 stages, and each stage was performed for 10 days, including a 5-day feed adaptation period and a 5-day feces and urine collection period, and the feed ingredients and chemical compositions of the feeds were as shown in Table 2.
Table 2 test diet composition and chemical composition (%), feeding base
Note that: the premix for growing pigs is provided for each kilogram of complete diet, wherein vitamin A is 5512IU; vitamin D3, 2200IU; vitamin E,30IU, vitamin K3,2.2mg, vitamin B12, 27.6ug; riboflavin B2,4.0mg; pantothenic acid, 14.0mg; nicotinic acid, 30.0mg; choline, 400.0mg; folic acid, 0.7mg; thiamine, 1.5mg; vitamin B6,3.0mg; biotin, 44.0ug; manganese, 40.0mg; iron, 75.0mg; zinc, 75.0mg; copper, 100.0mg; iodine, 0.3mg; selenium, 0.3mg.
S103, feeding management and sample collection
The metabolic cages were adapted for 7 days before the beginning of the first phase of the experiment, 30 pigs were weighed before the beginning of each phase, and the daily feeding amount was 4% of the body weight, and the equal amount was divided into 9:00 and 16:00 feeding twice daily without limiting drinking water. 30 pigs are respectively placed in 30 special metabolic cages made of stainless steel for feeding, and the length, width and height of each metabolic cage are set to be corresponding sizes according to the pig size, so that the pigs can lie freely upright and can not turn around. The temperature of the pig house is stabilized at about 22 ℃ and the air is kept smooth and clean.
Collecting all manure samples of each pig tested in each period, uniformly mixing, taking 500g, drying at 65 ℃ to constant weight, weighing and recording the weight after drying. Pulverizing, sieving with 40 mesh sieve, and storing at-20deg.C. Urine of each pig is collected in each period of test, 40mL of 5.0% hydrochloric acid is added into each liter of urine to inhibit volatilization of nitrogen in urine sample in the form of ammonia gas, and 100mL of the urine is taken and stored at-20 ℃ after the urine is uniformly mixed and filtered through 8 layers of gauze.
S104, index detection and effective energy calculation
Test diet, feed raw material and manure sample determination: total energy, moisture, coarse ash, coarse fat, coarse protein, neutral detergent fiber, acid detergent fiber. Urine sample measurement: crude protein and total energy.
The dry matter in all samples was determined according to GB/T6435-2006 method, the crude ash was determined according to GB/T6438-2007 method, the crude protein was determined according to GB/T6432-2018 method, the crude fat was determined according to GB/T6433-2006 method, the neutral washing fiber was determined according to GB/T20806-2006 method, the acid washing fiber was determined according to NY/T1459-2007 method, and the oxygen bomb was always used according to IOS 9831:1998.
Digestive energy= (total energy-fecal energy)/feed intake; metabolizable energy= (total energy-fecal energy-urinary energy)/feed intake.
Calculating an effective energy formula of the feed raw materials:
corn raw material effectiveness = corn diet effectiveness ≡97%.
The formula for calculating the digestion energy value and the metabolism energy value of the soybean meal, the sweet potato, the cassava residue, the coconut pulp, the shredded coconut stuffing, the bran and the pomace is as follows:
Raw material effectiveness= (test diet effectiveness-basic diet effectiveness ≡z×y) ≡x;
In the formula: x is the proportion of the materials to be tested in the test diet; z=97%; y is the proportion of the energy supply part of the basic diet contained in the test diet; the basic diet is corn-soybean meal type diet.
The apparent total intestinal digestibility (ATTD,%) was calculated as:
Test diet nutrient ATTD = (amount of chemical components fed-amount of chemical components excreted by manure)/(amount of chemical components fed;
Raw material nutrient ATTD = [ test diet chemical component ATTD- (1-W) ×chemical component ATTD in basal diet ] ≡w.
W: the raw materials to be tested provide a certain amount of nutrient in the test diet as a percentage of the total amount of the nutrient in the test diet.
