Xiaohong Tang

Youjin Luo

Jiake Lv

Chaofu Wei

Mechanisms of Soil Aggregates Stability in Purple Paddy Soil under Conservation Tillage of Sichuan Basin, China

Keywords: ridge culture, rotation, aggregate stability, organic carbon, paddy soil

Ridge culture is a special conservation tillage method, but the long-term influence of this tillage system on soil aggregate-size stability in paddy fields is largely unknown in southwest of china. The objectives of this paper are to evaluate soil aggregates stability and to determine the relationship between SOC and soil aggregate stability.Soil samples at 0-20 cm layer were adopted from a long-term (16 yr) field experiment including conventional tillage: plain culture, summer rice crop and winter upland crop under drained conditions (PUR-r), and conservation tillage: ridge culture without tillage, summer rice and winter fallow with floodwater layer annually (NTR-f), and winter upland crop under drained conditions (NTR-r), and wide ridge culture without tillage, summer rice crop and winter upland crop under conditions (NTRw-r), respectively. The determination of aggregate-size stability distribution involves the assumptions that soil aggregates can be categorized in terms of their size and water stability (slaking resistance). Experimentally this procedure involves the slaked and capillarywetted pretreatments; and a subsequent slaking treatment of aggregates >0.250 mm in size. WSMA and NMWD were applied to simulate the breakdown mechanisms of aggregates for studying soil stability based on aggregate resistance to slaking in paddy soil. The results showed that the amount of aggregates-size was greatly observed in the fraction of 2~6.72 mm under ridge culture in paddy soil (more than 50%) under slaking and capillary-wetting pretreatment. The proportion of soil macro-aggregates (>0.25 mm) in conservation tillage was greatly higher than that in conventional tillage under subsequent slaking treatment. Minimal differences of aggregate stability between slaking and wetting were observed, while significant differences were found between ridge culture and plain culture. The aggregates stability under slaking treatment ranked in the order of NTR-r>NTRw-r> NTR-f>PUR-r, while under wetting was NTRw-r>NTR-r>NTR-f>PUR-r, respectively. There was a positive correlation between the aggregates stability and SOC concentrations under wetting, and low correlation was observed under slaking pretreatment. Soil exposure with tillage and lack of rice/rape-seed stubble inputs caused declines in aggregation and organic carbon, both of which make soil susceptible to water erosion. Adoption of ridge culture with no-tillage integrated with crop rotation and stubble mulch significantly alter soil organic concentration, suggesting it was a valuable conservation practice for soil aggregation and soil organic carbon sequestration on paddy soil.

Introduction

Soil organic carbon (SOC) plays a crucial role in sustaining crop production and environmental soil services. A loss of SOC due to inappropriate land use or soil management practices can affect soil properties and lead to CO 2 emissions into atmosphere. On the other hand, appropriate land use and soil management can lead to an increase in SOC, improve soil properties and partially mitigate the rise in atmosphere CO 2 (Christensen, 1996;Lal and Kimble, 1997;[START_REF] Bernoux | Cropping systems, carbon sequestration and erosion in Brazil, a review[END_REF]. Among the numerous strategies that permit sequestering atmospheric carbon in agroecosystems, ridge culture practices have been well documented [START_REF] Halvorson | Tillage ,nitrogen and cropping system effects on soil carbon sequestration[END_REF][START_REF] Franzluebbers | Soil organic carbon sequestration and agricultural greenhouse gas emissions in the southeastern USA[END_REF]. But the impacts of no-tillage practices on soil aggregates composition and its stability can vary drastically with soil properties and no-tillage practices [START_REF] Puget | Nature of carbohydrates associated with water-stable aggregates of two cultivated soils[END_REF][START_REF] Bernoux | Cropping systems, carbon sequestration and erosion in Brazil, a review[END_REF]. Conventional tillage systems enhance SOC mineralization; soil aeration and water fluctuation [START_REF] Balesdent | Relationship of soil organic matter dynamics to physical protection and tillage[END_REF]. Conventional tillage also can disrupt soil aggregates and expose physically protected SOC to microbial decomposition, decreasing SOC content and soil aggregate stability. Conversely, conservation tillage accumulate residues on the soil surface as much and reduce soil mixing and disturbance and promotes soil aggregation through enhanced binding of soil particle as a result of greater SOM content and. Soil aggregation can increase SOC storage by reducing loss by erosion and from mineralization [START_REF] Paustian | Management options for reducing CO2 emissions from agricultural soils[END_REF]Six et al., 2002aSix et al., , 2002b)). Soil organic matter (SOM) can be physically protected from microbial mineralization through sorption to clay minerals (Hassink et al., 1993;Beare et al., 1994a;1994b) and enclosure within soil aggregates [START_REF] Tisdall | The effect of crop rotation on aggregation in a red-brown earth[END_REF]1982). Soil structure and soil organic matter (SOM) are two of the most dynamic properties that are extremely sensitive to crop and soil management. Soil aggregates are used for structural unit, which is a group of primary soil particles that cohere to each other more strongly than other surrounding particles. SOM is a major resource that links the chemical, physical and biological properties of soils, and is considered a major binding agent that stabilizes soil aggregates. Soil structure moderates soil and plant functions and is the framework for water, air, and nutrient flow to plants. Plants, in turn, furnish the soil with fresh residues and roots for aggregate structure development. The nature and properties of aggregates are thus determined by the quantity and quality of coarse residues and humus material and by the degree of their interaction with soil particles [START_REF] Jastrow | Soil aggregate formation and the accrual of particulate and mineral-associated organic matter[END_REF][START_REF] Haynes | Changes in microbiological biomass C, soil carbohydrate composition and aggregate stability induced by growth of selected crop and forage species under field conditions[END_REF][START_REF] Elliott | Aggregate structure and carbon, nitrogen, and phosphorus in native and cultivated soils[END_REF]. Plant roots, Fungal hyphae, mycorrhizal hyphae, bacterial cells, and algae develop simultaneously with the growth of plant roots and build up a visible organic skeleton to enmesh the mineral particles by adsorption to form young macro-aggregates, and they are greatly affected by tillage operations (Tisdall and Oades, 1982). Polysaccharides or mineral colloid form bonds of micro-aggregates through cementation of carboxylic or hydroxide groups with polyvalent bridges [START_REF] Puget | Dynamics of soil organic matter associated with particlesize fractions of water-stable aggregates[END_REF][START_REF] Kemper | Soil cohesion as affected by time and water content[END_REF][START_REF] Caron | Improvement of structural stability of a clay loam with drying[END_REF][START_REF] Cambardella | Particulate soil organic matter changes across a grassland cultivation sequence[END_REF].

Mechanisms of Soil Aggregates Stability in Purple Paddy Soil under Conservation Tillage of Sichuan Basin, China 3

Soil aggregate stability is the result of complex interactions among biological, chemical, and physical processes in the soil (Tisdall and Oades, 1982). A close relationship between SOC and aggregate stability has been established for temperate and tropical soil [START_REF] Six | Aggregation and soil organic matter accumulation in cultivated and native grassland soils[END_REF]2002a, 2002b). Water-stable breakdown mechanisms of soil aggregates involve the slaked and capillary-wetted pretreatments, and slowly wetting pretreatments. The slaked pretreatment causes considerable disruption. When air-dried soil is submerged in water, the air that is trapped inside the soil pores is rapidly displaced with water. Weak aggregates are disrupted as a consequence of the sudden release of this large buildup of internal air pressure. In contrast, the wetting pretreatment before wet sieving produces minimal disruption, because misted aggregates do not buildup air pressure in the pores and the air escapes with minimal aggregate disruption (Cambardella and Elliott 1993a;1993a;Chen, 1998;Gale et al., 2000;[START_REF] Li | Cultivation effects on temporal changes of organic carbon and aggregate stability in desert soil of Hexi Corridor region in China[END_REF]. Subsequent slaking can differentiate stable and unstable macro-aggregates [START_REF] Marquez | Aggregate-size Stability Distribution and soil stability[END_REF][START_REF] Beare | A comparison of methods for measuring water-stable aggregates: Implications for determining environmental effects on soil structure[END_REF].

Chongqing is mountainous, where most of rice fields are located at the foot of mountains. About half of rice fields are flooded permanently [START_REF] Xie | Theory and Technique of Paddy Field under Soil Virginization[END_REF]. The crop system of permanently flooded rice fields is, commonly, a single middle rice crop and in fallow with floodwater layer after rice harvesting. Ridge culture is an innovative approach to present permanently flooded rice fields from over reduced in redox potential due to permanently flooded. Fixed ridges are constructed about 30 cm wide, and rice plants and winter wheat plants (or oil-seed rape) were cultivated on both sides of the ridge without tillage instead of a single rice crop a year [START_REF] Xie | Theory and Technique of Paddy Field under Soil Virginization[END_REF]. All the changes involved in the innovative approach, such as changes from plain to ridge, from single middle rice crop to single middle rice crop and winter upland crop, and from permanently flooded to drainage in the winter crop season would improve soil conditions that influenced soil aggregates formation and transformation. Literature is replete with information on the effects of maturing, nutrient management, vegetative restoration, and tillage practices on the soil aggregates stability, and the combined effects of conservation tillage on the formation and stabilization of aggregates in purple paddy soil in related to SOC reservoir are limited [START_REF] Diego | Aggregate stability and microbial community dynamics under drying-wetting cycles in a silt loam soil[END_REF][START_REF] Li | Effects of fertilization on particulate organic carbon matter formation and aggregate stability in paddy soil[END_REF][START_REF] Peng | A review on relationship between soil organic carbon pools and soil structure stability[END_REF][START_REF] Grandy | Organic amendment and rotation crop effects on the recovery of soil organic matter and aggregation in potato cropping system[END_REF]. Therefore, a long-term field experiment was conducted to understand the mechanisms of soil aggregate stability under conservation tillage in a permanently flooded rice field with various treatments.

