# A Decision Model Forlive Pig Feeding Selection

Xinxin Sun, Longqing Sun, Yiyang Li

► To cite this version:

Xinxin Sun, Longqing Sun, Yiyang Li. A Decision Model Forlive Pig Feeding Selection. 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2015, Beijing, China. pp.82-93, 10.1007/978-3-319-48357-3_9. hal-01557818

HAL Id: hal-01557818

https://inria.hal.science/hal-01557818

Submitted on 6 Jul 2017

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
A Decision Model Forlive Pig Feeding Selection

Xinxin Sun¹,ª, Longqing Sun¹,ᵇ,*, Yiyang Li¹,ᶜ

¹College of Information and Electrical Engineering, China Agricultural University, Beijing
100083, China

*sunlq@cau.edu.cn, ªsunxinxin@cau.edu.cn

**Abstract:** With massive and intensive development of Chinese live pig industry, the imbalance of feeding nutrition turns out to be a primary problem. The main reason is that the nutrition needs to be adaptive to live pig's exact growth conditions in production management process. Regarding this, the paper aims at developing a feed-in selection model for pig breeding based on major nutrients predictive model proposed in the Nutrient Requirements of Swine published by U.S. NRC in 1998. The objective of this model is to achieve a minimum cost of feeding stuff under the premise that the nutrients satisfy pig's needs. According to values proposed in NRC and nutritional elements data, a feed-in selection model was developed to give proper suggestions on feeding dietary nutrients as well as exact type and quantity of pig feeding stuff. The work presented in this paper would contribute to the optimal precision feeding strategies so as to guarantee live pig growth quality in management process.

**Keywords:** live pig breeding, nutrients prediction, daily nutrition, feeding quantity, precision feeding, nutrition requirement

# 1. Introduction

The main cost of live pig feeding comes from the pig feeding stuff cost, accounting for 60-70% of the total cost of the large-scale pig feeding, and accounting for 70-80% of the total cost of pig specialized households[1], higher than labor costs (14-22%) and piglets costs (18-35%) [2]. There is at least 10% of the feeding stuff waste every year [3], result in feeding costs continue to rise, limiting our economic development of pig feeding and polluting the environment [4]. In the condition of ensuring the healthy growth of pigs, depending on the growing season, timing and quantitative feeding, fully tapping the feeding stuff nutrient availability, and improving feeding stuff conversion rate, are the key to reduce feeding costs and improve feeding efficiency.

From the live pig industry development status and trends of United States and Europe, there is a large systematic study in precision feeding aspects. In Denmark, pig daily food intake is controlled by computer, depending on the growing season, timing and quantitative feeding, pig breeding, achieve information and standardization[5]. The Danish manure normative system(DMNS) provide Danish farmers and authorities with tools for fertilizer planning control, the system include that dietary nutrient content, nutrient digestibility, feeding stuff intake and nutrient retention in the pig body. According to those information the system included, calculating the standard value of nutrients excreted, then getting the feeding stuff conversion rate, and providing the basis for the next
day grain feeding. In European countries, the feeding stuff conversion rate of Danish is the standard to correct their feeding stuff conversion rate [7]. In the Netherlands, the farming management software (Agrovision FARM) and the intelligent sow management system (Velos) are been used in pig feeding [8]. Agrovision FARM can record all important, true and reliable farming information. Velos can afford precise pig feeding in accordance with the feeding curve, avoiding feedwastage caused by artificial feeding and the pig body condition uneven caused by feeding inaccurate, thus ensuring the most accurate for every pig feeding. In the United States, the *Nutrient Requirements of Swine* which was published by U.S. NRC in 1998, providing a reliable basis for pigfeeding. According to different stages of pig breeding standards, U.S. researchers designed different feed formulation to reduce nutrient waste and manure nitrogen emissions, save feeding costs [10]. By using the technology of RFID radio frequency identification, wide network video surveillance, reach the intelligent pig feeding [7]. The use of automatically phased system makes pig feeding stuff conversion more efficient, feed fully compatible with the growth rate of pigs, neither because of lacking feeding stuff nutrients affect the growth rate of pigs, not because of excess nutrients in feed result in wastage. In our country, for the differences between China and the U.S. in terms of pig breeding species and breeding conditions, Fu Linsheng, Xiong Benhai and other researchers developed pig nutrition requirements dynamic forecasting system based on the NRC swine dynamic nutrition requirements, through appropriately adjusting the parameters to match the characteristics of Chinese pig breeding [9]. The system provide basic utility for a variety of pigs diet formulation designing under certain condition nutrient requirements, rationally using feed materials, and reducing feed costs and environmental pollution. The study of this system promotes the fine breeding, but the choice of the kinds of feeding stuff and feeding ration is not yet involved.

