SPATIAL VARIABILITY OF MICRONUTRIENTS IN CITRUS ORCHARD OF NORTH WESTERN PAKISTAN

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1 Sarhad J. Agric. Vol.29, No.3, 13 SPATIAL VARIABILITY OF MICRONUTRIENTS IN CITRUS ORCHARD OF NORTH WESTERN PAKISTAN YOUSAF NOOR *, SUBHANULLAH and ZAHIR SHAH Department of Soil and Environmental Sciences, The University of Agriculture, Peshawar, Pakistan *Correspondence author: ABSTRACT The spatial variability of micronutrients (Zn, Cu, Fe, Mn and B) in citrus orchards in Malakand Agency of Khyber Pakhtunkhwa Province during 8 was assessed and mapped. Soil samples at -3 cm depth from 24 different spots at 6 m distance from one another were collected from a citrus orchard located in Warther area of Dargai Malakand Agency and were analysed for micronutrients. Geostatistical technique of semivariogram analysis was applied on data to determine spatial structure of micronutrients in soils. Soil test values at other locations were interpolated using geostatistical technique of kriging and detailed isarithmic maps. The results showed that Zn was low in none, marginal in 4.17 % and adequate in 4.83 % samples. Similarly, B was low in none, marginal in % and adequate in % samples. However, Cu, Fe and Mn were adequate in % samples. Semivariogram analysis showed that Cu, Fe and B had strong, Zn had a moderate and Mn had a poor spatial structure described by linear model. Computer generated maps using kriging technique showed that almost all the maps had some spatial variation in different micronutrient contents in the field. These results suggested that the citrus orchard was not uniform in micronutrient contents and can be delineated into different categories for variable rate fertilizer management. Keywords: spatial variability, micronutrients, citrus orchard, soil fertility Citation: Noor, Y., Subhanullah and Z. Shah. 13. Spatial variability of micronutrients in citrus orchard of north western Pakistan. Sarhad J. Agric 29(3): INTRODUCTION Citrus (Citrus sinensis L.) is one of the leading fruit crops of the world with global availaibality and popularity contributing to human diets (Liu et al., 12). In Pakistan, the Khyber Pakhtunkhwa province is bestowed with a subtropical climate, diversity of soils with different elevations and is this suitable for a variety of fruit crops (Shah et al., 12). Among fruits, citrus is second to apple in the province of Khyber Pakhtunkhwa both areawise and in production. The soils and climatic conditions of Khyber Pakhtunkhwa are conducive for the production of sweet oranges. However, the citrus production in general is almost static, or even declining (Ahmed and Saleem, 6). The reasons for poor production may be numerous but improper and inadequate fertilization may be the major factors responsible for poor production. Several reports highlighted the deficiency of both major (N, P, K) and minor (Zn, Cu, Fe, Mn, B) nutrients in the citrus orchards of this part of the world (Khattak, 1991; Khattak et al., 1994; Haq et al., 199; Sharif et al., 1998; Zia et al., 6). A recent survey of micronutrients of citrus orchards in Malakand Division revealed that Zn was deficient in %, Mn in 96 %, B in 24 % and Cu in 16 % orchards using leaf analysis as indicator (Shah et al., 12). Adequate supplies of nutrients are essential for optimum growth and better production of citrus. Unfortunately, little attention is paid to the nutritional requirements of citrus orchards in Malakand Division. Although required in minute quantities, micronutrients are as essential as macronutrients, and play vital roles in plant growth and productions. Micronutrients assist plant growth mainly through their influence on many enzymatic reactions and metabolic activities. It has been reported that micronutrients application improved both yield and quality of citrus (Tariq et al., 7). Crop production is also affected by the presence of spatial variations in the field. Spatial variation of soil chemical and physical properties influences soil and crop management efficiency as well as the effectiveness of field research trials. Variability in soil properties causes uneven crop growth, confounds treatment effects in field experiments and decreases the effectiveness of uniformly applied fertilizer on a field scale (Mulla et al., 199; Mulla et al., 1992). On the other hand, spatial variability of soil properties can be used for interpolation of soil test values at un-sampled locations using limited data on sampling locations. Spatial variability of soil properties has been used for development of fertility management strategies and mapping of fields on small scale and districts on large scale (Bhatti and Mulla, 199). Citrus orchards are generally not uniform in soil fertility (Shah et al., 12). So uniform fertilizer application may not be economical in circumstances where fertility gradient across the site is not uniform. Spatial variation in soil fertility has been reported for cereal and vegetable fields (Bhatti and Mulla, 199; Shah et al., 13) but such information for fruit orchards is limited. If spatial variation in soil fertility of an orchard is known, fertilizer recommendations could be made for specific sites in a given orchard. This will reduce the unnecessary use of fertilizers and will enhance farm income.

