Spatial Variability of Soil Nutrients Content Related to Rice Yield (T Syam): Soil nutrients content and its spatial distribution are very important data for site specific fertilizer management to supply sufficient crop nutrition.  The study was carried out  at the farmer paddy field in Rejomulyo Village, Metro Town District of Lampung Province. The aim of this study was to evaluate the relationship between soil nutrients content (N, P, K) and rice yield. Soil samples were collected before fertilizers treatment by the grid sampling method and GPS was used as a tool for precisely determine sample site location.  Rice yield data were collected by small plot method on the each-of soil sample location. Spatial analysis using GS + software and statistical analysis using SPSS software. The result indicated that total nitrogen in the soil had a significantly correlation with the rice yield   (r = 0.95**) and their spatial distribution was relatively similar each others.  Spatial maps of soil nutrients content could be used for the variable rate fertilizers treatment, especially for nitrogen

Syam, Tamaluddin

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University Of Lampung Journal Publication

153J Trop Soils, Vol. 15, No. 2, 2010:  153-157Spatial Variability of Soil Nutrients Content Related to Rice Yield Tamaluddin Syam1Received 30 November  2009 / accepted 5 May 2010ABSTRACTKeywords:  Rice yield, soil nutrients content, spatial maps, variable rate fertilizerSpatial Variability of Soil Nutrients Content Related to Rice Yield (T Syam): Soil nutrients content and its spatialdistribution are very important data for site specific fertilizer management to supply sufficient crop nutrition.  Thestudy was carried out  at the farmer paddy field in Rejomulyo Village, Metro Town District of Lampung Province.The aim of this study was to evaluate the relationship between soil nutrients content (N, P, K) and rice yield. Soilsamples were collected before fertilizers treatment by the grid sampling method and GPS was used as a tool forprecisely determine sample site location.  Rice yield data were collected by small plot method on the each-of soilsample location. Spatial analysis using GS + software and statistical analysis using SPSS software. The result indicatedthat total nitrogen in the soil had a significantly correlation with the rice yield   (r = 0.95**) and their spatial distributionwas relatively similar each others.  Spatial maps of soil nutrients content could be used for the variable rate fertilizerstreatment, especially for nitrogen.1Soil Science Department, Faculty of Agriculture, The University of Lampung, Jl. Sumantri BrojonegoroNo. 1 Bandarlampung 35145, e-mail: tamal_syam@unila.ac.id J Trop Soils, Vol. 15, No. 2, 2010: 153-157 ISSN 0852-257XINTRODUCTIONPrecision  farming systems are an agriculturalmanagement technology which basically aims togenerate sustainable agricultural production and it isabout the farm management techniques which arebased on a specific spatial variability of landcharacteristics including soil nutrients content,temperature regime, water, and crop requirement inthe field.  The purpose of precision farming systemis to integrate the use of land resources characteristicsand crop requirements by the agronomic practices  dueto variability of land characteristics for every placeand time (McBratney and Pringle 1997). Furthermore,Voltz (1997) stated that appropriate farming systemsrequired accurate information about the landcharacteristics in detailed and land management toimplement specific land treatment. A site-specificmanagement basis would optimize yields and inputs(Reyniers et al. 2006). A fundamental question of thefarmers on precision farming concept is how tomeasure and properly treat the diversity of landproperties for site specific  management program onrationally cost (Grenzdorffer 1997).  