Manping Hou

Jinmin Hao

Ying Shi

Jun Yang

Qian Wen

Mingzhu Cha

Lingkun Xiong

A Study of Agricultural Zoning of Huang-Huai-Hai Plain Based on GIS 1

Keywords: Agricultural zoning, Producing Region Distribution, Agricultural Pattern, Huang-Huai-Hai Plain 2 Data Sources and Research

Many scholars in China have done a lot of research on regionalization of agricultural resources in the Huang-Huai-Hai Plain, but there is no quantitative research on agriculture of the whole plain. By using qualitative and quantitative analysis based on the basic data collected over 300 counties in the Huang-Huai-Hai Plain, considering such indicators as the natural resources of the plains and the yields of major crops and agricultural GDP,this paper designed the agricultural zoning of the plains. The Plain was classified into high-yield areas and low-producing areas. High-yield areas were divided into advantageous regions of foodstuff, advantageous regions of cotton, advantageous regions of oil, advantageous regions of foodstuff and cotton, advantageous regions of foodstuff and oil, advantageous regions of cotton and oil, and advantageous regions of foodstuff, oil and cotton. And these areas have been divided specifically. The research is of referential values for agricultural development of the Huang-Huai-Hai Plain, both practically and theoretically.

Introduction

Huang-Huai-Hai Plain is the largest plain in China. Land area accounts for about 30% of the plain area of the whole country and arable land accounts for 1/6. Its climate is advantageous for both the north and the south, and has great potential for agricultural development with higher level of modern agricultural technology. Agricultural zoning layout plays a decisive role in agricultural production in this region. Researchers abroad have done many studies in the regionalization of agricultural resources [START_REF] Luo | The application and research of GIS technology in the Fujian agricultural resources[END_REF][START_REF] Tang | Remote Sensing Technology in Rural Resources Planning and Prospects[END_REF][START_REF] Bi | Rational use of agricultural resources and ideas of protecting zones' research[END_REF][START_REF] Sabbah | Impact of irrigated agricultural practices on environmental quality and human health in the West Bank[END_REF][START_REF] Robertson | The gaps between ecosystem ecology and industrial agriculture ecosystems[END_REF][START_REF]Regional distribution planning of competitive agricultural products[END_REF][START_REF] Kawu | Sustainability assessment of soil and water resources use, development potential and Countermeasures in Huang-Huai-Hai plain[END_REF] . The author collected agricultural economic data of each county of the Plain, and used GIS platform for property analysis, and drew a more reliable quantitative foundation, and provided the basis for sustainable development of agriculture in the Plain.

foodstuff and cotton, advantageous regions of foodstuff and oil, advantageous regions of cotton and oil, advantageous regions of foodstuff, oil and cotton. In order to stabilize the total wheat production in the areas, the result indicated that the optimum method is to moderately reduce wheat acreage of the severe water shortage areas, and vigorously develop high-quality wheat, and expand the area of high-protein, high-fat, high starch content of corn, and accelerate the development of feed industry, brewing industry, and promote the conversion of corn processing, and actively develop high-protein soybean and other oilseeds, and form a stable cotton focus area [START_REF]Regional distribution planning of competitive agricultural products[END_REF] . Under the premise of ensuring food security, the overall layout is that the plain should focus on diverse production and operation where agricultural products (especially special agricultural products) plays a dominant role, and that the plain can achieve a large-scale production and industrial management, by scale land management and using modern technology and the developing socio-economic conditions.

High-yield area zoning

Advantageous regions of foodstuff, oil and cotton mainly include 14 counties in northern of Shandong west plains, 6 counties in Henan southeast plains, 4 counties in piedmont and the Anhui north plains. Advantageous regions of foodstuff and oil mainly include 25 counties in piedmont, 16 counties in Henan southeast plains, 10 counties in Shandong west plains, 6 counties in Anhui north plains. Advantageous regions of foodstuff and cotton were smaller in numbers, mainly including 5 counties in heilonggang region, 2 counties in Anhui plain, 2 counties in Henan southeast plains and 2 counties in Shandong west plains. Advantageous regions of cotton and oil mainly include 8 counties in Henan east plains, 7 counties in southern of Shandong west plains, 3 counties in Anhui north plains and 1 county in the southern of piedmont. Advantageous regions of foodstuff mainly include 11 counties in piedmont plains, 6 counties of Henan southeast plains, 9 counties in Anhui north plains and 1 county in Western Henan. Advantageous regions of cotton mainly include 8 countries in heilonggang region, 6 countries in Anhui north plains and 4 countries in Shandong west plains. Advantageous regions of oil mainly include 4 counties in the piedmont, 9 counties of Henan southeast plains, 5 counties in west Shandong plain and 5 counties in Anhui north plains. In addition, from the analysis of wheat, corn favoring areas distribution, wheat favoring areas are mainly in the piedmont plains, corn favoring areas are mainly in Shandong west plains. Wheat and corn favoring areas are mainly in the central region of the piedmont.

Agricultural Pattern of the High Yield Region

Based on water-saving cultivation, high-yielding zones had food production advantages, and optimized food variety and quality of structure and established top quality and high yield and efficient bulk agricultural commodity base of animal husbandry products. Advantageous regions of foodstuff and oil crops mainly produce special wheat, corn, oil and other pollution-free agricultural products. Advantageous regions of cotton produce high quality cotton in the main stream. Meanwhile, high-yielding zones moderately develop aquaculture industry to ensure food security objectives and quality efficiency objectives of the plains and the country are reached. In high-yielding areas of favorable conditions, production of mechanization, information technology and standardization was firstly implemented and then a model for the mechanization and modernization of agriculture was set in the country. High-yielding zones should develop processing industries to increase agricultural production and famers' income, and realize sustainable development of agriculture, the rural economy and ecological environment ultimately.

①Advantageous region of foodstuff, oil and cotton: soil and water resources in here is very advantageous. It is suitable for planting wheat, corn, cotton, oil etc. The area should be featured with a variety of crops of high quality varieties of foodstuff, oil and cotton in the future. Taking advantage of high yield of wheat and rich soil and water resources, the region should develop both summer and autumn planting, but can't expand the total acreage of wheat. In order to improve resource utilization, the region should be developed mainly in autumn. This region should form a scale and specialized cultivation of wheat, corn, cotton and oil quality product, also take advantage of companies (enterprises) with farmers and other forms, and form large-scale product processing bases, and moderately develop fodder cultivation, forest products and aquatic products, and form small-scale animal husbandry. In addition, it should increase planting of other crops with a dominant market position, and develop export-oriented agriculture. This area will become the first agricultural product advantageous district in the Plain.

From 2000 to 2006 in this area, average proportion of the acreage of foodstuff, cotton, oil was 12.50∶2.45∶1, and wheat and corn is 1.48:1; Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries was 28.50:1:12:2.1. As for improving foodstuff, cotton and oil cultivation structure, addition of feed grown, improvement of water-saving efficiency, ratio of foodstuff, cotton, oil, and feed may reach 8:3:1.5:1. Average ratio of total output value of agriculture, forestry, animal husbandry, and fisheries may reach 25∶1∶11∶2.5 recently. And structure of wheat and corn is basically unchanged.

②Advantageous regions of foodstuff and oil: the zones are mainly located in the piedmont, the southeast Henan plains, Shandong west plains and Anhui north plains. The area of its water resources are relatively abundant [START_REF] Kawu | Sustainability assessment of soil and water resources use, development potential and Countermeasures in Huang-Huai-Hai plain[END_REF] . Its soil is mainly cinnamon soil, and then moisture soil. Piedmont does not only have the most advantageous soil and water conditions, but also is good farmland construction areas. It has a high degree of land use. Its arable land reserve resource is rare, and is the more favorable areas of wheat. Northern piedmont is the common advantageous areas of wheat, corn-producing. Henan southeast plains areas are the more favorable areas of the wheat, the Shandong west plains area and Anhui north plains are the more favorable areas of the corn. Piedmont in northern areas should be based on the development of wheat, corn, oil and should make a modest reduction in cotton. Southern piedmont areas and Henan southeast plain areas should be based on the development of wheat, oil and should make a modest reduction in corn and cotton. Shandong west plains and Anhui north plains should be based on the development of corn and oil crops and should make a modest reduction in wheat and cotton. At the same time, the region should intensify production in the drought and saving water special crops, and implement large-scale cultivation, and develop intercropping systems and increase the proportion of summer crops, the acreage of forage crops and other economic crops. Forest in piedmont and southeast Henan plains areas is appropriate to increase the acreage of fruit trees. The region should achieve the integrated development of food, cash crops (except cotton) and fodder crops, and use industrial production and grain and oil processing industry to promote agricultural production. Henan southeast plains, Shandong west plains, Anhui north plains should be increased mechanization acreage.

From 2000 to 2006, average proportion of the acreage of foodstuff, cotton, oil, fruit in this area is 28.2∶1∶6.5∶3.70, and wheat and corn is 1.2∶1; Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries is 150∶1∶ 98∶8. As for improvement of foodstuff, cotton and oil cultivation structure, addition of feed grown, improvement of water-saving efficiency, ratio of foodstuff, cotton, oil, fruit may reach 24∶1∶8∶7 recently. The proportion of wheat and corn in the southern region is 1:1. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries may reach 100∶1∶70∶10 recently. And structure of wheat and corn in northern areas is basically unchanged.

③Advantageous regions of cotton and oil: the area soil is mainly moisture soil, pickled moisture soil, low-lying, easy to form the floods. But this region must strengthen water conservancy construction and improve soil fertility. The plant structure is large-scale cultivation of high-quality fuel, high-quality cotton, compressed wheat and corn acreage, moderate development of fodder cultivation, increasing areas of mechanized operations. Meanwhile, this region should depend mainly on the development of cotton and oil processing industry and develop export-oriented industries.