2 Yousaf Noor, et al. Spatial variability of micronutrients in citrus orchard 388 This research aims to assess the spatial variation and status of soil micronutrients (Zn, Cu, Fe, Mn, B) in a citrus orchard in Malakand Agency of Khyber Pakhtunkhwa province and to develop a map of spatial variability of micronutrients. MATERIALS AND METHODS A farmer s citrus orchard was selected in Warther area of Dargai Malakand Agency which is a mountainous tract located between and north latitude and and east longitude. Soil Sampling and Processing Soil samples at -3 cm depth were collected from 24 spots at 6 m distance from each other in the orchard were air dried, and stones and plant twigs were removed. The soil samples were grinded and sieved through <2. mm sieve, labelled and stored in plastic containers until ready for analysis. Determination of Micronutrients in Soil The concentrations of micronutrients (Zn, Cu, Fe and Mn) in soil were determined by the AB-DTPA extraction procedure (Soltanpour and Schwab, 1977). Soil sample ( g) was shaken with ml AB-DTPA in an open Erlenmeyer flask for min, the extract filtered and was read for Zn, Cu, Fe and Mn on an Atomic Absorption Spectrophotometer (Shimadzu, AA-63). The concentration of extractable B in soil was determined by the dilute hydrochloric acid method (Ryan et al., 1). For this,. g air-dry soil was shaken with ml of. N HCl for min. After filtering, B concentration in the extract was measured by the Azomethine-H method at 4 nm on Spectrophotometer (Shimadzu, UV-17). Statistical Procedures The data were subjected to standard statistical procedures given in Steel et al (1997) and Bhatti (6). Geostatistical technique of semivariogram analysis was used to determine spatial structure of various micronutrients. Soil test values at other locations were interpolated using geostatistical technique of kriging and detailed isarithmic maps were prepared at smaller gird spacing (Bhatti et al., 1991). RESULTS AND DISCUSSION Micronutrients Concentration in Soil of Citrus Orchard The data obtained on the concentration of extractable micronutrients in the soil of a citrus orchard are presented in Tables 1-2. The results showed that the concentration of Zn in soil ranged from 1.3 ug to 2.88 ug g -1 soil with a mean of 1.±.43 (Table 1). Similarly, the concentration of Cu ranged from 2. to 3.71 ug (mean of 2.84±.43), Fe ranged from 7.9 to 14.8 ug (mean 11.27±1.97), Mn ranged from 6. to 16.6 ug (mean.3±2.91) and B ranged from.49 ug to 1.11 ug g -1 soil (mean.78±.21). These results suggested that fertility gradient across the orchard was not uniform as micronutrient contents varied from spot to spot in the same orchard. Table 1. Micronutrients concentration (ug g -1 soil) in soil of a citrus orchard in Malakand Agency Micronutrient Mean SD Minimum Maximum Zn Cu Fe Mn B Comparing with the critical values of micronutrients concentration in soil established by Soltanpour (198), the results showed that Zn in soil was low (<.9 ug g -1 soil) in none, marginal (.9-1. ug g -1 soil) in 4.17 % and adequate (> 1. ug g -1 soil) in 4.83 % samples (Table 2). Similarly, B was low (<.4 ug g -1 soil) in none, marginal (.4-1. ug g -1 soil) in % and adequate (>1. ug g -1 soil) in % samples. The results further showed that the orchard had adequate concentration of Cu (>. ug g -1 soil), Fe (>. ug g -1 soil) and Mn (>1. ug g -1 soil) in soil. These results thus suggested that on average the soil of the citrus orchard was adequate in Cu, Fe and Mn but marginal in Zn and B. A recent survey of citrus orchards in Malakand Division revealed that these orchards were deficient in micronutrients to different extent as Zn was deficient in %, Mn in 96%, B in 24% and Cu in 16% orchards based on leaf analysis (Shah et al., 12). However, in same survey the results of soil and leaf analysis did not agree well as the soil analysis generally showed sufficiency while leaf analysis deficiency of micronutrients. Our results are generally similar to the findings of earlier researchers who also observed deficiency of both macro- and micro-nutrients in the soils of Khyber Pukhtunkhwa province (Rehman et al., 1993; Shah et al., 3; Wasiullah & Bhatti, 6; Shafi et al., 7; Shah et al., 12; Shah et al., 13). Low availability of micronutrients in soils of Khyber Pakhtunkhwa could be attributed to alkaline ph and calcareous nature of soils and negligible application of micronutrient fertilizers (Wasiullah and Bhatti, 6; Shah et al., 12).