In principle,precision farming system requires three maincomponents namely: (a) global positioning system(GPS) to determine precisely where the position ofthe samples, (b) proper time mechanism forcontrolling nutrients, pesticides, soil moisture andother production inputs, and (c) a database thatprovides information is needed to develop anappropriate package of inputs for various site specificconditions (Camberdella and Karlen 1999). Anintegrated approach of the agricultural process startsfrom the planning of soil tillage, planting, use offertilizers and pesticides, harvesting and post-harvestprocesses.Soil characteristics and  crop yield mapping werethe main key for the success of precision farmingsystems. Therefore the diversity of soil nutrientmapping and the yield should be accurate as possible,because it was used as a basis for determining specifictreatment in precision farming (Schuller 2001).  Thediversity of the  nutrient content  was very importantin precision farming systems, to achieve the cropneeds quickly and appropriately through fertilizing(Tinker 1976). Therefore, the spatial map of soilnutrients content  variability  became very importantAvailable online at:http://journal.unila.ac.id/index.php/tropicalsoilDOI: 10.5400/jts.2010.15.2.153154T Syam:  Spatial Variability of Soil Nutrients Content..in precision farming systems as a basis for granting afertilizer based on specific site specific fertilizationto improve the efficiency of fertilizer use. Accordingto Yanai  et al. (2000), Geostatistics Software was away that can be used to analyze the spatial diversityof soil properties. Results of analysis can be used asa basis for explaining the spatial diversity of soilproperties quantitatively. According to Juang  et al.(2002), the spatial distribution of the fertilizer-Pavailability index can be estimated by using a krigingmap.  Jalali (2007) suggested  that such classes of Kcould formed a basis for variable-rate application tomaintain an adequate K status for crop productionand to reduce potential K loss from soil by leaching.The amount of nutrient in the soil can be easilymanipulated by fertilization (McBratney and Pringle1997).The objective of this study was to evaluate thesoil nutrients content and its spatial distribution ofN, P and K related to  rice yield. The goal of thisstudy is to supply  plant nutrients  precisely byvariable rate fertilizer in accordance with theavailability of nutrient content in the soil.MATERIALS AND METHODSStudy SiteThe study was carried out on October 2005 atthe farmer paddy fields in the Rejomulyo Village,Metro City District, with the geographical positionof  9429145 to 9429370 m north and 534438 to534615 m east.Soil SamplingThe study was done using survey method.Sixteen soil samples were collected before tillage onthe top soil by the systematic sampling with thedistance of 50 m by 50 m and  0 to 20 cm depth.Distribution of sample sites were shown in Figure 1.To determine the precisely geographic position ofeach sample site, Global Positioning System (GPS)was used.Soil and Plant AnalysisAll of soil samples collected were air dried,crushed to pass the 2 mm sieve for analysis of totalnitrogen (N) by Kjeldahl Methods, available ofphosphorus (P) by Bray I, and exchangeablepotassium (K-dd) by NH4OAc.  Soil analysis carriedout in the Soil Science Laboratory Department of SoilScience, Faculty of Agriculture, the University ofLampung.Rice yield data were collected at the every pointwhere the soil sample sites by small plot with thesize of 5 m by 5 m.  The grain yield was weighedbased on the dry weigh of the water content field.Data AnalysisSemivariance analysis and spatial variability mapof soil nutrient content and rice yield were conductedusing Geostatistics plus software (GS +). and therelationships between nutrients content in the soil andthe rice yield were analyzed by classical statisticalanalysis. RESULTS AND DISCUSSION Statistical AnalysisDescriptive  statistical analysis  nutrient contentof N, P and K in the soil were listed in Table 1. Theresults of statistical analysis showed that total Ncontent varied in the range of 0.11 to 0.16%, whileavailable P was in the range of 2.48 to 18.12 ppm andexchangeable K  were 58.65 to 164.22 ppm.  