Minghua Shang

Gang Dong

Yuanjie Mu

Fujun Wang

Huaijun Ruan

The Application of Internet of Things in Pig Breeding

Keywords: The Internet of Things, pig-breeding, large-scale, application

A pig breeding IoT system is designed, in view of the human resources, natural re-sources consumption, the quality and safety problems occurred frequently, the management mode is backward and so on. In this paper, the system architecture, information awareness, system application of the three aspects of pig farming system is introduced.The system can use all aspects of pig farming to sales, has some reference to the intensive far ming of pigs.

Preface

China is the world's largest pork producer and consumer, the demand of pork promoted the rapid development of pig breeding industry. First, the number of pig herds are increasing.In terms of Shandong,the number of pigs for 24.0181 million in 2000, by the end of 2013 pigs grew to 29.3141 million [START_REF]Shandong Statistical Yearbook[END_REF]. Second, the pig breeding way has changed.The traditional way of farming is to take individual farmers as the unit of extensive farming methods [START_REF] Xiuhong | Design Scheme of Livestock and Poultry Farm[END_REF][START_REF] Changhua | Application and Prospect of Modern Livestock and Poultry Breeding Information Technology[END_REF],farming scale is small,due to the benefits and risks of breeding to promote the industry to accelerate the withdrawal of the family, large-scale breeding has been rapid expansion [START_REF] Mengshuai | Technical Support For the Modernization of Animal Husbandry Modernization[END_REF][START_REF] Biao | Study on the Scale Evolution Model of Pig Breeding Industry in China[END_REF][START_REF] Wei | Environmental Monitoring System Based on Internet of Things of Large-scale Livestock Breeding[END_REF][START_REF] Yuan | The Application of the Internet of Things Technology Based on RFID in Animal Husbandry[END_REF]. With the pig population increased and the large-scale farming expansion,the problem of pig breeding is becoming more and more prominent:Pig farming consumes a lot of natural resources, such as human resources and feed , feeding costs greatly increased [START_REF] Xuguo | The Application of the Internet of Things Technology in the Large-scale Livestock and Poultry Breeding Industry[END_REF][START_REF] Linhai | Study on the Moderate Scale of Pig Farms in the Cost of Environmental Pollution Control[END_REF];In the process of pig breeding, the nitrogen compounds, H2S, NH3, etc., are not strictly monitored,this is not conducive to the growth of pigs, but to some extent, the environment has caused a certain impact. Pork quality and safety problems occur frequently;Traditional production management mode is relatively backward, the data is difficult to collect and deal with it in time, which leads to the lag of production statistics, which has not adapted to the needs of modern production management [START_REF] Binyu | The Design of the Monitoring System of the Digital Aquaculture Production Process Based on the Internet of Things[END_REF]. Today, the development of Internet of things technology is very fast, has been in traffic, medical, security, environmental protection and other industries have been very good application. Apply the Internet of things technology to all aspects of pig breeding,through a variety of terminals, a variety of forms to allow producers, managers, anywhere access to the relevant information and daily management, will bring unprecedented opportunities for the pig breeding [START_REF] Benhai | Research Progress of the Application of the Internet of Things Technology in Animal Husbandry in China[END_REF].

System Framework

Apply the Internet of things technology to the whole process of pig breeding.System is mainly composed of three parts: information perception, data transmission and system application. The system architecture is shown in Figure 1. Information perception is a collection of information on the breeding environment and individual information, data transmission means that the environmental information is uploaded to the server through the gateway node.Pig individual information through smart phones, PAD, PDA and other handheld devices to collect and through mobile communication networks, the Internet to upload to the server.System application layer is a monitoring platform for pig breeding, it can provide a variety of terminals, a variety of methods of data viewing, equipment management, early warning parameters set, quality traceability and other functions.

Environmental Information Perception

Environmental information has a certain effect on the growth of pig: pig is a constant temperature animal, if the temperature is too high, the pig will be adjusted to heat, but the environment temperature is too high will make the adjustment range of pigs narrow; if the temperature is too low, it will lead to the consumption of pigs is too large, which leads to the increase of feed consumption. If the humidity in the pigsty is too high, it will reduce the pig's resistance, increase the probability of illness; if humidity is too low, it will cause respiratory disease in pigsty. The harmful gas such as H2S content is too high will cause inflammation and respiratory diseases, high concentration of NH3 will stimulate the respiratory tract mucosa and tuberculosis membrane of pigs, causing conjunctivitis, bronchitis and other diseases.

Environmental information has become more and more attention.

Design of Acquisition Node

In order to achieve better monitoring of environmental information, environmental information acquisition node is designed.The acquisition and processing of the multi parameter data of pig breeding environment and the function of wireless transmission are realized.The acquisition nodes mainly collect air temperature, air humidity, H2S, NH3 four parameters, the acquisition of real-time data processing, and is responsible for communicating with the gateway node.H2S, NH3 acquisition nodes as shown in Figure 2(a), the air temperature and humidity acquisition nodes, as shown in figure 2(b). The acquisition node is made of four parts (see Figure 3), which is composed of the core processing unit, signal processing unit, communication unit and power supply circuit. The signal processing unit is directly connected with the sensor (including temperature and humidity sensor, toxic gas sensor), and the NH3 sensor selects the NH3 3E Sensoric 1000 SE sensor, and the H2S sensor selects the H2S 3E Sensoric 100 S sensor.NH3 and H2S sensor use the same principle, in the monitoring to the corresponding gas will produce a weak current signal, signal acquisition circuit to get the current signal into voltage signal and amplification, and then get the voltage analog signal transmission to the core processing unit.Temperature and humidity sensor uses the SHT11 type sensor, it is slightly different with the gas sensor, it outputs digital signal, without the need for analog conversion.SHT11 sensor with strong anti-interference ability, low power consumption, fast response, high accuracy.

At the 14 resolution, the humidity was ±3%RH and the temperature accuracy was ±0.4℃.The core processing unit is connected to the temperature and humidity sensor through the I2C bus to obtain the data.

The core processing unit selects STM32 microcontroller, which has the features of low power consumption, low cost and stable performance.In NH3/H2S acquisition node, the core processing unit obtains the voltage analog signal of the signal processing unit through A/D sampling, and after correction, compensation according to the sensor site temperature (different operating temperature, the corresponding current signal of 1ppm gas) will be converted to the voltage signal to the gas collection value. The core processing unit of the air temperature and humidity acquisition node can obtain the numerical value of SHT11 transmission directly through the I2C bus. The communication module is composed of Si4432, which is simple, communication distance, supports multi band and low power consumption. The acquisition node and gateway node are composed of Si4432, and the information is transmitted to the gateway node.

Design of Gateway Node

The gateway node is a bridge between the system application platform and the data acquisition node, which affects the stability of the system. The main function of gateway node: access to various information collection node data; establish the system application platform and long connection can maintain real-time communication; in wireless sensor network and communication network platform, the ability to parse and transform the protocol; configuration: intensity collection node address addressable configuration parameters the base configuration properties that can be configured. Gateway hierarchy is shown in Figure 4. The gateway node selects the S3C2440 processor of Samsung, which is equipped with the Linux 2.6 kernel and Yaffs2 file system. The gateway node is located in the center of the star network of Si4432, and the data obtained from each node is obtained. After data acquisition, the network joint points analysis data packets, the data is updated to real-time display in the interface of Qt, and the data packets are transmitted to the remote server according to the protocol. Communication unit Ethernet or GPRS two ways and the remote server through the design of the heartbeat packet to maintain a long connection state, uplink transmission data, downlink transmission. The physical map of the gateway node is shown in Figure 5.

Production Management Information Perception

In livestock and poultry breeding enterprises in the production of information is still based on the traditional paper records, not only inefficient, error prone, and the data is difficult to timely collection and processing, resulting in a serious lag in production statistics.Livestock quality and safety traceability system requires the information of the whole industrial chain such as pig production, quality inspection, slaughter, transportation, freezing, sales and so on.In order to solve this problem, we designed a portable pig ear tag reading and writing equipment, and developed a set of APP software which named ZHINONGYUNDUAN based on the Android system, and it is necessary to use. Regardless of which link in the whole industry chain, when the need to enter the information, you can use a portable ear tag reader to read and write the device to read the information, the APP client software to enter the appropriate information, and then click on the preservation of information, you can save the collected data to the system. In this way, the individual and the production, quality inspection, slaughter, transportation, freezing, sales and other information links.The portable ear tag reading and writing equipment is made up of three parts: the core processor, the RFID read and write module and the Bluetooth module, and the structure of the device is shown in Figure 6.

Core processor

Power supply circuit

Bluetooth module RFID R/W module Coil Fig. 6. Structure of portable ear tag reading and writing equipment When using this system, the first portable ear tag information collection device (see Figure 7(a)) Bluetooth module and handheld terminal device pairing, portable pig ear tag read-write device using RFID technology, through the non-contact way to obtain pig ear tag information, and ear tag information is transmitted to the APP via Bluetooth (Fig. 8(a)). The corresponding user input information in APP software (Figure 8(b)), click save, relevant information can be transmitted to a remote server, the information flow is shown in figure 7.