For the problem of low feeding utilization rate and high breeding cost in the development of aquaculture technology, according to NRC modeling software, the objective of this study was to calculate pig daily nutritional requirements in a growth phase, based on the type of feed and the daily requirement, establishing feeding portfolio optimization model, obtaining the mixed feed and mixed proportions by solving the model, improve feed utilization, reduce breeding costs, achieve precise feeding of pig breeding.

## 2. Method

### 2.1 Daily requirement

Pig daily nutritional requirements is an important basis for the daily design, the pig nutritional requirements the U.S. National Research Council (NRC) recommended is considered the most authoritative pig standards. It uses a mathematical model to estimate the integral energy, protein, amino acids, minerals and vitamins growing pigs needed [9].

NRC is the use of three interrelated nutritional needs modes, growth model, pregnancy model and lactation model, to software calculate. In this paper, according to the growth model selecting Growing - Finishing Pigs as the study object, the main two growing stages are 25-38kg and 38-57kg. Inputting the data pig's weight, type, energy indicators and so on, outputting the nutritional requirements data, which includes digestible energy (DE)-based energy, amino acid
requirements, minerals and vitamins requirement. In the calculation, choosing nutrition requirements model of growth model to software calculate, the data obtained by NRC software model calculating shown in Table 1, Table 2, Table 3.

<table><caption>Table 1 Daily energy intake for each pig</caption><thead><tr><th>Body weight</th><th>Total energy (kg)</th><th>Digestible energy (IU)</th><th>Predicted (g)</th><th>Lipid (g)</th><th>{</th><th>Digestible fiber (g)</th><th>Vitamin (IU)</th><th>Calcium (g)</th><th>Phosphorus (g)</th></tr></thead><tbody><tr><td>25-38(kg)</td><td>1.451</td><td>4406</td><td>119</td><td>128</td><td>69.65</td><td>1926.5</td><td>1</td><td>9.00</td><td>4.19</td></tr><tr><td>*</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>38-57(kg)</td><td>1.904</td><td>5901</td><td>141</td><td>194</td><td>89.49</td><td>2609.6</td><td>5</td><td>11.31</td><td>5.26</td></tr><tr><td>*</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

Notes: *25-38(kg), *38-57(kg), mean sub-stages weight of growth pigs.

<table><caption>Table 2 Daily trace elements intake for each pig</caption><thead><tr><th>Body Weight</th><th>Sodium (g)</th><th>Chloride (g)</th><th>Magnesium (g)</th><th>Potassium (g)</th><th>Copper (mg)</th><th>Iodine (mg)</th><th>Iron (mg)</th><th>Zinc (mg)</th><th>Manganese (mg)</th><th>Selenium (mg)</th></tr></thead><tbody><tr><td>25-38(kg)</td><td>1.35</td><td>1.06</td><td>0.53</td><td>3.25</td><td>5.78</td><td>0.18</td><td>89.1</td><td>80</td><td>2.64</td><td>0.269</td></tr><tr><td>38-57(kg)</td><td>1.82</td><td>1.43</td><td>0.71</td><td>3.70</td><td>6.57</td><td>0.25</td><td>95.7</td><td>98</td><td>3.57</td><td>0.31</td></tr></tbody></table>

Notes: *25-38(kg), *38-57(kg), mean sub-stages weight of growth pigs.