AvailableP content in the soil was the highest coefficient of94293709429314942925894292019429145534438           534615                 534556534497Figure 1. Distribution of soil samples.155J Trop Soils, Vol. 15, No. 2, 2010:  153-157variability, and then followed by Exchangeable K andtotal N, respectively. Based on the existing CV value, available P canbe classified into a high diversity class, while theexchangeable K and total N was classified as low.The low diversity of total N in the soil was most likelycaused by nutrient characteristics of total N itselfwhich was mobile in the soil (Brady, 1990; Havlin,1999). Similar results were done by  Syam et al.(2004)  which stated that the coefficient of nutrientvariability in oil palm plantation were classified inthe highest category for available P, then followed bythe exchangeable K and total N.A correlation test analysis between nutrientcontent in the soil and rice yield showed that total Nwas a very high correlation (r = 0.95 **), and thenfollowed by exchangeable K which was categorizedas a high correlation (r = 0.56 *), whereas for availableP was no significant correlation (r = 0.015).  Thesimilar study which was conducted in the Hanau BrakVillage, South Lampung District showed similarresults which was total N content in the soil had avery high significant correlation (r = 0.96 **) withthe rice yield (Syam 2005).Semivariance AnalysisThe semivariance analysis of soil nutrientscontent were characterized by a semivariogram.Description Total N  (%) Available P   (ppm) Exch. K  (ppm) Minimum       0.11    2 .48   58 .65 Maximum       0.16 18.12 164.22 Average       0.13 11.18   89 .07 CV (%)     14.41 44.28   29 .87  Table 1.  The statistical analysis of nutrient contentin soil.Description  Model Nugget  (Co) Sill (Co+C)  Range (Ao) Nugget Ratio (Co/Co+C)   R2  Total N  Spherical  0.0001 0.0007 121.4 0.14 0.995 Available P   Exponential  19.03 41.04 112.8 0.46 0.066 Exchangeable K  Linier  672.21 672.21 155.5 1.00 0.015  Table 2.  The semivariogram parameters analysis of nutrient content in soil.Description and values of the semivariogramparameters were shown in Table 2.The best fit model for total N, available P, andexchangeable K in the soil were spherical,exponential, and linier, respectively.  The nuggetvalues (Co) was low for total N indicating the smallerror of the estimation processes. The sources of errorsin estimation process might be due to many factorssuch as sampling intensity, positioning chemicalanalysis, data recording and soil properties. Theresults of  nugget ratio showed that total N could beclassified into strongly spatial dependence, whereasfor available P classified into moderately spatialdependence, and then for exchangeable K in the soilwas classified into weakly spatial dependence.   Thisresult demonstrated that in the future samplingmaximum distance of total N,  available P, andexchangeable K in the soil were 121.4 m, 112.8, and155.5 m, respectively. Otherwise, any pair of nutrientvalues by the lag distance was greater than that rangewould be spatially independent. Kriged MapsThe spatial analysis results by kriged  map ofsoil nutrients content and distribution of total N,available P and exchangeable K, and rice yield wereshown in Figure 2.  Based on the appearance in Figure1, spatial distribution patterns of rice yield (Figure2D) were relatively similar to the distribution patternsof nutrient content of total N in the soil (Figure 2A),and it has a close relationship each other. This resultwas similar to the last study by Syam (2005) whichstated that the nutrient content of total N in the soilhad a high relationship with the rice yield which wasindicated by the kriged map spatial distributionpatterns is similar to each other.The kriged map of spatial variability of soilnutr ient content can be used as a basis forconsideration in variable rate fertilization, especiallyfor nitrogen element in order to supply the optimumrequirements for plant growth that can be optimized156T Syam:  Spatial Variability of Soil Nutrients Content A:  Total N     0.110 0.125 0.143 0.160 % 534615 534556 534497 534438  9429145 9429201 9429258 9429314 9429370   B:  Available P     2.48 10.76 11.55 18.12 ppm 534615 534556 534497 534438  9429145 9429201 9429258 9429314 9429370   C:  Exchangeable K    58.65 87.64 90.04 164.22 ppm  534615 534556 534497 534438  9429145 9429201 9429258 9429314 9429370  D:  Rice