Application of the System

The application of the system mainly includes:①Data real-time monitoring: users can view the real-time data of the various pig breeding environment information acquisition nodes, and can view the production management information;②Historical data query and export: environmental information collection node acquisition of data and the wisdom of the cloud APP access to the data stored in the Server SQL database, the user can choose according to their own needs to query the query data, but also can export the selected time period of data analysis;③Alarm management: users can set up the demand of air temperature and humidity, NH3/H2S gas content on the threshold, if the actual measurement value exceeds the threshold range of the system will automatically alarm to inform the user;④Equipment management: users can add / remove the environment information collection node, change the equipment (gateway node, environment information acquisition node) according to their own needs ID number.

For the realization of the traceability of pork products quality and safety process, the team based on information management of pig breeding, slaughtering, processing, storage and transportation and other production records, is developed for traceability terminal quality information of pork products (Figure 9(a)) and electronic scale source (Figure 9(b)).In the bar code generated by the special electronic scales, the information contained in the whole process of pig raising to pork production, quality inspection, slaughter, transportation, freezing and sales etc.. The whole process can be obtained by scanning the two-dimensional code in the quality of pork.

Brief Summary

This paper according to the actual needs of production,use the Internet of things technology,have developed a set of system for the management of pig farms.The system can collect the real-time data of the air temperature, humidity, H2S, NH3 in the environment of pig breeding according to the requirements of production, and obtain the production management information, and the information of the quality inspection, slaughter, transportation, freezing, sales and other information are linked with the pig individual, and realize the whole process of pork production. Although the network system of pig farms has been developed, it still has a large gap compared with the developed countries, which need to be improved in the future. The rapid development of the Internet of things technology will give the livestock and poultry breeding industry has brought a qualitative leap.

  Fig. 1. System architecture

Fig. 2 .Fig. 3 .

 23 Fig. 2. Physical picture of the collection node

Fig. 4 .

 4 Fig. 4. Hierarchical structure of gateway node

Fig. 5 .

 5 Fig. 5. Physical picture of the gateway node

Fig. 7 .Fig. 8 .

 78 Fig. 7. Collection equipment for portable ear tag information

Fig. 9 .

 9 Fig. 9. Pork product quality information traceability terminal

Acknowledgment

Funds for this research was provided by the National Science and Technology Plan Projects (2014BAD08B05-02), Shandong Province Major Projects of Independent Innovation (2014XGA13054), Shandong Province Key R&D Projects(2015GNC110024),Shandong Academy of Agricultural Sciences Technology Innovation Key Projects(2014CXZ09-1).


Yan Qi

Baoguo Wu

Shanghong Li
email: shanghongli@cau.edu.cn

Evaluation of Timber and Carbon Sequestration Income of Cunninghamia Lanceolata Timber Forest and Management Decision Support

Keywords: Evaluation, timber income, carbon sequestration income, Cunninghamia lanceolata, management decision support

Carbon sequestration exchange has just started in China. This study was based on the general plantation regions in Fujian China where Cunninghamia lanceolata is quite popular and has great economic and ecological significance for farmers and the society at large. This study used Hartman model to forecast the income of timber sales and carbon sequestration so as to integrate the model in the decision support system to find a practical tool for farmers to project their future monetary income to make sound operating decisions in terms of plantation density and rotation age, which is of practical significance and innovation.

Introduction

Facing the huge social demand for industrial forest products, as well as the serious challenge of the environmental protection put forward by the global climate warming, the sustainable management of artificial timber forest has the important dual role of economic benefits creation and environmental protection. The foreign countries advanced in forestry have achieved the 60% -93% of the total industrial forest products by using the artificial timber forest which takes only 1.2% -16% of their total forest area, [START_REF] Zhou | The sustainable operation of artificial forests in China[END_REF] which poses a challenge to China and at the same time provides very good experiences too.

The Cunninghamia lanceolata (China fir) is one of the unique fast-growing commercial timber tree species. It has fast growth speed, good timber material of being light and toughening at the same time, moderate intensity, and high quality. It is fragrant, resistant to insect decay and easy to process. Its broad economic use can be found in construction, furniture, appliances, shipbuilding, etc. The Cunninghamia lanceolata is widely planted in the 16 provinces and regions in south China. It is the one of the important forest resources in south China as one of the most important afforestation and fast-growing timber tree species in southern collective forest region of China. And it is the most widespread plantation and ecological system in Fujian province.

The Chinese fir plantation has great ecological, economic and social benefits. Therefore, it is of great significance to study on the sustainable management of the Chinese fir artificial timber forest.

Literature Review

 International College Beijing, China Agricultural University, Beijing, China

With the background of global climate change and environmental protection, research on carbon sequestration has drawn a lot of attention in the academic field, including the carbon sequestration related research about Cunninghamia lanceolata. Bayer et al highlighted the importance of forest biomes for maintaining and increasing biogeochemical carbon sequestration in their study, considering the biome-specific response to current climate and land use, and their projections for the future [START_REF] Bayer | Historical and future quantification of terrestrial carbon sequestration from a Greenhouse-Gas-Value perspective[END_REF] .

Huang et al analyzed the carbon sequestration in living biomass and soil organic carbon pools using the carbon estimation model and reached the amount of carbon stock up to date and in both the past and the future. According to them, from 1950 to 2012, plantations in China sequestered 1.686 Pg carbon by net uptake into biomass and emissions of soil organic carbon.

The carbon stock of China's present plantations was 7.894 Pg, 21.4% as forest biomass and 78.6% as soil organic carbon. They projected that China's carbon stock will reach a level of 3.169 Pg by 2050, and it will amount to 10.395 Pg. [START_REF] Huang | Carbon sequestration by forestation across China: Past, present, and future[END_REF] There have been some comparison studies. Yen and Lee conducted a comparison study on the aboveground carbon sequestration between moso bamboo (Phyllostachys heterocycla) and Chinese fir (Cunninghamia lanceolata) forests based on the allometric model. [START_REF] Yen | Comparing aboveground carbon sequestration between moso bamboo (Phyllostachys heterocycla) and China fir (Cunninghamia lanceolata) forests based on the allometric model[END_REF] NIU et al conducted a comparison study on the carbon storages in Cunninghamia lanceolata and Michelia macclurei plantations during a 22-year period in south China [START_REF] Niu | Comparisons of carbon storages in Cunninghamia lanceolata and Michelia macclurei plantations during a 22-year period in southern China[J][END_REF] .

Chen et al investigated changes of carbon stocks in Cunninghamia lanceolata plantations converted from a natural broadleaved forest, based on a typical chronosequence in mountain land of subtropical China, which includes six first-generation Chinese fir stands at different development stages. It was concluded that over-mature tree plantations had a limited role in continuously sequestering carbon, and that the soil organic pools of tree plantations can be hardly recovered to those of natural forests due to a large initial loss and a low late gain in soil organic carbon following tree plantation establishment. [START_REF] Chen | Carbon storage in a chronosequence of Chinese fir plantations in southern China[END_REF] The research on management of timber forest is of more significance to this study. In Wang et al's study, field data were combined with the forest ecosystem management model FORECAST to estimate the impacts of different forest management strategies, that is, the choice of different combinations of planting densities, rotation lengths, and different harvesting intensities, on carbon sequestration of Phoebe bournei plantations in south-eastern China [START_REF] Wang | Evaluation of the effects of forest management strategies on carbon sequestration in evergreen broad-leaved (Phoebe bournei ) plantation forests using FORECAST ecosystem model[END_REF] .

From Noormets et al's study, it is amazing to find that managed forests generate about 50% lower carbon stocks than unmanaged forests. It was found the same with the gross primary productivity (GPP) and total net primary productivity (NPP), but relatively more of the assimilated carbon is allocated to aboveground pools in managed than in unmanaged forests, whereas allocation to fine roots and rhizosymbionts is lower. [START_REF] Noormets | Effects of forest management on productivity and carbon sequestration: A review and hypothesis[END_REF] Therefore, a good management strategy should be able to balance the benefits of timber sales and carbon sequestration for the long-term sustainability.

Materials and Methods

The Hartman model was proposed by Richard Hartman in the middle of the 1970s. He introduced the amenity service function of forests to the Fautsmann model so as to combine the assessment of economic income with the ecological income of forests. The Hartman Model is an objective function equation taking a rotation period as the variable rendering a rotation age at which the integrated income can be maximized. [9][10] where,

T = rotation age R = discount rate C = regeneration cost p(T) = stumpage price at age T (Yuan/m 3 )
V(T) = growing stock of timber at age T (m 3 /mu) p(T) V(T) = the economic income of timber

f(t) =

function of amenity or ecological income

By calculating land expected values (LEV) at different rotation ages, a maximized expected value can be reached. In the meantime, the rotation age when LEV can be maximized can be found. This is helpful for reaching the reasonable management strategy.

Including the income of carbon sequestration in the Hartman model, the model looks like: [START_REF] Amacher | Economics of Forest Resources[END_REF] Where, Following that, the carbon sequestration reserves can be calculated according to the total biomass volume. Usually the calculation is based on the proportion of carbon storage in the dry weight of plant organics. The international practice is to adopt the rate of 0.50, thus total carbon sequestration reserves = total biomass*0.5. [START_REF] Xu | The estimating technology of forest biomass and carbon storage based on RS information(in Chinese)[END_REF] The monetary income of carbon sequestration then can be calculated finally. According to the first transaction practice of farmers' carbon sequestration exchange in China in 2014, 42 farmers Thus in this study, the price of forest carbon sequestration was set as 30 yuan/ton. [12] And in this paper, the parameter d was set to 1.