Xiaohong Tang 1,, Youjin Luo2, Jiake Lv2, Chaofu Wei 2

Materials and methods

Site and soil

Soil aggregates-size stability distribution measurement was conducted in a field experiment site (3026N ,10626E) set up in 1990 for comparison of nutrient cycling among convention (plain) culture and ridge culture with different crop systems of in the permanently flooded rice fields at the Experimental Farm of Southwest China University, Chongqing (223 m elevation) [START_REF] Gao | Effects of tillage systems on distribution of soil aggregates and organic carbon in purple paddy soil of Chongqing, China[END_REF]. Annual average rainfall and temperature were 1105 mm with 70 % in May to September and 18.3 ℃, respectively. the annual sunshine time is 1,276 h; and the frost-free period is about 334 d. The soil is Hydragric Anthrosol developed from the parent material of Jurassic purple shale and sandstone weathering product. Soil particles and aggregatessize distribution were determined in the treatments with plain culture and ridge culture, which were described in detail as follows: (1) plain culture: one treatment of PUR-r was prepared. In PUR-r, the field was ploughed 3-5 days before rice transplanting and a floodwater layer was maintained during the rice crop season, but was drained in the winter crop season for winter crop growth. (2) Ridge culture: three treatments of NTR-f, NTR-r and NTRw-r were prepared. In NTR-f, a fixed ridge was conducted at about 30 cm wide, and rice plants were planted on both sides of the ridge with no tillage. Before rice transplanting, weeds grew in the winter crop season and rice stubbles remained from the previous rice plants were covered with mud in ditches nearby(table 1). Through this practice, the ridges could be maintained for a long Table 1. Annual amount of rice crop residues and weeds to field under different tillage system kg hm -2 y -1 time. Ditches between two ridges were filled with water to the level of 0-3 mm below the top of ridge during the rice-growing period. After rice harvesting, the field was in fallow and water level in ditches dropped to 5-10 cm below the ridge top in the winter crop season. In NTR-R, management for rice culture was the same as that for NTR-f. Winter crops were planted in both sides of ridge in the same way as for rice crop.

Treatment

Mechanisms of Soil Aggregates Stability in Purple Paddy Soil under Conservation Tillage of Sichuan Basin, China 5

Water in ditches was drained in the winter crop season. In NTRw-r, management for rice culture and winter crop was the same as that of NTR-r. The width of ridge was three times more than that of NTR-r (figure 1). Winter crop planted in the treatments of PUR-r, NTR-r and NTRw-r was winter wheat from 1990 to 1997 and oil-seed rape from 1998 to 2000 [START_REF] Cai | Option for mitigation methane emission from permanently flooded rice field[END_REF]. The paddy soil of the experiment field was Eutric Cambisol derived from purple rock. Before the experiment started in 1990, soil organic carbon content was 13.0 ± 1.2 g kg -1 , soil pH was 6.91 ± 0.24, and clay (0.001 mm) content was 144.2 g kg -1 . Chemical fertilizers were applied to all the plots at an equal rate in every rice-growing season, i.e. 273 kg urea ha-1, 500 kg superphosphate ha -1 , and 150 kg KCl ha -1 . Superphosphate was applied as basal fertilization, urea and KCl were applied as basal fertilization and topdressing. No exogenous organic manure was applied to each plot at a rate of about 20 t ha -1 , before rice transplanting. After rice harvesting, rice stubbles about 50~60 cm above ground stood in the field until incorporation into soil before the following period of rice transplanting. The treatment plots, with 4 m×5 m each, were arranged in a complete randomized block experimental design with four replications. Under ridge culture, obvious changes of primary properties in paddy soil were found after 16 years (Table 2). Clay contents significantly increased by 34%, 79% and 51% under NTR-f, NTR-r and NTRw-r compared to that under PUR-r, respectively. SOC content decreased under NTR-f (10.11%), while increased under NTR-r and NTRw-r (18.00% and 9.66%, respectively). Changes of soil porosity indicated that soil structure had been improved under long-term conservation tillage.

Water-stable aggregates separation

Soil samples were collected to assess SOC and aggregates stability in October 2006 (one and a half months after rice harvesting). Soil was sampled at 0-20 cm for aggregates stability and SOC. Six samples were collected from each subplot and mixed to produce a composite sample from each treatment and replicate. In the laboratory, Subsamples for SOC determination were air-dried and sieved through a 0.25 mm mesh. Subsamples for aggregates-size separation were air-dried and sieved through a nest of two sieves to collect all the aggregates with a diameter between 2 and 6.72 mm mesh sizes.

Wet sieving using air-dried 2-6.72 mm sieved soil isolated aggregate-size fraction. Two 100-g subsamples of air-dried soil were used to analyze the aggregate stability distribution. Two pretreatments are applied before wet sieving: air drying followed by rapid immersion in deionized water (slaked) and air drying plus capillary rewetting to field capacity plus 5% (capillary-wetted) in two 250 ml beaker [START_REF] Six | Aggregation and soil organic matter accumulation in cultivated and native grassland soils[END_REF]. Both subsamples were stored overnight in a refrigerator at 4°C before wet sieving. Aggregates were physically separated in four aggregate-size fractions: (1) large macro-aggregates 2-6.72 mm in diameter, (2) small macro-aggregates between 0.25 and 2 mm in diameter, (3) micro-aggregates between 0.053 and 0.25 mm in diameter, and (4) the mineral fraction <0.053 mm in diameter. All the subsamples in 250 ml beakers were transferred on the top of a 3-nested sieve set (2 mm, 0.25 mm, and 0.053 mm) and submerged in deionized water for 5 minutes to allow slaking. A gentle vertical movement (strokes 2-3cm in amplitude and 5 min) within a column of water was done for 10 min using a wet sieving apparatus. After wet sieving, all the fractions were oven-dried at 70°C, except the large and small macro-aggregates obtained by the capillary-wetted pretreatment. These macro-aggregates were air dried and later used for the separation of larger and smaller stable macro-aggregates [START_REF] Pojasok | Assessment of a combination of wet sieving and turbidimetry to characterize the structural stability of moist aggregates[END_REF][START_REF] Elliott | Physical separation of soil organic matter[END_REF][START_REF] Six | Aggregation and soil organic matter accumulation in cultivated and native grassland soils[END_REF][START_REF] Marquez | Aggregate-size Stability Distribution and soil stability[END_REF].

Organic carbon concentration

SOC was determined from samples collected in aggregates separations using sulfuric acid oxidation with external heating [START_REF] Anderson | Tropical soil biology and Fertility: A Handbook of Methods[END_REF]. The mean size of aggregates is represented by the mean weight diameter (MWD) and natural mean weight diameter (NMWD). MWD and NMWD were obtained as indicated in Eqs. ( 1) and (2) [START_REF] Six | Aggregation and soil organic matter accumulation in cultivated and native grassland soils[END_REF][START_REF] Marquez | Aggregate-size Stability Distribution and soil stability[END_REF][START_REF] Van Steenbergen | Two simple indices for distributions of soil components among size classes[END_REF].

Mechanisms of Soil Aggregates Stability in

i n i i m r r MWD       1 1 1 2 (1)
Where i r is the mean equivalent diameter for each particle size interval

(mm), 1 0 r r  , 1   n n r r , i m is the weight of particles in the interval. m in m ax r r MWD NMWD   (2)
Where m ax r is the biggest initial diameter and m in r is the smallest initial diameter.

Statistical analysis

Statistical differences were determined with t Student test using statistica software (Statsoft, 2004).

Results

Soil aggregates composition

Distribution of soil aggregates under different breakdown mechanisms pretreatments was shown in table 3 andtable 4. Although the multitude of disruption of aggregates was different, soil aggregates contents was mainly discovered in the fraction of 2~6.72 mm in particle size in each treatment under different pretreatments. After slaking treatments, the percentage of 2~6.72 mm size was lowest in PUR-r and highest in NTR-r, which suggested that multitude of disruption of aggregates in PURr was more severe than that in NTR-r. There were strongly differences between conservation tillage and CT of 2~6.72 mm size contents. 2~6.72 mm size aggregates in NTR-r and NTRw-r were significantly higher compared to its value in PUR-r, about 130.18% and 144.33%, respectively. And 2~6.72 mm class also increased in Xiaohong Tang 1,, Youjin Luo2, Jiake Lv2, Chaofu Wei 2 NTR-f by 1.113 times over that in PUR-r. Significant differences between NTR-r and other treatments were discovered of the aggregates contents in the size of 0.25~2 mm, and its content under NTR-r was the lowest. Aggregates contents in all treatments under wetting treatment ranked in the order of PUR-r <NTR-f<NTR-r <NTRw-r, which was different from that under slaking treatment. The amount of 2~6.72 mm in NTR-f, NTR-r and NTRw-r increased by 22.02%, 32.07% and 35.84% to comparison with the control, respectively. There were no significant differences of 0.25~2 mm aggregates-size contents between conservation and conventional tillage. The contents of 0.25~2 mm aggregates-size under slaking treatment were higher than that under wetting treatment in each treatment except that in NTR-r. Aggregates contents decreased with the decrease of aggregates-size, which indicated that conservation tillage might increase water-stable macro-aggregates proportion at cultivated layers in purple paddy soil.