From 2000 to 2006 in this area, average proportion of the acreage of foodstuff, cotton, oil was 4.5∶1∶1.1; Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries is 27∶1.5∶12∶1. The ratio of foodstuff, cotton, oil may reach 3∶1∶1.1 recently. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries may reach 20∶2.5∶14∶1 which was the optimized structure recently.

④Advantageous regions of foodstuff and cotton: the soil is moisture soil with saline. It should develop water-saving foodstuff and cotton production, and modestly reduce cotton acreage and expand corn acreage. While Anhui north plain areas have obvious advantages of water resources, should increase the special corn production. This area should plant food, cash crops and fodder crops, and Anhui north plains should increase a modern planting effort.

From 2000 to 2006, in Anhui north plains, average proportion of the acreage of foodstuff, cotton, oil is 14∶1∶1.2, among them, wheat and corn was 3∶1; Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries is 15∶ 1∶7∶2.5. The ratio of foodstuff, cotton, oil may reach 12∶3∶1. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries may reach 16∶ 1∶12∶4 which is the optimized structure.

⑤Advantageous region of foodstuff: This area is only suitable for growing food crops, unsuitable for cotton and oil crops. The zones should strengthen a combination of water and soil transformation, especially transformation of the coastal saline soil in Anhui north plain. Anhui north plain areas should enhance scale and specialized planting, while other districts should develop comprehensive planting, reducing sown areas of cotton ordinary oil.

From 2000 to 2006, in Anhui north plains, average proportion of the acreage of foodstuff, cotton, oil is 15∶1∶2. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries is 20∶1∶9∶4. The ratio of foodstuff, cotton, oil may reach 20∶1∶3 recently. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries may reach to 18∶1∶10∶5 which is the optimized structure recently.

⑥Advantageous region of oil crops: this region is distributed in the plain areas of southeast Henan, Shandong west plain areas and Anhui north plains. The main soil is moisture soil. Areas of this type are only suitable for planting oil-bearing crops, low-producing areas for cotton and food crops. Its agricultural development should lay stress on the combination of water and soil. The goal is to form large-scale oil cultivation and oilseeds areas where oil crops are main cash crops.

From 2000 to 2006, in this area, average proportion of the acreage of foodstuff, cotton, oil, fruit tree is 21∶2∶6∶1. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries is 25∶1∶10∶2. The ratio of foodstuff, cotton, oil, fruit tree may reach 10∶3∶10∶1 recently. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries may reach 16∶1∶12∶2 which was the optimized structure recently.

⑦Advantageous region of cotton: the main soil is moisture soil. Areas of this type are only suitable for growing cotton, low-producing areas for foodstuff and oil crops. In Heilonggang areas should water-saving cropping patterns should be developed, combining water-saving with soil improvement. Anhui north plains should base on large-scale, specialized cultivation and develop cotton-based of various business models.

From 2000 to 2006, in this area, the average proportion of the acreage of foodstuff, cotton, oil, fruit, vegetables is 12∶3∶1.5∶1.2∶1. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries is 27∶1∶11∶2. The ratio of foodstuff, cotton, oil, fruit, vegetables may reach 6∶4∶1∶1∶1 recently. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries may reach 12∶1∶5∶1 which is the optimized structure recently.

Agricultural zoning layout of middle and low producing areas

Middle and low producing areas in the Plain areas is quite large, covering more than 110 counties (cities). They were mainly affected by drought, waterlog, salinity, wind and sand, lime concretion, barren and other barriers element [START_REF] Sun | China's natural agricultural and regional development[END_REF] . Due to a poor efficiency of the ecological environment, the region should improve the ecological environment through ecological structural adjustment. By using salt-tolerant, bio-cover and bio-drainage to change the movement of soil water and salt, it will gain ecological and economic benefits. The region can plant forest and foodstuff, vegetable in salinity lighter areas, and plant salt-tolerant vegetation in salinity areas. By using water-saving irrigation techniques, straw, organic fertilizers to improve soil structure and increase soil fertility, this region should save and protect water resources to achieve the target of high and stable yield.

In the northern parts of the region is mainly moisture soil and bog soil, while in the south is mainly moisture soil and lime concretion black soil. Controlling saline-alkali soil in the area is a long-term arduous task. The region needs to increase agricultural inputs and strengthen water conservancy measures. In addition, improvement of saline-alkali soil is also very important. The control of sand is a focus of the area, which should be based on biological measures and engineering measures, and combine forestry fruit with flowers and grass. Then the region can establish a sand ecological and economic protection system. The southern part should focus on improving lime concretion black soil and created farmland shelterbelts and establishing three-dimensional forest shelter, fertilizing organic materials and planting green manure. The northern parts should focus on water-saving agriculture, and developing various patterns of water-saving cropping [START_REF] Hou | Research of low consumption resources of ecological agriculture in Huang-Huai-Hai plain[END_REF] .

From 2000 to 2006, in this area, the average proportion of the acreage of foodstuff, cotton, oil, fruit tree, vegetables was 20∶1∶2∶1.2∶2. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries is 30∶ 1∶16∶2. The ratio of foodstuff, cotton, oil, fruit tree, vegetables may reach 15∶1∶5∶4∶5 recently. Average ratio of total output value of agriculture, forestry, animal husbandry, fisheries may reach 25∶1∶15∶2 which is the optimized structure recently.

Conclusion

This is a quantitative research, so the paper has got one step further than previous studies. Because of the huge workload of quantitative research, the author can only make a streamlined introduction in this paper. Accurate quantitative studies have yet to be further deepened. However, this study played a guiding role in agricultural development of the Huang-Huai-Hai Plain.

Fig. 1

 1 Fig. 1 Distribution Map of Foodstuff, Oil and Cotton Producing Region in Huang-Huai-Hai Plain

Supported by National Scientific and Technological Project(2004BA508B01)

The Huang-Huai-Hai Plain Agricultural Zoning3.1 High-yield Region Agricultural Overall ZoningMainly high-yielding area in the Plain related to the favorable conditions of water, soil, light, heat and other natural agricultural resources. High yielding regions were divided into seven advantageous regions: advantageous regions of foodstuff, advantageous regions of cotton, advantageous regions of oil, advantageous regions of


Bibo Ma

Haiyan Ji

Particle swarm optimization algorithm establish the model of tobacco ingredients in near infrared spectroscopy quantitative analysis

Keywords: Tobacco, Particle Swarm Optimization (PSO), Principal Component Analysis (PCA), Near infrared spectroscopy 1 Bibo Ma: Master. Research field: Spectral analysis Spectral analysis and sensing technique

57 tobacco samples were chosen, the near-infrared diffuse reflectance spectra at five different parts of tobacco leafs were averaged as the original spectra, the range of 4000-9000 wavenumber of spectral information was selected after wavelength selection, first-order differential was used to eliminate the impact of offset, PCA was used to reduce the dimensions and select the most representative of the principal components of the sample information. After these, use PSO and the data of chemical composition of nicotine and total nitrogen, to establish the models of near-infrared spectra of the main ingredient in tobacco quantitative analysis. In which, nicotine and total nitrogen quantitative analysis of modeling set correlation coefficients were 0.8886,0.9290; the prediction set correlation coefficients were 0.8786,0.8487. RMSEC values were 0.4737,0.2215; RMSEP values were 0.6417,0.2677. The results show that: PSO can be used to establish the model of nicotine and total nitrogen by near infrared spectroscopy quantitative analysis in tobacco.

Introduction

Near infrared reflectance spectroscopy does not require any chemical pretreatment for the sample. Compared with traditional chemical analysis and other spectroscopy methods, it has many advantages, such as cheap, convenient, fast and non-destructive characteristics [1] 。 Currently, there are some methods in the near-infrared spectroscopy quantitative analysis , such as partial least squares (PLS) 、 support vector machines(SVM) and artificial neural network(ANN). In 2007, Yan Qing Duan, Jia Jun Wang, and others use PLS method for quantitative analysis for the chemical composition of five kinds of tobacco sheet .The results showed that: near-infrared predictive value and the measured values have a good correlation, the model has better prediction accuracy [2] ; In 2007, Xu Liu, Hua Chen use the PCA-SVR and the ANN for a quantitative analysis of total sugar, reducing sugar, total nitrogen and nicotine content in tobacco.

The results show that: the SVR model has a better prediction [3] ; In 2009, Yong Zhang, Qian Cong use the SVM for a quantitative analysis of total sugar, reducing sugar, nicotine and total nitrogen in tobacco. The results show that: the SVM model's classification accuracy rate can up to 100%, the quantitative analysis of four components of the prediction coefficient of determination (R 2 ), the prediction mean square error (RMSEP) and the average relative error (RME) show that: the model has a better prediction [4] .

In this paper, PSO method is used in near-infrared spectroscopic quantitative analysis of total nitrogen and nicotine content in tobacco, in order to prove that the PSO method can be used in the near-infrared quantitative analysis in tobacco.

The basic principles 1.1 The basic principle of PSO

PSO,the English name is Particle Swarm Optimization, is proposed by Kennedy and Eberhart in the study of birds and fish group's behavior in 1995. It's a swarm intelligence algorithm [START_REF] Kennedy | Particle swarm optimization[END_REF] . In PSO, each optimization problem can be a bird in the search space (we can call it a particle). All the particles have an optimized to determine the fitness value by a function and have a speed to determine their direction and speed for flying.

Firstly, the algorithm initializes a group of random particles, and then finds the optimal solution by iteration. In each iteration, the particles update their speed and position by individual extreme and global extreme. The algorithm assumes that all particles are moving in the personal best position and global best position, and mark

) ... , ( 2 1 in i i i x x x x 
to initialize the position of the particle, mark as the best result for searching so far for the all particles. In each iteration, the particles update themselves by tracking the two optimal values, which is the value founded by particles themselves and the value founded by the entire population so far.

