INTRODUCTION Maize (Zea mays L.) is one of the most widely grown cereal crop which stands first with respect to production in the world. It is grown in an area of 184.3 million ha in the world with a production of 1041.7 million tons and 5,742 kg ha-1 productivity annually. In India currently, it is grown in an area of 9.86 million ha with a production of 31.51 million tons and productivity of 3,195 kg ha-1. In Karnataka, maize is grown in an area of 1.68 million ha with a production of 5.18 million tons and productivity of 3,092 kg ha-1 (Anon., 2021). In Indian Agriculture, at present, nutrient depletion is one of the threats as there is a wider gap between the removal and addition of nutrients. Agriculture is operating on a net negative balance (@ 10 million tons per annum) of plant nutrients in India (Ramakrishna et al., 2012). Use of fertilizers in an imbalanced manner by the farmer is one of the reason for lower production. Application of fertilizers without knowing the fertility status of the soil and crop nutrient requirement causes negative effects on soil and plant in terms of toxicity and deficiency of nutrients (Ray et al., 2000). For achieving higher yields farmers are using excess inorganic fertilizers but the fertilizer use requires knowledge of expected crop yield and response to applied nutrients. Hence, there is a scope for using different precision nutrient management techniques such as site-specific nutrient management (SSNM), nutrient expert (NE), diagnosis and recommendation integration system (DRIS), critical ratio and Soil Test Crop Response (STCR) approach etc., for balanced nutrition. Among these approaches, STCR approach helps for obtaining higher grain yield by improving the nutrient use efficiency. Fertilizer recommendation is made based on the fertilizer prescription equations in STCR approach. These equations will be developed by establishing a relationship between added fertilizers and soil test values. The fertilizer prescription based on STCR model are more precise, quantitative and meaningful because it involves both plant and soil analysis. Whereas, in conventional blanket recommendation, fertilizer prescription is made without considering nutrient contribution from the soil. For balanced fertilization, Ramamoorthy et al. (1967) provided the scientific basis i.e., yield target model which in turn gives a real balance between available nutrients already present in the soil and applied nutrients. The specific yield target equations based on the soil health ensures sustainable crop production (Bera et al., 2006) and also grab the crop growers towards economic use of costly inputs especially the chemical fertilizers depending on their economic status. Venugopalan et al. (2011) suggested that to mitigate the decline in soil fertility problem, nutrient management practices through STCR should be adopted instead of general recommendation for better productivity, environmental safety and sustainability. AICRP on STCR conducted many studies on development and validation of STCR equations for maize in many states even in Karnataka at Bangalore for red soils but, not for Northern Transitional Zone of Karnataka in Vertisols. So, the equations developed for similar type of soils (medium to deep black) at different places (Jabalpur, Jagtial, Rahuri and Coimbatore) were taken to validate under assured rainfall conditions. The equations cannot be adopted without validation study because, the equations developed elsewhere may not holds good for all the locations due to variation in soil type and climatic conditions and situations from one zone to another zone. So, the validation of the STCR fertilizer prescription equations for maize in Northern Transitional Zone of Karnataka is very much essential to identify the most suitable STCR prescription model for cultivation of maize in Vertisols. Hence, the present studies were under taken with a view of creating varied gradients in soil fertility in one and the same field and validation of different STCR equations for Kharif maize at varied soil fertility gradients. MATERIAL AND METHODS A field experiment was carried out at Main Agriculture Research Station (MARS), University of Agricultural Sciences, Dharwad, during 2018, which is situated at 15o 26N latitude and 75o 07 East longitude with an altitude of 678 m MSL. The rainfall during main cropping period was 462.8 mm and mean maximum and minimum temperature were 31.6 and 18.3oC, respectively. A composite soil sample was collected and analysed in order to characterize the experimental soil. The soil of the experimental site was clay (medium to deep black) in texture, neutral in pH (7.4) with medium level of