Soil aggregates stability

According to wet sieving as above, the contents of 2~6.72 mm and 0.25~2 mm aggregates-size macro-aggregates under subsequent slaking treatment, which were collected from the fractions of 2~6.72 mm and 0.25~2 mm under wetting treatment

Mechanisms of Soil Aggregates Stability in Purple Paddy Soil under Conservation Tillage of

Sichuan Basin, China 9

and then air-dried, were determined (Table 5). 0.25~2 mm stable aggregates in all treatments were increased in the order of PUR-r (0), NTR-f (5.47%), NTRw-r (8.33%) and NTR-r (13.76%). The proportion of stable aggregates 2~6.72 mm in NTR-f, NTRw-r and NTR-r was increased by 10.51%, 9.27% and 6.74% compared to the control, respectively. The percentage of stable macro-aggregates contents in all treatments (PUR-r, NTR-f, NTRw-r and NTR-r) after subsequent slaking treatment was 64.26%, 74.09%, 93.31% and 94.31%, respectively. Consequently, conservation tillage could enhance the resistance of aggregates to slaking stresses in paddy soil, and reduce the multitude of the disruption of aggregates. The aggregate-size stability distribution is the quantity of stable and unstable soil aggregates categorized by their size and stability to disruption. Water-stable aggregates can improve soil stability, and enhance physical protective ability for soil organic carbon. The aim of agricultural management is to create the stable soil structure. The percentage of water-stable macro-aggregates decreased in the order of NTR-r, NTRw-r, NTR-f and PUR-r under fast slaking treatment and NTRw-r, NTRr, NTR-f and PUR-r under wetting treatment, respectively. Similar distribution trends of water-stable macro-aggregates were observed under slaking treatment and wetting treatment when the stability of aggregates was represented as MWD and NMWD (table 6).

Organic carbon in aggregates

Organic carbon (OC) contents were mainly found in the fraction of 0.25~2 mm and 2~6.72 mm, and then in <0.053 mm size aggregates and least in 0.053~0.25 mm under fast slaking treatment in all treatments (Figure 2). There was a pronounced difference of SOC contents in the fraction of 2-6.72 mm between conservation and conventional tillage. SOC contents under NTR-r, NTRw-r and NTR-f were 42.24%, 43.03% and 33.31% higher than that in PUR-r, respectively. Significant difference was observed among treatments of organic carbon in 0.25~2 mm size class, ranked in the order of NTRw-r > NTR-r> NTR-f> PUR-r. SOC contents in 0.053~0.25 mm under NTRw-r and NTR-r were significantly higher 1.11 and 0.59 times over that in the control, while in the fraction of <0.053 mm were higher about 16.43% and 58.98%, respectively.

Fig. 2. Organic carbon contents in broken aggregates under slaking pretreatment

Distribution trends of SOC contents in aggregates under wetting pretreatment in all treatments were similarly to that under fast slaking pretreatment. Significant differences of SOC contents were found in aggregates of the tillage treatment and size fraction in each treatment and also found in micro-aggregates among treatments under wetting pretreatment. OC content in 0.053~0.25 mm after wetting treatments was Mechanisms of Soil Aggregates Stability in Purple Paddy Soil under Conservation Tillage of Sichuan Basin, China 11 higher than that under fast slaking pretreatment (Figure 3). Compared with the control, OC contents in the fraction of 2~6.72 mm and 0.25~2 mm under NTR-r were increased by 10.91% and 19.93%, while 0.7% and 28.47% under NTRw-r, respectively. It was worth paying attention to that OC content in each aggregates-size in the control under wetting pretreatment was higher than that under fast slaking pretreatment. There may be something wrong with the soil porosity when it was high in control, which could cause majority of particulate organic matter with internal or external aggregates to float upward during fast slaking pretreatment. Particle organic carbon was about more than 27% of total organic carbon in cultivated layer of purple paddy soil (Huang et al., 2005;[START_REF] Tufekcioglu | Fine root dynamics, coarse root biomass, root distribution, and soil respiration in a multispecics riparian buffer in central Iowa[END_REF] and was significant positive correlated with aggregates stability [START_REF] Li | Effects of fertilization on particulate organic carbon matter formation and aggregate stability in paddy soil[END_REF]. OC contents in stable and unstable macro-aggregates under subsequent slaking pretreatment were measured (Figure 4). OC contents in stable aggregates were always higher than that in unstable aggregates, and the OC contents in 0.25~2 mm stable aggregates were higher than that in 2~6.72 mm stable aggregates. Under subsequent slaking pretreatment, significant differences were observed between conservation tillage and the control. OC contents in 0.25~2 mm stable aggregate under NTR-r, NTRw-r and NTR-f were significantly increased by 38.64%, 24.26% and 24.52% compared to the control, respectively. OC contents in 2~6.72 mm stable aggregates under NTR-r and NTRw-r were 9.94% and 20.57% higher than that in the control, respectively. It may be sure that most of OC contents were enriched in stable macroaggregates under long-term ridge or wide ridge culture integrated with notillage, crop rotation and rice stubble. SOC contents increased under long-term ridge culture and aggregates stability was significantly enhanced. The disruption of aggregates during the slaking and wetting treatment produces smaller constituent aggregates. Aggregates contents decreased with the decrease in aggregates size, and the proportion of 2~6.72 mm aggregates-size was more than 50%. The magnitude of stable macro-aggregates under conservation tillage was also significantly higher than that under conventional tillage after subsequent slaking treatment. Excellent soil structure was determined not only by macro-aggregates but also by the quality and quantity of micro-aggregates, which may indicate the potential ability to format soil structure. Under wet-shaking treatment, bulk soil was mainly separated into the fraction of 0.02~0.25 mm aggregates-size (45~54%), and then 0.002~0.02 mm aggregates-size, macroaggregates and its organic carbon increased at surface layers (0~10 cm) in paddy soil [START_REF] Tang | Effects of conservation tillage systems on aggregates composition and organic carbon storage in purple paddy soil[END_REF]. In conclusion, fast slaking and wetting processes under natural condition may be the major breakdown mechanisms of macro-aggregates in purple paddy soil.

Aggregates stability is a quality indicator that directly related to soil organic matter, which can be redistributed within soil by tillage. Water stable aggregates in cultivated layers mainly caused by strike and extrusion of crop roots and cementation of secretion. The quantity of straw mulch returning into purple paddy soil ranked in the order of PUR-r > NTR-r > NTRw-r > NTR-f (Table 6). OC contents and aggregates stability in plain culture were lower than those in ridge culture. Macroaggregates, which are C-rich substances under conventional tillage, were disrupted,

Mechanisms of Soil Aggregates Stability in Purple Paddy Soil under Conservation Tillage of

Sichuan Basin, China 13

and increased smaller aggregates contents, which are lack of organic carbon, resulting in low soil organic matter content. Moreover, long-term tillage practices diminish the quality and length of fine roots and microbial population in the upper horizons, and reduced the amount of macro-aggregates. Crop residues were enriched in soil surface layer by making ridge and plot in NTR-r and NTRw-r and increased unstable carbon inputs (soil biomass carbon and particulate organic matter), which are the main binding (cementing) agent to form macro-aggregates. From conversion, conventional submersion or drying to ridge/plot capillary-wetted cultivation, gravity water has been eliminated, and water erosion has been mitigated under conservation tillage (NTR-r and NTRw-r), thus soil maintains capillary wetting. Because water, gas, and heat regime exchanges frequently, these enable soil under ridge to contract itself and consequently form stable soil structure. Pore character of soil aggregates is the main factor influencing wetting speed, such as pore size and camber. Caron reported that pore camber indexes in NT is three times more compared to in CT, water immerse rate decreased by 70% and increased aggregates stability [START_REF] Mazurak | Effect of gaseous phase on water-stable synthetic aggregates[END_REF][START_REF] Caron | Soil structural stability during rapid wetting: Influence of land use on some aggregate properties[END_REF]. It is suitable to form soil structure for soil pore type and quantity and soil density which was lower in NTR-r and NTRw-r compared to PUR-r that was caused by stable heat capability, relative stable electrical field, continuous immersing and strong water retention ability of labile organic matters which were rotted from root straw internal or external soil pore [START_REF] Xie | Theory and Technique of Paddy Field under Soil Virginization[END_REF][START_REF] Wei | Soil aggregate and its response to land management practices[END_REF].

Relationship between soil organic carbon and aggregates-size stability

Organic matter is one of the key factors influencing soil stability. OC magnitude has close connection with aggregates stability, but the multitude of correlation was site-specific. There was low correlation between organic carbon and aggregates stability under fast slaking pretreatment, however, significant positive correlation was observed under wetting pretreatment [START_REF] Li | Cultivation effects on temporal changes of organic carbon and aggregate stability in desert soil of Hexi Corridor region in China[END_REF][START_REF] Hernanz | Long-term effects of tillage systems and rotations on soil structural stability and organic carbon stratification in semiarid central Spain[END_REF]. Soils organic compounds not only buildup the cohesion and tensile strength among aggregates, and heighten soil aggregates stability, but also mitigate the wetting velocity because water capability of soil compounds was greatly higher than that in soil mineral. Moreover soil organic compounds hydrophobicity affects the wetting velocity. The addition of straw can promote microbe activity, and reinforce cohesion and hydrophobicity of aggregates. The impact of addition of straw multchon aggregates was greater than wet-dry cycles. Enhancement of soil hydrophobicity would hinder or delay infiltration velocity of soil water (Hallett et al., 1999), and make air in soil pore release slowly, thus reduce slaking resistance and enhance soil aggregates stability [START_REF] Capriel | Relationship between soil aliphatic fractions extracted with supercritical hexane, soil microbial biomass and soil aggregate stability[END_REF]. Soil hydrophobicity may illuminate the relationship between soil organic carbon and soil structure stability. Soil texture also has great impact on Soil hydrophobicity. When soil texture is different, Soil hydrophobicity has significant difference. Clay contents were 3.32 and 2.95 times in Xiaohong Tang 1,, Youjin Luo2, Jiake Lv2, Chaofu Wei 2 NTR-r and NTRw-r over that in PUR-r, respectively. Ridge culture could protect soil from erosion because crop residues remain relatively undisturbed on the soil surface in contrast to plain culture, and the precipitation infiltrated soil in the form of capillary water. For the reduction of water erosion, the proportion of clay in soils under ridge culture increased. Hallett (1999) reported that when clay content was more than 25% or even more 40%, soil hydrophobicity was all the same great, and even the soil hydrophobicity in high soil clay content was greater than in low soil clay content. This may be because that hydorphobic organic particulate itself was rather small or organic matter content was greatly high, which can enwrap large and small particulate and lead to more greatness of specific surface of soil hydrophobic organic compounds.

