Fertilizer Recommendations Research Articles

Comparison of STCR and Conventional Fertilizer Approaches for Improved Yield, Uptake and Nutrient Use Efficiency in Greengram

The present study investigates the effects of various fertilizer recommendation approaches on yield, nutrient uptake and nutrient use efficiency in greengram (BGS-9), conducted at ZARS, GKVK, Bengaluru during summer-2024. Soil test crop response (STCR) based fertilizer prescription equations were developed during kharif-2022 by following the methodology of Ramamoorthy et al., (1967) and were validated alongside post-harvest soil test value prediction equations. Results indicated that significantly higher seed yield (17.99 q ha⁻¹) was recorded in the STCR approach for the target yield of 15 q ha-1, where nutrients were applied through integrated approach based on actual soil test values (T3). The highest haulm yield (30.25 q ha⁻¹) was recorded in T2, which followed the STCR inorganic approach targeting 15 q ha⁻¹, based on predicted soil test values. Nutrient uptake results indicated that significantly higher nitrogen (110.73 kg ha⁻¹), phosphorus (11.39 kg ha⁻¹) and potassium (140.06 kg ha⁻¹) uptake were recorded in STCR treatments, particularly in those with an integrated approach. These treatments also validated better nutrient recovery and agronomic use efficiency compared to low, medium and high (LMH) and package of practice (POP) approaches. The findings confirm the accuracy of predicted soil test values in fertilizer prescription, indicating that repeated soil testing between crops may be unnecessary. The STCR based integrated approach provided balanced nutrient application, leading to optimal yield and nutrient uptake. This study highlights the effectiveness of STCR methodologies for efficient nutrient management and improved productivity in greengram.

EFFECT OF BIO-ORGANIC AND MINERAL FERTILIZATION, ON THE GROWTH AND YIELD OF CAULIFLOWER (Brassica oleraceae Var.botrytis)

A field experiment was carried out to study the effect of three factors, the first was biofertilization with four types (without addition, combination of A.brasilense + A. chroococcum combination of G.mosseae + T. harzianum, and combination of the two previous combinations), The second factor four types of organic fertilizer(without adding,vermicompost ,Orgevit, a combination of the two previous organic fertilizers),and the third factor mineral fertilizer with two levels (0% and 50%) of the fertilizer recommendation in addition to the full fertilizer recommendation treatment (second comparison).RCBD was used with three replications. The results showed that the triple interaction of the biofertilization treatments added with the organic fertilizer combination of organic fertilizer with 50% of the mineral fertilizer recommendation showed the highest averages for the characteristics of growth and the total yield, which gave79.740 Mg ha-1, and the content of leaves and the curd from N, P and K after harvest and the content of the soil of N, P and K after harvesting, which amounted to 70.81, 38.19, 370.44 mg kg soil-1,in comparison with the no addition treatment which gave the lowest averages .

EFFECT OF VERMICOMPOST AND BIOFERTILIZATION ON THE AVAILABILITY OF SOME SOIL NUTRIENTS, GROWTH AND YIELD OF SQUASH (Cucurbita pepo L.)

A field experiment was carried out to evaluate the effect of four application methods of vermicompost tea (without application, ground application, foliar spray, combination of - ground application + foliar spray) , four types of biofertilization (without application, Stenotrophomonas maltophilia, Bacillus megaterium, the combination consisting of S. maltophilia + B. megagaterium), and two levels (0, 50%) of the fertilizer recommendation in the availability of some soil nutrients and on the growth and yield of squash using as randomized complete block design with three replications. The results showed that the triple interaction of the combination of application vermicompost tea with the combination of biofertilizer and 50% of mineral fertilizer was effect significantly and gave the highest values for some vegetative growth parameters. Which included the dry weight of the vegetative part, the length and weight of the root, and total yield which amounted 196.35 g plant-1, 65.33 cm, 60.31 g plant-1, 45.14 Mgha-1, respectively. the available of nitrogen, phosphorous and potassium in soil at the end of the experiment, which amounted 60.56, 38.20 and 191.38 mg kg-1soil in comparison with the treatment without addition, which gave the lowest rates.