organic carbon (0.54 %) and electrical conductivity of 0.32 dS m-1. The initial status of soil available N, P2O5¬ and K2O was low (257 kg ha-1), medium (31 kg ha-1) and high (362 kg ha-1), respectively. Treatment structure, soil and plant analysis. The study comprised of two field experiments in two phases viz., fertility gradient experiment with an exhaustive crop of fodder maize var. African Tall (Phase I) to create different fertility gradients within the same field and validation of the STCR equations on varied soil fertility gradients with grain maize hybrid NK-6240 (Phase II). The details of materials used, methods followed, cultural operations cried out and STCR equations adopted in the experiment are described below. The approved treatment structure and lay out design as followed in the All India Coordinated Research Project (AICRP) for Investigations on Soil Test Crop Response (STCR) correlation based on “Inductive cum Targeted yield model” as envisaged by Ramamoorthy et al. (1967) was adopted in the present investigation. Gradient experiment. In the gradient experiment, operational range of variation in soil fertility was created deliberately to generate data covering appropriate range of values for each controllable variable (fertilizer dose) at different levels of uncontrollable variable (soil fertility) which could not be expected to occur at one place normally. Hence, in order to create fertility variations in the same field, a gradient experiment was conducted prior to the validation experiment. The entire experimental field was divided into three equal strips. The first strip received no fertilizer (N0P0K0), the second and third strips received 100 per cent (N1P1K1) and 200 per cent (N2P2K2) of the recommended dose of N, P2O5 and K2O kg ha-1, respectively. The recommended dose of fertilizer for fodder maize was 150:100:50 kg N, P2O5 and K2O ha-1, respectively as per the recommendation of University of Agricultural Sciences, Dharwad. After the fertilizer application (50 % N, entire P2O5 and K2O as basal dose and another 50 % N as top dress at 30 DAS), the gradient crop fodder maize (SA-Tall) was grown by using seed rate @ 60 kg ha-1 and the usual agronomic practices were carried out. Crop was grown to milking stage and harvested. At harvest, each fertility strip (strip I, II and III) was divided into three blocks (total nine blocks). The green biomass yield of fodder maize was taken and soil samples from each block were collected separately. Soil samples were processed and analysed for alkaline KMnO4 -N, Olsen-P and NH4OAc-K for estimation of available N, P2O5 and K2O, in I, II and III strips, respectively. The particulars of gradient experiment are depicted in Table 1. Validation study. This experiment was laid out in split plot design with three main plot and six sub plot treatments. After the establishment of fertility gradient, the variation in soil fertility at three strips (strip I, II and III) was taken as main plots (L0, L1 and L2 as low, medium and high fertility gradient, respectively) and STCR equations developed for Kharif grain maize under rainfed situation at four different locations viz., Jabalpur, Jagtial, Rahuri and Coimbatore, one RDF and one absolute control as sub plot treatments for validation of STCR equations in phase II experiment. The quantity of nutrients required to achieve target yield of 80 q ha-1 through STCR was calculated by using four different STCR equations and is given Table 2. The STCR equations developed at different locations used in the study were taken from compendium prepared by AICRP on STCR, Indian Institute of Soil Science, Nabibagh, Bhopal (Anon., 2015) and are as follows: Where, FN = Nitrogen supplied through fertilizer in kg ha-1 FP2O5 = Phosphorus supplied through fertilizer in kg ha-1 FK2O = Potassium supplied through fertilizer in kg ha-1 T= Target yield (q ha-1) SN, SP2O5, SK2O = Initial soil test value for available N, P2O5 and K2O in kg ha-1, respectively. The seeds of maize (NK-6240) were hand dibbled @ 22.5 kg ha-1 at 20 cm apart per hill in 60 cm rows to a depth of 4 to 5 cm on 23rd June 2018 and covered with soil. The recommended dose of fertilizer (RDF) for rainfed maize is 100:50:25 kg N: P2O5: K2O ha-1. These fertilizers were applied in the form of urea, diammonium phosphate (DAP) and muriate of potash (MOP), respectively. FYM was applied to the soil at the rate of 7.5 t ha-1 15 days prior to sowing of crop. Full dose of ‘P’ and ‘K’ and one third dose of N was applied as per the treatment and zinc sulphate at the rate of 10 kg ha-1 as basal dose at the time of sowing. ZnSO4 and FYM was common for all the treatments except absolute control. Remaining