Conclusion

Under slaking and wetting pretreatment, the amount of aggregates-size was mainly found in the diameter of 2~6.72 mm under ridge culture in paddy soil (more than 50%). The proportion of macro-aggregates under ridge culture treatment was greatly higher than that in conventional tillage soils under subsequent slaking pretreatment. The proportion of macro-aggregates and its OC content increased under long-term ridge culture in paddy field, which straightened soil aggregates stability. No significant difference of aggregates stability was found between slaking and wetting pretreatment. Organic carbon contents were obviously enriched in macro-aggregates, and SOC in aggregates were highly correlated with aggregates stability under wetting treatment. It is important to seek management practices that sustained soil resource. Keeping the soil in place is the best defense against soil degradation. Ridge culture without tillage could protect soil from erosion because crop residues remain undisturbed on the soil surface in contrast to plain culture where residue was incorporated. These evidences suggested that Long-term ridge culture may lead to changes of straw mulch inputs and soil microenvironment and enhancement of aggregates water stability.

Fig. 1 .

 1 Fig. 1. The type of the bulletin for experimental culture (a: plain culture, b: ridge culture, c: wide ridge culture)

Fig. 3 .Fig. 4 .

 34 Fig. 3. Organic carbon contents in slaked aggregates under slowly wetting pretreatment

Table 2 .

 2 Primary properties of paddy soil under long-term conservation tillage systems

	Sand	Silt	Clay	Organic C	Porosity
	Treatment
	(%)	(%)	(%)	(g kg -1 )	(%)

Table 3 .

 3 Composition of aggregates in purple paddy soil under slaking

	pretreatment	%
		<0.053	0.053~0.25	0.25~2	2~6.72
	Treatment					Recovery
		mm	mm	mm	mm
	PUP-r	13.21±1.48a	10.20±0.81ab	20.60±3.05a	52.92±0.75c	96.93
	NTR-f	9.40±0.53b	13.12±1.88a	16.61±4.62ab	58.90±5.44bc	98.02
	NTR-r	5.27±0.42c	5.66±0.86c	11.50±3.25c	76.41±4.56a	98.83
	NTRw-r	4.77±0.99c	7.88±3.76bc	15.11±4.13ab	68.89±8.65ab	96.65

Table 4 .

 4 Composition of aggregates in purple paddy soil under slowly wetting

	pretreatment	%
		<0.053	0.053~0.25	0.25~2	2~6.72	Recovery
	Treatment
		mm	mm	mm	mm
	PUP-r	14.48±0.56a	13.23±0.71a	18.30±1.08a	51.84±2.53b	97.85
	NTR-f	10.06±1.42b	11.11±0.53b	14.09±4.06a	63.26±5.90ab	98.52
	NTR-r	2.65±0.49c	8.95±1.26c	15.61±8.48a	68.47±10.32a	95.68
	NTRw-r	6.72±4.10bc	6.50±1.16d	14.74±0.59a	70.42±3.68a	98.38

Table 5 .

 5 Effects of subsequent slaking treatment on the percentage of macroaggregates in

	paddy soil
			0.25~2 mm			2~6.72 mm
				Stable			Stable
	Treat-	Stable	Total		Stable	Total
				Aggregate			aggregate
	ments	aggregate	aggregates		aggregate	aggregates
				percentage			percentage
		(g kg -1 )	(g kg -1 )		(g kg -1 )	(g kg -1 )
				%			%
	PUP-r	11.35	18.30	62.02	33.72	51.84	65.04
	NTR-f	9.51	14.09	67.49	47.80	63.26	75.56
	NTR-r	11.83	15.61	75.78	50.88	68.47	74.31
	NTRw-r	10.37	14.74	70.35	50.55	70.42	71.78

Table 6 .

 6 Percentage and mean weight diameter of the water stable macroaggregates(>

	0.25 mm)
	Treatments	WSMA(%)	MWD(mm)	NMWD(mm)

Acknowledgements

This work is supported by the Key Projects in the National Science & Technology Pillar Program (No.2006BAD05B0-02) and the foundation of Sichuan Educational Committee for Youths (No.09ZB049), and the Natural Science Foundation of Chongqing, China (No. CSTC, 2009BB1115).

Mechanisms of Soil Aggregates Stability in Purple Paddy Soil under Conservation Tillage of

Sichuan Basin, China


Rongchang Yuan

Haiganyuan

Si Chen

, Longqing Sun

Feng Qin

Han Zhang

Yukun Zhu

Daokun Ma

Research on the k-coverage local wireless network and its communication coordination mechanism design

Keywords: k-coverage, local wireless network, communication coordination, Monte Carlo

Based on the analysis of the present situation and features of local wireless network, combined the networking technologies, we constructing the wireless network layout algorithm and sensor nodes model. Through delaminating iterative optimization algorithm, optimal layout of sensor data collection and satisfy recognition, quasi-geoids orientation, signal coverage optimization have been realized. Compared the triangular, square and hexagon scheme, and get a general scheme of multiple complete coverage by calculate the length of sides on the polygon. Monte Carlo algorithm is used in choosing the optimum proposal comparing among the regular triangle, square and the hexagon in different conditions. For locating network, analyze the advantages and disadvantages of triangle, square and hexagon schemes in deferent positioning accuracy of double coverage, we set different layout schemes to different situations. Application manual is provided for the constructor to refer to these table lookup to attain the right numerical value.

Introduction

In the subject of internet of things, different kinds of information are transferred by sensor nodes. In order to improve the efficiency and stability of the transmission through networks, the layout of the nodes must be optimized. (Zhang Honghai and Hou Jennifer,2005;Yu Hongyi,2008) Zigbee is one of the hardware equipment used in the wireless communication technology. It has many advantages, for example, the connection distance is shorter and the complexity is smaller, the power consumption is lower and so on. In the automatic control and remote control field, it is widespread. Many communicators are inset with Zigbee. It consists of three models: the response model; the data manipulation model; the communication model. The response model is to receive the information. The information is transferred through the communication model. With such information, we can attain the location of the moving nodes. (Duc A. Tran, Usman Khan,2006) 2

Methods and Algorithms 2.1

The network evaluation function

When to evaluate a network, we often consider the following two factors: the network performance and the cost. The network performance includes the stability in transfer information and the accuracy in location. It depends on the overlapping area.

The cost depends on the number of nodes. The more nodes there are the higher cost and power consumption.

When the target area is k -coverage, the size of area covered is: cov be ered

S ab 

(1)

If the number of nodes in this area is n , the coverage area is:

2 all S n R   (2)
Where: a is the length of the target area, b is the width of the target area R is the effective communication radius.

At the same time, every point in the target area has the very same information collection accuracy.

Definition 1: the coverage rate of sensor  This passage comes up with the concept of coverage rate. It means the ratio between the size of target area and the sum of all the coverage area provided by the nodes.

1

1 n i i n i i S S      (3)
It can reflect on the utilization of the coverage area. The larger , the better the net performance is. At the same time, it can reflect the number of nodes. The fewer the nodes are, the lower the cost is. In another words, the lower the coverage rate, the better the layout of the network.

In a 1-coverage network, the calculation function is defined:

1 cov cov cov 1 ( ) / 1 er be ered be ered g S S S      (4)
Through the discussion, the coverage rate is solved. In the 1-coverage network, it is 82.7%. In fact, it can't reach the perfect value 1.

In a k -coverage network, the covered area can be considered as: cov be ered kS kab 

(5) All in all, in a k -coverage network, the calculation function is defined:

cov cov cov ( ) / 1 k er be ered be ered k g S S S      (6)

The layout of nodes in 1-coverage network

To design the nodes layout, for a target area, the main problem is how to make the area is covered without blind spot, which means that the point can`t be covered.

According to the simplification of the covered area-the circle, we can turn the problem into geometric. For a ab rectangle region, how to be fitted together can use the least circles and how many circles are needed. As no matter small the radius of the circle is, it impossible to cover the area without blind point, so we take the second best solution that the circle is replaced with its inscribed polygon and the node is located on the center of the polygon.

If there are x polygons put on the same vertex, and every n gon's interior angle is:

( 2) *180 / nn  (7) Then:

( 2) *180 360

n x n   (8)
The solution is:

4 2 2 x n   (9)
Because x is positive integer, then: Locate the nodes according to the above way, then we can get the covered area without blind points.

2 2 2 sin 2 C S L nR A A A R n       (11)
Where:

C A means the size of overlapping area.

L

A means the size of the circle with the effective communication radius.

S

A means the size of inscribed polygon. n is the number of the sides on the polygon.

When n , 0 C A  . So in order to make sure, there is no blind node.

When 6 n  , the overlapping area is minimum:

2 min 32 () 2 C AR   (12)
Using the hexagon to locate the nodes is the best layout (Zhang Chaohui,2010).

Using the Definition 1 in the model one, we can calculate the coverage rate

S  : 2 2 3 3 / 2 82.7% S S L A R AR      (13)
Then the calculation function is:

1

1 1 0.2092 S g     (14)

The layout of nodes in k-coverage network

During the research on k -coverage network, the two puzzles challenge us. One is that if the geometric shapes in k -coverage network is the same to the 1-coverage network. Another one is that how to calculate the distance between the two nodes.