<table><caption>Table 3 Daily vitamin intake for each pig</caption><thead><tr><th>Body Weight</th><th>A (IU)</th><th>D (IU)</th><th>E (IU)</th><th>K (mg)</th><th>B<sub>6</sub> (mg)</th><th>B<sub>12</sub> (µg)</th></tr></thead><tbody><tr><td>25-38(kg)</td><td>1714</td><td>198</td><td>14.51</td><td>0.66</td><td>1.32</td><td>13.7</td></tr><tr><td>38-57(kg)</td><td>2322</td><td>268</td><td>19.65</td><td>0.89</td><td>1.79</td><td>13.35</td></tr></tbody></table>

Notes: *25-38(kg), *38-57(kg), mean sub-stages weight of growth pigs.

Data in the table above are the main basis for this paper feeding selection. All selection, recipe selection must meet the growth needs, and the data obtained through the NRC modeling software are the requirements must be met, that is the constraints in the process of forecast calculation. According to the number of nutritional requirements and cost, select the most appropriate feeds to feed.

## 2.2 Feeding decision model

With the lowest cost as the objective function, the linear programming mathematic model was built [18]. Suppose there are *n* kinds of feeds to choose from for a growth phase, *m*<sub>i</sub>
represents the ith feed, $m_i^{max}$ and $m_i^{min}$ represent the max and min limits of feed, i as the
nutrients necessary number for the growth of pigs, $n_j$ represents the j th nutrient
element, $n_j^{max}$ and $n_j^{min}$ represent the max intake of nutrient and min intake of nutrients $n_j$; in unit
mass of $m_i$, the mass percentof nutrients $n_j$ denoted $u_{ij}$; the market price offeed $m_i$recorded as
$c_i$, the number of daily feed $m_i$as $x_i$, feeding costs can be expressed as the objective function is
shown as follows:

$$
Z = \min \sum_{i=1}^{n} c_i x_i \quad (i = 1, 2, \dots, n) \quad (1)
$$

Where Z represents the cost of feed fed, $c_i$ is the ith feed market price, $x_i$ represents the ith
day ration of $m_i$ feed.

Feed usage constraints [(2) - (4)]:

$$
m_i^{\min} \leq x_i \leq m_i^{\max} \quad (i = 1, 2, \dots, n) \quad (2)
$$

Where $x_i$ represents the ith day ration of $m_i$ feed, $m_i^{max}$ and $m_i^{min}$ represent the max and min limits of feed.

$$
n_j^{\min} \le \sum_{i=1}^{n} \mu_{ij} x_i \le n_j^{\max} \quad (i = 1, 2, \dots, n) \quad (3)
$$

Where $n_j^{max}$ and $n_j^{min}$ represent the max intake of nutrient and min intake of nutrients $n_j$; $n_j$ represents the jth nutrient element; $u_{ij}$ is the mass percent of nutrients $n_j$ denoted; the number of daily feed $m_i$ as $x_i$.

$$
x_i \ge 0 (i = 1, 2, \dots, n) (4)
$$

Where $x_i$ represents the ith day ration of $m_i$ feed.

Though model computing can obtained $x_i$as well as get quality for all kinds of feed, while
able to calculate the value of Z, which is the minimum cost of feed mix in$x_i$situations.
## 2.3 Data flow

<figure><img src="image_2.png" /><figcaption>Fig1. Pig feeding selection decision process</figcaption></figure>

The feeding selection decision process is illustrated in Figure 1, the model processes are listed below:

1. Determine the growth stage of pigs, getting pig weight data.

2. After knowing the weight using NRC modeling software calculate nutritional requirements the pig needed, which includes the digest energy (DE)-based energy, amino acid requirements, minerals and vitamins requirement.

3. Meeting the nutritional needs(get from 2) conditions, can purchased directly competing mixed feeding stuff, can also be mixed in accordance with the existing feeding stuff themselves, if mixed by themselves, determining the type of breeding materials and ingredients contained in the existing ratio.

4. Known nutritional requirements data and raw data feed decision to build a mathematical model to calculate the lowest cost feeding stuff mix, that kind of feed needed, how much needs.

