Targeted yield concept and a framework of fertilizer recommendation in irrigated rice domains of subtropical India

Targeted yield concept and a framework of fertilizer recommendation in irrigated rice domains of subtropical India 1 first-author 1 2 3 corresp ‡Corresponding Author ‡Corresponding Author †E-mail:b_pradip@rediffmail.com †E-mail:b_pradip@rediffmail.com b_pradip@rediffmail.com 1 1 3 National Bureau of Soil Survey & Land Use Planning, Indian Council of Agricultural Research, Salt Lake, Kolkata-700091, West Bengal, India National Bureau of Soil Survey & Land Use Planning, Indian Council of Agricultural Research, Salt Lake, Kolkata-700091, West Bengal, India West Bengal State Council of Science & Technology, Bikash Bhawan, Salt Lake, Kolkata-700091, West Bengal, India West Bengal State Council of Science & Technology, Bikash Bhawan, Salt Lake, Kolkata-700091, West Bengal, India Brain Korea 21 Century Advanced Geo-Environmental Research Team, School of Environmental Engineering, Kunsan National University, Kunsan, Jeonbuk 573-701, South Korea Brain Korea 21 Century Advanced Geo-Environmental Research Team, School of Environmental Engineering, Kunsan National University, Kunsan, Jeonbuk 573-701, South Korea Soil test crop response (STCR) correlation studies were carried out in Vindhyan alluvial plain during 2001 to 2004 taking IR-36 as test crop to quantify rice production in the context of the variability of soil properties and use of balanced fertilizers based on targeted yield concept. The soils were developed on gently sloping alluvial plain with different physiographic settings and notable variation in drainage condition. Soil properties show moderate variation in texture (loamy to clay), organic carbon content (4.4 to 9.8 g/kg), cation exchange capacity (10.2 to 22.4 cmol (p+)/kg) and pH (5.3 to 6.4). Soil fertility status for N is low to medium (224 to 348 kg/ha), P is medium to high (87 to 320 kg/ha) and K ranges from medium to high (158 to 678 kg/ha). Database regarding nutrient requirement in kg/t of grain produce (NR), the percent contribution from the soil available nutrients [CS (%)] and the percent contribution from the applied fertilizer nutrients [CF (%)] were computed for calibrating and formulating fertilizer recommendations. Validity of the yield target for 7 and 8 t/ha was tested in farmers’ fields and yields targets varied at less than 10%. The percent achievement of targets aimed at different level was more than 90%, indicating soil test based fertilizer recommendation approach was economically viable within the agro-ecological zone with relatively uniform cropping practices and socio-economic conditions. Alluvial soil Nutrient requirements Yield target Paddy INTRODUCTION 1 Damodar catchment is one of the most potential zones for paddy cultivation in India. Paddy is being cultivated about 80% area during monsoon season and about 60% area during winter season. To get more and more yield farmers inclined to the excess use of chemical fertilizers, but the decision on fertilizer use requires knowledge of the expected crop yield response to nutrient application, which is a function of crop nutrient needs, supply of nutrients from indigenous sources, and the short- and long-term fate of the fertilizer applied (Dobermann et al., 2003a 2003a ). Dumping of fertilizers by the farmers in the fields without information on soil fertility status and nutrient requirement by crop causes adverse effects on soil an crop regarding both nutrient toxicity and deficiency either by overuse or inadequate use (Ray et al., 2000 2000 ). Managing the location specific variability in nutrient supply is a key strategy to overcome the current mismatch of fertilizer rates and crop nutrient demand in irrigated rice environments (Dobermann and Cassman, 2002 2002 ). Soil test based application of plant nutrient helps to realize higher response ratio and benefit:cost ratio as the nutrients are applied in proportion to the magnitude of the deficiency of a particular nutrient and the correction of the nutrients imbalance in soil helps to harness the synergistic effects of balanced fertilization (Rao and Srivastava, 2000 2000 ). Location specific fertilizer recommendations are possible for soils of varying fertility, resource conditions of farmers and levels of targeted yield for similar soil classes and environment (Ahmed et al., 2002 2002 ). Field specific balanced amounts of N, P, K were prescribed based on crop based estimates of the indigenous supply of N, P and K and by modelling the expected yield response as a function of nutrient interaction was done by many workers (Dobermann and White 1998 1998 ; Witt et al., 