S105, determining effective performances of feed raw materials of ternary pigs, black pigs and dead pigs
The metabolic energy of the ternary pigs of ：13.67MJ/kg、16.25MJ/kg、12.97MJ/kg、13.12MJ/kg、16.98MJ/kg、10.55MJ/kg、6.80MJ/kg、6.45MJ/kg、5.71MJ/kg、19.37MJ/kg, ternary pigs of ：13.32MJ/kg、14.76MJ/kg、12.22MJ/kg、11.99MJ/kg、16.29MJ/kg、10.01MJ/kg、6.38MJ/kg、5.92MJ/kg、5.25MJ/kg、18.37MJ/kg; black pig digestion energy of ：13.84MJ/kg、15.99MJ/kg、13.21MJ/kg、13.32MJ/kg、17.52MJ/kg、11.82MJ/kg、7.86MJ/kg、7.29MJ/kg、7.47MJ/kg、20.77MJ/kg, black pig digestion energy of ：13.52MJ/kg、15.00MJ/kg、12.46MJ/kg、12.67MJ/kg、16.89MJ/kg、10.99MJ/kg、7.34MJ/kg、6.69MJ/kg、6.79MJ/kg、18.85MJ/kg; pig digestion energy of ：14.06MJ/kg、16.30MJ/kg、12.90MJ/kg、13.31MJ/kg、17.55MJ/kg、11.89MJ/kg、7.25MJ/kg、8.09MJ/kg、5.85MJ/kg、20.64MJ/kg, pig digestion energy of ：13.53MJ/kg、15.04MJ/kg、12.13MJ/kg、12.49MJ/kg、16.37MJ/kg、10.64MJ/kg、6.70MJ/kg、7.73MJ/kg、5.37MJ/kg、18.88MJ/kg;( pig digestion energy of 3256 pig digestion energy of ：14.06MJ/kg、16.30MJ/kg、12.90MJ/kg、13.31MJ/kg、17.55MJ/kg、11.89MJ/kg、7.25MJ/kg、8.09MJ/kg、5.85MJ/kg、20.64MJ/kg, pig digestion energy of ：13.84MJ/kg、15.99MJ/kg、13.21MJ/kg、13.32MJ/kg、17.52MJ/kg、11.82MJ/kg、7.86MJ/kg、7.29MJ/kg、7.47MJ/kg、20.77MJ/kg, pig digestion energy of 359 pig digestion energy of the pig and the pig digestion energy of the pig.
TABLE 3 digestion and metabolism differences of corn Material in ternary pigs, anemone Sus domestica and Anemone Sus domestica
Note that a-b different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
TABLE 4 three-way pig, anmo pig and Anmo pig have differences in the digestion and metabolism of soybean meal and diet
Note that a-b different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
TABLE 5 differences in the digestion and metabolism of cassava feedstock and diet by ternary and dead pigs
Note that a-b different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
TABLE 6 three-way pig, anmo pig and Anmo pig have differences in the digestion and metabolism of sweet potato raw materials and diet
Note that a-c different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
TABLE 7 ternary pig, anmo pig and Anmo pig have differences in digestion and metabolism of coconut meal raw materials and diet
Note that a-c different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
TABLE 8 digestion and metabolism differences of ternary pigs, anhydrous pigs and Anhydrous pigs on palm meal raw materials and diet
Note that a-c different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
TABLE 9 differences in the digestion and metabolism of cassava residue raw material and diet by ternary and dead pigs
Note that a-c different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
TABLE 10 differences in the digestive metabolic capacities of ternary pigs, dead pigs and dead pigs on pomace raw materials and diet
Note that a-c different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
Table 11 ternary pig, dead pig and dead pig have differences in their digestive metabolic capacity for bran-free material and diet
Note that a-c different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
TABLE 12 three-element pig, anmo pig and Anmo pig differ in their digestion and metabolism ability to feed
Note that a-c different letters from the shoulder marks of the same row indicate significant differences (P < 0.05).
From tables 3 to 12, the effective energy of the same raw materials of the three pigs shows a tendency that the pig for setting is higher than that of the pig for setting black, wherein the digestion energy and the metabolism energy of the pig for setting palm meal, cassava residue and bran are obviously lower than those of the pig for setting black, and the digestion energy and the metabolism energy of the pig for setting fruit residue are obviously lower than those of the pig for setting black. The digestion and metabolism capability differences of the three pigs are mainly expressed in the aspect of the digestibility of crude protein, neutral washing fiber and acid washing fiber in the feed raw materials (except for the bran), and particularly expressed in that the dead pig is higher than the dead pig by more than three-element pigs, and the digestibility of the dead pig and the dead pig is about 10% higher than that of the three-element pigs in the high-fiber raw materials. However, the digestibility of crude fat in unconventional feed materials is shown to be lower for the dead pigs than for the ternary pigs.