N was top dressed twice at 25 and 45 DAS @ one third each time. Experimental plot was kept free from weeds throughout the crop growing period. Atrazine was applied as a pre-emergent herbicide at the rate of 1 kg a.i. ha-1 immediately after sowing. One hand weeding was carried out at 30 DAS. One inter-cultivation cum earthing up operation was carried out immediately after second top dressing of N at 45 DAS. For stem borer management, Carbofuran was applied to the soil at the time of sowing at the rate of 7.5 kg ha-1. For fall armyworm management chlorpyriphos was soil drenched at seedling stage, Emamectin benzoate sprayed at 35 DAS and later poison bait was applied to whorl on 31st July 2018 at the rate of 25 kg ha-1. When the crop was at 65 days old Nomuraea rileyi (bio-agent) was sprayed against fall armyworm. Hexaconazole fungicide was sprayed against turcicum leaf blight and other foliar diseases at 80 DAS. All the growth parameters were recorded from five randomly selected plants at different growth stages of the crop. Agronomic parameters collected are plant height, number of green leaves plant-1, leaf area, leaf area index (LAI), leaf area duration (LAD), SPAD value and stem girth at different growth stages of the crop (40 DAS, 80 DAS and at harvest stage). SPAD chlorophyll meter readings were recorded with the help of SPAD meter at middle lamella of youngest fully opened third leaf from the top at different stages (Rostami et al., 2008). Diameter of the stem was measured at last but one internode from the ground with the help of Vernier caliper and stem girth (circumference) was worked out by using the formula 2πr (r = radius of the stem in cm and π = 3.142) and expressed in centimeters. Grain and stover yield from net plot area was converted into per hectare basis. The experimental data were analysed statistically as per the procedures given by Gomez and Gomez (1984). RESULTS AND DISCUSSION Effect of gradient experiment on green fodder yield and soil fertility status. Green fodder yield of exhaustive crop fodder maize was found to be increased from strip I to Strip III (25.53 to 40.38 t ha-1) (Table 1). The increase in yield was due to application of graded levels of fertilizers from 0 to 100 and 200 % for L0, L1 and L2 strips, respectively. The amount of fertilizer nutrients applied was also increased from strip I to strip III. Higher fodder maize yield recorded with strip III (40.38 t ha-1) followed by strip II (34.63 t ha-1) and lower fodder yield was recorded in strip I (25.53 t ha-1). Higher fodder yield was mainly due to application of higher amount of nutrients for strip III (300:200:100 kg N:P2O5:K2O ha-1) as compared to strip II (150:100:50 kg N:P2O5:K2O ha-1). Whereas, lower fodder yield in strip I, which did not receive any fertilizer nutrients, might be the reason for recording lesser amount of green fodder yield. Similarly, the higher soil available major nutrients were recorded in strip III (339:38:406 kg N:P2O5:K2O ha-1) as compared to strip II (180:35:335 kg N:P2O5:K2O ha-1). The higher available nutrients in strip III was due to application of higher amount of nutrients. Further, lower soil available nutrients (NPK) were recorded in strip I (119:26:295 kg N:P2O5:K2O ha-1). Since, no fertilizer was applied to strip I and fodder maize being an exhaustive crop sown with thick population and high growth rate might have removed greater amount of nutrients from the soil reserve for it’s growth and development and rendered the soil with lesser nutrient status. These results are in line with the findings of Basavaraja et al. (2017); Santhi et al. (2011) with fodder maize and Singh et al. (2021) with wheat as an exhaustive crop. Influence of soil fertility gradients on crop growth. Among the three soil fertility gradients (FGs), medium fertility gradient (MFG) recorded significantly higher grain and stover yield (82.3 and 101.2 q ha-1) than low fertility gradient (LFG). However, high fertility gradient (HFG) (81.1 and 101.1 q ha-1) was on par with MFG. The increase in grain yield in medium and high FG was to the tune of 5.24 and 3.84 per cent, respectively over low FG. Fertility gradients did not show any significant difference with respect to harvest index (Table 5). Growth parameters namely plant height (43.5, 190 and 195.6 cm), leaf area (19.5, 57.1 and 14 dm2), leaf area index (1.63, 4.76 and 1.16), leaf area duration (128 and 118 between 40 to 80 DAS and 80 DAS to at harvest), SPAD value (40.2 and 48.5 at 40 and 80 DAS) and stem girth (4.49, 7.60 and 7.72 cm) observed at all the growth stages (40, 80 DAS and at harvest, respectively) of maize were significantly higher in medium FG than low FG. High FG