We regard the second question as the breakthrough point to compute the distance between two nodes in k -coverage network. we have proven that there are three possibilities: regular triangle, square and the hexagon. And the node is located on the vertex.

We can see the vertex is the most difficult point to be covered. So if the vertex is covered by k times, the area is covered by k times. We select one of the vertex M, to solve ( , ) MM xyusing the equation of the straight lines: 12 LL 、 . In order to make sure M is covered k times, which is that there are k nodes lie in the effective communication circle of M:

2 2 2 ( ) ( ) M N M N x x y y R     (15) ( , ) NN xyis one of nodes N surrounded the node M.
Define a distance function:

2 2 2 ( ) ( ) M N M N G R x x y y      (16)
Only if G>0,the target area is k-coverage. Then the distance G can be expressed by 1

k 2 k . 2 2 2 12 ( , ) ( ) ( ) M N M N G k k R x x y y      (18)
We must find out the 1 k 2 k , then we can get the distance between M and N.

(1) Solution

Taking the 2-coverage for example, introduce above model in detail.

We have proved there are three shapes; regular triangle, square and the hexagon showed in the following Figure 2-2: The equation of 12

( a ) ( c ) ( c )
LL 、 : 2 3 3 2 y x m  (19) 2 3 3 2 y x m    (20)

M

We select one of the vertexes M (0, 3 / 2) m

.

Then we can get the 12 ', '

LLthrough translating 12 LL 、 , passing 1 k and 2 k units 11 3( ) 3 / 2 y x k m m    (21) 22 3( ) 3 / 2 y x k m m     (22)
Then coordinates of N :

12 ( ) / 2 N x k k m    (23) 12 ( 1) 3 / 2 N y k k m    (24)
Then the distances function:

22 2 2 2 2 2 2 1 2 ( ) ( ) / 4*(k +k ) +3/4m *(k1 k2) M N M N G R x x y y Rm         (25)
For k-coverage, we can express k using the multiply of 1 k and 2 k

It means the number of points of intersection.

k ab 

Where:

12 ,. k a k b 

From that, we can get the numerical value. Then we can get the function:

G( 12 , kk) 2 2 2 2 2 2 2 2 1 2 1 2 2 2 2 2 1 1 2 2 ( ) ( ) / 4*( ) 3 / 4 *( ) / 4*( ) M N M N G R x x y y R m k k m k k R m k k k k               (28)
To simply the distance G( 12 , kk) into the D( 12 , kk):

22 1 1 2 2 D k k k k    (29) Because 1
k and 2 k are all integer, we can get the value of them through gradual enlargement from (0,0), for example:(0,1),(0,-1),(-1,0)…… After getting the value of D, put the value in order of from small to bigger. The value order is the order to pick up 12 , kk .

We can get the value of the function D showed in Table 2-1: The constructor can refer to this application manual table lookup to attain the numerical value of 1 k and 2 k , then they can get the best layout. Using the same solutions, we can get the results of square and the hexagon.

(2)Algorithm

The flow chart in k -coverage network,See Figure 234:

Start Attain the size of area, the coverage radius, the times of area covered: k

Resolve k into the multiply of k1 and k2 (they are both integer).

Check up the table lookup and choose the k1 and k2 according to the order of D.

Attain the distance between nodes.

Finish

Communication Coordination

When the effective radius of repeater is larger than or equals to the area radius (some repeater radius can reach more than 100 meters), only a repeater can cover the whole area. In order to mitigate interference, besides the geographical separation, the -continuous tone-coded squelch system‖ (CTCSS), sometimes nicknamed -private line‖ (PL), Since a repeater has a special frequency pair and a particular PL, and there are different demand of network serves (different frequencies used for different purposes) and the number of user, the spectrum range need to be divided into multiple channels.

So our task is optimizing frequency channel coordinate and the use of PL according to the users' quantities and purposes on the basis of complete coverage.

Results and analysis

We already know that the layout scheme of triangular, square and hexagon by We have known that the double covered network in triangular scheme is actually covered triple by model two. So the ratio of double covered area with the whole area is 0 that is the positioning accuracy is 1.

As for square and hexagon, we take the area ratio by most times of simulation to calculate positioning accuracy and function values. The results show in table3-3: The higher value of function is, the better scheme of layout is. In order to select better layout scheme, we give a weight to each scheme based on the environment as table3-4 shows. In conclusion, the layout scheme is as follows.

(1) If the environment condition is good, choose the square scheme.

(2) If the environment condition is medium, choose the hexagon scheme.

(3) If the environment condition is bad, choose the triangular scheme.

From table 3-4, The positioning accuracy of triangular and square scheme can reach to 1, but is too low in hexagon scheme. So we take the method of reducing the distance of nodes to increase the positioning accuracy.

Use Monte Carlo Simulation; we get the relation of nodes distance and the positioning accuracy. It's show in table3-5: So the procedure of layout is to choose the scheme based on the environment.

And if the hexagon scheme is chosen, choose the nodes distance based on positioning accuracy.

Discussions

(1) To once complete coverage network, choose the hexagon scheme, and the node lies in the center, the length of sides is the effective radius.

(2) To more than once complete coverage, compared the triangular, square and hexagon scheme, and get a general scheme of multiple complete coverage by calculate the length of sides on the polygon.

(3) To locating network, compared the advantages and disadvantages of triangular, square and hexagon scheme based on positioning accuracy of double complete coverage.

  Figure 2-1. three different kinds of repetitive units

Figure 2

 2 Figure 2-2. the different shapes

FigureDefinition 2

 2 Figure 2-4. flow chart in k-coverage network (3)Cost of network Definition 1 Minimum repeat unit: the minimum unit while attaching the nodes, namely, triangular, square and hexagonal. Definition 2 Node densities: the ratio of minimum repeat units and the number of the nodes in it. Symbol by n .Because the cost of network only related to the numbers of nodes, the cost of a network can be expressed by / Sn , where S represent the area of minimum repeat unit.

  Figure3-1: Layout schemeUse Monte Carlo Simulation to calculate the three area ratio of double covered area with the whole area. The result shows in table3-1and table3-2.

Table 2 -

 2 1: the value of the function D when 12 , kk change from -10 to 10

	k2	k1	-10	-9	-8	-7	-6	-5	-4	-3	-2	-1	0	1	2	3	4	5	6	7	8	9	10
		-10	100	91	84	79	76	75	76	79	84	91	100	111	124	139	156	175	196	219	244	271	300
		-9	91	81	73	67	63	61	61	63	67	73	81	91	103	117	133	151	171	193	217	243	271
		-8	84	73	64	57	52	49	48	49	52	57	64	73	84	97	112	129	148	169	192	217	244
		-7	79	67	57	49	43	39	37	37	39	43	49	57	67	79	93	109	127	147	169	193	219
		-6	76	63	52	43	36	31	28	27	28	31	36	43	52	63	76	91	108	127	148	171	196
		-5	75	61	49	39	31	25	21	19	19	21	25	31	39	49	61	75	91	109	129	151	175
		-4	76	61	48	37	28	21	16	13	12	13	16	21	28	37	48	61	76	93	112	133	156
		-3	79	63	49	37	27	19	13	9	7	7	9	13	19	27	37	49	63	79	97	117	139
		-2	84	67	52	39	28	19	12	7	4	3	4	7	12	19	28	39	52	67	84	103	124
		-1	91	73	57	43	31	21	13	7	3	1	1	3	7	13	21	31	43	57	73	91	111
		0	100	81	64	49	36	25	16	9	4	1	0	1	4	9	16	25	36	49	64	81	100
		1	111	91	73	57	43	31	21	13	7	3	1	1	3	7	13	21	31	43	57	73	91
		2	124	103	84	67	52	39	28	19	12	7	4	3	4	7	12	19	28	39	52	67	84
		3	139	117	97	79	63	49	37	27	19	13	9	7	7	9	13	19	27	37	49	63	79
		4	156	133	112	93	76	61	48	37	28	21	16	13	12	13	16	21	28	37	48	61	76
		5	175	151	129	109	91	75	61	49	39	31	25	21	19	19	21	25	31	39	49	61	75
		6	196	171	148	127	108	91	76	63	52	43	36	31	28	27	28	31	36	43	52	63	76
		7	219	193	169	147	127	109	93	79	67	57	49	43	39	37	37	39	43	49	57	67	79
		8	244	217	192	169	148	129	112	97	84	73	64	57	52	49	48	49	52	57	64	73	84
		9	271	243	217	193	171	151	133	117	103	91	81	73	67	63	61	61	63	67	73	81	91
		10	300	271	244	219	196	175	156	139	124	111	100	91	84	79	76	75	76	79	84	91	100

Table 2 -

 2 2: the value of n

	scheme		n
	triangular	1/2
	square		3/4
	hexagonal	2
	From the three discussing above Table 2-3 , the evaluation function is
	** g q k 	S	(30)
		n

Table 4

 4

		-1: The area ratio in square
	Simulation times	The number of nodes	The area ratio
	50000	268	0.00536
	80000	441	0.005513
	100000	554	0.00554
	500000	2709	0.005418
	900000	4989	0.005543
	Table 3-2: The area ratio in hexagon
	Simulation times	The number of nodes	The area ratio
	50000	14678	0.29356
	80000	23475	0.293438
	100000	29393	0.29393

Table 3

 3

		-3: The positioning accuracy and function values
	scheme	triangular		square		hexagon
	Area ratio	0			0.005543		0.293313
	positioning accuracy	1			1			0.71
	function value	0.866	* qR	2	1.333	* qR	2	0.922	* qR	2

Table 3

 3

		-4: The weights based on environment
	environment	Good	Medium	bad
	triangular	0--0.3	0.3-0.7	0.7--1
	square	0.7--1	0.3-0.7	0--0.3
	hexagon	0--0.3	0.7--1	0.3-0.7