Yield 534615 534556 534497 534438  9429145 9429201 9429258 9429314 9429370    6,000 6,990 7,890 9,000 kg ha-1  crop production. However, it had to be consideredthat the level of yield was not only determined by thesoil nutrient content alone, but also it was influencedby the other environmental factors. Therefore, thespatial map of soil nutrients content and spatialdistribution of nutrients in the soil was one of themost important factor for the implementation ofprecision farming.CONCLUSIONSIt was concluded that the nutrient content of totalN in the soil was closely related to the rice yield.The increasing of total N content in the soil wasfollowed by increasing of rice yield. So that, spatialmaps of soil nutrients content variability can be usedas a basis for  variable rate fertilizers management  tosupply plant nutrients sufficiently.Figure 2. Spatial variability map of soil nutrients content of  total N, available P andexchangeable K, and rice yield.157J Trop Soils, Vol. 15, No. 2, 2010:  153-157 ACKNOWLEDGMENTSThe author would like to thank to  AchmadHidayat Buys and FX. Meindra Sulistya for theirhelping in conducting this study. Thank also goes toMr. Basir (Alm) and Mr. Sugito as the field farmers’owner which had allowed their land for study andother supporting information about the history of land.REFERENCESBrady NC.  1990.  The Nature and Properties of Soils.Tenth edition.  Macmillan Publishing Company, NewYork.  621 p.Cambardella CA and DL Karlen.  1999.  Spatial analysis ofsoil fertility parameters.  Precision Agric J 1: 5-14.Grenzdorffer, G.  1997.  Remote sensing and GIS for asite-specific farm management system. In: JV Stafford(ed). Precision Agriculture ‘97.  Vol. II BiossScientific  Publ. Ltd., Oxford, United Kingdom, pp.678-696.Havlin JL, JD Beaton, SL Tisdale and WL Nelson.  1999.Soil Fertility and Fertilizers: An Introduction toNutrient Management.  Sixth edition.  Prentice Hall,Upper Saddle River, New Jersey.  499 p.Jalali M.  2007.  Site-specific potassium application basedon the fertilizer potassium availability index of soil.Precision Agric J 8:199-211.Juang KW,  DC Liou and DY Lee.  2002.  Site-specificphosphorous application based on the Krigingfertilizer-phosphorous availability index of soils.  JEnviron Qual 31: 1248-1255.McBratney AB and MJ Pringle.  1997.  Spatial variabilityin soil-implication for precision agriculture. In: JVStafford (ed) Precision Agriculture ‘97.  Vol. I BiossScientific  Publ. Ltd., Oxford, United Kingdom, pp.3-31.Reyniers M, K Maertens, E Vrindts and J DeBaerdemaeker.  2006.  Yield variability related tolandscape properties of a loamy soil in CentralBelgium. Soil Till Res  88: 262-273.Schuller JK.  2001.  Variable rate technologies.  PaperSmart Farming II Workshop on Automation forAgriculture.  March 2001, Putra Jaya, Malaysia.Syam T, K Jusoff, AR Anuar, MH Tajudin dan ZZ Zakaria.2004.  Spatial analysis of soil nutrient content of N,P and  K on the oil palm plantation in semenanjungMalaysia.  J Trop Soil 8 (2): 137-143.Syam T.  2005.  Precision farming on paddy fields:Correlation between soil nutrients content and riceyields.  Proc. of seminar and annual meeting of DeanFaculty of Agriculture Association of West PartGovernment University.  The topic of nationalseminar is “Applied Sustainable Agriculture and theFuture Threat”.  September 14-16, 2005. AndalasUniversity, Padang.Tinker PB.  1976.  Soil requirements of the oil palm.  In:RHV Corley, JJ Hardon and BJ Wood (eds). Oil PalmResearch. Elsevier Scientific Publishing Co.Amsterdam, pp 165-181.Voltz M. 1997. Spatial variability of soil moisture regimesat different scales: Implication in the context ofprecision agriculture. Chapter included in “Precisionagriculture: Spatial and temporal variability ofenvironmental quality”, John Wiley & Sons Ltd,pp.18-37. Yanai J, CK Lee, M Umeda and T Kosaki.  2000.  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Spatial Variability of Soil Nutrients Content Related to Rice Yield

Journal of Tropical Soils

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Spatial Variability of Soil Nutrients Content Related to Rice Yield

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