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TABLE 3. Seasonal water amount (2010-2011) for lettuce irrigation in the case study. SURFACE (ha) DEC 2009 JAN 2010 FEB 2010 MAR 2010 APR 2010 SEP 2010 OCT 2010 NOV 2010 DEC 2010 JAN 2011 FEB 2011 MAR 2011 APR 2011 Irrigation water amount (m 3 ) 9.6821 38,118.43 25,928.66 1.4690 2,798.45 9.0481 4.2680 24,927.52 27,551.47 11,237.64 13,892.34 15,575.04 5.4080 21,388.64 20,761.31 7.6500 30,079.80 42,036.75 4. Conclusions The methodology employed for WUA can be perfectly adapted to irrigation systems in farms. In this paper this methodology has been applied to a commercial plot of 98.93 ha cultivated with Iceberg lettuce (Lactuca sativa L. cv. Capitata) and endowed with trickle irrigation, obtaining the following conclusions: Consumed irrigation water volumes per irrigated area are under crop water needs. The energy cost per unit irrigation supply (CENV T , €·m -3 ) is within the average values measured in the zone. The studied pumping system has a normal energy efficiency value and does not need urgent measures for its improvement, although an adequate adjusting would help to reach values over 60%. The studied irrigation system can be classified as consumer, energy consumption group 4, according to consumed active energy per unit irrigated area (EacSa, kWh·ha -1 ). Regarding general energy efficiency value (EEG), the system is classified as A (excelent energy efficiency), and the pumping station as C (normal energy efficiency). A change of energy tariff has not been considered since 3.1A is already the most adequate. However, energy consumption in more economical periods is recommended, being able to reach a cost saving around 27%. Study of annual offers from the companies is also proposed. The substitution of a automatic capacitor bank is an adequate measure to avoid surcharges for reactive energy, and is recovered in a short period of time. By means of the simultaneous control of monthly energy and water consumptions it is possible to improve the energy system efficiency and predict anomalous consumptions. Energy cost increases considerably the total cost of water, which differs between different networks. References Abadía, R., Rocamora, C., & Ruiz, A. (2008a). Protocolo de auditoría energética en comunidades de regantes. Instituto para Diversificación y Ahorro de la Energía, IDAE. Serie Divulgación Ahorro y Eficiencia Energética en Agricultura. 10. Madrid: Ministerio de Industria, Turismo y Comercio. Abadía, R., Rocamora, C., Ruiz, A., & Puerto, H. (2008b). Energy efficiency in irrigation distribution net-works I: Theory. Biosystems Engineering, 101(1), 21-27. Hospido, A., Mila i Canals, L., McLaren, S., Truninger, M., Edwards-Jones, G., & Clift, R. (2009). The role of seasonality in lettuce consumption: a case study of environmental and social aspects. International Journal of Life Cycle Assessment, 14 (5), 381-391.
Relationship among compaction, moisture and penetration resistance in horticultural soil. Carlos Gracia 1 , Estela Alemany 1 , Inmaculada Bautista 2 1 Unidad de Mecanización y Tecnología Agraria, Universidad Politécnica de Valencia. 2 Unidad de Edafología y Climatología. Grupo REFOREST, Universidad Politécnica de Valencia, Camino de vera s/n, 46022 Valencia, Spain. cgracia@dmta.upv.es ABSTRACT Penetration mechanical resistance in agricultural soil is recognized as a limiting parameter on root development. This makes it a necessary variable for an adequate management of the soil. However, in field measurements by means of a cone penetrometer become hard to achieve. In case of stony soils or soils with previous crop residues these measures also turn to be erroneous because of circumstantial interpositions into the vertical path of the cone. Therefore, it is useful to relate penetration resistance to other variables such as texture, organic matter, bulk density or moisture content which determination is more precise. This study sets the relationship among penetration resistance, bulk density and moisture content in a sandy clay loam horticultural soil containing a high percentage of small stones, as those found in Eastern Spain. However, this stony characteristic does not seem to advise against its use to grow vegetables. Penetration resistance was measured periodically by a cone penetrometer from laboratory soil samples. Samples got rid of stones, were enclosed in cylindrical containers and led to different levels of compaction. Compacted samples were moistened up to field capacity by capillary rise. Measures were taken as the soil dries by forced evaporation and up to the wilting point. Finally, the obtained measures led to a functional relationship between penetration resistance, moisture content and bulk density. From this, it is possible to generate tables for in field application. Keywords: compaction, moisture penetration resistance, penetrometer. 1. Introduction The capacity of plant roots to penetrate the ground is limited with increasing soil resistance (Mason et al., 1988). In many species, the growth of roots is prevented completely, from a specific resistance of 2.5 MPa (Taylor, 1971). The inability of roots to penetrate compacted soil is well documented in the literature (Kirkegaardet al., 1992; Venezia et al., 1995; Lakers, 2001). According to (Bengough et al., 2001), soil penetration resistance (SR) is, “the force required to push the cone into the soil divided by the cross-sectional area of its base.” Initially, the SR could be measured by a cone penetrometer (Bengough et al., 2001) considering the pressure exerted by the probe over the resistance to friction, and adhesion strength due to soil-metal (Farrell and Greacen, 1996). Although this method is widely employed, sometimes the use of a cone penetrometer turns out to be tough and defective. This is enhanced in high presence of stones or previous crop residues. Alternatively, it is proposed indirect measures of resistance to penetration, starting from their dependence on certain parameters of the soil. This will take into account, texture, organic matter content, bulk density, moisture content, among others. It comes to determining then, the functional relationship of