Effects of Recommended Fertilizer Application Strategies Based on Yield Goal and Nutrient Requirements on Drip-Irrigated Spring Wheat Yield and Nutrient Uptake

Excessive application of fertilizers in drip-irrigated wheat production can suppress yields, lower nutrient utilization efficiency, and lead to economic and environmental issues such as nitrogen residues in the soil. Based on a recommended fertilizer application (RF) strategy that takes into account target yield and nutrient requirements, this study explores the responses of wheat plant traits, changes in topsoil and subsoil nutrients, fertilizer utilization, and economic benefits under this strategy. From 2022 to 2023, a field experiment was conducted in a typical oasis spring wheat production area at the northern foot of the Tianshan Mountains in Xinjiang. The treatments included no fertilizer control (CK), the farmer’s conventional practice (FP), recommended fertilizer (RF), RF with nitrogen omission (RF-N), phosphorus omission (RF-P), and potassium omission (RF-K). The results showed that compared with FP, the RF reduced 91 kg N ha−1 (30.3%) and 33 kg P2O5 ha−1 (24.8%) in 2022, and 69 kg N ha−1 (23.0%) and 2 kg P2O5 ha−1 (1.5%) in 2023. The effect in 2023 was better; RF also decreased the NO3−1-N residue in the 0–100 cm soil layer by 40.1 kg N ha−1 compared with FP, with no significant difference in wheat grain yield (RF: 5382.9 kg ha−1) or economic benefit (RF: USD 1613.1 ha−1). Furthermore, there were no significant differences between RF and FP in pre-anthesis NP transport or post-anthesis NP accumulation; however, RF significantly increased pre-anthesis potassium transport volume (15.8%) and transport rate (12.5%). RF led to a 16.3% increase in nitrogen utilization efficiency (NUE), while there was no significant difference in phosphorus utilization efficiency (PUE) compared with FP. The fertilizer yield effect for RF was evaluated as N > P > K. Correlation analysis indicated that grain yield was significantly positively correlated with pre-anthesis NPK transport and post-anthesis NP accumulation. It was also positively correlated with organic matter, alkali-hydrolyzed nitrogen, and Olsen-P content in both the topsoil (0–20 cm) and subsoil (20–40 cm), but not with available potassium in the soil. Therefore, conducting soil tests and determining fertilizer recommendations based on the proposed RF method at harvest can reduce fertilizer usage and achieve a balance between the conflicting objectives of environmental protection, increased crop yields, nutrient utilization efficiency, and improved economic benefits in oasis agricultural areas facing excessive fertilizer application.

Effects of NPS Fertilizer Rate on Yield and Yield Components of Bread Wheat Production in Degem District, North Shewa Zone, Oromia, Ethiopia

Productivity of wheat was low due to depleted soil fertility and the blanket use of fertilizers. Fertilizer is the most vital input, contributing significantly to final wheat yields although wheat yields have long been low due to a lack of soil test-based site-specific fertilizer recommendations. This study aimed to determine an economically appropriate rate of NPS fertilizer based on calibrated Phosphorus for bread wheat production in the Degem district. The experiments laid out in randomized complete block design (RCBD) with three replications. The treatments were based on already determined Phosphorous critical and requirement factors and consisted of 100% Pc from TSP fertilizer, 25%, 50%, 75%, and 100% Pc from NPS fertilizer and control (without fertilizer). The phosphorus requirement factor (Pf) (5.85), phosphorus critical (Pc) (22 ppm), and optimum nitrogen optimum nitrogen (92 kg ha<sup>-1</sup>) were used from previous studies. Improved bread wheat variety senete was used at 150 kg/ ha seeds rate. The results of a statistical analysis of variance demonstrated that NPS fertilizer rates based on calibrated phosphorus had significant effects on bread wheat production. Partial budget analysis shows the maximum net benefit (101,570.65 Birr ha<sup>-1</sup>) with an acceptable marginal rate of return (MRR) (932’52 %) through the application of 75% of Pc from NPS with optimum nitrogen fertilizer use. Consequently, 75% Pc from NPS should be used in the Degem district for bread wheat production, with the optimum nitrogen. Thus, further scaled-up and demonstration of the technologies for bread wheat production in the Degem district.