5. If it satisfies the minimum cost and to meet the nutritional needs, you get to choose the end result of the calculation, if not, loop to 3 recalculate until getting the outcome, the calculation ended.
# 3. Results and discussion

## 3.1 Feeding Selection

### (1) Data analysis

In this section, through example represent the feeding decision mathematical model simulation process, according to the conditions of meeting the growth need of pig, with the existing status quo forage species breeding farms, pigs breeding mixed feeding stuff is calculated. There are five different options pig feed, such as A, B, C, D, E, the feed information as shown in Table 4.

<table><caption>Table 4 Proportion of the energy in the feeding stuff</caption><thead><tr><th>feeds</th><th>Digestible energy (IU)</th><th>Prediction (g/kg)</th><th>Crude fiber (g/kg)</th><th>Vitamin (mg/kg)</th><th>Calcium (g/kg)</th><th>Phosphorus (g/kg)</th><th>Price (yuan/kg)</th></tr></thead><tbody><tr><td>A</td><td>3050</td><td>280</td><td>100</td><td>9.9</td><td>45</td><td>8</td><td>7</td></tr><tr><td>B</td><td>3060</td><td>145</td><td>700</td><td>10</td><td>80</td><td>10</td><td>6.2</td></tr><tr><td>C</td><td>3050</td><td>160</td><td>200</td><td>9.5</td><td>70</td><td>9</td><td>6.3</td></tr><tr><td>D</td><td>3050</td><td>310</td><td>100</td><td>6</td><td>50</td><td>11</td><td>5.5</td></tr><tr><td>E</td><td>3060</td><td>150</td><td>100</td><td>6.5</td><td>10</td><td>5</td><td>5.2</td></tr></tbody></table>

### (2) Modeling

Under the conditions of meeting the nutrients requirements of pig growth, in order to minimize the cost of keeping the goal to establish programming model, such as the ratio of the feed formula (5-10) below.

Objective function:

$$Z_{min}=7x_{1}+6.2x_{2}+6.3x_{3}+5.5x_{4}+5.2x_{5} \quad (5)$$

Where the objective function is to get the cost of the optimal feed ration, $Z_{min}$ is the feeding stuff ration cost; $x_1, x_2, x_3, x_4, x_5$ represent A, B, C, D, E are five different pig feeding stuff ration, $x_i$ corresponds to the $i$th feeding stuff ration.

Satisfy the following constraints established:

$$280x_{1}+145x_{2}+160x_{3}+310x_{4}+150x_{5} \geq 141 \quad (6)$$

Where the protein are the growth feed pigs needs must be meet of feeding process, $x_1, x_2, x_3, x_4, x_5$ represent A, B, C, D, E five different pig feeding stuff ration ($x_i \geq 0, i=1,2,3,4,5$).

$$100x_{1}+700x_{2}+200x_{3}+100x_{4}+100x_{5} \geq 89.49 \quad (7)$$

Where the crude fiber is the growth feed pigs needs must be meet of feeding process, $x_1, x_2, x_3, x_4, x_5$ represent A, B, C, D, E five different pig feeding stuff ration ($x_i \geq 0, i=1,2,3,4,5$).

$$9.9x_{1}+10x_{2}+9.5x_{3}+6x_{4}+6.5x_{5} \geq 3.54 \quad (8)$$
Where the vitamins are the growth feed pigs needs must be meet of feeding process, $x_1$, $x_2, x_3$, $x_4$, $x_5$ represent A, B, C, D, E five different pig feeding stuffration ($x_i \ge 0, i = 1,2,3,4,5$).

$$45x_{1}^{+} 80x_{2}^{+} 70x_{3}^{+} 50x_{4}^{+} 10x_{5} \geq 11.31 \quad (9)$$

Where the calcium are the growth feed pigs needs must be meet of feeding process, $x_1$, $x_2, x_3$, $x_4$, $x_5$ represent A, B, C, D, E five different pig feeding stuff ration ($x_i \ge 0, i = 1,2,3,4,5$).

$$8x_{1}^{+} 10x_{2}^{+} 9x_{3}^{+} 11x_{4}^{+} 5x_{5} \geq 5.26 \quad (10)$$

Where the phosphorus must be meet the growth feeding pigs needs during the feeding process, $x_1$, $x_2, x_3$, $x_4$, $x_5$ represent A, B, C, D, E five different pig feeding stuff ration ($x_i \ge 0, i = 1, 2, 3, 4, 5$).