C
0 1 1 max ( ) ( ) ( ) ( ) 1 T rt rT rT t TT LEV T C f t e dt p T V T e e              rT d t rt c rT rT T t rt c T e e t q T V p e e T V T P e t g p C T LEV                1 ) ( ) ( ) ( ) ( ) ( ) (
The economic parameters have been reached by visiting farmers and markets in the general plantation regions in Fujian.

i.

According to the investigations on the forest land and mountain land in general regions, the land rent of the medium level is selected, that is, the opportunity cost of land use is 122.45 yuan/mu/year. In other words, the farmer would have a rental income of 122.45 yuan/mu/year if he or she let this land out to others.

ii. Renminbi benchmark interest rates of loans by the financial institutions in China are as follows.

Annual rate % Considering the assumption of continuous operation and land management, where farmers contract the land and land use rights and may extend the contract after the expiration of the original contract, so this study adopted mid/long-term interest rates of 5.40% as the expected rate of return.

Item

iii.

The initial plantation density is found at This study used the natural growth process table based on the status index 16 to reach the Chinese fir artificial timber forest tree volume, which laid the foundation for further calculation of the commercial timber income and carbon sequestration income. [START_REF] He | Study on natural growth model of Chinese fir plantation in ordinary growing area of Fujian (in Chinese)[J][END_REF] viii.

To convert the tree volume of Cunninghamia lanceolata to the general biomass of forests, this study adopted the following function: [START_REF] Wen | The tentative trial of using tree volume to estimate forest biomass[END_REF] B=12.82556+0.4621618V

Where, B represents the general biomass, V represents the tree volume

Findings and analysis

Using the Hartman model, both the expected timber income and expected carbon sequestration of the general plantation regions of Cunninghamia lanceolata timber forests in Fujian at three different levels of plantation density were found respectively. And more importantly, the highest land expected values of the Cunninghamia lanceolata timber forests and the corresponding ages to reach the land expected values were found at the same time.

From Table 1, at the plantation density of 133 plants/mu, the highest land expected value including the expected value of both timber income and carbon sequestration income can be reached at the forest age of 20 at 3,020.13 yuan/mu. It was also found that the highest expected value of timber income would be reached in the same year as the land expected value at year 20. At year 20, the expected value of the timber income is 2,262.63 yuan/mu, and expected value of the accumulated carbon sequestration of 757.50 yuan/mu.

Fig. 1. Comparison of Land Expected Values at different plantation density levels 5 Conclusion

Using Hartman model to calculate and forecast the land expected value of the Cunninghamia lanceolata timber forests is effective and important in identifying the ecological income of the forest operations. By doing this, the age of forests when the different levels of timber income and carbon sequestration income can be realized will be able to be found too. All the above proves the validity and usefulness of the Hartman model as the tool of the Cunninghamia lanceolata timber forests' income prediction.

This evaluation model will be integrated in the decision support system to assist farmers' operating decision making. Based on the evaluation and forecast results, the farmers are able to have an estimate of their future income under different operation schemes, that is, at different plantation densities and the arrangement of rotation, etc. And this is exactly the purpose of this study, that is, to apply this evaluation and forecast module in the decision support system so as to find a practical tool for the farmers to assist their decision making.

To conclude, China is expecting a complete national carbon sequestration exchange system, including the market system and the carbon emission quota allocation system, etc. Both theoretically and practically, carbon sequestration income is an important component of the integrated income of farmers of Cunninghamia lanceolata timber forests. It is important to educate the farmers to know about the ecological and economic value of carbon sequestration, -1872.17

  = regeneration cost (Yuan/mu) p(T) = stumpage price at age T (Yuan/m 3 ) p c = social benefits of carbon sequestration (Yuan/m 3 ) r = discount rate V(T) = growing stock of timber at age T (m 3 /mu)g(t)= timber growth at age t (m 3 /mu/year) q(t) = rate of decay of harvested timber at time t (%) d = time period during which the harvested timber completely decays Before reaching the yield of carbon sequestration, the general biomass of forests should be calculated based on the volume of timber.

  285 tons of carbon sequestration for the monetary income of 128,550 yuan in total.

  , to know well how to improve this part of income with the aid of related techniques.

  3 levels based on the practice of the general regions of plantation in Fujian, 133 plants/mu at the lowest level, 267 plants/mu at the medium level and 400 plants/mu at the highest level. They established the natural growth model and the natural growth process table of Chinese fir timber forest in Fujian general plantation regions.

	iv.	Afforestation cost: Seedling cost of 0.20 yuan/plant (20-50 CM of height, 0.3 CM of
		ground diameter); soil preparation, plantation, machinery and utility costs of 380
		yuan/mu; Total afforestation costs at 3 levels of initial plantation desinty are 406.60
		yuan/mu, 433.40 yuan/mu and 460 yuan/mu.
	v.	Cost of forest culture and management: nurture and protection cost 40 yuan/mu/year
		averagely during the different stages of growth of the timber forest; cost of fertilization
		and pest control is 100 yuan/mu/year averagely.
	vi.	Commercial timber price of Cunninghamia lanceolata is 900 yuan/m 3
	vii.	Trees growth model and the natural growth process table

This study adopted the tree growth model and table of volume given by Zongming He et al, where were based on the large amounts of data and information of 665 fixed and temporary HWWCCSC standard plantation plots of the general regions of Cunninghamia lanceolata in Fujian province.

Table 1 . Land Expected Value (LEV) of Cunninghamia lanceolata in general plantation regions of Fujian at the density of 133 plants/mu

 1 From Table2, at the plantation density of 267 plants/mu, the highest land expected value including the expected value of both timber income and carbon sequestration income can be reached at the forest age of 15 at 4,373.85 yuan/mu, different from that at the density level of 133 plants/mu. The highest expected value of timber income would be reached, again, in the same year as the land expected value at this density level. And at year 15, the expected value of the timber income is 3,859.08 yuan/mu, and expected value of the accumulated carbon sequestration of 514.77 yuan/mu.

	Age (year)	Tree volume (m 3 /mu)	NPV of accumulated annual cost (yuan/mu)	NPV of accumulated carbon sequestrati on(yuan/mu)	NPV of timber income (yuan/mu)	EV of timber income (yuan/mu)	EV of (yuan/mu) accumulated carbon sequestration	LEV (yuan/mu)	Discounting factor
	5	0.728000	1119.25	150.71	-1025.68	-4334.71	95.26	-4239.45	0.763379
	10	4.516667	1973.66	278.13	-11.39	-27.29	400.88	373.59	0.582748
	15	10.275333	2625.90	381.47	1081.46	1948.08	507.51	2455.59	0.444858
	20	16.440000	3123.81	588.74	1494.25	2262.63	757.50	3020.13	0.339596
	25	22.054667	3503.90	752.04	1235.21	1667.50	912.47	2579.96	0.259240
	30	26.805333	3794.05	1003.89	573.61	715.14	1172.22	1887.36	0.197899
	35	30.735333	4015.55	1200.38	-243.23	-286.52	1352.63	1066.12	0.151072

Table 2 . Land Expected Value (LEV) of Cunninghamia lanceolata in general plantation regions of Fujian at the density of 267 plants/mu

 2

	Age (year)	Tree volume (m 3 /mu)	NPV of accumulated annual cost (yuan/mu)	NPV of accumulated carbon sequestrati on(yuan/mu)	NPV of timber income (yuan/mu)	EV of timber income (yuan/mu)	EV of (yuan/mu) accumulated carbon sequestration	LEV (yuan/mu)	Discounting factor
	5	1.227333	1119.25	153.36	-709.42	-2998.13	96.93	-2901.20	0.763379
	10	6.769333	1973.66	287.86	1143.28	2740.01	405.64	3145.66	0.582748
	15	12.992000	2625.90	392.63	2142.34	3859.08	514.77	4373.85	0.444858
	20	18.244667	3123.81	604.83	2019.02	3057.25	776.40	3833.65	0.339596
	25	22.392667	3503.90	766.93	1287.27	1737.78	931.87	2669.65	0.259240
	30	25.606667	3794.05	1021.61	333.32	415.56	1196.05	1611.61	0.197899
	35	28.094667	4015.55	1215.38	-629.07	-741.02	1373.08	632.06	0.151072
		From

Table 3 ,

 3 at the plantation density of 400 plants/mu, the highest land expected value including the expected value of both timber income and carbon sequestration income can be reached at the forest age of 15 at 4,402.07 yuan/mu. Again, the highest expected value of timber income is reached in the same year as the land expected value. And at year 15, the expected value of the timber income is 3,885.21 yuan/mu, and expected value of the accumulated carbon sequestration of 516.87 yuan/mu.

Table3. Land Expected Value (LEV) of Cunninghamia lanceolata in general plantation regions of Fujian at the density of 400 plants/mu

  Figure1shows the different levels of land expected values of the timber forests at different ages and different density levels. As shown in Chart 1, it is obvious that the highest land expected value is generated at the plantation density level of 400 plants/mu. Again the highest expected value of timber income and carbon sequestration income can be found with the plantation density of 400 plants/mu.