Table 3 -

 3 5: The relation of nodes distance and the positioning accuracy

	Nodes distance	positioning accuracy

Acknowledgement. This work was supported by 863 programs (2009BADB0B05)


Kaiqun Hu

Zetian Fu

Ronghua Ji

Jun Wang

Lijun Qi
email: qilijun@cau.edu.cn

Design and Development of Variable Rate Spraying System Based on Canopy Volume Measurement

Keywords: Variable rate spraying system, Canopy Volume measurement, Ultrasonic sensor, Single chip

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

Introduction

Variable rate spraying technology could be divided into map-based and sensor-based variable rate technology by the information source of variable rate decision. Crop protection workers did many studies on variable rate spraying technology of map-based. American MICRO-TRAK company developed the MT series automatic variables control system, the monitoring member surveyed the insect situation by the GPS antenna equipments mounted in the field. When insect situation was monitored, position of the disease insect area, type and density of the disease insects could be recorded and sent to the PC by the GPS , and the prescription map was built and imported to the corresponding GIS [START_REF]The MT-9000 Automatic Rate Control. GPS and PC Compatible for Variable Rate Application[END_REF] . Baijing Qiu et al. developed a variables application control equipment of Automatic target detection based on GIS, whose work principle was as follow: information about the application prescription map was gained by GPS, the analysis and processing of real-time data and history data were completed by GIS, during application, the application instruction was built by the computer console based on GPS equipment orientation, speed information transmitted by radar sensors, circuit pressure and decision information [START_REF] Qiu | One variable-rate spraying equipment and its key technology[END_REF][START_REF] Li | Study on the control of variable-rate spraying in precision agriculture[END_REF] . Wanping Shi et al.

analyzed the makeup and control technology of variable rate control system based on GPS and GIS [START_REF] Shi | Variable rate spraying technology on the basis of GPS and GIS[END_REF] . Many studies were also done on the variable rate application technology based on sensor. Schumann et al. developed a measurement system of canopy volume, the Durand-Wayland ultrasonic ranging system [START_REF] Inc | Smart spray operator's manual[END_REF] was used in their study [START_REF] Schumann | [END_REF] . Ritchie et al. measured the canopy height using an airborne laser altimeter [7] . Nilsson developed a system to measure tree height and canopy volume, which included an airborne lidar system [8] . Lei Tian et al. developed an "automatic weed control system in tomato field based on machine vision" and a "application system based on difference GPS" [START_REF] Tian | Sensor-based precision chemical application systems[END_REF][START_REF] Tian | Development of a sensor-based precision herbicide application system[END_REF][START_REF] Tian | Development of precision sprayer for site-specific weed management[END_REF] . The variable rate application system could be divided into chemical injection control system and coordinate injection control system of chemical and water. Ess et al. of Purdue University presented the chemical injection control system. Rehfeld designed a constant-ratio and coaxial direct injection equipment [START_REF] Rehfeld | Fluid motor metering device[END_REF] . Womac et al. designed a coordinate control system of chemical and water [START_REF] Womac | Variable-concentration direct injection from fixed-ratio diluent-driven pumps[END_REF] . Yubo Guo et al. applied the static mixer into the direct injection variable rate spraying system [START_REF] Guo | Application of static state blender in auto mix pesticide equipment[END_REF] . Haiyan Zhou et al. presented a new variable ratio and rate injection spraying system [START_REF] Zhou | Variable ratio spraying pesticide injection system[END_REF] . A variable rate spraying system based on canopy volume measurement was developed, which used ultrasonic sensors to measure the tree canopy volume.

Overall Design of Variable Rate Spraying System

The orchard air-assisted sprayer Hardi LB-255 was fitted with ten ultrasonic sensors which were mounted on the mast fixed on the sprayer (five on each side of the mast) and two flow control mechanisms(one on each side of the machine) to modify the flow rate of the nozzles in real time. The ultrasonic sensors were used to detect the distances from the sensors to the foliage at the corresponding height. The canopy diameters of different heights would be computed by the distances detected by sensors, and then the canopy volumes could be calculated by the measurement method introduced by Kaiqun Hu [START_REF] Hu | Research on the Influence Factors of Ultrasonic Measurement System of Tree Canopy Volume[END_REF] . The single chips were used to send data from sensors to portable computer and transfer instructions from computer to flow control mechanisms in real time. Canopy volumes and canopy diameters measured by sensors were stored in the portable computer. The system was mainly made up of portable computer, single chips, ultrasonic sensors, flow control mechanisms and nozzle sets, and its schematic view is shown in Figure 1.

Where ultrasonic sensors L1-L5 and R1-R5 were mounted on the left and right side of the mast respectively, nozzles L1-L5 and R1-R5 were fixed on the left and right side of the sprayer respectively, flow control mechanism L and R were used to control the flow rates of Nozzles L1-L5 and Nozzles R1-R5 respectively.

Sensors mounted on left and right side were numbered from L1 to L5 and R1 to R5 respectively, and were used to detect the trees on the left and right side of the sprayer respectively. In order to reduce the signal interferences between adjacent sensors, the sensors on each side of the mast were divided into two groups respectively: sensor 1, 3, 5 and sensor 2, 4, which worked by turns. Sensors on the left side were taken as an example to introduce the work detail of sensors and single chip, whose work schematic view is shown in Figure 2. The temperature wouldn't affect the measurement precision of the system obviously, so temperature compensation circuits of ultrasonic sensors were not designed in this system. STC12C5A60S2 series single chip produced by Hong Jing Science and Technology Ltd was used in this research, which was a single clock/machine period single chip, and had characteristics of high speed, low power consumption and strong anti-interference. MAX810 special replacement circuit was integrated in the single chip. The photograph of single chip is shown in Figure 4.

Connection of Ultrasonic Sensor and Single Chip

Four interfaces were needed by a ultrasonic sensor, VCC and GND were connected with VCC and GND of single chip, Trig and Echo were connected with the P port.

Taking the left column sensors as an example, the connection of ultrasonic sensors and single chip is shown in Figure 5.

Installation Positions of Ultrasonic Sensors and single chips

A mast was fixed on the center of tractor tail, whose length, width (which was parallel with crop row) and height were 5m, 0.08m and 0.05m respectively. Sensors and single chips were mounted on the mast, whose installation schematic view is shown in Figure 6. Where H T is the tree height above the ground, H S is the height from ground to canopy skirt, D R is the crop row spacing, D C is the distance between sensors and center line of crop row, D i is the distance between sensor i and the canopy foliage, D S is the sensor spacing. The height above the ground of sensors and the sensor spacing could be adjusted by the actual experimental objects.

Fig. 6. Installation schematic view of ultrasonic sensors and single chips.

Design of Flow Control Mechanism

Nozzle flows were changed with the change of canopy diameter values measured by sensors, so electro proportion control valve (EPCV) and electromagnetism valve (EV) were used to adjust the nozzle flows. Schematic view of flow control mechanism is shown in Figure 7. Electro proportion control valves and electromagnetism valves were controlled by single chip based on the canopy diameters detected by ultrasonic sensors. Pressure of pump outlet was reduced by proportional decompressing valve, and was maintained between 0 and 0.6MPa to ensure the normal application pressure needed by application equipment. The flow and pressure were measured by flow meter and pressure meter respectively.

L5

Start interface of the whole system designed by VC software is shown in Figure 8. Three systems could be accessed from the start interface, which were laboratory measurement system of canopy volume, orchard measurement system of canopy volume and variable rate spraying system based on canopy volume measurement.

The working screen capture of orchard measurement system of canopy volume is shown in Figure 9, where "parameters setup" area is used to set system working parameters, such as the distance between sensors and center line of crop row, sensor spacing and heights above ground of sensors. "Canopy diameter display" is used to display the canopy diameters detected by sensors, the crop number is also displayed in this area. "Tree shape display" area is used to display the tree shape vividly. The buttons on the bottom of the are used to start or stop the work of sensors and quit the system. "Start left series sensors" and "start right series sensors" in Figure 9 are grayer, which indicates that the left and right series sensors are working. The experiment details were introduced by Kaiqun Hu [START_REF] Hu | Design and Research of Variable-rate Spraying System Based on Canopy Volume Measurement[END_REF] .

Fig. 7. Schematic view of flow control mechanism.

The working screen capture of variable rate spraying system based on canopy volume measurement is shown in Figure 10, where "parameters setup" area is used to set system parameters, "crop parameter display" area is used to display the crop number, canopy volume of a single crop and canopy diameters detected by sensors. "Nozzle flow display" area is used to display the current nozzle flows. Buttons on the bottom left of the interface are used to start or stop spraying and quit the system. "Start left spraying" button in Figure 9

Flow Chart Design

The control flow chart of single chip to ultrasonic sensors is shown in Figure 11.

Where the single chip is started and initialized first, and then waits for instructions from host computer. The single chip controls ultrasonic sensors by instructions of host computer, and also sends the measured data to computer by RS232 serial port for further data processing. Taking one ultrasonic sensor as an example, the work flow chart of sensor is shown in Figure 12. Where t is the calculagraph reading after completing sampling, the subscript represents sampling times, buffer T is used to store the lesser calculagraph reading of two adjacent samplings. At last, the minimum value was gained, and the minimum distance between sensors and canopy foliage was calculated.

Conclusion and Discussion

A variable rate spraying system based on canopy volume measurement was presented and developed, which included PC, single chip, ultrasonic sensors, flow control mechanism and nozzles. Hardware and soft ware designs were introduced in this research. Hardware design mainly included choice of hardware, connections of hardware and installation of hardware. Software design mainly included system interface design and flow chart design. Canopy volumes could be measured by this system, the measurement results could be displayed in system interface vividly, and the system control could be implemented from the system interface.