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POSTER SW: SOIL AND WATER ENGINEERI
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Presenter: Jose Euclides Paterniani
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1 Faculdade de Engenharia Agricola
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Matsura Department of hydraulic and
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P-2064 MULTIVARIATE STATISTICAL OF
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temperature-based (e.g., Thornthwai
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two types of reference surfaces rep
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(d) Baft (c) Bam (b) Kerma n (a) Ji
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Estevez, J., Gavilan, P., & Berenge
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2. Materials and Methods 2.1 The hy
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Ia = n × v ec Equation 3 which: Ia
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5. References ALLEN, R.G.; PEREIRA,
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The density analysis was performed
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Figure1 - Relationship between the
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4 Conclusions • The density obtai
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characteristics resulting from of g
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Table1. Morphological characteristi
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Transpiration of Eucalyptus spp see
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The fertilization growth and harden
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Cool, J. B., Rodrigo, G. N., Garcí
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Abstract Agriculture and water sour
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In 1985 and 1986 hygienic protectio
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spring area. It is also prohibited
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Biological Nitrogen Fixation In Gen
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We used a completely randomized in
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5. References AYERS, R.S.; WESTCOT,
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2 However, the cultures are not alw
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4 TABEL 2: Mean values of radiation
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accumulated ETo (mm dia -1 ) 6 900
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only the expansion of agricultural
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FIGURE 2: Content of chlorophyll a,
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Evapotranspiration and Crop Coeffic
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were respectively applied in the fi
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TABLE 1: Irrigation depth and actua
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NUTRIENT RETENTION IN WETLANDS USIN
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Table 2. Daily affluent concentrati
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IMPORTANCE OF DRY GEAR MASS CULTURE
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mobilizing assimilated exerted by c
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This method consists of covering th
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uncovered ones, that mixed the wate
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coliforms and E-coli that might hav
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WATER TREATMENT BY COAGULATION WITH
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in a grinder and passed through a 0
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3.2. Determination of the required
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Page 91 and 92: This methodology consists of a sequ
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Page 95 and 96: Water technology improvements and t
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Page 99 and 100: higher demand than those of scenari
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Page 103 and 104: uniformity of flowering. The irriga
Page 105 and 106: Table 3 - Analysis of variance for
Page 107 and 108: SUGARCANE FERTIRRIGATED WITH MINERA
Page 109 and 110: 3. Results and Discussion The value
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Page 113 and 114: Optimal Reservoir Operation Model w
Page 115 and 116: all periods are computed using Eq.