1999 1999 ). The present investigation aimed to study the relationship between the nutrient supplied by the soil and added fertilizers, their uptake and yield of paddy and to develop a guideline for judicious application of fertilizer for maximum production of paddy. MATERIALS AND METHODS 1 The study was conducted in three villages viz. Naopara, Kantia and Syamsundarpur in Barddhaman district, West Bengal, India for the year 2001 to 2004. Crop trials were conducted in four soil series viz. Syamsundarpur I, Syamsundarpur II, Naopara and Kantia, in the farmer’s field. Irrigated rice (IR-36) was also used as the winter crop in the third week of February and harvested in the third week of May. The crop was transplanted at a spacing of 14 cm×12 cm with 5 seedlings/hill. The crop received one fourth N and full dose of P 2 O 5 and K 2 O as basal application and remaining half and one fourth N were applied at 22 d after transplanting (DAT) and 45 DAT respectively. Nitrogen was applied through urea, phosphorus through diammonium phosphate (DAP) and potassium through muriate of potash. Five to seven centimeters deep good quality water was maintained in the field. All the plots were weeded thrice, once before first top dressing and again before second top dressing and last weeding 11 d after second weeding. Panicles were counted from 4 random locations in each plot and for filled grains/panicle, 20 panicles of each plot were separated and then average filled grains/panicle were calculated, whereas weight of 1000 filled grains was taken as test weight. Fifty-six soil samples (0~0.15 m depth) were collected, dried and passed through 2 mm sieve and analyzed for physicochemical characteristics as described by Jackson ( 1973 1973 ). Available nitrogen was analyzed by alkaline permanganate method (Subbaiah and Asija, 1956 1956 ), available phosphorus by Olsen et al.( 1954 1954 )’s method and available potassium by ammonium acetate method (Hanway and Heidal, 1952 1952 ). The layout was based on the approach developed by Ramamoorthy et al.( 1967 1967 ). Four levels of fertilizer treatment viz. N 1 P 1 K 1 (farmers practice), N 2 P 2 K 2 (soil test based i.e. recommended by the agricultural department of the district on the basis of soil test values), N 3 P 3 K 3 [soil test crop response (STCR) for 7 t/ha] and N 4 P 4 K 4 (STCR for 8 t/ha) with three replications each was done. Pre-sowing and post-harvest soil samples were analyzed according to the standard procedures. Plant sampling was done according to the procedure followed by Witt et al.( 1999 1999 ). In targeted yield approach for formulating fertilizer recommendations, the basic data viz. nutrient requirement (NR) (kg/t), percent contribution from the soil available nutrients [CS (%)] and the percent contribution from the applied fertilizer nutrients [CF (%)] were transfer into workable adjustment equation (Rao and Srivastava, 2000 2000 ). Fertilizer dose=[Nutrient requirement (kg/t) of grain]/[CF (%)] ×100× T (t/ha)−[CS (%)]/[CF (%)] ×[Soil test value (kg/ha)], where T is targeted yield (t/ha). RESULTS AND DISCUSSION 1 Crop trials were done with the basic assumption that fertilizer recommendations typically depend on crop response experiments in which spatial variability has been minimized for every independent variable affecting crop yield except for the nutrient in question, although many non-fertility variables viz. soil texture, soil bulk density, available water content and other fertility variables significantly impact crop yield (Kastens et al., 2003 2003 ). Soil characteristics 2 The soils were acidic to neutral in reaction with pH varying from 5.3 to 6.4 (Table 1 1 ). The organic carbon content varied from 0.44% to 0.98%. Texture of the surface soil varied from loam to clay with clay percent varying from 18.5% to 57.4%. CEC (cation exchange capacity) of the soils were medium with high base saturation. Field capacity and plant available water holding capacity values showed that the soils were highly capable of containing soil moisture. The soils were low to medium in N (ranging from 224 to 348 kg/ha), medium to high in P (ranging from 87 to 320 kg/ha) and medium to high in K (from 158 to 678 kg/ha). Available micronutrient status showed that the experimental soils were well supplemented with micronutrients. Though these soils are considered to be most fertile, they are deficient in nitrogen and humus but moderately supplied with phosphorus and potassium. DS1: Deep, moderately well drained, fine loamy soils developed on upland with loam surface texture and moderate erosion; DS2: Deep, imperfectly drained, fine soils developed on midland with silty clay loam surface