The new machine learning feature selection method used in fertilizer recommendation

The new machine learning feature selection method used in fertilizer recommendation

Hierarchical Bayesian semi-parametric models for measurement error correction in determining optimal fertilizer application levels

Measurement errors present a substantial challenge in accurately determining optimal fertilizer application levels, directly impacting agricultural efficiency and cost-effectiveness. This study examines the use of Hierarchical Bayesian Semi-Parametric (HBS) models to correct these errors, thereby improving precision in agricultural decision-making. By applying these models to a decade of data from Uasin Gishu County, Kenya, we evaluated key variables including maize yield, land size, and fertilizer levels. The results indicate that the HBS models effectively mitigate both systematic and random errors, leading to more accurate fertilizer recommendations. This advancement supports better resource management and higher crop yields. Our findings underscore the value of Bayesian methods in agricultural data analysis and highlight the critical role of accurate measurement and correction in achieving optimal outcomes. The implications of this research extend to improved decision-making processes and more sustainable agricultural practices.

Influence of Nitrogen and Phosphorus Fertilizers Applications for Tomato (<i>Solanum lycopersicum </i>L.) Production Under Irrigation in the Fogera District, Northwest Ethiopia

Small-scale tomato production under irrigation is a common practice in the Fogera area of the Amhara Region in Northwest Ethiopia. However, there were no location-specific economic optimum N and P fertilizer recommendations for tomato production in the area. Therefore, a field study was conducted in 2020 and 2021 to investigate the response of tomato to N and P fertilizer applications and determine the economic return of N and P fertilizers applications. Four levels of N (0, 46, 92, and 138 kg N ha<sup>-1</sup>) and three levels of P (0, 46, and 92 kg P<sub>2</sub>O<sub>5</sub> ha<sup>-1</sup>) were factorially combined and laid in a randomized complete block design with three replications. The results revealed that tomato yield and yield-related attributes were significantly (p<0.01) affected by the main effects of N. However, the main effect of P and its interaction with N did not considerably influence the yield and yield-related parameters. The highest marketable (39.3 t ha<sup>-1</sup>) and total fruit yields (46.2 t ha<sup>-1</sup>) of tomato were recorded from the application of 138 kg N ha<sup>-1</sup>. The highest net economic return of Ethiopian birr 185,538.50 with a marginal rate return of 1326.1% was recorded from the application of 138 kg N ha<sup>-1</sup>. Therefore, 138 kg ha<sup>-1</sup> N can be recommended to increase the yield and economic return of tomato production in Fogera area. However, as the yield response to N followed a linear response curve, further study with higher rates of N than those considered in the present study is recommended.

Soil texture analysis using controlled image processing

Soil texture analysis is crucial for crop selection, fertilizer recommendation, and production. Traditional soil testing in the lab using chemicals is highly time-consuming, expensive, and risky harmful chemicals; proper equipment and trained professionals are required to get the readings and to conduct the analysis. These issues can be resolved using image processing. In this study, we proposed a Blackbox prototype machine to take images in a controlled environment under the fixed intensity of light, distance, and standard dry conditions to analyze soil texture. This innovative machine, with its efficient and precise image processing capabilities, has the potential to revolutionize soil texture analysis. Also, we marked the center points of each type of soil texture as defined in the USDA texture triangle. Hundreds of soil samples were prepared for each type according to the center point's sand, silt, and clay ratio. The image processing-based model is trained for texture analysis. This research aims to reduce the soil texture analysis time and provide a system that can do extensive analyses automatically and with accuracy. The proposed Blackbox prototype machine has proven effective in providing a controlled environment for taking images. Also, the proposed model detects soil texture with a maximum accuracy of 99.5 %. A proposed model trained on the soil samples of different texture classes available in the USDA texture triangle accurately performed texture analysis. The results benefit the recommendation of appropriate crops and fertilizers based on a given soil sample in a very short time and cost-effectively.