### (3) Result

By decision model formula (5-10) constraint equation knowing that, if breeding farms choose to feedfeeding stuffA 0.0586g per pig per day, feeding stuffB 0.0762kg, feeding stuffD 0.3663kg, to meet the growing needs of pigs ,and investment the lowest total cost of 2.9 Yuan.

## 3.2 Analysis

From the simulation knowing that, according to the nutritional requirements datawhich are shown in tables (1-3), using the mathematical models to calculate to get all kinds of decision-mixed feeding stuff requirements, mixed feeding stuff (Mix) combinations are shown in Table 5. The mixed feeding stufffeedingis better than one feeding stuff feeding, such as A, B, C, D, E are five different methods of feeding pig feeding stuff alone, in the respects of feeding stuff costs and feeding ration., A, B, C, D, E, and Mix feeding volume and feeding cost comparison data are shown in Table 6.

<table><caption>**Table5**Calculated mixed feeding stuff (Mix)</caption><thead><tr><td>Selected feeds</td><td>Feed ration* (kg)</td><td>Cost* (yuan)</td></tr></thead><tbody><tr><td>A</td><td>0.0586</td><td>0.4</td></tr><tr><td>B</td><td>0.0762</td><td>0.5</td></tr><tr><td>D</td><td>0.3663</td><td>2.0</td></tr></tbody></table>

Note: *Feed ration, feeds a pig need a day; *Cost, feed a pig need spendinga day

<table><caption>**Table6**Comparisons of intake and cost between mixed and singlefeeding stuff</caption><thead><tr><td>Fed feeds</td><td>Feed ration* (kg)</td><td>Cost* (yuan)</td></tr></thead><tbody><tr><td>A</td><td>0.89</td><td>6.2</td></tr><tr><td>B</td><td>0.97</td><td>6.0</td></tr><tr><td>C</td><td>0.88</td><td>5.5</td></tr></tbody></table>
<table><tr><td>D</td><td>0.87</td><td>4.8</td></tr><tr><td>E</td><td>0.94</td><td>4.9</td></tr><tr><td>Mix</td><td>0.50</td><td>2.9</td></tr></table>

Note: *Feed ration, feeds a pig need a day; *Cost, feed per pig need spending per day

Analysis showed that, when a single feeding stuff breeding meet all the nutritional needs, some nutritional elements are excess result in feeding stuff waste. When nutrients to meet the requirements of crude fiber, protein and phosphorus ration greater than requirements, indirectly feeding stuff waste and excess nutrients polluting the environment during defecation. Selecting mixed feeding stuff fed to reduce breeding costs and waste of resources, and with a more balanced nutritional needs.

### 3.2.1 Price factor

In this paper, the model aims at giving the lowest cost of feeding stuff feeding combination in the breeding process, depending on the kind of prices of feeding stuff. The changing feed prices on the market impact model calculations for changes in feeding stuff prices, using the simulation models in terms of price changes feeding stuff case to get the selection result. For A, B, C, D, E the five kinds of pig feeding stuff, listing three groups changing price( I, II, III). Price I {7.6,2,6.3,5.5,5.2}; Price II {7.0,6.9,6.5,6.5,5.7}; Price III {7.5,6.9,6.5,6.7,4.5}. Calculated by the model, the results obtained 3 Group Mixed Feed Mix I, Mix II, Mix III, as the Table 7 shown.

<table><caption>**Table 7** Calculated results of feeding decision model</caption><thead><tr><th>Mix feeds</th><th>selection feeds</th><th>Costs*<br>(yuan)</th></tr></thead><tbody><tr><td>Mix I</td><td>A、B、D</td><td>2.9</td></tr><tr><td>Mix II</td><td>A、B、C、D</td><td>3.3</td></tr><tr><td>Mix III</td><td>B、C、D、E</td><td>3.7</td></tr></tbody></table>