	Age (year)	Tree volume (m 3 /mu)	NPV of accumulated annual cost (yuan/mu)	NPV of accumulate carbon sequestration (yuan/mu)	NPV of timber income (yuan/mu)	EV of timber income (yuan/mu)	EV of (yuan/mu) accumulate carbon sequestration	LEV (yuan/m u)	Discounting factor
	5	1.620000	1119.25	155.43	-466.24	-1970.42	98.24	-1872.17	0.763379
	10	7.420667	1973.66	290.98	1458.28	3494.97	407.77	3902.74	0.582748
	15 13.094667	2625.90	394.06	2156.84	3885.21	516.87	4402.07	0.444858
	20 17.748000	3123.81	605.89	1840.62	2787.11	779.52	3566.63	0.339596
	25 21.333333	3503.90	765.29	1013.51	1368.21	931.84	2300.05	0.259240

Acknowledgements.

This work was supported by National Natural Science Funds of China: Research on the Management Scheme Optimization Decision Model of Cunninghamia Lanceolata Timber Forest under grant [No. 31170513].


Jiye Zheng
email: ajiyezheng@163.com

Fengyun Wang

Lei Wang

Research and Design of Wireless Sensor Middleware Based on STM32

Keywords: STM32, wireless sensor, Middleware, ZigBee

In order to make agricultural production become more convenient,also meet the requirement of the modern intelligentagriculture to make control equipment integrated and miniaturization , the paper designed a wireless sensor middleware based on STM32. This wirelessgateway receives control command from the control software of agricultural IOT application which installed in the tablet computer through the WiFi/USARTmodule,after the data processing and protocol conversion,then send the control signal to the wireless sensor network through the USART port. At thesame time,if a particular model of agricultural sensor changes state,it also can timely feedback to the tablet computer to display through thegateway. This plan solved the problem of real-time monitoring of agricultural information and realized remote control. Theexperimental results show that,the wireless sensor middleware has the characteristics of light and handy,high control precision,data large quantityand high speed. It's very appropriate for intelligent agriculturalsystem application.

Introduction

With the rapid development of Internet of things, IOT middleware becomes one of the important research topics in related fields in recent years, also acquired a lot of research results, mainly divided into application service middleware, embedded middleware. Such as White [START_REF] White | Web logic event server: a light-weight, modular application server for event processing[C][END_REF] put forward a kind of typical middleware based on J2EE architecture, has a good scalability.paper [START_REF] Huang Etc | Wireless sensor network based on mobile Agent middleware[END_REF] proposed wireless sensor network middleware based on mobile Agent, the middleware has data management, integration, application target adaptive control strategy, Wang fan design and implemented an IOT middleware, that can filter the heterogeneous network data, integrate ZIGBEE and RFID (Radio Frequency Identification, RFID) data into a unified format [START_REF] Wang Fan | Design and implementation of Internet of things middleware based on ZIGBEE and RFID[END_REF]. Paper [START_REF] Yihua | The design and implementation of embedded RFID middleware[END_REF][START_REF] Bonnet | Towards sensor database systems[END_REF][START_REF] S R Madden | Tiny DB: An acquisitional query processing system for sensor networks[END_REF][START_REF] Srisat Hapornphat | Sensor information networking architecture[END_REF] proposed database based middleware, it views the entire network as a distributed database, users use similar to SQL query command to get the data needed, query is distributed to each node through the network, the nodes determine whether the sensory data satisfy the query conditions, and decide to send data or not.Deng Yihua etc. Put forward embedded RFID middleware on smart RFID read-write device [START_REF] Makoto | A sensor middleware for lightweight relocatable sensing programs[END_REF], it can realize the management of multiple read/write devices, strengthen the deployment flexibility.The domestic scholars make use of the gateway hardware to research IOT system [START_REF] Makoto | A sensor middleware for lightweight relocatable sensing programs[END_REF][START_REF] Pk Biswas | A mobile-agent-based collaborative framework for sensor network applications[END_REF][START_REF] Sharifi | A middleware layer mechanism for QoS support in wireless sensor networks[END_REF][START_REF] Heinzelman | Middleware to support sensor network applications[END_REF], however, the research and design of STM32 based wireless sensor network middleware is still relatively rare.

The research combines the ZigBee wireless sensor network with the STM32 MCU, it has the advantages of simple structure, strong generalization ability and others. The objective of this study is to develop aneasy method to implement the remote monitoring and control system for the agricultural production environment.

2Wireless gateway hardware platform design

Wireless gateway is the data transfer station of the Agro-IOT control system and communication media, it is critical to the whole system design. The main frame of the hardware platform is shown as figure 1.

Fig. 1.Wireless gateway overall architecture diagram

The hardware involved in this paper include wireless sensor nodes and gateway hardware, hardware design is introduced as follows. CC2530F32/64/128/256 separately with 32/64/128/256KB in-system programmable flash memory.

wireless sensor nodes

The microcontroller has 8KB RAM with data remaining capacity under various power supply. CC2530 has various operating modes such as active mode RX (CPU idle), active mode TX 1dBm (CPU idle), power supply mode 1 (4us awake), power supply mode 2 (sleep timer), power supply mode 3 (external interruption), wide voltage range of power supply and so on which makes the energy consumption very low.

The wireless transceiver adopts zigbee technology. It has low power consumption, rapid response and large network capacity etc features.Figure 2 shows thewireless sensor nodes used in the system. According to the function, node types can be divided into three categories, namely the acquisition node (only responsible for data collection), routing nodes (responsible for data gathering and routing), and the coordinator node (network management). All kinds of nodes on the hardware adopts the above design, the coordinator needs a binding to the gateway via the serial port.

ZigBeeRouter

gateway hardware

Gateway is the key module of this system, it needs to bind with the coordinator, the gateway Circuit

Diagram is shown in figure 3.

Wireless gateway software platform design

Wireless sensor network middleware software platform are actually established on the embedded development board wildfire STM32 ISO with transplantationof Linux system, and then Boa Web server, database Sqlite3 was also set up in the Linux system.

The main task of the wireless sensor network gateway is as follows: access to information of each node in the wireless sensor network, processing a request from the Internet, the wireless sensor network configuration management, and data statistics and analysis, etc. The main task of wireless sensor network is tomonitoring the state of the remote device. Literature [START_REF] Pedro | TinyCubus: A flexible and adaptive framework for sensor networks[END_REF] presents a so-called Cougar middleware system, Cougar views wireless sensor network as the distributed database and the network nodes are divided into clusters, cluster is a collection of multiple nodes, elects a node in the cluster as the cluster head.Paper [13] proposed a flexible wireless sensor network middleware system. The system using Web Service technology and middleware technology, the system views the wireless sensor network as middleware system, each node uses a different SOAP Engine, the coordinator node has a registration module, other sensor nodes have different event handlers, the user can use any SOAP proxy access coordinator node via TCP/IP protocol, and further access to the entire wireless sensor network.

In order to manage the wireless sensor network better and expand Internet connections to the wireless sensor network, through careful analysis of the wireless sensor network monitoring program, and combined with hardware gateway, this paper abstracts a new middleware model as shown in figure 4. Web server provides HTTP service to external applications, and internally access to interpreter by CGI;

Boa

CGI call CGI return

The interpreter responses to explain users command, and give orders to the cluster model control layer and accept its response; Model control layer abstracts the clusters for the wireless sensor network, and provides the control interface; Sensor network coordinator interface provides an interface for gateway to read and write in wireless sensor network , the actual implementation is divided into the gateway and the coordinator two part,the coordinator and the sensor nodes' communication uses data collection protocol.

Result and Discussion

Wireless Sensor Middleware was used in livestock and poultry breeding, agricultural facilities accurate monitoring, Edible fungus production information collection and similar applications, the coordinator node on the packet is bound to the embedded gateway. Using TCP/IP protocol stack, the communication between monitoring instrument and upper computer was realized. The real time information on the upper computer is like figure 5.

Conclusions

The research analyzed the IOT middleware research status, and combining the wireless sensor network practice, proposed the Wireless Sensor Middleware Based on STM32. The software has two characteristics include embedded server and application services, it adopted the idea of components, reduced the coupling between modules, the configurable and customizable functionality improved reusability, lower development costs, solve the problems of mass data processing, and provide the visual configuration monitoring platform, the realization of Internet of things "content" of the administration and monitoring, eliminate information isolated island. This middleware application was used in Edible fungus production information collection system, and the results show that the feasibility and effectiveness of the above frameworks and methods.

  CC2530 on-chip system is used for the wireless sensor nodes with very low cost and ultralow power consumption.It integrates the microprocessor module and a wireless transceiver module in one single chip. It has the excellent performance of RF transceiver adapting to IEEE 802.15.4 with extra high reception sensitivity and anti-interference. Its core is industry-standard enhanced 8051 microcontroller unit with code prefetching function. CC2530 has four different types of flash memory version i.e.

Fig. 2 .

 2 Fig. 2.Wireless sensor node hardware structure diagram

Fig. 3 .