Page 117 and 118: (a) Calibration (b) Verification Fi
Page 119 and 120: Characteristics of Heavy Metal Cont
Page 121 and 122: 2. Materials and Method 2.1. Study
Page 123 and 124: TABLE 2: Devices for collecting of
Page 125 and 126: Calibration of Hargreaves Equation
Page 127 and 128: Relative error (RE): Index of agree
Page 129 and 130: Stochastic modelling of Contaminant
Page 131 and 132: widely used for various fields such
Page 133 and 134: show that Extvalue and Logistic dis
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Page 145 and 146: Figure 9 High compaction. Bulk dens
Page 147 and 148: Simulation of water flow with root
Page 149 and 150: water contents were almost greater
Page 151 and 152: Operation and Energy Optimization M
Page 153 and 154: Urmia Salt Lake Urmia FIGURE 1: Gha
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Page 157 and 158: Application of Surface Cover and So
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Page 161 and 162: Choi, J. D., (1997). Effect of Rura
Page 163 and 164: 1.1. Scope and aim The growth of th
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Page 169 and 170: Reclaimed wastewater reuse has been
Page 171 and 172: Fig. 2 shows the monitoring results
Page 173 and 174: 3. Conclusions Reclaimed wastewater
Page 175 and 176: Q P Ia 2 P Ia S for P≥Ia Q 0
Page 177 and 178: data P (mm), gauged in 130 pluviogr
Page 179 and 180: TABLE 2: CN emp values obtained for
Page 181 and 182: References Chapman, T. G. & Maxwell
Page 183 and 184: This work, after applying Kennessey
Page 185 and 186: TABLE 2 - Partial runoff coefficien
Page 187 and 188: Figure 3 also reports a comparison
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TABLE 2: Summary of variance analys
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BEZERRA, I. L.; GHEYI, H. R.; FERNA
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2. Materials and Methods The study
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Figure 3. Hourly values of ET estim
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Ortega-Farias, S.O., Cuenca, R.H.,
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2 Material end methods The wastewat
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Queiroz et al. (2004) and (Fonseca
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Reference list CEREDA, M.P. (2001)
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2. Data and Methods 2.1. Methods Ir
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3. Results The water balance model
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Acknowledgments This work was carri
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and the need to reduce costs, it be
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40 mm 65.30 59.00 8.70 8.10 60 mm 6
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REFERENCES BERTRAND, J. P. et al. L
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The mathematical modeling in the wa
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OD (mg L -1 ) OD obs (mg L -1 ) TAB
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OD (mg L -1 ) DBO (mg L -1 ) 8,00 7
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Effect of Rice Straw Mulch on Runof
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mg/L, 14.6 mg/L, and 1.2 mg/L, resp
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1 PAPAYA SEEDLINGS PRODUCTION FROM
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3 into an oven with circulating air
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5 14 12 Stem diameter (mm) 10 8 6 4
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7 Root dry matter (g plant -1 ) 8 7
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CAVALCANTE, L. F.; CORDEIRO, J. C.;
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This document was created with Win2
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extractable and non-extractable bou
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MOD-E and MOD-B, and 65.99% and 80.
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Houot, S., Barriuso, E., Bergheaud,
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measures water content and electric
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As observed, increasing the dischar
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irrigation: a comparison of point a
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field operations (STRECK et al., 20
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3. Results and discussions Table 1
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4. Conclusions It can be concluded
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water maintenance. At the same time
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TABLE 1 Stream discharge for each m
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TABLE 5 Correlation analysis of wat
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turbulent flow energy produced by w
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The numerical model was validated a
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4. Conclusion FIGURE 6: The shape o
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2.1 Case study The Zayandeh-Rud bas
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economic factors. In this is a very
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FIGURE 1. Location of the Wuliangsu
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WT( o C) (a) 30 25 20 15 10 5 0 -5
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(a) (b) (c) (d) (e) (f) (g) (h) (i)
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• The effectiveness of the crop c
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As evidenced by Rana et al. (2005),
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1.20 1.20 2010 2011 0.90 0.90 K c 0
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elationships. There is forest area,
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B = ( c − a) A − ( c − d) c
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References Choi, W.-J., Lee, S.-M.,
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of faecal bacteria (Kummerer, 2004;
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FIGURE 1 - Project tasks and links
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Oliveira, A.B. & Henriques, M. (201
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1 Introduction To irrigate is to su
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the inverter that provides a refere
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OLIVEIRA FILHO, D. ; SAMPAIO, R. P.
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1.1 Description of the Study Area T
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Refrences: Bruce J.P. (1994). Natur
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RE because it has the advantages ov
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with L 1 2 com obs J ( k ) = ∑{ f
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Relative hydraulic conductivity r 1
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surfaces requires information on th
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climate. Therefore a special coeffi
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FIGURE 2: The relation between K pa
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Coagulation using Moringa oleifera
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After the assembly of the experimen
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For the positive control test, the
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MULTIVARIATE STATISTICAL OF PRINCIP
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The multiple regression equations w
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Table 3 - Regression models that be
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Is Imaging Analysis Quantifying the
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of the computer. All additional ima
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The final enhanced images were segm
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image analysis is well suited and f
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EVALUATION OF CROP CANOPY EFFECT ON
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∂e ∂e ∂e + u + v ∂t ∂x
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4. Results and discussion 4.1. Spat
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Benchmarking of Irrigated Agricultu
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Indicators can be thought of as sta
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total area is about 13,700 km2. The
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