S2, establishing a dead pig and dead pig effective prediction model based on effective performances of ternary pigs
The method is characterized in that a data set is established by using the digestion energy and the metabolism energy of 10 raw materials on a ternary pig, a dead pig and a dead pig respectively, and dry matters, organic matters, crude ash, crude fat, crude protein, neutral washing fibers and acid washing fibers of feed raw materials, and correlation analysis is carried out to construct a dead pig and dead pig effective performance prediction model based on the ternary pig and performance values and chemical components of the feed raw materials.
S201 correlation analysis
The digestion energy among the three pigs is obviously and positively correlated with the metabolism energy value, the organic matter content is obviously correlated with the digestion energy metabolism energy of the dead pig, the crude fat content is obviously correlated with the digestion energy of the dead pig and the digestion energy of the dead pig, the effective efficiency is positively correlated with the total energy, the organic matter, the crude fat and the crude protein, and the effective efficiency is negatively correlated with the crude ash, the neutral washing fiber and the acidic washing fiber. (see Table 13 for details)
TABLE 13 analysis of the digestive Metabolic energy correlation of ternary pigs, anemone Sonchi pigs and the chemical composition correlation of raw materials
Note that: "+" means that P <0.05, "+" means that P <0.01,
S202, establishing a prediction equation
The total energy content of the feed raw material nutrient components is an effect factor for predicting the digestive energy value of the dead pigs and the dead pigs, and the coarse ash content of the feed raw material is an effect factor for predicting the metabolic energy of the dead pigs. Based on the effective performance of the ternary pigs and the content of conventional nutrients in the feed, the optimal prediction equation of the digestive energy and the metabolic energy of the dead pigs and the dead pigs is finally determined as follows: (see Table 14 for details)
DE( Black pig )＝0.916ME Ternary pig +0.159GE-0.387,R2＝0.995
ME( Black pig )＝0.945ME Ternary pig +0.11NDF+0.279,R2＝0.997
DE( Pig-mounted pig )＝0.932DE Ternary pig +0.136GE-0.967,R2＝0.989
ME( Pig-mounted pig )＝0.871DE Ternary pig -1.39Ash+1.828,R2＝0.989
Wherein DE is digestive energy, ME is metabolic energy, GE is total energy, NDF is neutral washing fiber, ash is coarse Ash, R 2 is a determining coefficient, P is a P value, and P is less than 0.01.
Table 14 equation for predicting effective performance of live-black pigs and live-pig feed based on effective performance of ternary pigs
Note that: the energy and the chemical component content of the raw materials in the equation are both feeding bases, RMSE is root mean square error, and the smaller the value is, the more accurate the equation is.
The prediction model for the effective performance of the feed raw materials of the dead pigs and the dead pigs can rapidly predict the digestion energy and the metabolic energy value of a certain feed raw material on the dead pigs and the dead pigs according to the feed raw material database of the ternary pigs. The method promotes the perfection of the effective database of the dead pigs and the dead pigs, is a research foundation established by the research of the follow-up nutrition requirements of the dead pigs and the raising standard, and has important significance for finally realizing the accurate nutrition and efficient raising of the dead pigs and promoting the establishment of the local pig feed raw material nutrition database in China. The method has the advantages that the huge workload of the traditional digestive metabolism animal experiment is avoided, the existing ternary pig feed raw material database is quickly transferred to the dead pigs and the dead pigs, and the method has important application value in the standardized cultivation process of the dead pigs, the dead pigs and other local pigs.
While the above embodiments have been shown and described, it should be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives, and variations of the above embodiments may be made by those of ordinary skill in the art without departing from the scope of the invention.