 3 Fig. 3.Gateway Circuit Diagram Gateway hardware uses STM32F103ZET which core is ARM Cortex-M3. F1-series is the first generation microcontrollers of STM32 that is considered as its mainstream of ARM MCU. With the development of technology, F1 series has many improvements such as CPU speed, size of internal memory and type of peripherals. The excellent peripherals and low-power, low-voltage operation make it with high performance. It is highly integrated with the simple structure and easily used tools which cost is very low. STM32 is control core of the wireless gateway, it mainly divides into five modules, include WiFi module, RF module, a central controller module, power module, JTAG emulation debugging module respectively.

Fig. 4 .

 4 Fig. 4.Wireless sensor network middleware structure model Middleware structure model has many modules include Cluster model controller, Command interpreter, Boa server, database controller and Sensor network coordination interface and so on.

Fig. 5 .

 5 Fig. 5.Real time data from the remote sensors

Acknowledgment

Funds for this research was provided by the National Science and Technology Support Program (2014BAD08B05-02), Shandong Academy of Agricultural Sciences(SAAS) Youth Scientific Research Funds Project (2015YQN58), Independent Innovation Projects of Shandong Province(2014ZZCX07104).


Minjuan Liu
email: liuminjuan@caas.cn

Lu Chen

Xue Yuan
email: cyuanxue@caas.cn

Ting Wang
email: dwangting@caas.cn

Yun Yan
email: eyanyun@caas.cn

Yuefei Wang
email: fwangyuefei@caas.cn

The knowledge structure and core journals analysis of crop science based on mapping knowledge domains

Keywords: :international Journals, crop science, journal co-citation analysis, mapping knowledge domains 1

This paper aims at revealing the potential structure of crop science and core journals distribution to provide reference and help for crop research and journal work. On the basis of journal co-citation analysis this paper draws the co-citation map of Crop Science Journal by means of mapping knowledge domains and information visualization technology. 86 crop science journals can be roughly divided into two groups and each group of journals can be subdivided into two regions. Plant science (including plant physiology, plant ecology, plant cell etc.) and biology and chemistry (including biochemistry and molecular biology, gene and genetics etc.) are the mainstream research field of crop science. Crop production and soil science is another important branch of crop science. In addition, there is the phenomenon of cross integration between crop science and environment, horticultural science, plant protection, food processing, animal husbandry etc.

Introduction

Crop Science is one of the core disciplines of agricultural science, the theory and technology of which plays an important role in agriculture and rural economic development as an important support. In the 21st century, the situation of international Crop Science and technology had a huge change, which is penetrated continually by the bio-technology and information technology . The combination of high-tech and traditional technology promote the rapid development of crop science and technology [START_REF] Wan | The development direction of crop science "11th five-year plan[END_REF] . The rapidly change of technological development brings crop science with opportunities and challenges. If grasp the subject development dynamics, we can get opportunities in the fierce competition. Scientific researchers always want to publish the new results and findings as soon as possible to achieve the occupation of frontier research in this field, attention of academia and peer recognition and so on. Therefore, knowledge of paper, to some extent, represents the latest research level when scientific papers published in the literature. Especially in those influential journals, many outstanding scientists of the world publish high-level scientific papers. Therefore, an core journal is not only an important media to disseminate research results, but also through the periodical analysis, it can help researchers to quickly understand the current research and grasp the latest trends. Journals without external links can be organically linked by Journal co-citation analysis, which can reveal the relationship of interdependence and cross between journals, determine the professional scope, and help to identify core journals. The combination of Journal co-citation analysis and mapping knowledge domains can show up potential subject structure and power distribution of a field in a visually intuitive graph. The journals with a closer relationship concentrate together to form a different cluster result of different research directions and fields, which vividly depict the subject structure and core journals of the field [START_REF] Zhao | The Knowledge Mapping Analysis on the Research of Biohydrogen[END_REF] . Journal co-citation analysis started to develop on the basis of literature co-citation analysis. The concept of " literature Co-citation " was put forward in 1973 by the American intelligence scientist Henry Small [START_REF] Small | Co-citation in the scientific literature: A new measure of the relationship between two documents [J][END_REF] , after their studies were the first to carry out in 1974, extensive cocitation analysis followed up. In the later co-citation analysis, most of the research is literature co-citation analysis and author co-citation analysis represented by Small and White [START_REF] Small | Clustering the science citation index using co-citations Ⅱ: mapping science[END_REF][START_REF] Small | Multiple citation patterns in scientific literature: the circle and hill models[END_REF][START_REF] Small | The relationship of information science to the social science: A co-citation analysis[END_REF][6][START_REF] White | A co-citation map of the social indicators movement[END_REF][START_REF] White | Authors as markers of intellectual spaces: Co-citation in studies of science, technology and society [J][END_REF][START_REF] Miyomato | A technique of two-stage clustering applied to environment and civil engineering and related methods of citation analysis[END_REF] . There were a lot of co-citation analysis and empirical research at home and abroad, but journal co-citation analysis and empirical research is not too much. For example, in 1991, McCain used journal co-citation analysis for practice to analyze the economics scholarly journals [START_REF] Mccain | Mapping economics through the journal literature: An experiment in journal co-citation analysis[END_REF] ; in 2000, Ding, Y use journal co-citation analysis and visualization to study the development process of Intelligence retrieves during 1987--1997 [START_REF] Ding | Journal as markers of intellectual space: Journal cocitation analysis of information Retrieval area,1987-1997[END_REF] ; in 2003, Tsay, MY visualized of the semiconductor areas with journal cocitation analysis [START_REF] Tsay | Journal co-citation analysis of semiconductor literature[END_REF] ; in 2004, Liu Zao studied the literature of urban planning and visualized document structure with journal co-citation analysis [START_REF] Liu | Visualizing the intellectual structure in urban studies: A journal co-citation analysis (1992 -2002[END_REF] ; in 2005, Marshakova Shaikevich, I. used journal co-citation analysis and visualization in the subject of women's studies and library and information science, and pointed out the distribution of its subject areas [START_REF] Marshakova-Shaikevich | Bibliometric maps of field of science[END_REF] ; in China, in 2006, Hou H.Y. used co-citation analysis and draw the science map of international metrology core journals [START_REF] Hou | International Measurement Science core journals and knowledge map[J][END_REF] ;in 2008, Qiu J. P., Zhao W. H. used co-citation cluster analysis and core-periphery model to mainly analyze the 21 editing and publishing journals and determine the core journals of the discipline [START_REF] Qiu | A Metric Demonstration of Journal Co-citation[END_REF] ;in 2009, Zhao Y. respectively used journal co-citation analysis and draw knowledge maps of Library and Information Science and biological hydrogen production [START_REF] Zhao | International Biohydrogen Key Periodical co-citation analysis and mapping knowledge[END_REF][START_REF] Zhao | The Knowledge Mapping Analysis on the Research of Biohydrogen[END_REF][START_REF] Zhao | Visualizing a Discipline:Journal Co-citation Analysis of Library and Information Science[END_REF] ; in 2009, Qin C. J. draw the knowledge map of the relationship between agricultural history of China and neighboring discipline based on journal co-citation analysis [START_REF] Qin | The Empirical Research of the Knowledge Domains Map Between Subject Relationship Based on Journal Co-citation Analysis Method [J[END_REF] , in 2010, Liang Y. X. et al. used journal co-citation analysis method to learn the status of citation analysis discipline [START_REF] Liang | Citation disciplinary status analytics[END_REF] . Although there is relatively little research on journal co-citation analysis, but it is not only an effective way to research subjects and the structure and characteristics of literature, but also has its unique in the study of the overall discipline structure and the nature and characteristics of professional journals [START_REF] Zhao | Journal co-citation analysis: a method of research discipline and the structure and characteristic of journals[END_REF] . However, in the previous studies, there were more empirical research on the library and information science, and lacked application and validation in other fields, especially in the agricultural area; Also, the selecting target journals of co-citation analysis more dependent on existing database journals category or used the way of the keywords retrieval, so it can not be used in the field whose journals classification are not covered in database or can not use keywords retrieval. In this paper, it delineates the core journals gradually spreading from a single female parent journal based on citation analysis, in order to try to expand the applied disciplines of journal co-citation analysis, use visualization techniques to draw crop science map on the basis of the journal co-citation analysis of crop science journals. On the one hand, it can help researchers to understand Crop science knowledge structure and research focus. On the other hand, it can help researchers to know the characteristics of the journals and give reference for selecting the appropriate journal to submit the article.

Data source and methods

The research data are all from the Science Citation Index Expanded database of Thomson Scientific, The last update time is May 2013. This study uses the journal co-citation analysis methods to reveal the interdependence cross relationship between journals, what's more, with the emerging international method of mapping knowledge domain and information visualization technology, drawing the journal co-citation map of crop science to vividly reveal the structure of the crop science core journals groups. The mainly methods include factor analysis, cluster analysis and multidimensional scaling, which the factor analysis by principal components analysis and varimax orthogonal rotation, cluster analysis by Hierarchical Clustering and Multidimensional Scaling by ALSCAL. The research combined two analytical approaches, which are bibexcel and SPSS for obtaining visualizing information of crop science. Analysis steps: First, selecting CROP SCIENCE as the female parent, which is the most important journal in the field of the crop science, by the method of single co-citation analysis, there are 2008 papers with 78121 citations in CROP SCIENCE from 2008 to May 2013 were analyzed and evaluated. Second, selecting the journals which are higher cited by Crop Science for further cocitation analysis, there are 5819 papers with 240823 citations in these journals from 2008 to May 2013, then 98 journals which the cited frequency over 300 times among these journals are chosen to do a further analysis. Last, cleaning the data of 98 journals, and finally choosing 86 journals to do the cocitation analysis, which are much more important journals in the field of crop science.