Estimation of Nutrient Uptake and Available Nutrient Status of Rabi Safflower Through Soil Test Crop Response in Rainfed Ecosystem

Background: Adoption of SSNM is directly affected by cost of fertilizer. Soil test crop response (STCR) concept attribute to contribution of soil and targeted yield level for fertilizer recommendation for a selected crop. This approach is also known as prescription based fertilizer recommendations. It is specific type of soil, climatic condition and specific location. Nutrient requirement is differ for different crops. The available soil nutrients efficient used and added to those available soil nutrients through fertilizers is different for different type of soil geography under a particular set of climatic conditions. Methods: A research experiment was carried out during rabi 2017-18, 2018-19 and 2019-20 at Research Farm of Agronomy, Dr. P.D.K.V, Akola (Maharashtra). Fertilizers were applied based on uptake pattern of crop, target yield levels and soil test values. The experiment was laid out in FRBD-Factorial randomized block design with two factors. Total 15 treatment combinations were formed which replication 4 times. Result: Significantly greater uptake of nitrogen (62.76, 74.67 and 81.89 kg ha-1), phosphorus (19.15, 24.32 and 29.38 kg ha-1), potassium (80.32, 92.14 and 99.18 kg ha-1), sulphur (18.46, 24.10 and 26.03 kg ha-1) and zinc (493.97, 571.01 and 620.91 g ha-1) recorded in treatment where crop supplied with farm yard manure @ 5 t ha-1 than rest of treatments during 2017-18, 2018-19 and 2019-20, respectively. A similar trend was observed in respect of soil nutrient status such as available N, P2O5, K2O, S and Zn. Application of fertilizers through soil test crop response equation with zinc sulphate @ 25 kg ha-1 and Sulphur @ 10 kg ha-1 registered maximum total uptake of nitrogen (66.89, 78.99 and 90.06 kg ha-1), phosphorus (20.78, 25.31 and 31.96 kg ha-1), potassium (86.05, 97.99 and 109.09 kg ha-1), sulphur (20.27, 26.39 and 29.80 kg ha-1) and zinc (537.78, 618.06 and 696.21 g ha-1) than rest of nutrient management treatments during three years of field experiment, respectively. The same trend was observed with respect to available N, P2O5, K2O, S and Zn under respective treatment during three years of experimentation.

Corn yield response to phosphorus fertilizer in Michigan: a metamodeling approach for phosphorus management policies

Phosphorus (P) pollution from nonpoint sources is a persistent agricultural externality. P fertilizer use in excess of crop removal leads to soil P accumulation and increases chance of P runoff from agricultural fields. For fertilizer-intensive crops such as corn, effective nutrient management can partly mitigate the externality associated with fertilizer use. In states such as Michigan with abundant freshwater resources that are vulnerable to P pollution and where corn is grown intensively, understanding yield response is instrumental for P management policies. We analyze corn yield response to P fertilizer and control for soil P. We use farmer survey data from 1650 corn farmers in Michigan and a crop-simulation model to obtain data in a metamodeling approach to estimate yield function. Using the estimated function in profit maximization set up, we calculate agronomically and economically optimal profit-maximizing P application rates for Michigan, across agricultural regions, and across different soil types. We find that corn yield responds to P only in low soil P (0–5 ppm or mg kg−1) fields and the economically optimal P rate for Michigan is [63, 68] kg ha−1 or [53, 61] lbs acre−1 for low soil P fields and would be zero for fields with adequate soil P. For existing soil P levels in Michigan, the self-reported P application of Michigan corn farmers exceeds the profit-maximizing P application rate. We compare our analysis results with self-reported survey data to demonstrate excess P applications. Since many fields in Michigan have high soil P, additional P application in excess of crop removal increases risks of eutrophication. We also find that 10 % increase in P prices faced by farmers would lead to 3.1 % reduction in the economically optimal P application rate. Based on these results, we discuss suitable policy options such as fertilizer “usage fee” and tailored fertilizer recommendations.