The system realized the automatic measurement of canopy volumes, but more experiments should be done to determine the accuracy and applicability of the system, affection of weather conditions such as wind velocity, wind direction on the system, and the canopy volume measurement time of the system should be analyzed to confirm whether the time delay is allowed in the whole variable rate spraying system.

Fig. 1 .

 1 Fig. 1. Schematic view of variable rate spraying system based on canopy volume measurement.

Fig. 2 .

 2 Fig. 2. Work schematic view of ultrasonic sensors and single chip.

Fig. 3 .

 3 Fig. 3. Photograph of ultrasonic sensor.

Fig. 4 .

 4 Fig.4. The photograph of single chip. 1 power plug 2 power switch 3 P0 port 4 power contact pin 5 5V power contact pin 6 buzzer 7

Fig. 5 .

 5 Fig.5. Connection schematic view of ultrasonic sensors and single chip.

  is grayer, which indicates that only the left started, so only the crop parameters and nozzle flows of left spraying unit are displayed in Figure10.

Fig. 8 .

 8 Fig. 8. Start interface of the whole system.

Fig. 9 .

 9 Fig. 9. The working screen capture of orchard measurement system of canopy volume.

Fig. 10 .

 10 Fig. 10. The working screen capture of variable rate spraying system based on canopy volume measurement.

Fig. 11 .Fig. 12 .

 1112 Fig. 11. The control flow chart of single chip to ultrasonic sensors

Acknowledgements: We wish to thank Zhang Jianhua for their technical assistance. The work was funded by the National Key Technology R&D Program of China (2007BAD89B04) and the National High-tech R&D Program of China (2008AA100905).


Yuting Yang

Haijiang Tai

Daoliang Li

Yaoguang Wei

A Wireless Sink Node Using Information Fusion for Water Quality Information Collection in Factory Aquaculture

Keywords: the wireless sink node, information fusion, Support Vector Regression, Fuzzy Algorithmic Approach

Abstract: Water quality information collection is an important part of factory aquaculture. This paper proposes a kind of wireless sink nodes using information fusion for water quality information collection in factory aquaculture. In the sink nodes, Support Vector Regression and fuzzy algorithmic approach are used for information fusion. Making decisions according to information fusion, it converts the collected water quality information into a simple parameter that signified the current state of water quality. The sink nodes can eliminate redundant information, reduce information transmission, thus save energy effectively and prolong the network life.

INTRODUCTION

 In china, the traditional aquaculture is usually in the consumption of natural resources and at the cost of environmental pollution. Recently, the factory aquaculture has occupied an important position in china, and been the representative of the advanced agriculture and the trend of agricultural modernization. So the development of factory aquaculture is the inevitable requirement to realize the fishery breeding sustainable development. As we know, infrastructure equipment modernization is the basic condition to develop factory farming. Similarly, as the important component of factory aquaculture, water quality monitoring is the key link to promote factory aquaculture toward automation, large-scale, high yield and high quality. In monitoring area, sensor nodes usually gather all kinds of water quality information, such as temperature, light, dissolved oxygen, Ph,etc, which codetermine to the current water quality conditions [START_REF] Chatzigiannakis | Efficient data propagation strategies in wireless sensor networks using a single mobile sink[END_REF][START_REF] Zhang | Field Measurement and Analysis on Diumal Stratification in Taihu Lake[END_REF] .

Presently, the great majority water quality monitoring systems adopt the same method that data which was collected by each node will be transferred to the monitoring center directly, besides the monitoring center process data and send the control instruction. But this method brings so big burden that transmission speed is slow. Moreover, many of the data transmission are redundant information for the monitoring center. Actually, the monitoring center just pays attention to the abnormal water quality conditions, and it will take control measures about water environment in abnormal conditions [START_REF] Hitha | Mid Fusion: An adaptive middleware for information fusion in sensor network applications[END_REF][START_REF] Wang | A genetic algorithm for determining nonadditive set functions in information fusion[END_REF][START_REF] Bomberger | A new approach to higher-level information fusion using associative learning in semantic networks of spiking neurons[END_REF] .

This paper, we refer to add the wireless sink node gather into the water quality monitoring system.

Through information fusion at the sink node, all kinds of complicated water quality information will be converted into a simple parameter, and only send the abnormal water environmental data, which can extremely eliminate redundant information, effectively reduce the input data, thus save energy, prolong the network life, and improve the reaction of the whole monitoring system validly and accurately.

HARDWARE STRUCTURE DESIGN

Figure 1 is the structure diagram of the wireless sink node, the device works as follows: As the CPU of the wireless sink node, the chip S3C2410 that was made by Samsung Company integrated the ARM920T core processor with 32-bits micro controller. The microprocessor contains 16KB instructions, 16KB data cache, LCD controller, RAM controller, NAND flash controller, a 12C bus controller, a 12S bus controller, four PWM timer and an internal timer, touch screen interface, two USB interface controller, four DMA channel, three UART, two SPI, parallel I/O interface, and maximum basic frequency is 203MHz. Depending on the rich peripherals and interface, it can accomplish some full-featured application under the condition of low cost and low power consumption. SPI serial port makes it possible to connect S3C2410 with XBEE chips, which realizes the data transmission between the embedded platform and the sensor nodes via ZigBee network; Two-way UART serial port connect respectively with MC35I chip and MAXI490 chip, so as to realize cable connection between the sink node and the monitoring centers, then accomplish data and control instructions transmission and related data storage via the GPRS network [START_REF] Du | Design of water quality monitoring wireless sensor network system based Oil wireless sensor[END_REF] .

This equipment introduces dual mode communication. On the one hand, data which are collected by each sensor node that is deployed in the factory aquaculture area will be transferred to the wireless sink node through ZigBee communication module based on the RF chip XBEE. Furthermore, the on-site environment parameters and control instructions are sent via the ZigBee wireless network, which obtains reliable, accurate data transmission and data analysis. Its characteristics are at short range, low complexity, low power consumption, low cost, communication distance from standard of 75 meters to hundreds of meters or a few kilometers, and supporting for unlimited expansion. According to the demand of factory aquaculture, and considering the difference between the factory breeding and the standardization pond farming, the structure of wireless sensor network is based on the ZigBee protocol. In addition, ZigBee network has different network topology of tree, star, etc. The paper is designed with the tree network structure, namely a cluster is constituted with a wireless sink node (primary device), lots of wireless sensor nodes and some wireless control nodes (slave unit), and relay node; then a network is constituted with many clusters [START_REF] Gonzá Lez-Soriano | Remote Web Monitoring and Activation of an Experimental On-off Dissolved Oxygen Concentration Control Model Applied to Aquaculture Tanks[END_REF][START_REF] Cheng | An Online Monitoring System of Water Quality Based on ZigBee[END_REF] .

On the other hand, the connection of sink node with monitoring centers is in two ways of wired and wireless. Via GPRS network, the sink node could connect with the remote monitoring center. The MC35I GPRS module was designed into the equipment, and its output pins connect directly with the ARM processor's serial port 0(UART0

INFORMATION FUSION

Because what the monitoring center just pays attention to is the abnormal water quality condition.

Only when the environmental conditions are in the abnormal situation may take control measures. If

doing Information Fusion at sink node to find abnormal water environment and only sending abnormal water quality data, which can eliminate the redundant information, reduce the amount of data transmission, save energy, prolong the network life effectively, improve the rapidity and correctness of the whole monitoring system's response [START_REF] Jin | A Novel Design of Water Environment Monitoring System Based on WSN[END_REF][START_REF] Yan | Short-Term Predicting Model for Dissolved Oxygen of Hyriopsis Cumingii Ponds Based on Elman Neural Network[END_REF] . After each collection node power up, do the port and memory initialization first and apply for the ZigBee network. After getting the response of the network, scan each node by the network and then assign the network address that is not used within the given time to the node. Detection of whether the response of sensor is normal. If not, storage the alarm information for preparation to exchange information with the sink node, and at the same time set to 1 at the alarm bite. If it's normal, it can transmit data to sink node at short distance by the ZigBee. Then information fusion can be done at the sink node. The whole process of information fusion is shown in figure 2.

This part of the information fusion is divided into two components, the first part is data fusion pretreatment.

Start

Data Fusion Pretreatment

Data fusion pretreatment includes both abnormal data cleaning and data transformation.

Abnormal Data Cleaning

In this section, the main responsibility are abnormal data identification, eliminating noise, correcting the inconsistent data , deleting data redundancy and the completion of detection with sample data that are significant difference with other data in the collected data set. For abnormal data and noise, the principles of management is cleaning and not to participate in the fusion processing. x should be gross error and be eliminated.

| | | | 3 ii v x x S     (1)
After every obliterating gross error, the rest of data will be recounted S. According to the new numerical that had become smaller S, further determining are measured again to judge whether there is gross error until without gross error. Bessel formula is as follow:

2 1 ( ) ( ) 1 i i i k i S x k x k x n    (2)

Data Normalization

In order to eliminate error that is caused by differences in the dimension within different data source, the data from different data source will be normalized. min max min

i i xx x xx    (3)

Data Fusion

Completing data pretreatment, the second part of information fusion is data fusion based on Support Vector Regression (SVR) and fuzzy algorithmic approach.

Support Vector Regression

In the factory aquaculture, because of indoor cultivation we can rule out the interference of natural environment, such as wind speed, wind direction, rainfall, etc. What we mainly concern is two factors, the water temperature and dissolved oxygen. Besides, the dissolved oxygen is the most important factor to effect the healthy growth of aquatic products. However, the adjustment of water quality in the breeding relate to what water quality factor are measured accurately and timely. But as circumstances change, there are certain delay itself for dissolve oxygen, and there is also the problem of transmission delay. So, the paper puts forward the information fusion algorithm which gets dissolved oxygen and water temperature as the input parameters of SVR, then the predicted value of dissolved oxygen as the result of information fusion. What the dissolved oxygen of next time is on behalf of water quality conditions make it convenient to control breeding environment timely and accurately [START_REF] Wang | Remote Water Quality Monitoring System Based ON WSN and GPRS[END_REF][START_REF] Li | Improvement of remote monitoring on water quality in a subtropical reservoir by incorporating grammatical evolution with parallel genetic algorithms into satellite imagery[END_REF] .