To establish co-citation matrix with the data of 86 journals by Bibexcel, then use the matrix do some factor analysis, cluster analysis and Multidimensional Scaling by SPSS to draw the journal co-citation map of Crop Science with 86 journals, which can vividly reveal the relationship between journals and disciplinary structure of Crop Science.

3

Results and Discussion

Parental journal and citation analysis

The parental journal "CROP SCIENCE" which was founded in 1997, the impact factor is

2) Factor analysis

On the basis of the Multidimensional Scaling, this study combined factor analysis and cluster analysis to supplement and improve the multidimensional scaling. This study did a principal components analysis on the Pearson correlation matrix of 86 journals by SPSS , It extract three main components factors and cumulative variance reached 86.709%, which means three components factors have been able to explain the information contained in all variables well. TABLE 3 make a list of variables (journals) which factor loading is over 0.7.

3) Cluster analysis

Meanwhile, this study did a cluster analysis on these 86 journals to further examine the similarity between the journals to supplement multidimensional scaling. Similar to factor analysis, the study choose Hierarchical Clustering to analysis the Pearson correlation matrix of 86 journals by SPSS. Figure 2 shows the result of cluster analysis. It's obviously to see that these 86 journals is better to classified into two clusters.

Fig.2. Hierarchical clustering tree diagram of 86 journals

4) Multidimensional scaling analysis

In order to reveal the affinities between journals and further determine the discipline structure of journals in crop areas, we carried multidimensional scaling analysis by putting the journal similarity matrix into SPSS, which can display the relationship between the original high-dimensional data in low-dimensional space. As the picture 3, each dot represents a journal, and the location of periodicals show similarity (common disciplines or methods, etc.) between journals. The more similar the more Cluster 2

Cluster 1 together, and then form a knowledge group. In the knowledge group, the journal which has the closest relation with other point is in the middle of the journal position map, which shows that it is the core of knowledge group; the other hand, more in the periphery.

On the basis of the results of the factor analysis and cluster analysis, we draw the cocitation multidimensional scaling analysis diagram of 86 journals, shown in Figure 3.

Conclusions

According to the result of Journal Citation analysis and co-citation mapping knowledge, we can see that the international crop science research can be divided into two parts in recent years. The first part focus on plants (crops) own research (Journal Group 2), including plant physiology, plant ecology, plant cells, etc. and biochemistry and molecular biology, gene and genetics, etc., which is mainstream areas and more concerned by crop science researchers now. Another part is more concerned about the between plants (crops), soil, resources and environment, including crop production, soil science and environment science, which is another important branch of crop science. In addition, some journals of resource and environment, horticulture, crop protection, food processing, animal husbandry are found to be highly cited by crop science journals, which proves that interdisciplinary integration between crop science and other subjects, and the journals from these areas have become the journals concerned by crop researchers. Overall, the journal co-citation analysis is an effective method for revealing core journals of disciplines. Journals co-citation analysis can reveal the structure of discipline by the way of cited journals co-citation analysis, which is from the perspective of the journal analysis. Thus, through the journal position in the different disciplines, we can judge core journals of different subjects to help researchers to find more useful information [START_REF] Zhao | Visualizing a Discipline:Journal Co-citation Analysis of Library and Information Science[END_REF] . Comparing with the previous research, the difference is that, it delineates the target journals group gradually spreading from a single female parent journal, namely in the way of using an important journal of crop science based on citation analysis to gradually delineate the subject core journals. From the result of International crop science related Journals co-citation analysis, it is satisfactory that it can reflect objectively the crop science underlying structure and core journals distribution by the journal co-citation analysis combined with visualization techniques. It is successful that the applied discipline is expanded. However, when using the journal co-citation analysis, it must pay more attention on data collection and processing methods and process control, or it will have a direct impact on the accuracy of the analysis results. I believe that there are two aspects need to be taken seriously. One is periodical cleaning, which is necessary because the journals abbreviated titles may be not unified and some journal title may change, so inattention could cause distortion of data and affect the final results. The other one is the choice of the study object, factor analysis, clustering and multidimensional scaling method and the error of statistical analysis, which will affect the results objectivity, so it must carefully plan in order to ensure effective and objective analysis of the results. In the future studies, we will continue to combine journal published papers and the integration of new technologies and analysis methods to explore more accurate and reliable methods of revealing potential knowledge structure and core journal distribution in different fields.

3. 2 1 )Fig. 1 .

 211 Fig.1. 86 journals co-citation matrix (parts)

Fig. 3 .

 3 Fig. 3. The co-citation map of 86 important crop science journals

Table 1 .

 1 1.513, published by the Crop Science Society of America (CSSA). The journal publishes crop genetics and breeding; crop physiology and metabolism; crop ecology, crop production and management; seed physiology, seed production and technology; lawn learning; genomics, molecular genetics and biotechnology; plant genetics resources and pest control and other aspects and original research papers. The journal is indexed in SCI belongs to Q2, covers most fields of crop science and well-known in crop science. Therefore, this study chosen "CROP SCIENCE" as the parental journal, which can be a good representation of crop science. Through citation analysis, there were 2736 journals cited by "CROP SCIENCE" ,the total citation frequency is 62950 times. In Table1, the top 7 journals which were cited by CROP SCIENCE more than 1000 times are listed. Top 7 journals cited by CROP SCIENCE CROP SCIENCE", its self-cited frequency is 11483 times and accounts for 18.24%. Therefore, this study chosen the 4 journal as the parental journal to do further co-citation analysis to identify the important journals in the field of crop science. Between 2008 and May 2013, these 4 journals has published 5819 papers with 240823 citations, there were 7113 journals cited by these 4 journals and the total cited frequency is 198362 times. Table2gives 98 journals which were cited more than 300. It's necessary to clean the data of 98 journals, merge the same journals, eliminate the review journals and the journal that was not indexed in SCI, eventually retained 86 journals to do co-citation analysis.

	Rank	Cited frequency	Cited journal
	1	11483	CROP SCI
	2	3905	THEOR APPL GENET
	3	2576	AGRONOMY JOURNAL
	4	1658	EUPHYTICA
	5	1484	GENETICS
	6	1304	PLANT PHYSIOL
	7	1168	FIELD CROP RES
	"CROP SCIENCE", "THE THEORETICAL AND APPLIED GENETICS", "THE
	AGRONOMY JOURNAL " and " EUPHYTICA " are cited by "CROP SCIENCE"
	more than 1500 times , the total cited frequency can reach 19622, accounting for
	31.17% of all journal, and "

Table 2 .

 2 98 journals cited more than 300 by 4 parental journals

			Cited				Cited
	Rank	Cited journal	frequency	Journal ID Rank	Cited journal	frequency	Journal ID
	1	CROP SCI	19947	a25	50	GENOME RES	588	a35
	2	THEOR APPL GENET	18898	a94	51	J CEREAL SCI	586	a47
	3	AGRON J	8868	a6	52	PLANT PATHOL	583	a83
	4	GENETICS	6804	a33	53	AM J BOT	573	a7
	5	EUPHYTICA	6575	a28	54	COMMUN SOIL SCI PLAN	563	a24
	6	PLANT PHYSIOL	3447	a84	55	ADV AGRON	563	a2
	7	P NATL ACAD SCI USA	3047	a70	56	ANNU REV PHYTOPATHOL	558	a11
	8	GENOME	2927	a34	57	PLANT CELL ENVIRON	549	a76
	9	FIELD CROP RES	2806	a31	58	MOL ECOL	535	a61
	10	PLANT BREEDING	2443	a73	59	MOL GEN GENET	527	a62
	11	PHYTOPATHOLOGY	2414	a72	60	J ANIM SCI	523	a46
	12	PLANT DIS	2290	a79	61	J ECON ENTOMOL	522	a49
	13	MOL BREEDING	2075	a60	62	J SCI FOOD AGR	518	a56
	14	PLANT CELL	1985	a75	63	ANN APPL BIOL	506	a8
	15	SCIENCE	1860	a89	64	SOIL TILL RES	504	a92
	16	PLANT J	1821	a80	65	ACTA HORTIC	460	a1
	17	J EXP BOT	1688	a51	66	GENOMICS	456	a36
	18	SOIL SCI SOC AM J	1674	a91	67	WEED TECHNOL	454	a98
	19	Crop & Pasture Science	1594	a14	68	J PLANT NUTR	434	a53
	20	CAN J PLANT SCI	1568	a21	69	MOL BIOL EVOL	424	a59
	21	PLANT MOL BIOL	1299	a81	70	J DAIRY SCI	419	a48
	22	PLANT SOIL	1273	a86	71	BIOMETRICS	415	a18
	23	J HERED	1217	a52	72	T ASAE	409	a93
	24	NATURE	1210	a67	73	PLANT CELL PHYSIOL	401	a77

Table 3 .