Nutrient Dynamics in Integrated Crop–Livestock Systems: Effects of Stocking Rates and Nitrogen System Fertilization on Litter Decomposition and Release

Current fertilizer recommendations often neglect nutrient cycling across crop rotations. This study aimed to assess the decay rate and nutrient (N, P, K) release patterns of sorghum, black oat, and corn residues (omitido) in an integrated crop–livestock system. The experiment used factorial treatments based on two sward heights (high and low) and two nitrogen fertilization levels (N-pasture at 200 kg N ha−1 and N-corn at 0 kg N ha−1). Litter bags were collected at various intervals from each crop to measure nutrient release patterns and decomposition rates. The results showed that pasture height and nitrogen fertilization significantly influenced decomposition and nutrient release, affecting the subsequent grain crop phase. Potassium was released rapidly and in high amounts. Nitrogen fertilization during the pasture phase prevented nitrogen and phosphorus immobilization in black oat residue and reduced immobilization in corn residue. These findings highlight the importance of accounting for nutrient cycling and decomposition rates in fertilization strategies to enhance the sustainability of integrated crop–livestock systems.

Nitrogen credits after peanut (Arachis hypogaea L.)

AbstractState‐level cooperative extension services provide fertilizer recommendations for row crops in the United States. Of these, nitrogen (N) recommendations are arguably the most important because N is the most common yield‐limiting nutrient in nonlegume crop production systems. Throughout the peanut (Arachis hypogaea L.) growing region of the United States, Cooperative Extension Services generally recommends 22–67 kg N/ha credit to crops following peanut, likely due to the assumption that peanut, being a legume, contributes N to the following crop. The body of peer‐reviewed literature indicates that N credits from peanut to the subsequent crop are negligible. Recent literature indicates that apparent differences in yield following peanut compared to a nonlegume are a result of nonlegume crop residue favoring N immobilization rather than N mineralization from peanut residue. Taken together, recent research corroborates the few previous scientific publications addressing the issue, namely, that cooperative extension service recommendations to reduce N fertilization to crops after peanut are not supported by the peer‐reviewed literature. Future field research should include summer fallows to determine if yield differences between legumes and nonlegumes are due to N credits by the legume or N immobilization by nonlegumes. Data on N loss pathways following peanut are needed to identify management strategies that can mitigate N losses after peanut harvest. In conclusion, the preponderance of peer‐reviewed science does not support current Extension recommendations regarding peanut N credits to the following crop.

Assessment of portable X-ray fluorescence (pXRF) for plant-available nutrient prediction in biochar-amended soils

Portable X-ray Fluorescence probe (pXRF) is a tool used to measure many elements quickly and efficiently in soil with minimal sample preparation. Although this sensing technique has been widely used to determine total elemental concentrations, it has not been calibrated for plant-available nutrient predictions. We evaluated the potential of using pXRF for fast plant-available nutrient quantification. Two experiments were conducted in soils treated with two types of biochars to obtain a practical range of soil pH (5.5 − 8.0) and organic carbon (2.0 − 5.5%). Biochars applied were derived from switchgrass (SGB) and poultry litter (PLB). The first experiment received biochars at application rates up to 8% (w/w) and had no plants. The second experiment had up to 4% of SGB or PLB planted with ryegrass (Lolium perenne). Linear regression (LR), polynomial regression (PolR), power regression (PowR), and stepwise multiple linear regression (SMLR) were the models tested. Regardless of the extraction method, phosphorus (P) showed a strong relationship between pXRF and several laboratory extraction methods; however, K prediction via pXRF was sensitive to the plant factor. The optimum soil available-P corresponding to the maximum P uptake in plant tissues can be assessed with pXRF. The LR was inconsistent for calcium (Ca), sulfur (S), and copper (Cu) and non-significant for magnesium (Mg), iron (Fe), and zinc (Zn). Our results showed that pXRF is applicable to estimate P availability in soils receiving organic amendments. More evaluations are needed with diverse soil types to confirm the findings before using pXRF for fertilizer recommendation.