Note: *Cost, feed a pig need spending a day

The model results were analyzed, and the three groups of mixed feeding stuff costs were compared with a single feeding costs (Table 6), we find that the mathematical model of mixed feeding stuff to get the lowest cost, shown in Figure 2. The price I, price II, price III three groups of different prices feeding stuff, mixed feeding stuff Mix cost obtained (shown in black bars shown in block) are minimum by solving the model, the calculation results show that the three groups of computing results, the selection of only one feeding stuff to breed, under the conditions required to meet the nutritional needs of feeding stuff costs were greater than the cost it takes to Mix, price changes in conditions, the model still can calculate the lowest-cost breeding selection results.
<figure><img src="image_3.png" /><figcaption>Fig. 2 Comparison of cost between mixed and single feeding stuff</figcaption></figure>

### 3.2.2 Specified mixed feeding stuff

Under certain circumstances, breeding pig feeding stuff with special requirements, for the same growth stage pig, due to the different growth status the needs of pig feeding stuff different, poor growth conditions may need to be bred a certain or a few specific pig feed feeding stuff, different growth stage with different nutritional requirements, feeding the specific needs of different feeding stuff, in order to meet these conditions, in particular the feeding stuff of feed A and feeding stuff of fed specific B, D, use the model to calculate the breeding selection decision, the results shown in Table 8.

<table><caption>**Table 8**Calculated results of feeding decision model</caption><thead><tr><th>Mix feeds</th><th>selection feeds</th><th>Costs*<br>(yuan)</th></tr></thead><tbody><tr><td>Specific A</td><td>A、</td><td>3.70</td></tr><tr><td>Specific B、D</td><td>B、C、D、E</td><td>3.71</td></tr></tbody></table>

Note: *Cost, feed a pig need spending a day

The results of the data analysis showed that under certain circumstances the feeding stuff ration, the model calculated the lowest cost of mixed feed, shown in Figure 3. Feeding stuff A in the feeding of two specific and particular conditions of feeding stuff B of A, B, C, D, E, Mix these six kinds of feeding costs compared to Figure 3, breeding feeding stuff A group known specific investment Mix Hey cost of 3.70 Yuan, the specific feed fed group B, D Mix feeding cost of 3.71 Yuan, the lowest point are in the fold, the minimum cost of breeding, feeding fixed feeding stuff under specific conditions, to get through the model to calculate the most cost excellent choice of feeding stuff result.
<figure><img src="image_4.png" /><figcaption>Fig.3 Comparison of cost between specific feeding A and feeding B, D</figcaption></figure>

### 3.2.3 Nutritional needs

In the process of pig breeding, different season with different effects on pig growth, higher temperatures summer and low temperatures winter have different effects on pig feeding stuff intake and nutrient requirements. Summer reduce the needs for appropriate high crude fiber intake of growth pig, and winter low temperatures need to increase energy intake of protein for pig, which is required to change the conditions of the model equation constraint. In summer and winter the two conditions, for example, through a decision-making model for solving the feed mixed feeding stuff to get the results shown in Table 9.

<table><caption>**Table 9** Calculated results of feeding decision model</caption><thead><tr><th>Constrains</th><th>Selection<br>feeding stuff</th><th>Costs<br>(yuan)</th></tr></thead><tbody><tr><td>Winner</td><td>A、B、D</td><td>2.90</td></tr><tr><td>Summer</td><td>B、D</td><td>3.3</td></tr></tbody></table>

Note: *Cost, feed a pig need spending a day

Though the results of the analysis, we know that in the summer and winter both cases, the results calculated by the model are bred in to meet the nutritional needs of growing conditions, day feeding stuff costs 2.9 Yuan and 3.3 Yuan, comparing with a separate feeding A, B, C, D, E five kinds of feed costs necessary 6.2,6.0,5.5,4.8,4.9 (Yuan), is the optimal cost of the pig breeding, that seasonal changes in nutritional requirements change of pig growth conditions, the model calculated optimal costs mixed feeding stuff.
## 4. Conclusion

The aim of this paper is to build a pig feeding optimization mathematical model and obtain the lowest-cost feeding mixed results. A model was developed based on optimal cost, considering three elements: price factor, specified feeding stuff and nutritional requirements. The results were analyzed demonstrating its validity according to growing pig conditions. Use of the feeding selection decision model can enable more precise feeding, proper selection of feeding stuff, lower cost and increasing economic benefit of pig breeding.