) ... , ( 2 1 in i i i v v v v  to initialize
After finding the two values, particles update their velocity and position according to the following formula [START_REF] Shao | [END_REF] :

) ( ) ( ) ( ) ( 2 2 1 1 id gd id id id id x p r c x p r c old v w new v           ⑴ ) ( ) ( ) ( new v old x new x id id id   ⑵ DT w w t w w max / ) ( min max max     ⑶
In this formula, w is constant of non-negative, we call it the inertia factor, which is used to balance the global searching and the local searching. Shi and other people for the first time introduce to update formula for the inertia weight of the speed in PSO [START_REF] Shi | A modified particle swarm optimizer[END_REF] . In this paper, we propose max w =0.9,

min w =0.4 [8] ; 1 c =2.8, 2 c =1.3; 1 r and 2 r are random number in [0,1], DT max
is the maximum number of iterations , in order to control the closing conditions of the algorithm; t is the current number of iterations. In this paper, w decrease gradually from [0.9,0.4] [9] .

Firstly, calculate the new speed of the particles by the distance of the original particle velocity and position between the two optimal locations according to the formula (1). Then particles move to a new location according to the formula (2). So back and forth. If it reached the specified number of iterations, the program terminates.

The processes of PSO

(1) Initialize the initial position and velocity of a group of particles and set the number of iterations for 5000

(2) Set the mean square error as the fitness value and get the fitness value of each particle by calculating (3) For every particle, compare it's fitness value with the best position (pbest,) if better than pbest, use it as the current optimal particle position (pbest);

(4) For every particle, compare it's pbest with the best position gbest of all particles, if better than gbest, use it as the current optimal particle position (gbest);

(5) According to the formula (1) and ( 2), adjust the speed and position of the particle;

(6) If it has not reach the end of the conditions, turn to step 2;

Here, the termination condition is that the required iterations can get the number of 5000.

Experimental part 2.1 The sources of material

In this paper, the tobacco data is K326 tobacco varieties, which is coming from the national 18 origins and is divided into three tobacco grades (B2F, X2F, C3F).

The collection of spectral information

In this paper, the spectra data is collected on five different parts of the tobacco leaf, and then take the average of the five parts as the spectrum. Tobacco original near infrared spectroscopy is showed in Figure 1.

The preprocess of spectral

It can be seen from Figure 1, the main crest of tobacco information is concentrated in the 4000-9000 wavenumber. Therefore, in order to save modeling time, and eliminate the unwanted ingredients in the spectral information, in this paper, the wavenumber in the range of 4000-9000 cm -1 information are selected for the study.

The spectrum is showed in Figure 2 after wavelength selection. In this paper, use the first difference to eliminate the impact of the offset. The spectrum is showed in Figure 3 after the first difference. Then use the principal component analysis (PCA) to reduce the dimension and get the principal component of the spectrum. Use the PSO to create a system model. In the model, the main components of the spectral data is as the variable input of the model, the chemical values of nicotine and total nitrogen content is as the output of the model [10] . Use the data of mean square error between the calculated results and the real chemical value as the fitness function, in order to adjust the speed and position of the particle in the particle swarm and determine the global optimal solution. In the paper, the number of the principal components, the range of chemical value content of nicotine and the total nitrogen in modeling and in the prediction are showed in Table 1.

The parameter settings of the model

In PSO, the parameter setting is very important. In order to improve the ability of modeling and prediction, in this paper, the algorithm parameter settings are showed in Table 2.

Table 2. The parameter settings of the model

The parameter settings of the model

The location of the particles (X) Random

The velocity of the particle (V) Random, but between[-

The establishment and evaluation of the model

In this paper, in all of 57 K326 tobacco data, use 40 samples as the set of modeling, 17 samples as the set of prediction. In the model, the total nitrogen modeling set of correlation coefficient is 0.9290, the prediction set of correlation coefficient is 0.8487; nicotine modeling set of correlation coefficient is 0.8886, the correlation coefficient of prediction set is 0.8786. Other related indicators of the rest of the model are showed in Table 3. Figure 4 is PSO regression of nicotine modeling set and prediction set. Figure 5 is PSO regression of total nitrogen modeling set and prediction set.

Results and Discussion

57 tobacco samples were chosen, the near-infrared diffuse reflectance spectra at five different parts of tobacco leafs were averaged as the original spectra, the range of 4000-9000 wavenumber of spectral information was selected after wavelength selection, first-order differential was used to eliminate the impact of offset. PCA was used to reduce the dimensions and select the most representative of the principal components of the sample information. After these, use PSO and the data of chemical composition of nicotine and total nitrogen, to establish the models of near-infrared spectra of the main ingredient in tobacco quantitative analysis. In which, nicotine and total nitrogen quantitative analysis of modeling set correlation coefficients were 0.8886,0.9290; the prediction set correlation coefficients were 0.8786,0.8487.

RMSEC values were 0.4737,0.2215; RMSEP values were 0.6417,0.2677. The results

show that: PSO can be used to establish the model of nicotine and total nitrogen by near infrared spectroscopy quantitative analysis in tobacco.

Fig. 1 .

 1 Fig. 1. Tobacco original near infrared spectroscopy

Fig. 2 Fig. 3 .

 23 Fig. 2 spectra after the wavelength selection

Table 1 .

 1 Range of chemical content and the number of principal components

			The range of	The
	Sample	Samples	model	range of	Principal
	Name	number		prediction	components
			(%)	(%)
	Nicotine	57	0.88-4.68	0.94-4. 67	14
	total nitrogen	57	1.45-3.83	1.58-3. 55	15

Table 3 .

 3 The indicators of evaluating the model

		Sample		Modelin		Modeling	Predictio	Prediction
		Name		g R		RMSEC	n R	RMSEP
	Nicotine	0.8886		0.4737	0.8786	0.6417
			total
	nitrogen		0.9290		0.2215	0.8487	0.2677
						PSO method						PSO method
	Nicotine.Model.Pred	1.00 2.00 3.00 4.00 5.00 6.00	R 2 = 0.7896					Nicotine.Pred.Pred	1.50 2.00 2.50 3.00 3.50 4.00 4.50	R 2	= 0.7719
			0.50	1.50	2.50	3.50	4.50	5.50			0.50	1.50	2.50	3.50	4.50	5.50
					Nicotine.Model.Chem						Nicotine.Pred.Chem
					Fig. 4 PSO regression of nicotine modeling set and prediction set
						PSO method						PSO method
	Total	nitrogen.Model.Pred	1.50 2.00 2.50 3.00 3.50 4.00 4.50	R 2	= 0.8630				Total	nitrogen.Pred.Pred	1.50 2.00 2.50 3.00 3.50	R 2	= 0.7289
			1.00									1.00
				1.00	1.50 2.00	2.50 3.00	3.50 4.00			1.00 1.50 2.00 2.50 3.00 3.50 4.00
					Total nitrogen.Model.Chem					Total nitrogen.Pred.Chem
				Fig. 5 PSO regression of total nitrogen modeling set and prediction set

x 10


Liu Yang
email: yangliu@cau.edu.cn

Gang Wu

Yuyao Song

Lanlan Dong
email: donglanlan2005@126.com

Grain Moisture Sensor Data Fusion Based on Improved Radial Basis Function Neural Network

Keywords: Radial Basis Function Never Network, moisture measurement, k-means clustering, hidden layer neuron

Difficulty was known to get satisfactory measurement effect on precision in capacitive grain's moisture measurement due to many influencing factors, such as temperature, species, compaction and so on. The data confusion method of Radial Basis Function (RBF) nerve network is adopted. With improved orthogonal optimal method, the RBF nerve network's weight factors can be obtained. This method can avoid artificially selected the number of hidden units, which can cause low learn precision or over learn. Tests showed that the improved RBF network algorithm reduces the network structure, greatly enhances the learning speed of calculation. By using of the improved RBF nerve network, the precision for wheat's moisture measurement has been improved.

Introduction

There are some methods for grain moisture measurement, e.g. resistance measuring, capacitance measuring, measuring with Infrared Radiation, micro wave, neutron spectrum, NMR, etc [1~3]. The advantages of low cost, high sensibility, wide dynamic range and simplicity for real time measuring make the capacitive moisture meter as one of the common method used for grain moisture measurement. The Dielectric Constant (DC) of dry grain is 2~5, while the DC for pure water is 81. As the moisture in the tested sample grows, the DC value also grows. This is the basis for Capacitive Moisture Meter (CMM) measuring [START_REF] Zhai | Data Processing of Moisture Content Measurement Based on Data Fusion[END_REF].

Different type of grain has different DC. The CMM measuring is affected by sample's temperature, category and compactness. The conventional way of measuring the capacitive moisture only measures the capacitor value to get the moisture level, which is not accurate. Temperature compensation for the moisture measuring is actually to solve the accuracy problem by multi-sensor information fusion.

There are a number of methods for such data fusion applied in industrial technology, e.g. Multi-dimensional Regression Analysis, Bayesian Derivation, Artificial Neural Network, D-S Theory and Fuzzy Set Theory. It is as important academically as it is practically to get the best data fusion based on different models.

In recent years, the BP Neural Network has been used for linearization or temperature compensation for measured data. Same as the other forward network algorithms, BP Neural Network algorithm can be trapped by local optimum. In late 80's last century, J. Mody [START_REF] Hardy | Multiquadric Equations of Topography and Other Irregualr Sufaces[END_REF] and C. Darken [START_REF] Harder | R: Interpolation using surface splines[END_REF] proposed the Radial Basis Function (RBF) Neural Network [7~9]. RBF Network has a character called optimal approximation, which will avoid local optimum trap during network establishing. This makes RBF a more effective and fast responding neural network, with a strong nonlinear processing capability. It is presented here the mathematical model for RBF Neural Network applied on grain moisture measuring.