 3 Variables (journals) which factor loading is over 0.7

		Rank	Journal	Factor	Rank	Journal	Factor	Rank	Journal	Factor
			ID	loading		ID	loading		ID	loading
		1	a82	.978	19	a89	.927	37	a58	.813
		2	a63	.974	20	a80	.924	38	a77	.813
		3	a35	.974	21	a75	.917	39	a68	.807
		4	a17	.973	22	a7	.917	40	a72	.806
	Factor1	5	a65	.970	23	a34	.916	41	a94	.772
		6	a69	.968	24	a70	.909	42	a23	.769
		7	a66	.965	25	a64	.908	43	a18	.769
		8	a59	.965	26	a32	.891	44	a51	.763
		9	a36	.964	27	a85	.890	45	a79	.758
		10	a19	.964	28	a78	.890	46	a83	.752
		11	a61	.947	29	a73	.881	47	a87	.748
		12	a39	.947	30	a33	.871	48	a25	.747
		13	a52	.944	31	a27	.864	49	a49	.746
		14	a67	.941	32	a84	.851	50	a30	.728
		15	a10	.940	33	a28	.843	51	a40	.724
		16	a38	.937	34	a45	.833	52	a9	.703
		17	a81	.936	35	a41	.815	53	a14	.700
		18	a60	.930	36	a47	.814

  The value of stress is 0.03653 and RSQ is 0.99662, so it reflects a very good fitting degree. The 86 journals are clearly divided into two parts, group 1 includes 26 journals, and group 2 includes 60 journals. The group 1 can be divided into two parts. A1 has the most journals, which mainly includes the journals of crop production, soil science, agricultural resources and the environment and other related areas. The AGRON J, SOIL SCI SOC AM J, PLANT SOIL and some journals are the representations of this area, reflecting the inseparable relationship between crops and soil, water and environment. A2 area includes several agricultural comprehensive journals, and FIELD CROP RES is typical representation, which focus on crop production and cultivation, and become the connection of Journal group 1 and group 2. The Group 2 can also be subdivided into two areas. B1 contains many journals which have tight connection and short distance from the origin, and some journals highly cited by the parental journal focused on here, which proves that this area is a core area concentrating crop science journals, covering the most important branches of Crop Science. It mainly includes the journals of crop genetics and breeding, plant science, biochemistry and molecular biology, gene and genetics, which attract more attention of crop science researchers and is the most core journals. The journal of CROP SCI,

	THEOR APPL GENET, GENETICS, EUPHYTICA, PLANT BREEDING,
	GENOME, P NATL ACAD SCI USA, PLANT PHYSIOL, PHYTOPATHOLOGY,
	PLANT DIS and other journals are the representation. From the view of position ,B2
	likes the bridge of journals group 2 and group 1, which has more closely relation with
	A2, including the journals more closer to A2 which has Crop & Pasture Science as a
	representative of agriculture comprehensive journals, also including the journals of
	ANN BOT-LONDON and HORTSCIENCE as a representative of botany and
	horticulture.

Acknowledgment

Funds for this research was provided by the Chinese Academy of Agricultural Sciences Science and Technology Innovation Projects (CAAS-ASTIP-2015-AII).


Liping Zhang
email: zhangliping@caas.cn

The Countermeasures of carrying on Web of the Research Institutions in the era of big data ---Consider the web of Chinese Academy of Agricultural Sciences

Keywords: Big data, Website construction, data resources 1

In recent years, large data caused great concern in industry, academia and government. As an important department for scientific research and innovation, the academy portal show the level of science research innovation ability and it is a main platform of transformation of scientific research achievement. In this paper, the construction portal of Chinese Academy of Agricultural Sciences Situation as the background, points out the shortcomings of the current construction site, and make a few suggestions for website development in the big data environment.

 [START_REF] Mayer-Schonberger | Zhejiang: Zhejiang people[END_REF]information of scientific research conditions, management and scientific research output and enhance capacity for the scientific data and resources acquisition, protection and utilization. The acquisition and utilization of scientific research data will be an importment work in the future. At the same time, the planning points out the problems in the construction of data.

current situation and problems

CAAS Web Portal included 10 functional departments websites and 41 research institutes websites ,have two major functions of department office and service research, and it is an importance display window for showing scientific research strength and service agriculture. Since it was on the line in 1997, website has played an importment role for science research and management. Now, CAAS portal has included 51 institutes secondary network. But according to statistics, total websites in CAAS has arrived 236. The specific site condition survey results are shown in table 1

Lowly data processing capacity

With the requirements of computing resources and storage resources continue to improve, high performance data processing platform is necessary condition to deal with data resources. The development and use of high performance computing in 80 years of the last century has already begun. National "973" and "863" programs had put on a lot of funds in research of high performance computing and it had applied many fields such as defense and security, oil exploration, weather forecasting, bioinformatics, gene and nanotechnology and other aspects. In "fifteen" period, CAS has made remarkable achievements in high-performance computing environment and had developed domestic-made supercomputer Shuguang 2000-Ⅱ and Lenovo Pentium 6800 supercomputer. But CAAS has not its own high-performance computing center and all high-performance computing demands are dependent on other societies. Since the high-performance computing research in different directions have different software and hardware requirements and highly specialized, the results computed by outside computing center cannot reach the preset requirements, and data security can't be protected. The survey in 2014 showed that more than 2/3 institutes particularly animal husbandry, biology, vegetables and flowers, have used high performance data processing, while other institutes also expressed requirement of high performance data processing.

website services model is single

In the current era of rapid development of the Internet, the ways people access information and communication are also diverse, new media such as

Suggestions of web data resources construction in the future

The planning in 2014 proposed that information technology development goals in the future will be around the overall goal of "build a world-class agricultural research institutes," and build domestic first-class agricultural research institutions in information service platform and to provide first-class information technology services for agricultural research through the integration and sharing of agricultural research data.

Improve system of data resources construction

Construction of the database is a long-term project. Ensuring the smooth development of construction of the database, we need to establish clear rules and regulations in the fund, personnel and data collection, storage and so on.

Have a realistic implementation plan and funding.

The planning in 2014 has listed a timetable implementation for specific information construction which including planning storage and computing platforms and data resources construction funds needed. Program is divided into two phases, the first five years will focus on the construction of network infrastructure, and the second year will deepen the service and data mining. The first task of a five-year plan have been identified, the specific implementation plan table 3.

Construction of the data resources needs full-time institutions and technical personnel.

We should establish academy-level information technology allied agencies and improve the information technology systems of each institute. Currently, information construction in CAAS is responsible of Agricutural Information Institute. Only two related offices includeing 25 employees are charge of network maintenance and site updates. Other information technology personnel is even more lacking. In the planning, CAAS will established a-hundred-person team of network operation and maintenance and website editors ,and set policies to improve staffing and operational system of information technology ,and regular train and assessment technical personnel. Hence we need to establish comprehensive information centralized management and to format a clear division working mechanism for each institute.

And on this basis we would explore to establish the academy co-ordination, each institute the participation, cooperation and win-win management and service models.

To improve network infrastructure construction Environment

Network infrastructure is a prerequisite to protect the data storage and computing preconditions. In order to meet the data resource construction of network infrastructure environment we should know the needs of each network. First, it is necessary to clearly know network requirement and to overall layout design network function, structure and layout. Meanwhile we should improve power system, monitoring systems, fire systems, refrigeration systems and other facilities. The Planning put forward that CAAS will be completed in the network infrastructure to meet the next decade, the development of information technology within five years(Table 4);Secondly, we should construct high-speed data transmission channels, improve network transmission environment and establish a without barriers data sharing and transmission line to link 42 institutes distributed in the 20 provinces. The establishment of advanced technology and personnel management of access control and fingerprint input facilities Surveillance system Establishment of an international advanced automatic monitoring system, electricity, air conditioning, UPS automatic monitoring Fire Fighting System

The establishment of smoke, temperature sense of alarm systems and automatic fire extinguishing equipment Cooling System

Using professional precision equipment to ensure the room temperature, humidity, fresh air status

To build network platform of the development for data resources

Data resources are one of the main research achievements of scientific research.

According to research firm IDC predicts that the world's raw data storage capacity will be an annual increase of more than 50% by weight, and all of data is not only growing in volume but the growing complexity of data resources. Therefore, the establishment of massive data collection, storage platforms and computing center will be a necessary condition for the era of big data research institutes and development.

Construction big data cloud storage center

Big data analysis and research has been carried out and quickly deployed in a variety of different research areas, such as genomics, proteomics in particular, its data growth rate will exceed the legendary speed IT design development, because data storage capacity and data processing capacity of the existing data center can't meet the future needs of scientific computing and analysis. Survey about information technology showed in Figure 1: This indicates that in the case of rapid growth of data the pressure storage capacity is the biggest problem of the network construction. Therefore, in order to meet the data storage demands of big data era, building cloud storage center is to meet the necessary conditions for the future of store large data. The planning proposed to establish a data cloud storage platform for information integration and islands of information and proposed to provide long-term data preservation service, remote backup service and online storage service associated monitoring and surveillance data.