was on par with medium FG. But, number of green leaves plant-1 failed to show any significant difference (Table 3 and 4). Whereas, the performance of Rahuri and Coimbatore STCR equations were not so good in high FG even though the soil available status was more. This was mainly due to decreased levels of applied fertilizer nitrogen with respect to Coimbatore and Rahuri equations. The lesser performance of these two equations has led to lesser mean value of main plot (HFG) over MFG. The nutrient contribution from the soil is less as compared to applied mineral fertilizers especially the nitrogen. Giri et al. (2015) observed lesser nutrient (N, P2O5 and K2O) contribution from soil to total uptake of maize crop over applied fertilizers during development of STCR equations and similar results were also obtained by Basavaraja et al. (2016) in rice crop, Basavaraja et al. (2017) in finger millet for both the years, Praveena et al. (2013) in cotton and Singh et al. (2021) in direct seeded rice. Performance of different STCR equations. Among different STCR equations, application of nutrients as per the STCR equation developed at Jabalpur produced higher grain and stover yield (101.4 and 120.9 q ha-1) than all other equations. The increase in grain yield was to the tune of 54.1 per cent over RDF and 12.91, 10.33 and 4 per cent over Jagtial, Rahuri and Coimbatore STCR equations (Table 5). Significantly higher growth parameters namely plant height (50.1, 204.3 and 212.6 cm), number of green leaves plant-1 (6.51, 12.6 and 3.1), leaf area (23.7, 68.1 and 17.8 dm2), leaf area index (1.97, 5.67 and 1.49), leaf area duration (153 and 143 between 40-80 DAS and 80 DAS-at harvest, respectively), SPAD values (45.0 and 54.2 at 40 and 80 DAS respectively) and stem girth (5.21, 8.44 and 8.60 cm) observed with Jabalpur STCR equation at all growth stages (40, 80 DAS and at harvest, respectively) of maize than other equations and RDF as well as absolute control (Table 3 and 4). The higher grain and stover yield was mainly due to better translocation of photosynthates from source to sink and higher growth parameters and yield attributing characters like cob length, cob girth, grain rows per cob, grains per row, grains per cob, grain weight per cob, test weight and shelling percentage. The above results clearly indicate the importance of nutrient application precisely to achieve specific yield targets. Application of higher levels of inorganic fertilizers have increased the above ground biomass as well as grain yield of maize (Amouzou et al., 2018). These results are in line with those obtained by Basavaraja et al. (2014); Ghodke (2013); Singh et al. (2015) in grain maize and Kanchana et al. (2020) in pearl millet. Interaction effect of soil fertility gradients and STCR equations developed at different centres. The interaction between two STCR equations at same fertility gradient (FG), nutrients applied as per Coimbatore STCR equation recorded higher grain and stover yield (104.1 and 123 q ha-1) and growth parameters in LFG. But, at medium and high FG, higher grain (105.1 and 101.4 q ha-1, respectively) and stover (124.1 and 121.4 q ha-1 respectively) yield and all the growth parameters were recorded with STCR equation developed at Jabalpur. The increase in grain yield in best treatment was to the extent of 84.57, 53.87 and 39.66 per cent over RDF and 282.72, 187.15 and 119.95 per cent over absolute control in low, medium and high FG, respectively (Table 5). The interaction between fertility gradient with same or different STCR equations was also found to be significant. STCR equation developed at Jabalpur (MP) in MFG produced higher grain and stover yield (105.1 and 124.1 q ha-1) than all other treatment combinations. However, the same equation in HFG (101.4 and 121.4 q ha-1) and equation developed at Coimbatore in LFG (104.1 and 123 q ha-1), respectively were on par with Jabalpur STCR equation in MFG. Interaction study failed to show any significant difference with respect to harvest index. The growth parameters were also higher with Jabalpur STCR equation at MFG as depicted in Table 3 and 4. This was due to higher N and P application through Jabalpur STCR equation with optimum doses of K2O fertilizers. Further, the increased trend in all growth parameters and yield was observed with RDF and absolute control from low to high fertility gradient. It clearly indicated the variation in soil fertility gradients. When we apply same doses of fertilizer to different soil FGs, the grain yield increases with increasing soil fertility gradients. These results are in accordance with the findings of Giri et al. (2015); Singh et al. (2015); Singh et al. (2021).