3 Sarhad J. Agric. Vol.29, No.3, Table 2. Soil samples from a citrus orchard classified as low, marginal or adequate in micronutrients based on soil concentration (ug g -1 soil) Micronutrient Low (%)* Marginal (%) Adequate (%) Zn Cu Fe Mn B * Out of 24 samples Spatial Variability of Micronutrients in Citrus Orchard Semivariogram analysis of micronutrients status of the citrus orchard showed that all micronutrients had spatial patterns of distribution (Table 3). However, the spatial structures of Cu (R 2.4, Fig 2), Fe (R 2.84, Fig 3) and B (R 2.82, Fig ) were strong while that of Zn (R 2.2, Fig 1) was moderate and Mn (R 2.12, Fig 4) was poor. All these patterns were described by linear model. In other soils of Khyber Pakhtunkhwa, Zn and Mn showed moderate spatial structure in Kohat district while Zn and Fe as moderate spatial dependence in Bannu district (Shah et al., 13). These differences could be due to variation in soil texture, fertilizer management practices i.e. extrinsic as well as inherent factors (Vieira et al., 1983; Breseler et al., 1993; Tabor et al., 1984; Spiker et al., ; Rafique et al., 6). Fig. 1. Semivariance and best fitting model for AB-DTPA extractable Zn in soil of a citrus orchard Fig. 2. Semivariance and best fitting model for AB-DTPA extractable Cu in soil of a citrus orchard Interpolation and Mapping of Soil Micronutrients The measured data and the semivariogram models developed were used to estimate the soil test values at unsampled locations using geostatistical technique of kriging. These values were then used for mapping purposes using surfer. The map for AB-DTPA extractable Zn (Fig. 6) showed that the eastern part of the orchard had relatively high Zn content which decreased towards the western part. Overall, Zn was marginal (.9-1. ug g -1 ) in the soil. The map for AB-DTPA extractable Cu (Fig. 7) showed that the western middle part had relatively high Cu content which decreased towards the west-southern corner as well as towards the eastern

4 Yousaf Noor, et al. Spatial variability of micronutrients in citrus orchard 39 middle part. However, overall Cu was adequate (>. ug g -1 ) in the soil. Map for AB-DTPA extractable Fe (Fig. 8) showed that the middle part had relatively high Fe content which decreased towards the northern and southern parts. Overall, Fe was adequate (>. ug g -1 ) in the soil. Map for AB-DTPA extractable Mn (Fig. 9) showed that the northern part had relatively low Mn content than the other parts which increased towards the southern part. However, Mn was adequate (>1. ug g -1 ) in the soil. The map for B content (Fig. ) showed that the northern part had relatively low B content than the other parts which increased towards the southern part. Overall, B was marginal (.4-1. ug g -1 ) in the soil. Table 3. Parameters of semivariogram models for AB-DTPA extractable micronutrients in soil of a citrus orchard in Malakand Agency Micronutrient Nugget Slope Sill Range (m) R 2 Model (ug g -1 ) Zn Linear Cu Linear Fe Linear Mn Linear B (dilute HCl) Linear Maps of various micronutrients also showed spatial structure in their distribution and hence may be useful for delineating soils into low, medium and high nutrient contents for formulating fertilizer recommendations on site-specific basis. Rafique et al. (6) also observed spatial variability of plant nutrients content in cotton leaves and wheat plants and used it as a tool for delineating soils into low, medium and high nutrient contents and for formulating fertilizer recommendations for site-specific management. Kriging was used for interpolation and mapping in this study. Kriging has been used successfully to develop variable rate fertilizer management strategy by many scientists in the past (Wallenhaupt et al., 1994; Bhatti et al., 1999; Rafique et al., 6). The importance of determining spatial variability using geostatistics and preparing isarithmic maps has been proved useful for site-specific fertilizer management as a suitable tool for increased agricultural production with minimum environmental degradation (Mulla et al., 1992; Bhatti et al., 1998a; Takata et al., 7; Takata et al., 8; Mastui et al., 8). These techniques have been