texture and slight erosion; DS3: Deep, moderately well drained, fine soils developed on midland with silty clay surface texture and slight erosion; DS4: Deep, poorly drained, fine soils developed on lowland with clay surface texture and slight erosion. Org. C: Organic carbon; CEC: Cation exchange capacity; BS: Base saturation; AWC: Available water capacity 2 Soils 2 Description of soils (DS) * * 6 Physicochemical properties 3 Fertility status (kg/ha) pH (H 2 O) Org. C (%) Clay (%) CEC [cmol (p + )/kg] BS (%) AWC (kg/kg) N P 2 O 5 K 2 O Syamsundarpur I series 2 DS1 2 6.4 2 0.44 2 18.5 2 10.2 2 79 2 0.144 2 241~269 2 256~276 2 158~169 (Typic Haplustepts) Syamsundarpur II series 2 DS2 2 6.0 2 0.98 2 36.9 2 18.5 2 79 2 0.166 2 265~327 2 87~113 2 517~565 (Aeric Endoaquepts) Naopara series 2 DS3 2 5.3 2 0.98 2 34.9 2 14.6 2 72 2 0.160 2 245~348 2 248~320 2 365~678 (Aeric Endoaquepts) Kantia series 2 DS4 2 6.0 2 0.73 2 57.4 2 22.4 2 79 2 0.189 2 224~285 2 115~185 2 205~272 (Typic Endoaquepts) Yield targeting of paddy based on soil test 2 Experimental data on follow up tail as frontline demonstration, 13 for each soil series during the period 2001~2003 were conducted in farmers field and are given in Tables 2 2 and 3 3 . From the field experiment the basic data on nutrient requirements (NR) to produce one quintal of rice, percent contribution of nutrients from soil [CS (%)] and fertilizer [CF (%)] were evaluated. Indigenous sources in an irrigated system include plant available nutrients derived from chemical and biological transformations of soil solids, biological N 2 fixation in the floodwater-soil system, atmospheric deposition and solutes and sediments deposited by irrigation (Cassman et al., 1998 1998 ). Nutrient requirement per ton of rice production were observed to be 14.8, 10.5 and 18.6 kg N, P 2 O 5 and K 2 O respectively. Contribution of N, P 2 O 5 and K 2 O as estimated from soil and fertilizer sources was 13.56%, 31.59%, 19.33% and 67.64%, 84.67%, 139.89% respectively. These results indicate that nutrient contribution from fertilizer sources was greater than that from the soil source. The findings are in closely accorded with those reported by Ray et al.( 2000 2000 ) and Meena et al.( 2001 2001 ). It is interestingly noted that contribution of K 2 O for rice (Table 2 2 ) was observed to be more than 100% (139.89%). This high value of K could be due to the interaction effect of higher doses of N, P and the primary effect of starter K doses in the treated plots, which might have caused the release of soil potassium form, resulting in the higher uptake from the native soil sources by the crop (Ray et al., 2000 2000 ). Similar type of higher efficiency potassic fertilizer was also reported for rice by Ahmed et al.( 2002 2002 ) in alluvial soil, for maize by Reddy et al.( 2000 2000 ) in inceptisols and for jute by Ray et al.( 2000 2000 ) in inceptisols. NR: Nutrient requirement (kg/t) of grain production; CS (%): Percent nutrient contributed from soil (soil efficiency); CF (%): Percent nutrient contributed from fertilizer (fertilizer efficiency); T : Yield target (t/ha); S N , S P and S K : Soil available nitrogen, phosphorus and potassium (kg/ha); F N , F P and F K : Fertilizer nitrogen, phosphorus (P 2 O 5 ) and potassium (K 2 O) required (kg/ha) 2 Nutrient 3 Basic data 2 Targeted yield equations NR (kg/t) CS (%) CF (%) N 14.8 13.56 67.64 F N =2.19 T −0.2 S N P 2 O 5 10.5 31.59 84.67 F P =1.24 T −0.37 S P K 2 O 18.6 19.33 139.89 F K =1.33 T −0.14 S K Yield target of 7.0 t/ha has been achieved with comparatively lower application of N and P 2 O 5 fertilizers but higher application of K 2 O, in comparison to doses applied in farmers practice (FP) and soil based recommendations. As for example in the alluvial soils of West Bengal, in the winter season highest paddy yield was 6.0 t/ha regardless of the N level used but could be raised to 7.4 t/ha with increased application of K-fertilizers (Tiwari, 2002 2002 ). This is probably due to the higher N-use efficiency as well as increased N-recovery by crops under increased K-application (Marschner, 1995 1995 ). Yield targets of 7 and 8 t/ha for rice (cv. IR-36) were achieved within −10% yield deviation (Table 3 3 ) from the expected yield targets in all the cases. In all sites, grain yields of rice through general recommendation (GRD) of fertilizers lagged behind the yield obtained at 7 and 8 t/ha fixed target. These results accorded with the findings of Ray et al.