Structure of RBF Neural Network For Grain Moisture Measuring

Structure of Neural Network

There are a few major factors affecting the measuring accuracy of grain moisture: the ambient temperature, the testing frequency and the compactness of the grain. This model composes by input layer, hidden layer and output layer. The input layer has 3 neurons, the hidden layer has I neurons, the output layer has one neuron. The neural network topology is show in Figure 1.

Input Layer

Mathematics Model

The input vector is  

1 2 3 ,, x x x  X ; 1 2 3
,, x x x are temperature, frequency and compactness. The output vector is Y = y, y is grain moisture.

RBF network hidden layer output (the ith node):

  ii u X t   . (1)
In the sentence, RBF function ( ) is Gauss function, t i is the centre of ith hidden node,  is Euclidean Norm.

From the mathematical model, it is known that:

ii i y w u    . (2)
In the sentence, i w is ith connection weight between the ith output i u and the system output y,  is respectively the neurons threshold of output.

W, as a Vector with I dimensions, is given by weights matrix composed of output connection weights:

  12 ,, iI w w w w  W . ( 3
)
To get RBF network for a measuring system, which has N groups of inputs and outputs, can be described in mathematical model as: to get the optimum weights matrix W so as to achieve minimum error between output of RBF network and the expected output of the samples. The target function is:

2 2 1 11 min ( ) 22 N k k k k B d y       k dY . ( 4
)
k Y is kth output vector of RBF network, k d is kth expected output vector of training samples.

Training Algorithm of RBF Neural Network

There are 2 stages for this algorithm. Stage 1 is to determine the centre of the radial primary function for the hidden layer; stage 2 is the get the optimum weights matrix from nonlinear programming model. The method that the centre is chose randomly, selected by self-organization and K-means clustering algorithm are methods that determine the centre of the radial primary function. Comparing to the other methods, K-means clustering algorithm has a advantage that it can reduce the sample space by automatically classifying the sample space to k classes, automatically getting the centre of the radial primary function for every class. The stage 2 of K-means clustering algorithm get the weight vector by Orthogonal Least Squares (OLS), but small k may lead to bad accuracy; big k will lead to bad accuracy and complex network. The improved RBF network OLS algorithm is proposed to solve this problem in the text.

Conventional RBF Network Algorithm

Three parameters are needed to be computed and learned: center vector in basis function, variance vector and weight value matrix.

  arg min ( ) i i in  kk X X t ( 1, 2, , ) iI  (5)
In the sentence, () i tnis ith centre vector of nth iteration basis function.

Fourth, adjust the centre vector of basis function according to the follow method.

 

( ) ( ) ( ) ) ( 1) () ii i i n n n i i n n       kk t X t X t t =( other (6)
In the sentence,  is a step and 0< <1.

At last, judge whether all training samples are learned and distribution don't change. If so, calculation is over, or making 1 nn , turning to second step. Final ( 1, 2, , ) i iI  t is the final ith centre vector of the basis function.

2) Calculating the Variance:

The approximate formula that calculate the variance is as follow when Gaussian function is selected as RBF function:

max 12 2 I D I        (7)
In the sentence, I is the number of hidden node, and max D is maximum distance between centres selected.

3) Calculating the weight vector: OLS and Givens OLS are the general methods to calculating the weight vector W .

Improved RBF Network OLS Algrithm

Structural optimization in network is a difficult. The general structure has large numbers of hidden nodes and leads to over-learn. The general orthogonal method is the traditional Gram-Schmidt which has rounding error. The hidden network structure is optimized with the improved method in the article. I eigenvectors are obtained by K-mean clustering [START_REF] Liu | Study on RBF Neural Network Improvement and its Application[END_REF]. Suppose the output testing samples column vector is:

The hidden layer output vector 12 , , ,

T I u u u    U . ( 9
)
The expected output vector can be expressed by hidden layer function output vector:

 d UW E .

(10)

In the sentence, E is error vector. Make U as orthogonal triangular factorization with Gram-Schmidt orthogonal algorithm [START_REF] Huan | Matrix Theory and its Application[END_REF]:

 U QR . (11)
The elements in upper triangular matrix R are computed in row but not in line in improved Gram-Schmidt method which lead to lower rounding error. For details, viewing 1 q as the result of ,

2 jj R u R R j I             11 T (1) 1 j j j 1 qu q u u u q . ( 12
)
After the computation, , , , Then, Ortho-normalized

(1) 2 u : ,, (1)
(1) 3I uu minus the parallel component of (1)

2 u : (1) (1) 22 22 2 2 22 (1) (2) (1) 2 2 2 2
,/ ,3

T j j j j j R u R R R j I             qu q u u u q (13)
Thus,

(2) (2)

,,

I uu are orthogonal with 12 , qq. Repeating the steps, the orthogonal matrix Q and upper triangular matrix R are obtained. The structure network is optimized with improved Gram-Schmidt method and detail solving process is designed in the article. The improved optimized network structure is obtained by sentence (10):

2 1 I TT i i g    d d E E . (14)
In the sentence, 2

I T i i g    GG 12 ( , ..., ,..., ) T iI g g g g    G RW Q d Suppose the compression ratio is: 2 [ ] / 1 T ii err g i I    dd . ( 1
) 15
Above result show that as the rounding error is lower in the improved Gram-Schmidt, the numbers of the hidden layer nodes can be computed precisely. The computation amount is decreased and over learned problem is avoided.

Comparing experiments have been done to verify the function of the improved RBF algorithm[13~14] in this article, which is supposed to achieve higher moisture detecting accuracy.

BP network, traditional RBF network and improved RBF methods are used to compare for data fusion process. 300 groups of wheat samples are prepared for the experiments. Among which, 250 samples are used for learning algorithm, and 50 groups are used for measuring.

Compare the Measuring Results With the Method of Improved RBF to That With Method Without Data-fusion Process

Testing values and standard values of the two methods are listed in the Table 1 and2 The Tables show that with the method without data-fusion, the error is ±5.0%. With the method of improved RBF, the error is reduced to ±1.9%. The maximum error and minimum error is respectively ±1.9% and ±0.2% when measuring with the improved RBF method. The maximum error and minimum error is respectively ±4.0% and ±0.3% when measuring with the BP network method.

■ Fig. 2. Comparison of measure results between textual algorithms to BP neural network algorithms.

Compare the Measuring Results with the Method of Improved RBF to that with Regular RBF Method

Computational scales for these two methods are compared with the same initial conditions. The initial conditions are: three input variables and one output variable with 300 learning samples. The conventional algorithm takes the same feature samples as one group by clustering algorithm, reducing the hidden nodes from 250 to 164. The improved Gram-Schmidt method[17~18] is used to solve network weight and confirm the numbers of the hidden nodes automatically, reducing the hidden nodes to 56. The maximum error range error is respectively ±1.9% and ±3.1% when measuring with the improved RBF method and regular RBF method.

■ Fig. 3. Comparison of measure results between textual algorithms to RBF network algorithms.

Conclusion

The data fusion method of RBF neural network is adopted in this study. With improved orthogonal-optimizing method, the study shows, while the RBF nerve network's weighing factors are obtained, the number of hidden units can be acquired. This method can avoid too few nerve elements that will result has been approved for its advantages over the ordinary methods with laboratory tests on grain of wheat, rice, corn, etc [19~20].

Fig. 1 .

 1 RBF network structure of moisture measurement system.

12 [

 12

1 u

 1 , at the same time ,, 2I uu minus the parallel component of

4. 2

 2 Figure2shows the compared curves of the measuring result using two methods. The solid line and dotted line show respectively the measuring error made by the improved RBF method, and that made by BP network method[15~16].The maximum error and minimum error is respectively ±1.9% and ±0.2% when measuring with the improved RBF method. The maximum error and minimum error is respectively ±4.0% and ±0.3% when measuring with the BP network method.

Figure

  Figure shows the compared curves of the measuring result using two methods. The solid line and dotted line show respectively the measuring error made by the improved RBF method and regular RBF method.The maximum error range error is respectively ±1.9% and ±3.1% when measuring with the improved RBF method and regular RBF method.

Table 1 .

 1 . Compare the Standard Values to the Results Processed without Data Fusion

	No.	y (%)	d (%)	Error (%)	No	y (%)	d (%)	Error (%)
	1	6.29	6.2	1.5	9	14.02	14.5	-3.3
	2	7.26	7.1	2.2	10	14.74	15.2	-3.0
	3	8.15	8.3	-1.8	11	15.55	16.1	-3.4
	4	8.82	9.0	-2.0	12	18.41	17.7	4.0
	5	10.02	10.2	-1.8	13	19.72	19.0	3.8
	6	10.78	11.0	-2.0	14	21.19	20.3	4.4
	7	12.67	12.3	3.0	15	6.60	6.5	1.6
	8	14.02	13.6	3.1	16	7.45	7.3	2.1

Table 2 .