used to prepare contour maps of other important soil properties (Burgos et al., 6). The use of geo-statistical techniques and preparation of contour maps of heavy metals proved better for identification of contaminated hotspots more concisely and accurately (Burgos et al., 6). In the light of above discussion, The contour maps of nutrient contents in soil or plants would help the researchers for identification of deficient areas in the field. This would and help developing strategies for applying fertilizers on site specific need. base using variable fertilizers rate technology to correct deficiencies of plant nutrients. This variable fertilizer rate strategy would avoid over or under-application of fertilizers which will be both economical and environmentally friendly. Fig. 3. Semivariance and best fitting model for AB-DTPA extractable Fe in soil of a citrus orchard

5 Sarhad J. Agric. Vol.29, No.3, Fig. 4. Semivariance and best fitting model for AB-DTPA extractable Mn in soil of a citrus orchard Fig.. Semivariance and best fitting model for dilute HCl extractable B in soil of a citrus orchard N W E S Fig. 6 Map of Zn content of the soil of a citrus orchard by kriging

6 Yousaf Noor, et al. Spatial variability of micronutrients in citrus orchard 392 Fig. 7. Map of Cu content of the soil of a citrus orchard by kriging Fig Map of Fe content of the soil of a citrus orchard by kriging Fig Map of Mn content of the soil of a citrus orchard by kriging CONCLUSIONS AND RECOMMENDATIONS Fig.. Map of B content of the soil of a citrus orchard by kriging The experiment has shown that Cu, Fe and Mn were adequate in % soil samples but Zn and B were marginal in 4.17 % and % samples respectively. Semivariogram analysis of micronutrients status showed that the spatial structures of Cu, Fe and B were strong but that of Zn was moderate and Mn was poor indicating variation in same orchard. ACKNOWLEDGEMENT This study was financially supported partially by the Higher Education Commission, Islamabad through Indigenous PhD Scholar program and partially by the ALP research program. REFERENCES Ahmed, A. and M.T. Saleem. 6. Citrus and its nutrition. Farming Outlook. (1):

7 Sarhad J. Agric. Vol.29, No.3, Bhatti, A.U., A. Bakhsh, M. Afzal and A.H. Gurmani Mapping of major plant nutrients and crop productivity using geostatistical techniques for fertilizer management. Pak. J. Soil Sci. 16: Bhatti, A.U., F. Hussain, Farmanullah and M.J. Khan Use of spatial patterns of soil properties and wheat yields in geostatistics for determination of fertilizer rates. Commun. Soil. Sci. Plant. Anal. 29: Bhatti, A.U., D.J. Mulla and B.E. Frazier. 1991: Estimation of soil properties and wheat yields on complex eroded hills using geostatistics and thematic mapper images. Remote. Sens. Environt. 37: Bhatti, A.U. and D.J. Mulla Spatial variability of soil properties and wheat yields on complex hills and their fertility management. J. Indian Soc. Soil Sci. 43(1): 3-8. Bresseler, E., G. Dagan and R.A. Hanks. 1993: Statistical analysis of crop yield under controlled line source irrigation. Soil Sci Soc Am J. 46: Burgos, P.E., E. Madejin, A.P. Mora and F. Calbera. 6. Spatial variability of the chemical characteristics of a trace element contaminated soil before and other remediation. Geoderma. 13: Haq, I. U., A. Ghani and H. U. Rehman Nutritional status of citrus orchards in NWFP and the effect of fertilizer application on fruit production. Directorate of Soils and Plant Nutrition, A.R.I, Tarnab, Peshawar, NWFP Pakistan. Technical Bulletin 1/9. Khan, H., S. Ali and S.A. Hussain Fertilization of stone fruit orchards, Deptt. of Agric. ARI, Tarnab, (Peshawar) NWFP, Pakistan. Farmer Bulletin No. 7. Khattak, J. K., M. Sharif and S. Naz Nutrient status of citrus orchard soils in Peshawar valley. Sarhad J. Agric. (4): Khattak, J.K Micronturients in Agriculture. BARD, PARC, Islamabad. Liu, Y.Q., E. Heying and S.A. Tanumihardjo. 12. History, global distribution, and nutritional importance of citrus fruits. Comprehensive Rev. Food Sci.Food Saf. 11: 3-4. Mulla, D.J., A.U. Bhatti and R. Kunkel Methods for removing spatial variability from field research trails. Adv. Soil Sci.13: Mulla, D.J., A.U. Bhatti, M.W. Hammond and J.A. Benson A comparison of winter wheat yield and quality under uniform versus spatially variable fertilizer management. Agric. Ecosyst. Environ. 