The standard SVR algorithm is divided into the linear and nonlinear. The basic idea of the SVR is:

it will transform the sample space into another feature space through the nonlinear transformation, and construct regression function in the feature space. The nonlinear transformation could be achieved by defining the appropriate kernel function ( ,

) ij K x x . Besides, ( , ) ( ) ( ) i j i j K x x x x  , () x
 is a kind of nonlinear functions.

Given the training data, {( , ), 1, 2, , }

ij x x i n  , i
x is learning samples, and i y is the corresponding target. Define linear insensitive loss function is:

() 0 () () () y f x y f x y f x y f x            (4)
Namely, if the D-value between the target y and after learning of the structure regression estimation function f(x) is less than  , the loss is 0.

With the nonlinear circumstances, the regression estimation function is:

( ) ( ) T f x x b     (5)
Looking for a couple of  and b ,which minimize 1 2

T under the same type [START_REF] Chatzigiannakis | Efficient data propagation strategies in wireless sensor networks using a single mobile sink[END_REF]. Also consider to introduce the relaxation value * , ii  when the constraint conditions could not be fulfilled, so the optimization problem is:

* 1 * 1 () 2 . . ( )
() n T ii i i i i i i i Min C s t y x b x b y                                   * 0, 1, 2, , i in   (6)
Using Lagrange multiplier to solve the constrained optimization problem, so construct the Lagrange function:

    2 * * * * * 1 1 1 1 1 ( ) ( ) ( ) 2 n n n n P i i i i i i i i i i i i i i i i i L C y x b y x b                                              (7)
By the optimization theory, make P L to * , , , ii b    respectively for asking partial differentia, and make its 0.

  * 0 0 ( ) 0

n i i i i L x               (8)   * 0 00 n ii i L b          (9) 00 ii i L C          (10) ** * 00 ii i L C          (11)
When applies the type (5) in the type (4), we get the dual optimization problem.

* * * * 1 1 1 1 * 1 1 ( )( ) ( , ) ( ) ( ) 2 . . ( ) 0 n n n n i i j j i j i i i i i i j i i n ii i Max K x x y st                                      * 0 , 0 ii CC      (12)
Support vector (SV) is part of parameters that make

i i i x esv f x K x x b      ( 13
)
We also get:

  * * 0 0 1 ( ) ( , ) ( ) ( , ) j i j i i j j j i i j j j i C x esv C x esv NSV b y K x x y K x x N                                 (14)
Besides, the function ( , ) i K x x , which is known as the Kernel Function. Kernel functions enable dot product to be performed in high-dimensional feature space using low dimensional space data input without knowing the actual transform function  .All kernel functions must satisfy Mercer' condition that corresponds to the inner product of some feature space. The radial basis function (RBF) is commonly used as the kernel for regression:

  2 x i xx i K   ( ,x)=exp (15)
After training and learning, we will establish the support vector regression model so as to realize the information fusion of acquisition. Then we will convert the results to practical engineering unit through inverse transformation [START_REF] Liu | Design of Intelligent Dissolved Oxygen Detecting System Based on CAN Bus and Embedded USB Host[END_REF][START_REF] Wei | Prediction of Dissolved Oxygen Content in Aquaculture of Sea Cucumber Using Support Vector Regression[END_REF] .

max min min () ii x x x x x      (16)
Where max min , xx is respectively the maximum and minimum value before normalization in Eq. (3).

Fuzzy Algorithmic Approach

Through the analysis of real object, Fuzzy algorithm is developed to process data and construct fuzzy mathematical model. With subordinate relations, the data set was changed into the fuzzy set to determine the membership function. Fuzzy statistics is more than the basis of experience a psychological process. It often works through the psychological measurement, and search the fuzziness of the thing itself [START_REF] Lin | A Remote Automated System for a Case Study of Dissolved Oxygen Monitoring and Control[END_REF] .

In the paper, we adopt fuzzy algorithmic approach with triangle membership functions to make fuzzy computation for dissolved oxygen that had been calculated via the support vector regression algorithm. Then it's divided into the different water quality abnormal conditions as table 1

STUDY SITE AND IMPLEMENTATION

The practical wireless sink nodes had already been integrated in the water quality monitoring system which was implemented in the factory aquaculture farm of Xin Yongfeng aquaculture Co., LTD, located in Tianjin, China, one of Intensive Aquaculture Research Demonstration Centers of China Agriculture University. The system has stable operated more than one year and has obtained many water quality parameters. The water quality monitoring system is shown in Figure 3. According to the actual demand, the collection nodes include DO sensor and temperature sensor which have the ability of self-calibration, self-compensation and self-diagnosis. Besides, the sensors are solar powered and adopt dormancy strategy to save energy. So the whole working process is that collection nodes collects water temperature and dissolved oxygen, and then sends the data to sink nodes through ZigBee wireless protocol; Secondly, in the sink nodes. making decisions according to information fusion, which converts the collected water quality information into a simple parameter that signified the current state of water quality; On-site monitoring center can directly get the regularly updated data from sink nodes through RS485 interface, then provide the function of data show, data storage and data download; At the same time, the sink nodes can transmit the data to remote monitoring center through GPRS channel, and remote monitoring center can also undertake the works of data receiving, data storage and data download. Besides the monitoring center will take control measures with water environment in abnormal condition.

RESULTS AND CONCLUSION

When being used in the water quality monitoring of factory aquaculture, the water quality monitoring system is stable and can meet the production need. The data which has been adopted in this paper spanned 6 days, from June 8 to June 13, 2011. The sampling interval is 30 minutes, which means 48sets of data has been collected per day, the total samples is 284. Figure 4 shows accurate value of water temperature and dissolved oxygen collected by the system.

In this paper, we put forward the information fusion algorithm which gets dissolved oxygen and water temperature as the input parameters of SVR, then the predicted value of dissolved oxygen as the result of information fusion. So we adopt 230sets of data as the training data to train the SVR modes, the last 54 sets of data as testing data to analysis the prediction performance of SVR. After the regression process, we get the optimal function as shown in Eq. ( 13) that can be used to take prediction.

Because the sampling interval is 30 minutes, so we predict the dissolved oxygen value of 30 minutes later.

CONCLUSION

To solve the problems of water quality information collection and satisfy the needs of factory aquaculture farms, this paper designs a sink node using information fusion to integrate into the water quality monitoring system.

The ARM7 architecture of the 32-bit processors was introduced in the sink nodes as the hardware foundation. And depending on the rich peripherals and interface, it can accomplish some full-featured application under the condition of low cost and low power consumption. According to the actual requirements, the multi-mode of communication were adopted as follow: Firstly, the use of GPRS communication module will assist with collection data transmission to the sink nodes; Secondly, the on-site monitoring center could directly get the water quality information that had been processed at the sink nodes through the 485 interface; Furthermore, for the remote monitoring center, the on-site environment parameters and control commands of platform were via the ZigBee wireless network for data transmission. can obtain reliable, accurate data transmission and analytical. It can not only obtain reliable, accurate data transmission and analysis, but also satisfy the different operating requirements of farmers.

What's more, the sink nodes also have the function of information fusion that adopts Support Vector Regression and fuzzy algorithmic approach. According to information fusion, we can make decision to convert the collected water quality information into the simple parameters that could be on behalf of the current state of water quality. The measurement can eliminate redundant information, reduce information transmission, thus save energy effectively and prolong the network life. With information fusion, Water quality abnormal information can be found in real time, so as to improve the reaction validly and accurately of the whole water quality monitoring system.

Besides, the paper puts forward the information fusion algorithm that gets dissolved oxygen and water temperature as the input parameters of SVR, then the predicted value of dissolved oxygen as the result of information fusion. What the dissolved oxygen of next time is on behalf of water quality conditions make it convenient to control breeding environment timely and accurately.

At present, the sink nodes have been applied successfully into the water quality monitoring system, which were implemented at Intensive Aquaculture Research Demonstration Center in Tianjin. So it has a widely application value and market prospect.

Fig1.

  Fig1. The structure diagram of the wireless sink node

Fig2.

  Fig2. Information fusion flow chart

Fig3.

  Fig3. Water quality monitoring system

Fig. 4 .

 4 Fig.4. Accurate value of water temperature and dissolved oxygen In the experiments, the LIBSVM package had been used for SVM pattern recognition and regression. The package was designed by the Taiwan university professor LinChin-Jen. The specific steps as follows: (1) Format data sets according to the requirements of the LIBSVM package. Put the

  Here we adopt the 3 standards based on statistic analysis. Firstly, it's assumption that a set of test data only contain the random error, and carry on calculation processing to get standard deviation, determine a range according to certain probability. It's supposed that exceeding the error range is rather the random error than the gross error, and contains the gross error of data should be rejected. With 3 criterion for judging calculation, firstly it's to get the average x of the value

i x to replace true value, then residual obtained ii v x x , getting standard deviation calculated by Bessel formula to replace  , comparing the value of 3S with each residual i v , if the residual i v of some suspicious data i x meet next type, the data i

Acknowledgment: This research is financially supported by the Science and Technology Projects of Tianjin Binhai new area: the Integrated Application and Demonstration of Factory Breeding Technology with High Efficiency and Low Carbon, the Twelfth Five-Year-Plant Outline for National Economic and Social Development of the People's Republic of China (2011BAD21B01) and Beijing Natural Science Foundation (4092024). The authors would like to thank the members of Intensive Aquaculture Research Demonstration Center in Tianjin for their hospitality and assistance.