 2 Compare the Standard Values to the Results Processed By Improved RBF Neural Network

	No.	y (%)	d (%)	Error (%)	No	y (%)	d (%)	Error (%)
	1	6.29	6.2	1.45	9	14.56	14.5	0.41
	2	7.12	7.1	0.28	10	15.43	15.2	1.51
	3	8.32	8.3	0.24	11	16.44	16.1	2.11
	4	9.03	9.0	0.33	12	17.66	17.7	-0.26
	5	10.22	10.2	0.20	13	18.96	19.0	-0.21
	6	10.20	11.0	1.82	14	20.50	20.3	0.99
	7	12.68	12.3	3.09	15	6.61	6.5	1.69
	8	13.19	13.6	-3.01	16	7.34	7.3	0.55


Yao Zhan

Yi Lin

Chunfang Wang

Jianping Li

Yong Yu

Application of quadratic rotation-orthogonal composite experimental design to Assess the relationship between growth environment and ultraweak luminescence of mint

Keywords: mint, growth environment, ultraweak luminescence

Quadratic rotation-orthogonal composite experimental design was applied in this experiment to obtain the ultraweak luminescence property of mint affected by multilateral growth environmental factors including illumination, temperature, humidity, and moisture. The influence models of four factors on luminescence were established. Analysis showed that different factors and their interactions had different effect on luminous value, among which the interaction of illumination and humidity had the most significant influence on luminescence of mint (p ≤ 0.01). And the maximum luminous value was obtained when ten stick of lamp tube (intensity of illumination value 4229 Lx) was used, mean temperature, humidity and water were 35 ℃, 85% and 90 mL/d respectively. On the base of that, linear effects and their interactions that affected ultraweak luminescence were also studied.

Introduction

It is one century since people know the ultraweak luminescence of plants. Although the mechanism has not been completely revealed, researches have already demonstrated that ultraweak luminescence is a dynamic indicator that reflects the metabolism, function mediation and information exchange inner and outer the cells in organisms [START_REF] Ramamoorthy | Induction of systemic resistance by plant growth promoting rhizobacteria in crop plants against pests and diseases[END_REF][START_REF] Zhang | Ultraweak bioluminescence in plant[END_REF] . The discovery of the intimate positive correlation between plant luminescence and vitality is one of the most basic achievements and is one of the most important detecting techniques applied in modern farming management [START_REF] Lie | Laser microbeam technique, biological ultraweak photon emission and biological vitomystery[END_REF] .

For instance, viability and luminescence of soybeans were improved significantly after electromagnetic radiation. But the viability of Mung bean was brought down by using metabolic inhibitor, and the same as the luminescence [START_REF] Zhang | Ultra-weak Chemiluminescence Analytical Technology Principle and Application[END_REF] . Similar consequences were obtained in previous studies with rice, peanut leaf and spinach [START_REF] Zhang | Application of ultraweak bioluminescence in vegetable research[END_REF] .

On the basis of that, many researches aiming at viability support and detection were done to study rules and factors that influence the bio-photon emission. Plant's viability and luminescence are affected by some physical (oxygen, temperature, irradiation, etc.) [START_REF] Cheng | Study on ultraweak luminescence of pisum sativum seeds at the stage of germination[END_REF][START_REF] Tan | Spectral studies of ultra-weak biophoton emission from Plant's leabes[END_REF][START_REF] Ma | Vegetable seed radiosensitivity and kinetic analysis of super-weak bioluminescence[END_REF][START_REF] Gao | A preliminary study of irradiation disturbance on the rapid bacteria assay with ATP bioluminescence technique for agricultural products[END_REF] , chemical (oxidant, metabolic inhibitor, etc.) factors [START_REF] Chen | Rapid determination of rice seed vigour by spontaneous chemiluminescence and singlet oxygen generation during early imbibition[END_REF] , hormone and environmental stress [START_REF] Strand | Some agrometeorological aspects of pest and disease management for the 21st century[END_REF][START_REF] Yazgan | New approach for calculating the relative risk level of pesticides[END_REF][START_REF] Li | The study of a system for the diagnosis and prevention of pests, diseases and nutritional deficiency of greenhouse tomato[END_REF] . Benefited from the development of electronic and information technology, the alteration of plant's luminescence will be identified preferentially before the change of viability property is observed. It facilitates the application of ultraweak luminescence technology in the fields of industrial seeding nursery, intelligent cultivation and breed.

However, the study of plant's ultraweak luminescence is not complete, especially the luminescence properties affected by multilateral growth environment factors, and the effect of interaction of different factors is not clear to plant luminescence, which significantly restricts the application in the fields mentioned before.

In this article, quadratic rotation-orthogonal composite experimental design was used to study the luminescence properties of mint that affected by multilateral growth environment factors, and the relationship between luminescence properties and different factors and their interaction was explored. Correlative knowledge was prepared to facilitate the application of ultraweak luminescence testing technology in modern farming management.

Materials and methods

Materials and processing

15 bonsai of mints were supplied by Zhongtai nursery stock base of Hangzhou New Blue-Sky Landscape Group, mints grew in a greenhouse with identical environment and nutrient conditions for 45 days, and the degrees of dense foliage were kept similar.

Mints were put into an artificial climate incubator (Artificial Climate Box, RXZ) after collected, kept in 30℃ and 90% in humidity and exposed in light before use. The experiment was carried out on three replicates.

Range of environment factors

The environment factors of osmanthus tree seedings include illumination, temperature, relative humidity and moisture. These factors were controlled by RXZ except for moisture that artificially controlled by using a injector with scales. Ranges of these four factors were formulated as follows: Humidity: the relative humidity was controlled by RXZ at 65%~85%, accuracy is ±1%.

Moisture: according to the moisture range (10~90 mL/d) obtained from preliminary test, moisture was controlled artificially by using a injector with scales at the same time of everyday.

Measurement of ultraweak luminescence value

The optimum detect condition of ultraweak luminescence was obtained from pre-experiment. mint was cultivated in given conditions for 3 days before test, 0.2 g of mint (leaves) was detected under 35 ℃ to get the maximum luminescence value.

Photo-induced delayed luminescence was observed at the beginning of test, emission of mint leaves in constant time interval decreased rapidly and waved evidently. After 3 ~ 5 min, delayed luminescence disappeared gradually, emission tended to be steady. Hence, the whole data acquisition time of each experiment was 10 min, and data of last 5 min was adopted (detection cup without samples as control).

Experimental design and data analysis

Quadratic rotation-orthogonal composite experimental design was used to analyze the effect of illumination, temperature, relative humidity, moisture, and interaction to the luminescence of samples. Quadratic rotation-orthogonal composite experimental design in coded and actual level of variables and the luminous value of each sample were detected (data not shown). 36 experiments were carried out with 12 replicates at the center point.

The result was analyzed to build the model of environmental factors to ultraweak luminescence by using Data Processing System (DPS), the optimum values of environment variables were obtained when luminous value was maximum, and the effects of influential factors and interactions on luminescence of mint were further studied.

Results and analysis 2.1 Regression analysis and optimal parameter analysis

Polynomial regression equation with linear, quadratic and interaction terms was obtained by using DPS, analysis of variance (ANOVA) of each effect was shown in Tab.1.

Tab. 1 showed effects of single factors and interactions of four environment factors of four environment variables on the luminous value of mint. the regression equation of response function had a high correlation coefficient (r=0.993), can be used to predict luminous value of mint in trial stretch. To determine the value of four factors including illumination, temperature, moisture and humidity required by mint, optimal calculation of luminous value was carried out based on the intimate positive correlation between luminous value and viability of plants. Results showed that the maximum luminous value of mint (18.7 photon/s) was acquired when 10 lamps were used (illumination value was 4 229 Lx), temperature, humidity and moisture were 35 ℃, 65% and 90 mL/d respectively. Because of the intimate positive correlation between luminous value and viability of plants, viability of mint was higher under the optimum environmental condition than that under any other conditions.

Analysis of effect of each factor and interaction on ultraweak luminous value

In order to facilitate further analysis of single factors and interaction effects on luminous value, the regression model shown in Tab.1 was corrected. First, non-significant terms in Tab.1 were rejected, the rest of terms (coded level) constitute the relational model with the luminous value of mint (Eq.1). The correlation coefficient was further elevated (r=0.953).

Y=1.83119-0.62317x 3 +0.67242x 4 +0.48344x

1 2 +0.44216x 3 2 +0.48463x 4 2 -0.84385x 1 x 3 +0.54536x 1 x 4 +0.77622x 2 x 4
(1) Luminous value (viability) of mint was higher while illumination increased, that is because light is energy source of photosynthesis, and is the essential growth condition for chloroplast development and chlorophyll synthesis. Light can also regulate the activity of some enzymes in carbon cycle of photosynthesis. At some extent, a linear increase was observed in photosynthetic rate with the increase of illumination. Fig. 5 showed that the luminous value changed with moisture, firstly luminous value initially decreased then increased with moisture, with the increase of temperature, luminous value became increased with moisture. Similarly, luminous value of mint decreased with the increase of temperature when moisture was in low level, but with the increase of moisture, luminous value became increased with temperature. It indicated that environmental temperature affected the luminous value, but the impact was performed by the interaction of temperature and moisture, and the interaction had significant effect on luminous value of mint (Tab. 1).

Effect of each factor on ultraweak luminous value of mint

Interaction effect of three factors on ultraweak luminous value of mint

Conclusion

Single factors and interactions of illumination, temperature, humidity and moisture all have effect on the luminous character of mint leaves. For single factors, moisture and humidity have more significant effect on luminescence of mint than others. The

  Illumination: according to the average illumination of the greenhouse, illuminance was regulated by ten 40 W fluorescent tubes, intensity was controlled by opening different numbers of tubes (intensity of one 40 W fluorescent tube is 422.9±10.1 Lx). Temperature: the temperature range was automatically controlled by RXZ at 15 ℃ ~ 35 ℃, accuracy was ±0.5 ℃.

Fig.( 1 - 3 )

 13 Fig.(1-3) showed that luminous value of mint increased with illumination and moisture, but decreased with humidity when the other factors were optimum. The maximum luminous value of mint was obtained when 10 lamps were used (mean

Furthermore, as the

  photosynthesis rate and viability of plants. In other words, luminous value increased when humidity decreased.