38: Matsui, N., J. Suekuni, S. Havanond, A. Nishimiya, J. Yanai, and T. Kosaki. 8. Determination of soil-related factors controlling initial mangrove (Rhizophora apiculata BL) grown in an abandoned shrimp pond. J. Plant Nutr. Soil Sci. 4: Page, A.L., R.H. Miller, and D.R. Keeney Methods of soil analysis Part-2 (2 nd Ed.). Chemical and Microbiological Properties. Agronomy. No. 9. American Society of Agronomy, SSSA. Madison, WI. Rafique, E., A. Rashid, J. Ryan, and A.U. Bhatti. 6. Zinc deficiency in rainfed wheat in Pakistan: Magnitude, spatial variability, management and plant analysis diagnostic norms. Commun. Soil. Sci. Plant. Anal. 37: Rehman, N., A. Rehman, and M.Z. Hussain On-farm test values of NWFP soils. Directorate of Soil and Plant Nutrition, ARI Tarnab, Peshawar, Pakistan. Ryan, J., G. Estefan, and A. Rashid. 1. Soils and Plant Analysis Laboratory Manual. Second Edition, Jointly published by the International Center for Agricultural Research in the Dry Areas (ICARDA) and the National Agricultural Research Center (NARC), available from ICRADA, Aleppo, Syria, x+172 pp. Shafi, M., J. Bakht, M.T. Jan, and Z. Shah. 7. Soil C and N dynamics and maize (Zea mays L.) yield as affected by cropping systems and residue management in North western Pakistan. Soil. Tillage. Res. 94: -29. Shah, Z., S.H. Shah, M.B. Peoples, G.D. Schwenke, and D.F. Herridge. 3. Crop residue and fertilizer N effects on nitrogen fixation and yields of legume-cereal rotations and soil organic fertility. Field Crops Res. 83: Shah, Z., M.Z. Shah, M. Tariq, J. Bakht and H. Rahman. 12. Survey of citrus orchards for micronutrients deficiency in Swat Valley of Khyber Pakhtunkhwa Pakistan. Pak. J. Bot. 44(2): 7-7. Shah, Z, Wasiullah, A.U. Bhatti and H. Rahman. 13. Spatial variability of nutrient contents in wheat plants in semi-arid region of north western Pakistan. Commun. Soil. Sci. Plant. Anal. 44(16): Sharif, M., A. Qayyum, and J.K. Khattak Nutrients status of citrus orchard soils in Swat valley. Sarhad J. Agric. 14(3):

8 Yousaf Noor, et al. Spatial variability of micronutrients in citrus orchard 394 Spiker, J., S.P. Vriend, and P.F.M. Vans-Ganns.. Natural and anthropogenic patterns of co-variance and spatial variability of minor and trace elements in agricultural top soil. Geoderma. 127: Soltanpour, P.N., and A.P. Schwab A new soil test for simultaneous extraction of macro- and micronutrients in alkaline soils. Commun. Soil Sci. Plant Anal. 8: Steel, R.G.D., J. H. Torrie, and D.A. Dicke Principles and Procedures of Statistics. A biomatrical approach 3 rd addition. The McGraw-Hill, Companies, Inc, NY. USA. Tabor, J.A., A.W. Warrick, D.A. Pennington, and D.E. Myers Spatial variability of nitrate in irrigation cotton. I. Petioles. J. Soil Sci. Soc. Am. 48: Takata, Y., S. Funakawa, K. Akshalov, N. Ishida, and T. Kosaki. 7. Spatial prediction of soil organic matter in northern Kazakhastan based on topographic and vegetation information. J. Plant Nutr. Soil Sci. 3: Takata, Y., S. Funakawa, J. Yanai, A. Mishima, K. Akshalov, N. Ishida, and T. Kosaki. 8: Influence of crop rotation system on the spatial and temporal variation of the soil organic carbon budget in northern Kazakhastan. J. Plant Nutr. Soil Sci. 4: Tariq, M., M. Sharif, Z. Shah and R. Khan. 7. Effect of foliar application of micronutrients on the yield and quality of sweet orange (Citrus sinensis L.). Pak. J. Biol.Sci. (11): Vieira, S.R., Hatfield, J.I., Nelson, D.R. and Biggar, J.W Geostatistical theory and application to variability of some agronomical properties. Hilgardia 1(3): 1-7. Wallenhaupt, N.C., R.P. Walkowski, and M.C. Klayton Mapping soil test values for phosphorus and potassium for variable rate fertilizer application. J. Prod. Agric. 7: Wasiullah, and A.U. Bhatti. 6. Fertility status evaluation of soils of Kohat and Bannu districts. Sarhad J. Agric. 22(3): Zia, M.J., R. Ahmad, I. Khaliq, A. Ahmad and M. Irshad. 6. Micronutrient status and management in orchard soil: applied aspects. Soil. Environ. 2(1): 6-16.