How meeting the ten pedometrics challenges can deliver healthy‐soil contributions to SDG‐related ecosystem services

AbstractWhen considering ecosystem services in line with relevant Sustainable Development Goals, the proposed logical sequence of the ten pedometric challenges can form a framework defining effective contributions by the soil science discipline to the sustainability challenge facing society. Defining relatively simple, but scientifically sound, indicators and thresholds for ecosystem services can be the basis for a transparent regulatory system justifying payment for ecosystem services provided to society. The current serious lack of trust between the policy and farming arenas can and should be restored by scientists and farmers working jointly in Living Labs, aiming to become Lighthouses, to be part of Communites of Practice (CoP). A Living Lab case study is reviewed showing that much know‐how is already available to define indicators and innovative cutting‐edge methodology adds attractive new opportunities for rapid and relatively cheap characterizations. Field work remains essential and just routinely applying standard techniques fed by existing databases may lead to poor results. Research on indicator‐thresholds has a high priority. In the case study, the important soil fertility indicator was based on the current procedure of field sampling and fertilization recommendations by specialized agencies, that is already followed by 85% of farmers. This could be expanded by including indicators for other ecosystem services thereby contributing substantially to the societal sustainability debate. Soil health plays a key role when contributing to all ecosystem services. Showing this with specific examples in a Living Lab/Lighthouse and CoP context is the best way to promote the profession which is needed to justify current major funding. Not only cutting‐edge research can contribute to defining indicators and thresholds. A hundred years of research has produced many valuable insights and methodologies that can be applied as well. The: ‘better’ can be the enemy of the: ‘good’. The sustainable development challenge is highly urgent: there is no time to lose.

Enhancing Agricultural Sustainability through Precision Fertilizer Recommendations: A Machine Learning Approach with Comparative Ensemble Analysis

Enhancing Agricultural Sustainability through Precision Fertilizer Recommendations: A Machine Learning Approach with Comparative Ensemble Analysis

Random forest machine learning for maize yield and agronomic efficiency prediction in Ghana

Maize (Zea mays) is an important staple crop for food security in Sub-Saharan Africa. However, there is need to increase production to feed a growing population. In Ghana, this is mainly done by increasing acreage with adverse environmental consequences, rather than yield increment per unit area. Accurate prediction of maize yields and nutrient use efficiency in production is critical to making informed decisions toward economic and ecological sustainability. We trained the random forest machine learning algorithm to predict maize yield and agronomic efficiency in Ghana using soil, climate, environment, and management factors, including fertilizer application. We calibrated and evaluated the performance of the random forest machine learning algorithm using a 5 × 10-fold nested cross-validation approach. Data from 482 maize field trials consisting of 3136 georeferenced treatment plots conducted in Ghana from 1991 to 2020 were used to train the algorithm, identify important predictor variables, and quantify the uncertainties associated with the random forest predictions. The mean error, root mean squared error, model efficiency coefficient and 90 % prediction interval coverage probability were calculated. The results obtained on test data demonstrate good prediction performance for yield (MEC = 0.81) and moderate performance for agronomic efficiency (MEC = 0.63, 0.55 and 0.54 for AE-N, AE-P and AE-K, respectively). We found that climatic variables were less important predictors than soil variables for yield prediction, but temperature was of key importance to yield prediction and rainfall to agronomic efficiency. The developed random forest models provided a better understanding of the drivers of maize yield and agronomic efficiency in a tropical climate and an insight towards improving fertilizer recommendations for sustainable maize production and food security in Sub-Saharan Africa.

Use and recovery of P reserves in Southern Brazil Oxisols under no-till with low and high P availability