Claims (6)
1. A method for predicting the effective performance of a feed material for a live pig and a live pig based on the effective performance of a feed material for a tertiary pig, comprising the steps of:
S1, measuring and comparing effective energy and nutrient digestibility of feed raw materials of ternary pigs, black pigs and dead pigs: the method comprises the following steps:
s101, determining the outline nutrients of the feed raw materials to be evaluated;
S102, preparing a test diet formula;
S103, feeding management and sample collection;
S104, index detection and effective energy calculation:
the formula for calculating the digestion energy value and the metabolism energy value of the soybean meal, the sweet potato, the cassava residue, the coconut pulp, the shredded coconut stuffing, the bran and the pomace is as follows:
Raw material effectiveness= (test diet effectiveness-basic diet effectiveness ≡z×y) ≡x;
In the formula: x is the proportion of the materials to be tested in the test diet; z=97%; y is the proportion of the energy supply part of the basic diet contained in the test diet; the basic diet is corn-soybean meal type diet;
The apparent total intestinal digestibility ATTD is calculated by the following formula:
Test diet nutrient ATTD = (amount of chemical components fed-amount of chemical components excreted by manure)/(amount of chemical components fed;
raw material nutrient ATTD = [ test diet chemical component ATTD- (1-W) x chemical component ATTD in basal diet ] ++w;
w: the method comprises the steps that the raw materials to be tested provide a certain nutrient content in the test diet in percentage of the total nutrient content in the test diet;
S105, determining the effective performance of feed raw materials of the ternary pigs, the black pigs and the dead pigs;
s2, establishing a dead pig and dead pig effective prediction model based on effective performance of the ternary pig feed raw materials; s2 specifically comprises the following steps:
s201, correlation analysis: performing correlation analysis on the result measured in the step S1;
S202, establishing a prediction equation: establishing a prediction equation according to the result of the correlation analysis: DE Black pig ＝0.916ME Ternary pig +0.159GE-0.387,R2 =0.995
ME Black pig ＝0.945ME Ternary pig +0.11NDF+0.279,R2＝0.997
DE Pig-mounted pig ＝0.932DE Ternary pig +0.136GE-0.967,R2＝0.989
ME Pig-mounted pig ＝0.871DE Ternary pig -1.39Ash+1.828,R2＝0.989
Wherein DE is digestive energy, ME is metabolic energy, GE is total energy, NDF is neutral washing fiber, ash is coarse Ash, and R 2 is a determining coefficient.
2. The method for predicting the effective performance of feed materials for live-action pigs and live-action pigs based on the effective performance of feed materials for ternary pigs according to claim 1, wherein the feed materials to be evaluated in the step S101 include corn, soybean meal, sweet potato, tapioca, shredded coconut, coconut meal, bran, tapioca, palm meal and pomace.
3. The method for predicting the effective performance of a live-black pig and live-pig feed based on the effective performance of a ternary pig feed material according to claim 1, wherein the general nutrients in the step S101 include dry matter, moisture, organic matter, coarse ash, coarse fat, coarse protein, neutral washing fiber, acid washing fiber, and total energy.
4. The method for predicting the effectiveness of a feed for a dead pig and a dead pig based on the effectiveness of a ternary pig feed according to claim 1, wherein the test diet formulation in step S102 comprises ten kinds of diet, respectively corn diet, corn-bean meal diet, diet containing 38.8% sweet potato, diet containing 38.8% tapioca, diet containing 29.1% bran, diet containing 29.1% coconut meal, diet containing 29.1% palm meal, diet containing 29.1% tapioca, and diet containing 29.1% fruit dreg.
5. The method for predicting the effective performance of feed materials for live-action pigs and live-action pigs based on the effective performance of feed materials for ternary pigs according to claim 1, wherein the determining of the effective performance of feed materials in step S105 comprises: testing total energy, moisture, organic matters, crude ash, crude fat, crude protein, neutral washing fiber and acid washing fiber in diet, feed raw materials and manure samples; measurement of crude protein and total energy in urine samples.
6. The method for predicting the effective performances of the pig feed and the pig feed based on the effective performances of the three pig feed according to claim 1, wherein the result of the correlation analysis in the step S201 is that the digestion energy among the three pigs is extremely significantly correlated with the metabolic energy value, the organic matter content is significantly correlated with the digestion energy metabolic energy of the pig feed, the crude fat content is significantly correlated with the digestion energy of the pig feed and the digestion energy of the pig feed, the effective performances are positively correlated with the total energy, the organic matter, the crude fat and the crude protein, and the effective performances are negatively correlated with the crude ash, the neutral washing fiber and the acidic washing fiber.
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