Fig. 1 .Fig. 2 .Fig. 3 .Fig. 4 .

 1234 Fig. 1. Effect of illumination on the bio-illumination of mint sample

Fig. 4

 4 Fig.4showed that the variation trend of luminous value changed with varied

Fig. 5 .Fig. 6 .

 56 Fig. 5. Effect of moisture and illumination on the bio-illumination of mint sample

  interaction of illumination and humidity has the most significant effect on luminescence. Besides, the mathematical model established in this study effectively reflects the impacts of various environment factors on ultraweak luminous properties of mint. Acknowledgements. This research was supported by a grant from the Research Fund for the Doctoral Program of Higher Education of China (RFDP) (No. 20090101120081), the major science and technology project of Science Technology Department of Zhejiang Province, China (No. 2008C02006-4), and the project of Education Department of Zhejiang Province, China (No. Y20080327).

Table 1 .

 1 Model and condensed ANOVA (analysis of variance) table in coded level of -light, x 2 -temperature, x 3 -relative humidity, x 4 -moisture.

		variables
	Source of variations	Coefficient of polynomial	F-Value
		1.83119
	x 1	0.04471	0.03496 NS
	x 2	0.12061	0.25445 NS
	x 3	-0.62317	6.79296**
	x 4	0.67242	7.90896**
	x 1 2	0.48344	5.45088**
	x 2 2	0.07280	0.12361 NS
	x 3 2	0.44216	4.55968**
	x 4 2	0.48463	5.47771**
	x 1 x 2	0.14325	0.23931 NS
	x 1 x 3	-0.84385	8.30386***

NS

Non-significant at p > 0.10. * Significant at p ≤ 0.10. ** Significant at p ≤ 0.05. *** Significant at p ≤ 0.01.


Yong Yu

Yao Zhan

Yi Lin

Chunfang Wang

Jianping Li
email: jpli@zju.edu.cn

Application of Quadratic Rotation-Orthogonal Composite Experimental Design to Assess the Relationship between Growth Environment and Ultraweak Luminescence of Osmanthus Tree Seedings

Keywords: Osmanthus tree seedings, Growth environment, Ultraweak luminescence

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Ultraweak luminescence is a kind of low level biological photon emission which was first discovered by a former Soviet Union scientist G. Gurwitsh in his famous onion experiment in 1923. Although the mechanism is not revealed completely up to now, it has been demonstrated that ultraweak luminescence is a dynamic indicator that reflects the metabolism, function mediation and information exchange inner and outer the cells in organisms [START_REF] Ramamoorthy | Induction of systemic resistance by plant growth promoting rhizobacteria in crop plants against pests and diseases[END_REF][START_REF] Zhang | Ultraweak bioluminescence in plant[END_REF] . The discovery of the intimate positive correlation between plant luminescence and vitality is one of the most basic achievements and is one of the most important detecting techniques applied in modern farming management [START_REF] Lie | Laser microbeam technique, biological ultraweak photon emission and biological vitomystery[END_REF] .

Researches showed that viability and luminescence of soybeans were improved significantly after electromagnetic radiation. The viability of Mung bean was brought down by using metabolic inhibitor, and the same as the luminescence [START_REF] Zhang | Ultra-weak Chemiluminescence Analytical Technology Principle and Application[END_REF] . Similar consequences were obtained in previous studies with rice, peanut leaf and spinach [START_REF] Zhang | Application of ultraweak bioluminescence in vegetable research[END_REF] .

On the basis of that, many researches aiming at viability support and detection were done to study rules and factors that influence the bio-photon emission. Plant's viability and luminescence are affected by some physical (oxygen, temperature, irradiation, etc.) [START_REF] Cheng | Study on ultraweak luminescence of pisum sativum seeds at the stage of germination[END_REF][START_REF] Tan | Spectral studies of ultra-weak biophoton emission from Plant's leabes[END_REF][START_REF] Lin | Changes in ultraweak luminescence intensity, respiration rate and physiological metabolism of chrysamthemum during floral differentiation[END_REF][START_REF] Guo | Effects of high temperature on bioluminescence and energy metabolism of malus hupehensis (Pamp) rehd.var.pingyeensis jiang[END_REF] , chemical (oxidant, metabolic inhibitor, etc.) factors [START_REF] Chen | Rapid determination of rice seed vigour by spontaneous chemiluminescence and singlet oxygen generation during early imbibition[END_REF] , hormone and environmental stress [START_REF] Strand | Some agrometeorological aspects of pest and disease management for the 21st century[END_REF][START_REF] Yazgan | New approach for calculating the relative risk level of pesticides[END_REF][START_REF] Li | The study of a system for the diagnosis and prevention of pests, diseases and nutritional deficiency of greenhouse tomato[END_REF] . Benefited from the development of electronic and information technology, the alteration of plant's luminescence can be identified ahead of the change of viability. It effectively facilitates the application of ultraweak luminescence technology in the fields of industrial seeding nursery, intelligent cultivation and breed.

However, the study of plant's ultraweak luminescence is not complete, especially the luminescence properties affected by multilateral growth environment factors, and the effect of interaction of different factors is not clear to plant luminescence, which significantly restricts the application in the fields mentioned before.

In this article, quadratic rotation-orthogonal composite experimental design was used to study the luminescence properties of osmanthus tree seedings that affected by multilateral growth environment factors, and the relationship between luminescence properties and different factors and their interaction was explored. Correlative knowledge was prepared to promote the application of ultraweak luminescence testing technology in modern farming management.

Materials and methods

Materials and processing

of Hangzhou New Blue-Sky Landscape Group, seedings grew in a greenhouse with identical environment and nutrient conditions for 30 days, and the degrees of dense foliage were kept similar. Seedings were put into an artificial climate incubator (Artificial Climate Box, RXZ) after collected, kept in 30℃ and 90% in humidity and exposed in light before use. The experiment was carried out on three replicates.

Range of environment factors

The environment factors of osmanthus tree seedings include illumination, temperature, relative humidity and moisture. These factors were controlled by RXZ except for moisture that artificially controlled by using a injector with scales. Ranges of these four factors were formulated as follows:

Illumination: according to the average illumination of the greenhouse, illuminance was regulated by ten 40 W fluorescent tubes, intensity was controlled by opening different numbers of tubes (intensity of one 40 W fluorescent tube is 422.9±10.1 Lx).

Temperature: the temperature range was automatically controlled by RXZ at 15 ℃ ~ 35 ℃, accuracy was ±0.5 ℃.

Humidity: the relative humidity was controlled by RXZ at 65%~85%, accuracy is ±1%.

Moisture: according to the moisture range (10~90 mL/d) obtained from preliminary test, moisture was controlled artificially by using a injector with scales at the same time of everyday.

Measurement of ultraweak luminescence value

The optimum detect condition of luminescence was obtained from pre-experiment.

Osmanthus seedings were cultivated in given conditions for 3 days before test, 2 g of seedings (leaves) were detected under 35 ℃ to get the maximum luminescence value.

Photo-induced delayed luminescence was observed at the beginning of test, emission of seeding leaves in constant time interval decreased rapidly and waved evidently. After 3 ~ 5 min, delayed luminescence disappeared gradually, emission tended to be steady. Hence, the whole data acquisition time of each experiment was 10 min, and data of last 5 min was adopted (detection cup without samples as control).

Experimental design and data analysis

Quadratic rotation-orthogonal composite experimental design was used to analyze the effect of illumination, temperature, relative humidity, moisture, and interaction to the luminescence of samples. Quadratic rotation-orthogonal composite experimental design in coded and actual level of variables and the luminous value of each sample were detected (data not shown). 36 experiments were carried out with 12 replicates at the center point.

The result was analyzed to build the model of environmental factors to the luminescence by using Data Processing System (DPS), the optimum values of environment variables were obtained when luminous value was maximum, and the effect of influential factors and interaction on luminescence was further studied.

Results and analysis

Regression analysis and optimal parameter analysis

Polynomial regression equation with linear, quadratic and interaction terms was obtained by using DPS, analysis of variance (ANOVA) of each effect was shown in Tab.1.

Tab.1 showed that linear effects of 4 environment factors significantly (P ≤ 0.01) affected the luminous value of leaves, according to P-value, the impact of each linear effect followed the order: moisture > humidity > temperature > illumination and the impact of nonlinear effect followed the order: moisture > humidity > illumination > temperature. Hence, moisture, humidity, illumination, temperature were all significant factors that influenced the growth of seeding leaves, and should be paid attention in modern farming management. Non-significant at p > 0.10; * Significant at p ≤ 0.10; ** Significant at p ≤ 0.05; *** Significant at p ≤ 0.01.

Besides, interactions of four environment factors had different influence on the luminous value of seeding leaves. It was revealed that moisture was a crucial factor which affected the growth of seedings, its importance was reflected not only in it as a single factor, but also in the strong interaction between it and the other three factors.

Nevertheless, illumination had no strong interaction with temperature or humidity, therefore, regulation of moisture and illumination should be attached great importance in modern farming management of osmanthus tree seedings.

Tab.1 also showed that regression equation of response function had a high correlation coefficient(r=0.993), can be used to forecast luminous value of seedings in trial stretch.

To determine the value of four factors including illumination, temperature, moisture and humidity required by osmanthus tree seedings [START_REF] Lie | Laser microbeam technique, biological ultraweak photon emission and biological vitomystery[END_REF] , optimal calculation of luminous value was carried out based on the intimate positive correlation between luminous value and viability of plants. Results showed that the maximum luminous value (48.11 photon/s) was acquired when 10 lamps were used (illumination value was 4 229 Lx), temperature, humidity and moisture were 35 ℃, 65% and 90 mL/d respectively. Experiments showed that luminous value was 45.76 photon/s under this optimum condition, slightly lower than the predicted value, but higher than that under other experimental conditions.