( 2000 2000 ). Between the two targets tried, targeting for 7 t/ha recorded relatively higher response ratio than with 8 t/ha though it has also recorded higher yields. This might be due to the better use efficiency of applied NPK fertilizers at low yield target levels (Santhi et al., 2002 2002 ). A minor modification was made in the ready reckoner; FP : Farmers practice i.e. the fertilizer doses the farmers generally applied in the area; GRD: General recommendation by the agricultural department of the district on the basis of soil test values; B : C ratio: Benefit:cost ratios 2 Soil series (farmer) 3 Soil test values (kg/ha) 2 Treatments 3 Fertilizer doses (kg/ha) 2 Yield (t/ha) 2 Increased over control (t/ha) 2 Yield deviation (%) 2 B : C ratio N P 2 O 5 K 2 O N P 2 O 5 K 2 O 5 Syamsundarpur I (T. Dutta) 5 245 5 70 5 162 FP 100 80 40 6.002 3.512 – 1.54 GRD 120 50 50 6.150 3.660 – 1.61 7 t/ha target 104 61 70 6.669 4.179 −4.73 1.72 8 t/ha target 126 73 84 7.225 4.735 −9.69 1.81 Control 0 0 0 2.490 – – – 5 Syamsundarpur II (N. Bhattacharjee) 5 272 5 80 5 340 FP 100 80 40 6.113 3.573 – 1.56 GRD 120 50 40 6.224 3.684 – 1.62 7 t/ha target 100 57 46 6.817 4.277 −2.61 1.75 8 t/ha target 121 70 59 7.558 5.018 −5.53 1.89 Control 0 0 0 2.460 – – – 5 Naopara (S. Ghosh) 5 345 5 110 5 385 FP 100 80 40 6.224 3.584 – 1.59 GRD 100 40 40 6.373 3.733 – 1.66 7 t/ha target 84 46 40 6.817 4.177 −2.61 1.75 8 t/ha target 106 59 53 7.632 4.992 −4.60 1.89 Control 0 0 0 2.640 – – – 5 Kantia (N. Mondal) 5 275 5 90 5 220 FP 100 80 40 6.113 3.503 – 1.56 GRD 120 40 50 6.298 3.688 – 1.64 7 t/ha target 100 54 62 6.854 4.244 −2.10 1.76 8 t/ha target 120 66 76 7.595 4.985 −5.10 1.89 Control 0 0 0 2.610 – – – However for efficient utilization of applied fertilizer some other parameters like soil pH, organic carbon status, soil texture, bulk density, water holding capacity, soil drainage, etc. should also be considered, since these are the major determining factors of soil nutrient retention. This is for the development of an effective fertilizer schedule as well as nutrient supply source in view of the better nutrient absorption and assimilation by the plants. Predicting equation for post-harvest soil test values 2 Using a soil test based approach to nutrient management requires index measurement related to crop yield or the effective nutrient supply during the growth period, regular monitoring of soil test values and well developed service infrastructure with excellent quality control (Dobermann et al., 2003b 2003b ) which is not feasible in farmers point of view. So it has become necessary to predict the soil test values after the harvest of a crop. It is done by post-harvest soil test value predicting equations making use of the vital soil test values, applied fertilizer doses and the obtained nutrients uptake. The functional relationship is as follows Y ph = a + b 1 × F + b 2 × IS + b 3 ×Yield/(Uptake of nutrient), where Y ph is the post-harvest soil test value, F is the applied fertilizer nutrient and IS is the initial soil test value, a is an absolute constant and b 1 , b 2 and b 3 are the respective regression coefficients. The predicting equations are highly significant for the major nutrient viz. N, P 2 O 5 and K 2 O in the study area (Table 4 4 ). The soil test values generated through this predicting equation may be utilized for soil test based fertilizer recommendation for the next crop in the crop rotation. S N , S P and S K : Soil available nitrogen, phosphorus (P 2 O 5 ) and potassium (K 2 O) (kg/ha); F N , F P and F K : Fertilizer nitrogen, phosphorus (P 2 O 5 ) and potassium (K 2 O) required (kg/ha); RY is rice yield (kg/ha) Significant at 1% level Nutrient R 2 Multiple regression equation N 0.93 ** ** Y N =−22.70+1.0 S N +0.15 F N −0.56 RY P 2 O 5 0.94 ** ** Y P =−1.70+0.64 S P +0.41 F P −0.29 RY K 2 O 0.99 ** ** Y K =24.80+0.93 S K +087 F K −2.29 RY CONCLUSION 1 Nutrient management for rice should focus on developing fertilizer recommendations for spatial domains with relatively uniform agro-ecological characteristics, cropping practices and socio-economic conditions. The study will help to make guidelines for the amount of fertilizer used in rice cultivation. With the variation in conditions like different cultivars, soil conditions, etc. fertilizer requirement will change. However the change will not be significant for cultivars of similar producing capacity. 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Internal nutrient efficiencies of irrigated lowland rice in tropical and subtropical Asia 10.1631/jzus.2006.B0963 Project supported by the Indian Council of Agricultural Research, and the National Agricultural Technology Program, India 2006-04-03 2006-09-26 2006-11-17 2022-01-05 Copyright © 2006, Journal of Zhejiang University Science 2006 Journal of Zhejiang University-SCIENCE B (Biomedicine and Biotechnology) 12 07