ABSTRACT The accessibility of soil P reserves by plants on highly weathered Brazilian soils remains unclear. In this study, we assessed the contribution of soil P fractions to P uptake by soybean plants in two no-till Oxisols (Latossolos), with low and high initial content of available P. The recommended P rates (viz., 153 and 50 kg ha -1 yr -1 in the low-P and high-P soil, respectively) were applied in the form of triple superphosphate (TSP) or Bayovar rock phosphate (BRP) plus a treatment without fertilizer. Yields of winter cereals and soybean on the studied soils were examined over a period of three years. Soil samples were collected in the 0.00-0.10 m soil layer and subjected to sequential chemical fractionation of P. In the last crop season, the P content of soybean shoot biomass was determined. Soil P fractions and P content of soybean shoots were subjected to path analysis. The addition BRP in the low-P soil resulted in a winter cereal yield of 2.0 Mg ha -1 lower than TSP. In the scenario of high P, it is possible to maintain high crop yields even without phosphate fertilization for three consecutive years. Path analyses demonstrated the addition of P using either TSP or BRP boosted the contribution of the more labile inorganic P fractions. The addition of BRP should be avoided in P-deficient soils. The addition TSP or BRP reduces the pressure of plants to use soil P reserves. Therefore, the soil P legacy should be considered in fertilization recommendations for high-P soils in NT.

Inductive cum targeted yield model-based integrated fertilizer prescription for sweet corn (Zea mays L. Saccharata) on Alfisols of Southern India.

Striking the right nutrient balance is essential for sustainable farming and ecosystem health. In this regard, field experiments were conducted in three phases viz., fertility gradient experiment, main experiment and validation experiment through a soil test crop response approach to develop and validate fertilizer prescription equations for sweet corn in comparison with general recommended dose and soil fertility rating approach. The soil data, fresh cob yield, and NPK uptake were used for establishing four important basic parameters, viz., nutrient requirement (kg t-1), contribution of nutrients from fertilizers, soil, and organic manure. The results revealed that nutrients required to produce one tonne of fresh cob yield (NR) were 5.85 kg, 0.87 kg and 4.31kg for N, P and K, respectively under the STCR NPK alone approach and 6.07 kg, 0.92 kg and 4.33 kg for N, P and K, respectively under STCR NPK+FYM approach. In the validation experiment, STCR NPK+FYM approach for the targeted yield of 25 t ha-1 recorded higher fresh cob yield (23.38 t ha-1) and dry stover yield (35.07 t ha-1) which were significantly higher compared to general recommended dose and soil fertility rating approach. The developed STCR equations for the aforesaid crop are valid as the percent deviation of cob yield from the targeted yield was within ±10%. Similarly, highest nutrient use efficiency was achieved with the STCR approach, specifically when targeting a lower yield through an NPK+FYM mode. Thus, implementation of the STCR approach of fertilizer prescription, with or without FYM, at targeted yields of 25 and 22 t ha-1, not only surpassed the effects of the other fertilizer recommendation approach in terms of cob yields, but also increased NPK uptake, improved nutrient use efficiency and greater economic returns.

Effect of Transplanting Dates and Nutrient Management Options on Nutrient Partitioning and Accumulation in Rice

ABSTRACT Rice is the most important crop in India and additionally the hub of food security of the worldwide population. Integrated application of manures and fertilizers played a pivotal role for improvement of soil physico-chemical properties under different cropping systems as well as nutrient accumulation and grain yield in rice. The present investigation was conducted in sandy loam soil at Agronomy Research Farm of Odisha University of Agriculture and Technology, Bhubaneswar, Odisha, India during 2018–2019 having sub-humid climate. Field experiment was designed to evaluate the effect of two date of transplanting, which were allotted to main plots and three combinations of nutrient management options allotted for sub plots on rice crop (var. Naveen). Among all the plant parts, leaf showed higher accumulation of nitrogen (3.69, 1.92%), stem showed higher accumulation of both phosphorus (0.43, 0.35%) and potassium (2.59, 2.09%) than other plant parts during vegetative stages, while panicle showed higher accumulation of nitrogen (1.22%), phosphorus (0.28%) during harvesting stages of the rice crop. Significantly higher nitrogen accumulation in different plant parts were optimized under Soil Test Based Fertilizer Recommendation (STBFR) + Green Manure (GM; Sesbania rostrata) (0.99, 0.46, 1.28%) method of nutrient management, while phosphorus (0.10, 0.11, 0.28%) and potassium (1.00, 1.64, 0.33%) accumulation were found to be significantly higher in different plant parts under STBFR + Farm Yard Manure (FYM) method of nutrient management. Thus, early transplanting and application of STBFR + GM/FYM could be recommended for higher nutrient accumulation in rice crop.