Analysis of effect of each factor and interaction on ultraweak luminous value

In order to facilitate further analysis of single factors and interaction effects on luminous value, the regression model shown in Tab.1 was corrected. First, non-significant terms were rejected, the rest of terms (coded level) constitute the relational model with the luminous value of osmanthus (Eq.1).

Y=4.3258+1.4379x1+1.6296x2+1.5571x3+3.2204x4+1.0128x12+0.7103x22+0.9153x32 +1.3853x42+0.7056x1x2+1.3894x1x4-1.1431x2x3+1.0469x2x4+0.9381x3x4

The correlation coefficient was further elevated (r=0.983).

2.2.1

Effect of each factor on ultraweak luminous value of osmanthus tree seedings Different from effects of other interactions, interaction of temperature and humidity was unique to luminescence of osmanthus. Almost linear correlation was observed between temperature and luminous value when osmanthus tree seedings were in low humidity, with the increase of humidity, luminous value became initially decreased then increased. Furthermore, the maximum luminous value appeared at the maximum temperature in the condition of low humidity, in contrast the maximum luminescence showed at the minimum temperature when it was in high humidity. Meanwhile, the minimum luminescence in high humidity was much higher than that was in low humidity. The same trend was observed in humidity.

So it should be noticed in modern farming management of osmanthus tree seedings that the influence of humidity on viability reduced while in high temperature, and when it was in high humidity, effect of temperature decreased in the same way. Hence, energy could be saved by controlling one of the two factors.

Discussion

Fig. 1-Fig. 3 showed that no matter single factor response curve or two-factor response surface, there was a minimum luminous value of seedings influenced by illumination, temperature, humidity and moisture. Luminescence increased when variables were higher or lower than that corresponding to the minimum luminous value. It could not explained that growth of osmanthus tree seedings was promoted when four variables were higher or lower than certain critical values.

It can be explained by Liu [START_REF] Liu | Homeostatic photobiomodulation[END_REF] who demonstrated the theory of coherent states and its application in physical stimulation of acupoint [15][START_REF] Liu | Time theory on meridian: I. Acupoint research[END_REF] . According to the theory, acupoint is commonly existed in organisms, and it affects bio-photon emission.

Generally, most normal cells in organisms like osmanthus tree seedings are in a sub-change state, and photons can be easily stored in this state. In other words, osmanthus seedings are in the most steady state when photon emission is lowest.

When environmental variables are higher or lower, the growth status is destroyed and then pathological phenomena such as the increase of luminescence are observed.

For instance, oversized and undersized cells both indicate pathological changes in human body. However, this pathological phenomenon is sometimes profitable when it comes to sensory demanded plants and animal products. For example, when environmental variables are higher than the most stable level, osmanthus tree may be taller, having larger leaf area and more buds, though it is a pathological phenomenon strictly. These can be explained by the physiological resistance of bio-systems when the environment condition deviates the most stable state. For modern farming management, it is to take advantage of this bio-resistance to get products that meet these sensory needs.

Conclusion

Single factors and interactions of illumination, temperature, humidity and moisture have effect on the luminous character of osmanthus tree seeding leaves. This is explained by the variation of acupoint state when the environment factors change. For single factors, moisture and humidity are more significant than illumination and temperature. For interactions, the interactions of illumination and moisture, temperature and humidity have the most significant influence on bio-emission, and the interaction of temperature and humidity has particular effect comparing with others.

In addition, the mathematical model established in this study effectively reflects the impacts of various environmental factors on ultraweak luminous properties of osmanthus tree seedlings.

Fig. 1 and

 1 Fig.1 and Fig.2 showed that luminous value of seedings first decrease then increase with four single factors when the other factors were zero. The maximum luminous value was obtained when factors reached maximum respectively, and because of the positive correlation between ultraweak luminescence and viability of plants.

Fig. 1 .Fig. 2 .Fig. 3 .

 123 Fig. 1. Effect of illumination and temperature on the bio-illumination of osmanthus tree seedings sample

Table 1

 1 Model and condensed ANOVA (analysis of variance) table in coded level of

		variables
	Source of variations	Coefficient of polynomial	F-Value
	Constant	4.3258	-
	x 1	1.4379	21.02781***
	x 2	1.6296	27.00721***
	x 3	1.5571	24.65757***

Note: Variables: x 1 -light, x 2 -temperature, x 3 -relative humidity, x 4 -moisture.

Acknowledgements. This research was supported by a grant from the Research Fund for the Doctoral Program of Higher Education of China (RFDP) (No. 20090101120081), the major science and technology project of Science Technology Department of Zhejiang Province, China (No. 2008C02006-4), and the project of Education Department of Zhejiang Province, China (No. Y20080327).


Hong Chen

Qiyong Weng

Meixiang Chi

Rongzhou Qiu

Jian Zhao
email: zhaojian@faas.cn

Construction of Monitoring System of Dangerous and Harmful Species of Import Taiwan Fruits and Vegetables Based on GIS

Keywords: GIS, import Taiwan fruits and vegetables, dangerous and harmful species, monitoring system

In order to improve the efficiency of dangerous and harmful species monitoring of import Taiwan fruits and vegetables and achieve informatization, networking and visualization of monitoring, this paper uses geography information system technology to develop monitoring system of import Taiwan fruits and vegetables dangerous and harmful species on the basis of the analysis of monitoring business needs. The system realizes some useful functions, such as showing monitoring data in map, map operation, monitoring data report and monitoring data management. This paper supply informatization supporting platform to dangerous and harmful species monitoring of import Taiwan fruits and vegetables and provide information support for scientific decision-making of alien invasive biological prevention and control department.

Introduction

In recent years, with the cross-strait relations gradually easing, between two sides of the agricultural cooperation and trade also have entered a development of the fast lane. From the CPC Central Committee and the State Council departments at all levels have issued a series of preferential policies to promote cross-strait agricultural exchanges and cooperation and to encourage Taiwan farmers to the mainland venture capital. Due to the expansion of cross-strait agricultural trade require fast inspection of Taiwan's agricultural products and implement a policy named "green clearance" to fruit and vegetable of Taiwan on entry inspection and quarantine. The fruit and vegetable of Taiwan planting area expands unceasingly in the mainland, constantly increasing the risk of pests and diseases of the Taiwan fruits and vegetables at the introduction. The high-risk diseases and pests within Taiwan fruits and vegetables have found on the mainland, which create potential big losses for fruit and vegetable planting in the mainland [START_REF]Network collaboration platform of Dangerous and Harmful Species of Import Taiwan Fruits and Vegetables Prevention and control technology research and demonstration[END_REF]. In response to this form, to carry out the entry of dangerous and harmful species monitoring of Taiwan fruits and vegetables and to keep abreast of the occurrence and distribution of the epidemic have great significance to formulate scientific prevention and control measures.

Recently, quarantine departments have been monitoring and researching dangerous and harmful species found in fruits and vegetables entering Taiwan and have achieved certain results, in coastal provinces importing a large number of Taiwan fruits and vegetables [START_REF] Huimin | A Preliminary Report on the Monitoring of Bactrocera in Fuzhou[END_REF], [START_REF] Furong | Detection and Pathotype Identification of Pepper Mild Mottle Virus in Sweet Pepper Seeds from Taiwan[END_REF], [START_REF] Furong | Detection and Identification of Acidovorax Citrulli from Imported Watermelon Seeds[END_REF], [START_REF] Furong | Detection and Identification of the Tomato Mosaic Virus in Imported Tomato Seeds[END_REF], [START_REF] Pengying | Taiwan's Wax Apples Intercepted Anselmella miltoni Girault[END_REF]. However, most of the monitoring also used handwritten notes, which are not conducive to data preservation and could easily damage and loss records. This will impact analysis and research of monitoring data in the future. In addition, most of the monitoring data are detailed position information, reflecting the significant spatial distribution characteristics. The monitoring of the spatial distribution and the route of transmission of invasive alien species is one of the core content of the work of prevention and control. How about making the monitoring data of the spatial distribution characteristics to get a better display, data management and application issues need to be addressed. In view of the above consideration, this paper proposes building a monitoring system of import Taiwan fruits and vegetables dangerous pests based on GIS. With GIS spatial data processing and display capabilities, combined with the techniques of database technology, network technology and rich client technology, develop data reporting and management platform for dangerous and harmful species monitoring, which provides decision support for quarantine and pest prevention and control.

System Design

System Construction Goal

Dangerous and harmful species monitoring monitors and detects the occurrence and development of a certain period of the disease, pests or weeds within a certain range [START_REF] Wancai | Thought on Promote Agricultural Pest Monitoring and Warning Development[END_REF]. However, a complete dangerous and harmful species monitoring system should include a standardized monitoring processes and standardized data management system. According to the monitoring requirements, the goal of constructing the monitoring system of dangerous and harmful species of import Taiwan fruits and vegetables includes below elements.

1. Establish monitoring data standard of dangerous and harmful species of import Taiwan fruits and vegetables and establish a unified database.

2. Apply GIS technology to realize dangerous and harmful species monitoring data online publishing, data display and spatial queries, providing decision-making of prevention and control with spatial distribution data.

3. Realize multi-source collaborative dangerous and harmful species monitoring data reporting, auditing, and management, supplying unified data management and sharing platform to monitoring.

System Framework

The development of the monitoring system of dangerous and harmful species of import Taiwan fruits and vegetables uses the browser/server framework of multi-tier architecture. Improving system maintainability, security, and extensibility, system reasonably splits functionality and business logic in different layers, as fig. 1. show The framework of system business functions is divided into four layers except system users. User performance layer is responsible for system interaction with the user, receiving user input or data reported and returning the results of the system running. Data service layer sets up map data and business data transmission channel between the user and the system. Business logic layer achieves all business processing functions of the system. Data storage layer is used to store various types of system information. At the same time, monitoring data standards and data management mechanisms ensure the efficient operation of the system and standardized management.