## Acknowledgement

This paper was supported by the Shandong Province innovation special (2014XGA13054). Supported by National Science and Technology Supporting Program (2014BAD08B05).

## References

1. Chen ming. Study on Nutrient Diagnosis and Diet Formulation System of Swine. [D]. Beijing: Chinese Academy of Agricultural Sciences. 2011(6).

2. Yu wen, Kong fantao, Yu haipeng. Chinese farmers backyard pig production cost element analysis. [J]. China Swine Industry. 2012(3).

3. Zhao xianwu. How to improve the growing and finishing pigs weight gain and feed efficiency. [J] Swine Production. 2007(3).

4. Xiong yuanzhu. Pig Industry Technology Review and Prospects. [J]. Farming and Feed. 2005(10).

5. Chen guoyu, Wei jianmin. European pig inspection experience [J]. China Animal Industry. 2013.

6. Henry Jorgensen, Trakarn Prapaspongsa. Models to quantify excretion of dry matter, nitrogen, phosphorus and carbon in growing pigs fed regional daily. JOURNAL OF ANIMAL SCIENCE AND BIOTECHNOLOGY.2013: 4-42

7. Gu zhaobing, Xu laishun. Status quo and development trend of foreign pig industry. [R]. Animal Husbandry and Veterinary Medicine. 2012.44(7).

8. Yi ge. Intelligent pig management. Global Vision [N]. 2013.

9. Fu linsheng, Xiong benhai. Development of Dynamic Projection System for Nutrient Requirements of Swine [J]. Agriculture Network Information. 2009(7).

10. Lei minggang, Feng xunwei. U.S. Swine production technology development of new trends. [J] China Swine Industry. 2012(11).

11. Xing qian. Research and Application of Intelligent Pig-keeping Based on Association Rules [D]. Chongqing University of Technology. 2012.

12. Fang kui, Wang juan. Research on foreign pig breeding information model [J]. Swine Industry Science 2009(5).

13. Wu xiuyun, Song ying. Optimization of the complete feed formula model of Plateau Lean Meat Pig [J]. Ecology Of Domestic Animal. 2003.24(1).

14. Zhang ying. Solving the MATLAB linear programming model in realizing [J]. JOURNAL OF TONGHUA TEACHERS COLLEGE. 2009,30:11-31.

15. SCHERER C, WEILAND S. Linear matrix inequalities in control [D]. Delft University of
Tdchnology,2005

16.Xu Liying, Yu Chengxian, Xing Bin, et al. PDA-based aquaculture feeding decision support system[J]. Transactions of the CSAE, 2008, 24(Supp.2):250-254.

17.C. Pomar, J. Pomar. The impact of daily multiphase feeding on animal performance,body composition, nitrogen and phosphorus excretions, and feed costs in growing-finishing pigs. Animal (2014), 8:5, pp 704-713

18.Qin ye. DESIGN AND IMPLEMENT OF DAIRY COW FEED STUFF PRESCRIPTION DECISION SUPPORT SYSTEM BASED ON.NET.Beijing University Of Posts and Telecommunications [D].2009

19.Ma dehao. Research and Implementation Of Abalone Precision Aquaculture Decision Support System [D]. Shandong Agricultural University.2013.

20.Wang kui. ANALYSIS ON THE HOG RAISING SCALE AND THEIR BENEFIT [D]. Southwestern University.2010.

21.Xu li. Design and implementation of management system of automatic feeding [D]. Nanjing university of posts and telecommunication. 2013.

22.Chen ningling. Analysis of Feed Grain Consumption of China and Forcasting the Demand for Feed Grain in Chinese Hog and Poultry husbandry. Southwestern University.2011.

23.Maike Naatjes and Andreas Susenbeth. Energy requirement of growing pigs under commercial housing conditions. Archives of Animal Nutrition. 2014.68:2, 93-110

24.Li ye. ANALISIS ON THE HOG RAISING SCALE AND THEIR COSTS BENEFIT [D]. Northwest Agriculture and Forestry University.2007.