Construction High Performance Computing Data Center

In contemporary agricultural science research, since scientific data surge that the possibility of obtaining more and more science depends on acquiring, processing a sufficient amount of data capacity. Establishment of high-performance computing data center can provide genomics, proteomics, bioinformatics, new materials and other high-performance computing services. CAAS have a strong demand for high-performance computing.According to 2014 survey results, more than 2/3 of the institutes is applying high performance computing, 1/3 of the institutes also has the needs of high performance computing.Along with the agricultural development of information technology, agricultural research is becoming comprehensive and interactive .It is urgent to the needs of multi-field, regional, cooperation in collaborative research teams. All types information collection and data mining and analysis has become the main direction of agricultural research and development. Because the database has accumulated a massive data of flora and fauna resources, monitoring and sensing data, network data, traditional data mining massive data mining model can't meet the demand for computing power, thus it is the need to establish a new data mining models with high-performance computing capabilities. Building high-performance computing centers should combine with the actual needs of research work. By the research institutes requirement of the high-performance computing application, we can build a high-performance computing platform including a scientific-basis parallel computing platform software platform, system application software platform and tools. Build high-performance computing centers can also provide remote sensing data, sensor data, network data and other large data analysis and processing business for domestic and international users. Building cloud computing platform will achieve effective dispersion mining resources, integration, sharing.

Construction of the data collection and processing center resources

Website statistics show that in 2015, all of the 236 sites, 227 sites generated data used the database management.Data collection and processing center construction can rely on the network resource data platform to meet the decentralized or centralized storage of agricultural natural resources and science and data resources to achieve centralized remote integration and data sharing agricultural scientific data resources. Construction of Agricultural Sciences data integration center, we can improve the efficiency of data query services, protect the security of the data. For experimental data (experimental) chamber of agriculture science, agricultural science field station and observation station generated, we can deploy data collection layer, field control layer, data storage layer and business application layer architecture system, establish a wireless sensor network system, the completion of agricultural production monitoring network laying demand, eventually things will transmit information to the data collection center. Ultimately, by constructing a data center networking platform we can provide experimental (test) data network platform for intelligence gathering and storage, and improve the processing efficiency of field observation data.

Established national agricultural resources Things monitoring platform

Establishment of national agricultural resources monitoring platform can integrate multi agricultural condition monitoring resources, expand and upgrade the existing infrastructure integration and software integration systems. According to the principle of cloud computing and cloud service management,we can design and build the platform architecture, deployment platform equipment, development software system, than gradually establish a national agricultural condition monitoring platform. The platform can achieve coverage area of the county's main crop types, to provide realtime dynamic for agricultural research and agricultural production and long-term accumulation of data resources, to provide support for agricultural production and scientific guidance for disaster emergency management.

broaden the web services model, increased resource sharing and communication platform

The planning in 2014,has put forword to use the latest technology such as responsive web design to optimize the design and development of adaptive Chinese portals, and develop the network carriers to support for smartphones, tablet computers, TV, PC monitor, IOS and Android mobile phone carrier access. New media platformsIis another task, such as building weibo WeChat which can broad the personalized information service mode and active push, diversified information services.

A large-scale production, sharing and application data era is just beginning, as Professor Victor said, the real value of big data is like an iceberg floating in the ocean, we can only see the tip of the iceberg at first glance, most hide beneath the surface. Carry out research work, will also be with the arrival of the era of big data, a huge change, and construction site data resources, but also will become all the researchers involved in scientific research is an important content.

Figure 1 :

 1 Figure 1: Chinese Academy of Agricultural Sciences Research Network Storage Problems table

Table 1 .

 1 . Number of existing sites and views Construction of Web database has begun in the 1980's and it has arrived 185 as of 2014.Here are several examples in early phase. In the 1980s, the database of feed nutrition had been jointly build by Institute of Animal Sciences and the Computing Center head by Academician Ziyi Zhang.In the 1990s,seed resources database built by professor Xian Zhen Zhang has reached 42 million types by 2014. The agricultural science and technology data platform information presided over of a few years ago by professor Xianxue Meng had been put into application in which involves 12 individual sciences,72 subject database groups, 672 databases and 1987TB data quantity browsed by 50-60 million people every day. Seed resources database in China has accumulated hundreds of millions of seed resource data. With development of genetics and breeding subject the gene sequence of important crops and animals measured precisely have formed a huge gene database. There are many All kinds of scale national construction scientific data and resource data center.But,it has a weak ability in data collection and integration.There has only 14 data websites in the CAAS portal. According to statistics in 2014,the other 185 data resources websites are independent with the CAAS portal.All of these data resources cann't share and analysis. Web site data storage format and location are shown in table2.

	Unit	The number of sites	IP average daily traffic	Average daily page views
	Agricultural Institute of CAAS Information	43	1310	7647
	China National Rice Research Institute	19	1009	4211
	Food Science and Technology Institute of CAAS	13	1010	3123
	Farmland Irrigation Research Institute	13	977	2785
	Management of CAAS	12	18901	98142
	Biotechnology Research Institute of CAAS	12	812	4205
	Institute of Environment and
	Sustainable Development in	11	657	1223
	Agriculture,CAAS
	Biogas Institute of Ministry of Agriculture	11	612	1129
	……	……	……	……

table 2 :

 2 Web site data storage format and location

			Data storage form		storage location
	Number of sites	database	spreadsheet	network center in CAAS	network in institutes	Network in The third party
	236		227	9	21	22	193
	2.1	Network is weak
	2.1.

1 Lack of overall website construction planning and financial support.

	Since the CAAS portal has been setup, website establishment, development and daily
	maintenance run by each institutes. Because there is no unified planning and special
	funds to support, website construction and service level is uneven and database
	construction and maintenance status are poor .Nothing of unified management and
	data sharing platform it is difficult to data sharing and analysis in the future.
	According to statistics, nearly 2/5 of the institutes do not have the operation and
	maintenance expenses. Compared with the Chinese academy of sciences, CAAS
	funds in development of information is far smaller. CAS information construction
	began in the "fifth" period. By the end of "Thirteen Five" ,it has accumulated invested
	several million dollars.

2.1.2 Network Infrastructure environment is weak.

	scientific research data between the institute, the base, the test station and field station
	can not be shared and transmitted.
	2.
	According to statistics, Chinese Academy of Agricultural Sciences 41 research
	institutes, 10 departments in 2014 generated approximately 10TB of data per day, and
	10% annual growth rate, while the storage capacity of the existing network center
	room of the CAAS can not meet demand.All of the institutes in CAAS distributed 24
	provinces in the country. Since there is no interconnection of data transmission lines,

2 Lack of unified planning of data resource construction

	Data resource construction is a long-term work and need a reasonable system to
	ensure data accuracy and availability. lacking of unified standards data need to
	repeat collection, repeat input and maintained by multiple departments. At it caused
	information update asynchronously and non unified. The specific problems in
	following several aspects:
	First, there is not a unified data format and compatible standards. According to the
	survey, all of 42 institutes have

built their own financial and personnel platform, but because CAAS did not establish a unified system compatibility standards, data in one dapartments is not compatible with another department. As the amount of data is growing rapidly, it will increase the workload of management and work harder. Secondly, CAAS lack research management platform, such as platform for research software and scientific instruments sharing. Instrument and software is an important part of the use of scientific research funds.Because CAAS have not scientific research software and instrument unified purchase plan and sharing mechanism it caused software and instrume purchased repeatly and utilized lowly. Third, there is a lack of scientific research data storage mechanism. Most of the scientific research data edit and save by each group, lacking of system and professional. According to statistics in 2014, 115 research institutes or units has built its own web site that one institute have about 3.3 of web sites on the average. But it is lack of unified management and effective utilization , scientific research data is low usage rate .

  Twitter and micro-channel has become an important way of communicating information. And smart phones, tablet PCs and other mobile Internet terminals grow explosively. As of mid-June 2013, China's mobile phone users reached 464 million. Mobile office has become a more relaxed and effective way of working in the future. But CAAS portal website only has a traditional Internet platform and is lack of function to diverse and release data resources.

Table 3

 3

		:The planning timetable from 2015 to 2020
	No	program			aim		Execution Time
				Formulate framework	technology	standards	2015.1-2015.6
	1	Rules regulations	and	Formulate standards	Information	construction	2016.7-2017.12
				Formulate operation and management of information	2015.7-2016.12
	2	Administrative Information Construction	Institutes information database based on completed and e-government applications.	2015.1-2016.12
	3	Network-based environmental improvement	Construction of high-speed and stable school district Wireless network coverage network transmission channel and network bandwidth access levels and	2015.1-2016.12
	4	High-performance platform computing		Construction mining resources, integration, sharing. of high-performance computing platform to achieve effective	2018.1-2018.12
	5	Construction site of new media	Construction of multi-media platforms and carrier information dissemination,	2015.1-2019.12
		platforms.		diversify information services.
		Security		Through third-party security cloud
	6	conditions		platform, to all sites within the Academy	2016.1-2019.12
		building		belongs range safety monitoring service.
	7	Data Sharing and Analysis Platform	Scientific Data virtual shared environment construction Data analysis platform (tools) Construction	2016.1-2017.12 2017.1-2019.12

Table 4

 4

	: 2015 --2020 the central office-based environment construction plan
	program	aim
	Center room area By 2020, the total area of 5000m 2
	Power Systems	Build double circuit power supply systems and power protection
		UPS8 hour online
	Security System

Foundation item: Chinese Academy of Agricultural Sciences website content resources, research organizations and service models