System Business Process

In the business process, the system operation and management staff can be divided into: fields investigator, data manager, data auditor and administrator. All categories of staff have different permissions, as fig. 2 show. The field investigator is responsible for monitoring the occurrence and spread of dangerous and harmful species and submitting monitoring data to the system through the network. Monitoring positions and monitoring objects depend on the basic data included in the system database. In practice, if the monitoring positions and the monitored objects change, investigator data must require the administrator to apply for basic data changes. The data manager is responsible for basic data management and change. The administrator is responsible for managing system users, user permissions and the map services. The data auditor is responsible for auditing and publication of the data. The monitoring data and the basic data changes passed audit can be entered into the database and data that has not been approved will be sent back to the data submitter to modify. Only approved data will be released.

Fig. 2. The system business process

Data standards and database design

In order to ensure the standardization of the system data resource construction, this paper developed pest monitoring data collection standards and basic data collection standards based on the monitoring practice. Among them, pest monitoring data collection standards include: pest survey standard, disease survey standard, weed survey standard and specimen labeling standards. The basic data collection standards, including: data standards of fruit and vegetable, fruit and vegetable cultivation data standards, data standards of monitoring positon and species data standards. In addition, data forms were specially designed for each type of data content.

The system database design is based on data standards, to meet the needs of business operation of the system. The system databases are made up of business databases and spatial databases. The business databases manage dangerous and harmful species monitoring and systems running data, including five aspects: investigation of dangerous and harmful species data( pests, diseases, weeds, specimen labels), fruit and vegetable varieties of resources data, fruit and vegetable planting data, monitoring positions data( plantation, processing enterprises, distribution center, the port of entry), and system management data(users information, system permissions).The spatial databases store basic geographic data for the map display, including national administrative divisions data (province, municipality and county), national administrative center data(province, city, county, township and village), railways, roads and rivers, etc.

System realization

Development tools and runtime environment

After fully considering the construction goal and the function design, system of the development tools and runtime environment in the following table: Adobe Flash Player multiple data response and transaction processing between the client and server, which cause the page repeatedly refresh and affect the system user experience effect [START_REF] Junwei | Primary Designing and Implementation of Monitoring Information System for Epidemic Situation of Quarantine Pest Based on ArcGIS and[END_REF]. At the same time, traditional Web applications due to the scalability, interaction, semantic, page links and other problems, resulting in inefficient system development, difficult maintenance, that limits the system application [START_REF] Yonggang | Discussion of WebGIS Reseach Based on Flex_RIA and REST[END_REF]. To solve these problems, the Rich Internet Application(RIA) technologies used in the development of the system to compensate for the lack of traditional Web applications.

The RIA effectively integrates desktop applications powerful user interaction with the Web application cost-effective deployment and excellent cross-platform features, representing the new trend of the development of network application [START_REF] Liang | Research on Hydro-environment Analysis System of Three Gorges Reservoir Based on RIA[END_REF]. System WebGIS interfaces used Adobe's RIA framework -the Flex, with ESRI's ArcGIS API for Flex development components, achieving rich spatial data display and user experience.

GIS Service technology

GIS service is a set of functional entities of geographic information software in the network environment, exposing package functionality through the interface [START_REF] Dayu | Research and Realization of Composition of Geographic Information System Services Based on BPEL[END_REF]. It combines the Web Service technology and GIS technology with the characteristics of cross platform, telescopic, fully functional, system integration and low cost, and high degree of standardization, that provides an effective solutions to the GIS system of internal coupling high ,lack of interoperability, difficulty integrate with other systems and other issues [START_REF] Xiaojun | Design and Implementation of the Spatial Decision Support System for Agriculture[END_REF]. This paper used ArcGIS Server software releases REST standard data interface as GIS services. Independent service for different functional applications is deployed to achieve the efficient sharing of multi-source geographic data, providing basic geographic information support to unified system data display.

Tile map technology

If the client browses the map using real-time rendering mode, each response from the server to the client's request must be each real-time rendering maps and results are returned to the client display. Considering the application environments of the system which are mostly in the relatively backward areas of rural that have terrible network infrastructure conditions,real-time map rendering is not only inefficient but also affect the user operation. Therefore, the deployment of the system used a tile map technology to cache map in the server. When the client initiates a request can be directly read static images in the cache, which can effectively improve the mapping and transmission efficiency and provide fast map display effect [START_REF] Menglong | Study on the Application of Tile Map Technology in Desktop GIS[END_REF].

System function realization

The monitoring system of dangerous and harmful species of import Taiwan fruits and vegetables is divided into: monitoring data published and display subsystem and monitoring data reported and management subsystem, as fig. 3 show: Fig. 3. The system function structure

Construction of monitoring data published and display subsystem

The monitoring data published and display subsystem using GIS technology is responsible for displaying data to public users and realizes data browse and query based on map interface, as fig. 4 show. As the use of RIA technology makes interface with drag controls, smooth scrolling animation, effect enhances the display of maps and get rid of the traditional Web page monotonous user operation. This subsystem has main functions below: 1. Map operations: the realization of the basic map interface operations. For example: zoom in, zoom out, pan, full extent, overview map, layer management and so on.

2. Data browser: do not enter any query to display data to help the user quickly view the data on the map. When you open a type of data query window, the subsystem will automatically display in the map for all of this type data spatial distribution points. Click on one point will pop-up detail information box of the data.

3. Data query: the subsystem data query function has three types, including monitoring data query, monitoring position data query and fruit and vegetable distribution data query. Different types have different terms in the query. Subsystem uses separate query window for each query type and the query results also uses a different marker style to show the distinction to increase the contrast effect of the spatial distribution of different data types. In addition, most of the type of query can be subdivided into subclass, in the same query window using different page tab to arrange query condition. When you close the query window, the subsystem will clear the results of the map and free up system resources.

4. Auxiliary function: provide mapping, positioning bookmark, print and other complex map operations. These features improve the ability to interact with the map interface and a supplement to map operations.

Construction of monitoring data reported and management subsystem

The monitoring data reported and management subsystem is responsible for system management and data maintenance, which don't open to the public users. The user groups of the subsystem are limited to the four kinds of system managers. The subsystem through the user account and access control to restrict the operation of the different users, preventing data breaches caused by the different users cross operation. This subsystem has main functions below:

1. Users management: supply the management of the system user data and permissions configuration. Due to the particularity of the system data reporting and management of business, users management operations only by the system administrator.

2. Monitoring data management: this function includes data reporting and audit. Data reporting page provides data furnished, the data submitted and data status view. When submitting large amounts of data, the system can save the data reported in batches until all data furnished. Monitoring data audit page lists the reported monitoring data in list form.The data auditor can select a data record to view detailed information about it. If the data is qualified by the audit, it will be entered into the system database. If the data is not approved, it will be displayed in the data status view page in order to further modify by fields investigator.

3. Basic data management: provide the management operations of the system basic data(monitoring positon data, species data and fruit and vegetable distribution data) such as add, modify, and delete. Three kinds of data are located in a different page tab, arranged in a list and switched through the navigation bar.

Construction of basic data

The basic data accumulation is a necessary precondition for carrying out applications. This paper has collected some basic data about Fujian and Guangdong which have imported a large number of Taiwan fruit and vegetable. At present, the system has collected 24 records of fruit and vegetable data; 66 records of dangerous and harmful species data; 132 records of various types of monitoring position data; 230 records of fruit and vegetable distribution data.

Conclusion and Discussion

This paper introduced GIS technology into dangerous and harmful species prevention and control work, analyzed the needs of the business of import Taiwan fruits and vegetables dangerous and harmful species monitoring data management and proposed construction scheme of monitoring system. The system effectively integrates monitor data reporting, management and presentation of business processes based on collaborative division of multi-role labor. In the system construction of the integrated use of RIA, GIS services, tile maps and other information technology, make the interactive experience of the system map interface has been enhanced significantly. The system could provide the prevention and control of decision-making with data in support of import Taiwan fruits and vegetables dangerous and harmful species occurrence and spread, provide information channels for reporting of monitoring data and supply information platform to inter-regional or cross-sectoral monitoring data sharing.

The dangerous and harmful species prevention and control as a systemic project, monitoring is a key component. However, the lack of the functions of epidemic prediction and analysis in support of the IT technology will restrict the application of the system. How is monitoring data effectively applied? How to play GIS technology advantages in spatial analysis? How to combine the monitoring data and prediction models to provide better information services for the prevention and control of decision-making? All of these issues will be addressed in the further focus.

Fig. 1 .

 1 Fig. 1. The system framework

Fig. 4 .

 4 Fig. 4. The monitoring data release and display subsystem interface

Table 1 .

 1 The system development tools and operation environment

3.2 Key technology research 3.2.1 RIA technology

  The WebGIS rely principally on the map interface for data display and interaction. In the traditional Web application, a number of complex applications often require

	Classification	Content	Name
	Development	Web Development Tool	Microsoft VisualStudio 2008
	Tools	Web Development Environment	Microsoft .NET
		Web Development Language	C#
		GIS Development Tool	Adobe Flex 4.0
		GIS Development Language	Actionscript
		GIS Development Component	ArcGIS API for Flex 2.5
	Operation	Database Platform	Microsoft SQL Server 2005
	Environment	Server Operation System	Windows Server 2003 SP2
		Web Service Platform	IIS 6.0
		GIS Service Platform	ArcGIS Server 9.3
		Client Plug-in